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Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020–March 2021

ORIGINAL RESEARCH — Volume 18 — July 1, 2021

Lyudmyla Kompaniyets, PhD 1 ; Audrey F. Pennington, PhD 1 ; Alyson B. Goodman, MD 1 ,2 ; Hannah G. Rosenblum, MD 1 ,3 ; Brook Belay, MD 1 ; Jean Y. Ko, PhD 1 ,2 ; Jennifer R. Chevinsky, MD 1 ,3 ; Lyna Z. Schieber, DPhil, MD 1 ; April D. Summers, MPH 1 ; Amy M. Lavery, PhD 1 ; Leigh Ellyn Preston, DrPH 1 ; Melissa L. Danielson, MSPH 1 ; Zhaohui Cui, PhD 1 ; Gonza Namulanda, DrPH 1 ; Hussain Yusuf, MD 1 ; William R. Mac Kenzie, MD 1 ,2 ; Karen K. Wong, MD 1 ,2 ; James Baggs, PhD 1 ; Tegan K. Boehmer, PhD 1 ,2 ; Adi V. Gundlapalli, MD, PhD 1 ( View author affiliations )

Suggested citation for this article: Kompaniyets L, Pennington AF, Goodman AB, Rosenblum HG, Belay B, Ko JY, et al. Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020–March 2021. Prev Chronic Dis 2021;18:210123. DOI: http://dx.doi.org/10.5888/pcd18.210123 external icon .

PEER REVIEWED

Introduction

Acknowledgments, author information.

What is already known about this topic?

Severe COVID-19 illness in adults has been linked to underlying medical conditions.

What is added by this report?

In this cross-sectional study of 540,667 adult hospitalized patients with COVID-19, 94.9% had at least 1 underlying medical condition. Hypertension and disorders of lipid metabolism were the most frequent, whereas obesity, diabetes with complication, anxiety disorders, and the total number of conditions were the strongest risk factors for severe COVID-19 illness.

What are the implications for public health practice?

Preventing COVID-19 in populations with these underlying conditions and multiple conditions should remain a public health priority, with targeted mitigation efforts and ensuring high uptake of vaccine, when available, in these individuals and their close contacts.

Severe COVID-19 illness in adults has been linked to underlying medical conditions. This study identified frequent underlying conditions and their attributable risk of severe COVID-19 illness.

We used data from more than 800 US hospitals in the Premier Healthcare Database Special COVID-19 Release (PHD-SR) to describe hospitalized patients aged 18 years or older with COVID-19 from March 2020 through March 2021. We used multivariable generalized linear models to estimate adjusted risk of intensive care unit admission, invasive mechanical ventilation, and death associated with frequent conditions and total number of conditions.

Among 4,899,447 hospitalized adults in PHD-SR, 540,667 (11.0%) were patients with COVID-19, of whom 94.9% had at least 1 underlying medical condition. Essential hypertension (50.4%), disorders of lipid metabolism (49.4%), and obesity (33.0%) were the most common. The strongest risk factors for death were obesity (adjusted risk ratio [aRR] = 1.30; 95% CI, 1.27–1.33), anxiety and fear-related disorders (aRR = 1.28; 95% CI, 1.25–1.31), and diabetes with complication (aRR = 1.26; 95% CI, 1.24–1.28), as well as the total number of conditions, with aRRs of death ranging from 1.53 (95% CI, 1.41–1.67) for patients with 1 condition to 3.82 (95% CI, 3.45–4.23) for patients with more than 10 conditions (compared with patients with no conditions).

Certain underlying conditions and the number of conditions were associated with severe COVID-19 illness. Hypertension and disorders of lipid metabolism were the most frequent, whereas obesity, diabetes with complication, and anxiety disorders were the strongest risk factors for severe COVID-19 illness. Careful evaluation and management of underlying conditions among patients with COVID-19 can help stratify risk for severe illness.

As the COVID-19 pandemic continues, a need remains to understand indicators for severe illness, defined as admission to an intensive care unit (ICU) or stepdown unit, invasive mechanical ventilation (IMV), or death (1). Several underlying medical conditions among adults, including diabetes, obesity, chronic kidney disease (CKD), hypertension, and immunosuppression, have been reported to be associated with increased risk for severe illness from COVID-19 (2-4). However, many existing studies are limited in geographic representation, restricted to cases early in the outbreak, or focused on a limited number of preselected conditions and/or severe outcomes (3–5). Finally, few studies have shown the effect of the number of underlying medical conditions on the risk for severe COVID-19 illness (6).

Both the baseline prevalence of a condition and the magnitude of its association with COVID-19 illness help determine the impact of a condition at a population level. This study, based on a large electronic administrative discharge data set, sought to describe the most frequent underlying medical conditions among hospitalized patients with COVID-19 and their associations with severe illness. This information can better inform clinical practice and public health priorities, such as identifying populations for focused prevention efforts and potential vaccine prioritization.

We used the Premier Healthcare Database Special COVID-19 Release (PHD-SR, release date May 11, 2021), a large, US hospital-based, all-payer database (7). The sample included patients aged 18 years or older who had an inpatient encounter with an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis of U07.1 (“COVID-19, virus identified”) from April 1, 2020, through March 31, 2021, or B97.29 (“other coronavirus as the cause of diseases classified elsewhere,” recommended before the April 2020 release of U07.1) from March 1, 2020, through April 30, 2020 (8,9).

We examined 3 indicators of severe COVID-19 illness: admission to an ICU or stepdown unit, IMV, and death. These indicators were not mutually exclusive.

We considered 2 exposures of interest: 1) specific underlying medical conditions and 2) the number of conditions. We captured data on both exposures by using ICD-10-CM diagnosis codes from inpatient or outpatient hospital records in PHD-SR from January 2019 up to and including a patient’s first inpatient encounter for COVID-19. We used 1 encounter with an ICD-10-CM code to establish the presence of an underlying condition because few patients had multiple encounters in this hospital database. We excluded 3 ICD-10-CM codes (ie, oxygen support, dependence on a ventilator, and tracheostomy) listed during the patient’s COVID-19 encounter because they could be part of COVID-19 treatment.

We used a multistep approach to identify underlying medical conditions. First, we used the Chronic Condition Indicator (CCI) to identify chronic ICD-10-CM codes (11,803 of 73,205 total ICD-10-CM codes), which were then aggregated into 314 categories using the Clinical Classifications Software Refined (CCSR) (10,11). To further differentiate underlying conditions from acute complications of COVID-19, a panel of physicians (K.K.W., W.M.K., H.G.R., B.B., N.T.A., J.M.N.) classified the 314 CCSR categories into “likely underlying” (274 categories; eg, asthma); “indeterminate,” which could include underlying or acute complications or both (29 categories; eg, cardiac dysrhythmias); or “likely acute” (11 categories; eg, acute pulmonary embolism). We used the “likely underlying” CCSR categories for our analysis of underlying medical conditions and excluded the “indeterminate” or “likely acute” CCSR categories. People diagnosed with both CCSR categories of “diabetes with complication” and “diabetes without complication” (n = 55,141) were classified as having diabetes with complication. The number of underlying medical conditions was defined as the number of unique CCSR categories associated with each patient (0, 1, 2–5, 6–10, >10).

Statistical analyses

We described the sample by patient and hospital characteristics. Then we selected the most frequent underlying CCSR categories with a prevalence of 10% or more in the sample. We used multivariable generalized linear models with Poisson distribution and log link function to estimate adjusted risk ratios (aRRs) for 3 outcomes of interest among hospitalized patients: ICU admission, IMV, and death (reference was surviving hospitalized patients without that outcome). We performed these estimations by 1) including all frequent CCSR categories in the same model (“full model”) and 2) including 1 CCSR category per statistical model (“restricted model”). We focused our interpretations on the CCSR categories whose direction of association (positive or negative) was consistent between the restricted and the full model. We also conducted a stratified analysis of frequent conditions by age group (frequency ≥10.0% in each age group). Finally, we estimated the association between the number of CCSR categories and the 3 severity outcomes.

All models used robust SEs clustered on hospital identification, and controlled for patient age, sex, race/ethnicity, payer type, hospital urbanicity, US Census region of hospital, admission month, and admission month squared (to account for potential nonlinear unobservable changes in treatment, patient profile, or severity of illness during the pandemic). All analyses were conducted using R version 4.0.2 (The R Foundation) and Stata version 15.1 (StataCorp LLC).

We performed 2 sensitivity analyses using all chronic CCSR categories, including those determined by the clinician panel to be “likely underlying,” “indeterminate,” and “likely acute.” We performed 1 sensitivity analysis in the main sample and another that was limited to encounters that preceded the first COVID-19 inpatient encounter. These analyses were used to validate the associations found in the main analysis, as well as to examine the conditions excluded from the main analysis after clinical review.

This activity was reviewed by the Centers for Disease Control and Prevention (CDC) and was conducted according to applicable federal law and CDC policy.

Among 4,899,447 hospitalized patients in PHD-SR, 540,667 (11.0%) patients met the study inclusion criteria for COVID-19 ( Table 1 ). Of patients hospitalized with COVID-19, 94.9% had at least 1 documented underlying CCSR condition, 249,522 (46.2%) had an ICU admission, 76,680 (14.2%) received IMV, and 80,174 (14.8%) died. The study sample included 261,078 (48.3%) female patients, 94,670 (17.5%) non-Hispanic Black patients, and 93,171 (17.2%) Hispanic or Latino patients. The median age was 66 years, and the most common insurance types were Medicare (292,978 [54.2%]) and commercial (130,995 [24.2%]). The 863 hospitals visited by patients included in the study were distributed across all US Census regions.

We found 18 underlying CCSR categories with a frequency of 10.0% or more in the sample; the most common were essential hypertension (272,591 [50.4%]), disorders of lipid metabolism (267,057 [49.4%]; top ICD-10-CM code was hyperlipidemia), obesity (178,153 [33.0%]), diabetes with complication (171,727 [31.8%]), and coronary atherosclerosis and other heart disease (134,839 [24.9%]) ( Figure 1 ), .

Relative risk of death in the full model was 30% higher with obesity (95% CI, 27%–33%), 28% higher with anxiety and fear-related disorders (95% CI, 25%–31%), 26% higher with diabetes with complication (95% CI, 24%–28%), 21% higher with CKD (95% CI, 19%–24%), 18% higher with neurocognitive disorders including dementia and Alzheimer’s disease (95% CI, 15%–21%), 18% higher with chronic obstructive pulmonary disease and bronchiectasis (95% CI, 16%–20%), 17% higher with aplastic anemia including anemia in CKD (95% CI, 14%–19%), 14% higher with coronary atherosclerosis and other heart disease (95% CI, 12%–16%), and 4% higher with thyroid disorders including hypothyroidism (95% CI, 2%–6%) ( Table 2 ). These conditions were also associated with a higher risk of IMV and ICU admission.

Diabetes without complication was associated with a 6% lower risk of death (aRR = 0.94; 95% CI, 0.91–0.97), 9% lower risk of IMV (aRR = 0.91; 95% CI, 0.88–0.94), and 2% lower risk of ICU admission (aRR = 0.98; 95% CI, 0.97–0.998). Essential hypertension was associated with an 8% lower risk of death (aRR = 0.92; 95% CI, 0.90–0.93), 6% lower risk of IMV (aRR = 0.94; 95% CI, 0.92–0.95), and a 1% lower risk of ICU admission (aRR = 0.99; 95% CI, 0.97–0.999). Asthma was associated with a 9% lower risk of death (aRR = 0.91; 95% CI, 0.89–0.94) and a 4% lower risk of IMV (aRR = 0.96; 95% CI, 0.94–0.99).

Age-stratified analysis showed that the number of frequent underlying medical conditions (present in ≥10.0% of patients) was higher with older age ( Table 3 ). The most frequent conditions were obesity, diabetes, and essential hypertension among patients younger than 65, and disorders of lipid metabolism, essential hypertension, diabetes, and coronary atherosclerosis among patients aged 65 or older. Among patients aged 18 to 39, essential hypertension was associated with a 26% higher risk of death (95% CI, 10%–44%), 25% higher risk of IMV (95% CI, 17%–35%), and an 11% higher risk of ICU admission (95% CI, 7%–15%). In the same age group, asthma was frequent and was associated with a 9% (95% CI, 5%–13%) higher risk of ICU admission but was not significantly associated with higher risk of IMV or death. Other specified status (CCSR category indicating a need for specific medical support, such as a wheelchair or renal dialysis) was a frequent category among patients aged 40 to 64 and 65 or older and was associated with a 7% (1%–13%) and 4% (1%–6%) higher risk of death, respectively.

We found a dose–response association between the total number of underlying medical conditions and risk of severe COVID-19 illness ( Figure 2 ). Compared with patients with no documented underlying medical conditions, patients’ risk of death was 1.53 times (95% CI, 1.41–1.67) as high if they had 1 condition, 2.55 times (95% CI, 2.32–2.80) as high if they had 2 to 5 conditions, 3.29 times (95% CI, 2.98–3.63) as high if they had 6 to 10 conditions, and 3.82 times (95% CI, 3.45–4.23) as high if they had more than 10 conditions. Adjusted RRs for IMV ranged from 1.57 (95% CI, 1.45–1.70) with 1 condition to 4.47 (95% CI, 4.07–4.90) with more than 10 conditions. Adjusted risk ratios for ICU admission ranged from 1.32 (95% CI =1.27–1.36) for patients with 1 condition to 1.96 (95% CI, 1.82–2.11) for patients with more than 10 conditions .

In the first sensitivity analysis, performed by using all CCSR categories, we identified 6 additional frequent “indeterminate” CCSR categories: cardiac dysrhythmias (n = 124,367 [23.0%]), heart failure (n = 104,858 [19.4%]), other specified nervous system disorders (n = 89,929 [16.6%]; top ICD-10-CM code, metabolic encephalopathy), other specified and unspecified nutritional and metabolic disorders (n = 89,337 [16.5%]; top code, hypomagnesemia), coagulation and hemorrhagic disorders (n = 75,766 [14.0%]), and diseases of white blood cells (n = 57,765 [10.7%]). The risk ratio estimates of most previously found underlying conditions were lower with the inclusion of these 6 conditions in the full models.

In the second sensitivity analysis, which used a subset of 278,215 patients with at least 1 encounter in the PHD-SR before their first COVID-19 hospitalization, diabetes without complication was associated with an 8% (95% CI, 5%–12%) higher risk of death, a 13% (95% CI, 10%–17%) higher risk of IMV, and a 5% (95% CI, 4%–7%) higher risk of ICU admission; sleep–wake disorders were associated with an 8% (95% CI, 5%–11%) higher risk of IMV. Anxiety and fear-related disorders were associated with a 2% (95% CI, 0.4%–4%) higher risk of ICU admission but not with a higher risk of death or IMV, on the basis of the full model.

Among 4,899,447 hospitalized US adults in the PHD-SR, 540,667 (11.0%) were hospitalized with COVID-19. Among patients hospitalized with COVID-19, we found 18 most frequent underlying conditions, of which 9 were associated with severe COVID-19 illness. These 9 conditions were both prevalent in the sample (affecting 81.9% of inpatients with COVID-19) and associated with severe COVID-19 illness, suggesting a high impact at the population level. Essential hypertension and disorders of lipid metabolism were the most frequent conditions, whereas obesity, anxiety and fear-related disorders, diabetes with complication, and CKD were the strongest risk factors for death among hospitalized patients with COVID-19. This analysis builds on 2 previous analyses using data from the PHD-SR (3,5), by including more underlying medical conditions in the frequency analysis (274 CCSR categories), including 9 additional months of data, and examining outcomes other than mortality. The analysis also shows that the total number of underlying conditions is strongly associated with severe COVID-19 illness.

The percentage of the US adult population known to have 2 or more underlying medical conditions ranges from approximately 38% to 64% by state (12). Previous studies demonstrated that patients with medically attended COVID-19 often had multiple underlying medical conditions (6). However, studies have rarely focused on the effect of the number of conditions on severe COVID-19 illness. We found that the risk of death, IMV, and ICU admission was often incrementally higher with a higher number of underlying medical conditions. Our finding that the number of underlying medical conditions is itself a risk factor for severe disease from COVID-19 identifies a population that has not been clearly described in previous literature.

Our results reinforce previous findings of higher risk of severe illness associated with diabetes with complication (13), obesity (4,14), coronary atherosclerosis and other heart disease (4), chronic obstructive pulmonary disease (15), and neurocognitive disorders (3,4). Additionally, we identified several conditions for which little data exist regarding risk for severe COVID-19 illness, such as thyroid disorders (including hypothyroidism) and anxiety and fear-related disorders.

Hypertension and disorders of lipid metabolism (the most prevalent conditions), and obesity and diabetes with complication (strong risk factors for death, IMV, and ICU admission) are associated with well-described hormonal and inflammatory pathways, also previously shown to be risk factors for severe COVID-19 illness (16). High baseline prevalence of obesity and diabetes, combined with their association with severe COVID-19 illness, suggest that these 2 conditions could have an outsized impact on the population with COVID-19. Prevention and treatment of these conditions may be an important strategy that could improve national resilience against chronic threats and acute crises. Essential hypertension, for which evidence is mixed on its association with severe COVID-19 illness (1), was shown in our analysis to be the most prevalent condition. It was found to be associated with a higher risk of severe COVID-19 illness only among patients aged 18 to 39 but with a lower risk of severe COVID-19 illness among older patients and in the full sample. This finding supports a possible link with severe COVID-19 illness and identifies essential hypertension as a risk factor, especially among younger patients.

Uncomplicated diabetes was found to be negatively associated with the risk of death and IMV. A positive association with risk of ICU admission was found only among patients aged 18 to 39. A previous study showed that although type 2 diabetes was a risk factor for mortality from severe COVID-19 illness, patients with diabetes and well-controlled blood glucose had lower mortality than those with diabetes and poorly controlled blood glucose (13). Our sensitivity analysis of a subset of patients with pre-COVID encounters identified a higher relative risk of death associated with uncomplicated diabetes present before the first COVID hospitalization. Coding bias (uncomplicated diabetes may be less frequently coded in hospitalizations with severe outcomes) (17) or reverse causality (diabetes complications arising from COVID-19 illness or treatment) (18) could explain this finding.

Anxiety and fear-related disorders were a prevalent condition in our sample; they were also the second highest risk factor for death among the underlying conditions considered in our study. The reasons for this finding are likely multifactorial and may include a reduced ability to prevent infection among patients with anxiety disorders, the immunomodulatory and/or cardiovascular effects of medications used to treat these disorders, or severe COVID-19 illness exacerbating anxiety disorders (19,20). In a subset of patients with pre-COVID encounters in our study, anxiety diagnosed before COVID-19 was not independently associated with death or IMV during COVID-19 hospitalization and, therefore, it is also plausible that anxiety was diagnosed during COVID-19 illness and may be a resulting sequela of COVID-19 (21). Future studies could explore the temporal and causal associations between anxiety disorders and severe COVID-19 illness.

Our finding of a positive association of CKD and coronary atherosclerosis and other heart disease with severe COVID-19 illness has been well described at the epidemiologic level (22). We also found that people with neurocognitive disorders (including dementia and Alzheimer’s disease) were at a higher risk of severe COVID-19 illness, which could be associated with difficulties in access to care and difficulties in following safeguarding procedures (23). Our finding of an association of anemia (specifically, anemia in CKD) with severe COVID-19 illness may be driven by a reduced capacity to respond to acute infections in people with this condition (24).

Asthma diagnosis was present among 10.5% of hospitalized patients with COVID-19 in PHD-SR, which is higher than the 8.0% national prevalence of asthma in 2019 (25). At the same time, we found asthma to be associated with a lower risk of death in the full sample; a positive association with ICU admission was found only among patients younger than 40. This finding supports the mixed evidence on asthma as a risk factor for severe COVID-19 illness (1), although the association between asthma and severe COVID-19 illness could differ by the degree of asthma severity (26).

A sensitivity analysis revealed 6 “indeterminate” conditions (such as coagulation and hemorrhagic disorders, cardiac dysrhythmias, and heart failure) that were both frequent and associated with at least 1 severe COVID-19 illness outcome. Without better information on the temporality of these 6 conditions relative to the COVID-19 illness, we were unable to determine whether these were truly underlying conditions (27,28). Our second sensitivity analysis, restricted to 278,215 patients with encounters that preceded the first COVID-19 encounter, found a positive association of sleep–wake disorders and uncomplicated diabetes with severe COVID-19 illness. Weaker associations of other frequent conditions with COVID-19 illness in this analysis (compared with the main results) could be due to under-ascertainment of certain conditions that resulted from using data only for pre-COVID encounters.

Our study has limitations. First, using ICD-10-CM diagnostic codes to identify COVID-19 cases might result in misclassification, although COVID-19 codes in PHD-SR showed high sensitivity and specificity with SARS-CoV-2 test results (29). Second, ICU risk estimates could be biased if ICU admission reflected factors other than severity of COVID-19, such as anticipation of future severity among health care professionals. Third, because our data were observational, we could not establish causal associations between the underlying conditions and severe COVID-19 illness. Fourth, relying on ICD-10-CM codes to identify underlying medical conditions may have underestimated their prevalence. For example, obesity was diagnosed in 33.0% of the patients, which is possibly an underestimate of this condition, given the national prevalence of 42.4% in 2017–2018 (30) and the prevalence of 50.8% among patients with available height and weight data in PHD-SR (14). Fifth, prior literature shows evidence of both increased documentation (31) and underdiagnosis of certain chronic conditions among patients with more severe illness (17). Sixth, the interrelation of the conditions made it difficult to obtain independent associations, which could explain why certain conditions (disorders of lipid metabolism, sleep–wake disorders, esophageal disorders, and depressive disorders) had a positive association with COVID-19 illness when not adjusted for other conditions and a negative association when adjusted for other conditions. These differences could be explained by 1) confounding in the restricted model, 2) lack of independent effects in the full model, or 3) potential overadjustment in the full model by including variables that were on the causal pathway between the condition of interest and the outcome. Seventh, we were unable to assess the associations of current treatment modalities or medications for underlying medical conditions and severe COVID-19 illness because that information was not available in detail. Finally, including only the most frequent underlying medical conditions in the estimations of risk could have caused us to miss less prevalent risk factors of severity; however, conditions of any frequency were accounted for in the “number of conditions” predictor.

Our study found that 9 of 18 frequent underlying medical conditions among adults hospitalized with COVID-19 were associated with severe illness. Combined with the high prevalence of these conditions (affecting 81.9% of hospitalized patients with COVID-19 in PHD-SR), this finding suggests a potentially high impact at the population level. The highest risk of severe COVID-19 illness was associated with obesity, anxiety and fear-related disorders, diabetes with complication, CKD, and neurocognitive disorders. Among patients younger than 40, essential hypertension was also a risk factor for death. The total number of underlying medical conditions was a strong risk factor of severe COVID-19 illness. Preventing COVID-19 in populations with these conditions and multiple conditions should remain a public health priority, along with targeted mitigation efforts and ensuring high uptake of vaccine, when available, in these people and their close contacts.

The following additional information is available from the corresponding author upon request: a figure showing the distribution of the number of underlying medical conditions among adults hospitalized with COVID-19 in PHD-SR; a table showing the most frequent underlying medical conditions among hospitalized adults in PHD-SR with a COVID-19 visit, by severity of COVID-19 illness; and 4 tables showing detailed results of the 2 sensitivity analyses.

The authors thank Sachin Agnihotri, MS, Indira Srinivasan, MS, David Nitschke, BS, and Kimberly Riggle, BBA, of the CDC COVID-19 Response Data, Analytics, and Visualization Task Force; and John House, MS, (Premier Inc.) for facilitating access to these data. We thank Jennifer M. Nelson, MD, and Nickolas T. Agathis, MD, of the CDC COVID-19 Community Interventions and Critical Populations Task Force for contributing to the clinical review of underlying medical conditions. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of CDC or the US Public Health Service. The authors have no funding to disclose. No copyrighted materials were used in this article.

Corresponding Author: Lyudmyla Kompaniyets, PhD, Centers for Disease Control and Prevention, 4770 Buford Hwy, MS S107-5, Atlanta GA 30341. Telephone: 404-498-0611. Email: [email protected] .

Author Affiliations: 1 COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia. 2 US Public Health Service Commissioned Corps, Rockville, Maryland. 3 Epidemic Intelligence Service, Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, Georgia.

• Centers for Disease Control and Prevention. Evidence used to update the list of underlying medical conditions that increase a person’s risk of severe illness from COVID-19. Updated March 29, 2021. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/evidence-table.html. Accessed April 26, 2021.
• Ko JY, Danielson ML, Town M, Derado G, Greenlund KJ, Daily Kirley P, et al. ; COVID-NET Surveillance Team. Risk factors for COVID-19-associated hospitalization: COVID-19-Associated Hospitalization Surveillance Network and Behavioral Risk Factor Surveillance System. Clin Infect Dis 2020;ciaa1419. CrossRef external icon PubMed external icon
• Rosenthal N, Cao Z, Gundrum J, Sianis J, Safo S. Risk factors associated with in-hospital mortality in a US national sample of patients with COVID-19. JAMA Netw Open 2020;3(12):e2029058. CrossRef external icon PubMed external icon
• Kim L, Garg S, O’Halloran A, Whitaker M, Pham H, Anderson EJ, et al. Risk factors for intensive care unit admission and in-hospital mortality among hospitalized adults identified through the U.S. Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET). Clin Infect Dis 2021;72(9):e206–14. CrossRef external icon PubMed external icon
• Goodman KE, Magder LS, Baghdadi JD, Pineles L, Levine AR, Perencevich EN, et al. Impact of sex and metabolic comorbidities on COVID-19 mortality risk across age groups: 66,646 inpatients across 613 U.S. hospitals. Clin Infect Dis 2020;ciaa1787. CrossRef external icon PubMed external icon
• Iaccarino G, Grassi G, Borghi C, Ferri C, Salvetti M, Volpe M, et al. ; SARS-RAS Investigators. Age and multimorbidity predict death among COVID-19 patients: results of the SARS–RAS study of the Italian Society of Hypertension. Hypertension 2020;76(2):366–72. CrossRef external icon PubMed external icon
• Premier. Premier Healthcare Database (COVID-19): data that informs and performs. 2020. http://offers.premierinc.com/rs/381-NBB-525/images/PHD_COVID-19_White_Paper.pdf. Accessed February 8, 2021.
• Centers for Disease Control and Prevention. New ICD-10-CM code for the 2019 novel coronavirus (COVID-19), April 1, 2020. 2020. https://www.cdc.gov/nchs/data/icd/Announcement-New-ICD-code-for-coronavirus-3-18-2020.pdf. Accessed April 26, 2021.
• Centers for Disease Control and Prevention. Coding encounters related to COVID-19 coronavirus outbreak, February 20, 2020. 2020. https://www.cdc.gov/nchs/data/icd/ICD-10-CM-Official-Coding-Gudance-Interim-Advice-coronavirus-feb-20-2020.pdf. Accessed June 7, 2021.
• Agency for Healthcare Research and Quality. Chronic Condition Indicator (CCI) for ICD-10-CM (beta version). https://www.hcup-us.ahrq.gov/toolssoftware/chronic_icd10/chronic_icd10.jsp. Accessed April 26, 2021.
• Agency for Healthcare Research and Quality. Clinical Classifications Software Refined (CCSR). https://www.hcup-us.ahrq.gov/toolssoftware/ccsr/ccs_refined.jsp. Accessed April 26, 2021.
• Newman D, Tong M, Levine E, Kishore S. Prevalence of multiple chronic conditions by U.S. state and territory, 2017. PLoS One 2020;15(5):e0232346. CrossRef external icon PubMed external icon
• Zhu L, She ZG, Cheng X, Qin JJ, Zhang XJ, Cai J, et al. Association of blood glucose control and outcomes in patients with COVID-19 and pre-existing type 2 diabetes. Cell Metab 2020;31(6):1068–1077.e3. CrossRef external icon PubMed external icon
• Kompaniyets L, Goodman AB, Belay B, Freedman DS, Sucosky MS, Lange SJ, et al. Body mass index and risk for COVID-19-related hospitalization, intensive care unit admission, invasive mechanical ventilation, and death — United States, March–December 2020. MMWR Morb Mortal Wkly Rep 2021;70(10):355–61. CrossRef external icon PubMed external icon
• Lippi G, Henry BM. Chronic obstructive pulmonary disease is associated with severe coronavirus disease 2019 (COVID-19). Respir Med 2020;167:105941. CrossRef external icon PubMed external icon
• Guisado-Vasco P, Cano-Megías M, Rodríguez-López M, de-Luna-Boquera IM, Carnevali-Ruiz D; Immunosuppressants Against COVID-19 Working Team. COVID-19 and metabolic syndrome: NF-κB activation. Crossroads. Trends Endocrinol Metab 2020;31(11):802–3. CrossRef external icon PubMed external icon
• Weir RE Jr, Lyttle CS, Meltzer DO, Dong TS, Ruhnke GW. The relative ability of comorbidity ascertainment methodologies to predict in-hospital mortality among hospitalized community-acquired pneumonia patients. Med Care 2018;56(11):950–5. CrossRef external icon PubMed external icon
• Pal R, Bhadada SK. COVID-19 and diabetes mellitus: an unholy interaction of two pandemics. Diabetes Metab Syndr 2020;14(4):513–7. CrossRef external icon PubMed external icon
• Glaus J, von Känel R, Lasserre AM, Strippoli MF, Vandeleur CL, Castelao E, et al. The bidirectional relationship between anxiety disorders and circulating levels of inflammatory markers: results from a large longitudinal population-based study. Depress Anxiety 2018;35(4):360–71. CrossRef external icon PubMed external icon
• Lega I, Nisticò L, Palmieri L, Caroppo E, Lo Noce C, Donfrancesco C, et al. ; Italian National Institute of Health COVID-19 Mortality Group. Psychiatric disorders among hospitalized patients deceased with COVID-19 in Italy. EClinicalMedicine 2021;100854. CrossRef external icon PubMed external icon
• Taquet M, Geddes JR, Husain M, Luciano S, Harrison PJ. 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records. Lancet Psychiatry 2021;8(5):416–27. CrossRef external icon PubMed external icon
• Naeini MB, Sahebi M, Nikbakht F, Jamshidi Z, Ahmadimanesh M, Hashemi M, et al. A meta-meta-analysis: evaluation of meta-analyses published in the effectiveness of cardiovascular comorbidities on the severity of COVID-19. Obes Med 2021;22:100323. CrossRef external icon PubMed external icon
• Mukaetova-Ladinska EB, Kronenberg G, Raha-Chowdhury R. COVID-19 and neurocognitive disorders. Curr Opin Psychiatry 2021;34(2):149–56. CrossRef external icon PubMed external icon
• Khaled SA, Hafez AA. Aplastic anemia and COVID-19: how to break the vicious circuit? Am J Blood Res 2020;10(4):60–7. PubMed external icon
• Centers for Disease Control and Prevention. Most recent national asthma data. https://www.cdc.gov/asthma/most_recent_national_asthma_data.htm. Accessed May 23, 2021.
• Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature 2020;584(7821):430–6. CrossRef external icon PubMed external icon
• Goldhaber SZ. Risk factors for venous thromboembolism. J Am Coll Cardiol 2010;56(1):1–7. CrossRef external icon PubMed external icon
• Liu J, Han P, Wu J, Gong J, Tian D. Prevalence and predictive value of hypocalcemia in severe COVID-19 patients. J Infect Public Health 2020;13(9):1224–8. CrossRef external icon PubMed external icon
• Kadri SS, Gundrum J, Warner S, Cao Z, Babiker A, Klompas M, et al. Uptake and accuracy of the diagnosis code for COVID-19 among US hospitalizations. JAMA 2020;324(24):2553–4. CrossRef external icon PubMed external icon
• Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of obesity and severe obesity among adults: United States, 2017–2018. NCHS Data Brief 2020;(360):1–8. PubMed external icon
• Chong WF, Ding YY, Heng BH. A comparison of comorbidities obtained from hospital administrative data and medical charts in older patients with pneumonia. BMC Health Serv Res 2011;11(1):105. CrossRef external icon PubMed external icon

Abbreviation: IQR, interquartile range. a Some categories may not add up to 100% because of rounding. b Columns are not mutually exclusive. c Underlying medical conditions were defined by 1) using Chronic Condition Indicator to identify chronic International Classification of Diseases, Tenth Revision, Clinical Modification codes; 2) aggregating the codes into a smaller number of meaningful categories using the Clinical Classifications Software Refined (CCSR); 3) a clinical review of CCSR categories that classified the CCSR codes as “likely underlying,” “indeterminate,” and “likely acute”; and 4) including only “likely underlying” CCSR categories and excluding “indeterminate” and “likely acute” CCSR categories.

Abbreviations: ICU, intensive care unit; IMV, invasive mechanical ventilation; CCSR, Clinical Classifications Software Refined. a Underlying medical conditions were defined by 1) using Chronic Condition Indicator to identify chronic International Classification of Diseases, Tenth Revision, Clinical Modification codes; 2) aggregating the codes into a smaller number of meaningful categories by using the CCSR; 3) a clinical review of CCSR categories that classified the CCSR codes as “likely underlying,” “indeterminate,” and “likely acute”; and 4) including only “likely underlying” CCSR categories and excluding “indeterminate” and “likely acute” CCSR categories. b The reference category for each condition is the absence of that condition; the reference category for diabetes with complication and diabetes without complication is the absence of diabetes. c Full model: Each column includes the results of a single generalized linear model (with Poisson distribution and log link function) that includes all 18 of the most frequent underlying medical conditions (reference: absence of the condition), age group, sex, race/ethnicity, payer type, hospital urbanicity, US Census region of hospital, admission month, and admission month squared. d Restricted model: Each column includes the results of 18 general linear models (with Poisson distribution and log link function), each including only the underlying medical condition (reference: absence of the condition), age group, sex, race/ethnicity, payer type, hospital urbanicity, US Census region of hospital, admission month, and admission month squared. Patients who died without using ICU care or IMV were excluded from the sample when estimating the model with the outcome of ICU care or IMV, respectively. e Based on the results from the full model.

Abbreviations: ICU, intensive care unit; IMV, invasive mechanical ventilation; CCSR, Clinical Classifications Software Refined. a Underlying medical conditions were defined by 1) using Chronic Condition Indicator to identify chronic International Classification of Diseases, Tenth Revision, Clinical Modification codes; 2) aggregating the codes into a smaller number of meaningful categories by using the CCSR; 3) a clinical review of CCSR categories that classified the CCSR codes as “likely underlying,” “indeterminate,” and “likely acute”; 4) including only “likely underlying” CCSR categories and excluding “indeterminate” and “likely acute” CCSR categories. b The reference category for each condition is the absence of that condition; the reference category for diabetes with complication and diabetes without complication is the absence of diabetes. c Each column includes the results of a generalized linear model (with Poisson distribution and log link function), stratified by age group (18–39, 40–64, ≥65) that includes frequent (present in ≥10.0% of patients) underlying medical conditions, age, sex, race/ethnicity, payer type, hospital urbanicity, US Census region of hospital, admission month, and admission month squared. Patients who died without using ICU care or IMV were excluded from the sample when estimating the model with the outcome of ICU care or IMV, respectively.

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What It's Like to Do an MD-PhD Program

New section.

Two medical students answer questions about what it's like to do an MD-PhD program.

Elias (Eli) Wisdom

Undergraduate:   Pacific University, Oregon Major:   BS, Biology Medical school:  Oregon Health & Science University (OHSU) Anticipated Graduation Year:  2028 Bio: Eli Wisdom is an MD-PhD student at Oregon Health & Science University (OHSU) studying the molecular mechanisms of Parkinson’s Disease. He grew up in the small rural town of La Grande, Oregon,  where he gained a deep appreciation for community and service and a fascination with the natural world. At Pacific University, he completed his degree in Biology while also a playing varsity baseball. After graduating he was as an Associate in Neuroscience at Yale School of Medicine for two years before starting an MD-PhD program. Outside of school, he enjoys competing in triathlons, camping, and spending time with family.

Sreya Sanyal

Undergraduate:  New Jersey Institute of Technology        Major:  Biology & History Double Major Medical school:   Rutgers Robert Wood Johnson Medical School Anticipated Graduation Year:  2031 Bio: Sreya Sanyal is a MD-PhD student at Robert Wood Johnson Medical School and Princeton University. She is Bengali and she aspires to become a laboratory principal investigator in the field of oncology. Outside of academia, she enjoys singing, cooking, going to museums, and lifting at the gym.  

Why did you decide to pursue an MD-PhD program?

Eli:  As an undergraduate student, I found my first biomedical research experience to be quite thrilling and seriously considered pursuing a career in research. Medical school had surfaced as an opportunity, too, as I was deeply passionate about serving others and caring for the sick, but I felt that basic science research was the backbone of advancing clinical care. I first learned that combined MD-PhD programs existed in my senior year when I was taking part in a summer research program at another academic institute. I learned that in a dual-degree program, I could become rigorously trained as a research scientist and as a physician – and could do both in my future career. To learn more, I reached out to a few physician-scientists to who shared how much they loved their careers. In the clinic, their patients and associated medical problems provided new ideas for exploration in the laboratory. And in the laboratory, the insights they gained could inform the way they treated their patients. Sreya:  I’ve wanted to become an oncologist ever since I was 11 and my mother died from gastric cancer. When I shadowed hematologist oncologists in academic settings, I became more interested in their work in clinical trials and research. Entering college, I explored translational research through my undergraduate biomedical engineering lab experiences. As I met more people in the field of drug development and oncology, I realized that I wanted to be at the cutting edge of this work, but I still had the desire to see patients. Through a lot of soul searching and luck, I was able to embark on a career in medical research by pursing an MD-PhD. Using my training as a physician-scientist, I plan to establish my own lab or work in other ways to improve translational research in the oncological space.

What kinds of career options does the MD-PhD program give you?

Eli:   From my experience, rigorous training in medicine and scientific research prepares you best for a career in academic medicine. This often means working at a large teaching hospital, where you have an opportunity to conduct independent scientific research, care for patients, and teach students. While it can differ depending on the medical specialty or the individual, a typical physician-scientist may spend 80% of their time conducting research and 20% caring for patients.  However, there are many other career paths available to MD-PhD graduates. Students may also pursue careers working for private research organizations, pharmaceutical and biotechnology companies, or government agencies.  Sreya:  In my experience as an MD-PhD student interested in oncology, I have a wide array of career options to explore. As a clinician-scientist, I can lead research teams and conduct studies in cancer biology, treatment approaches, and translational medicine. In these roles, I can also mentor students interested in my field, allowing me to advance scientific knowledge while shaping the next generation of researchers. Alternatively, I could directly impact patients' lives by increasing my clinical time spent as an oncologist, developing personalized treatment plans, and contributing to clinical trials. The pharmaceutical and biotechnology industries also present exciting opportunities for me where I would be able to work on drug development, clinical research, or medical affairs, playing an essential role in bringing innovative therapies to market. With my combined medical and research expertise, I am well-equipped to make a meaningful difference in oncology through various rewarding career paths.

What type of research experience did you have before entering the program?

Eli: I attended a liberal arts college where students engaged in scientific research through 2–4-month long classes, which were combined lecture and laboratory experiences. Building on excitement from these courses, I pursued a summer research internship at a large biomedical research institute the summer prior to my senior year. I loved this initial exposure to working in a high-powered scientific research center. From working in state-of-the-art reach laboratories, to solving scientific problems in creative ways, and watching physicians bounce between research and patient care – I was hooked.  Sreya:  Before starting my current program, I had two significant research experiences. First, I worked in a lab that focused on creating materials for drug delivery in the field of biomedical engineering. We used special gels to deliver important substances to specific parts of the body, which had significant effects on the surrounding tissues, such as promoting blood vessel growth and blocking certain enzymes. I spent about 10 hours a week for three years in this lab and contributed to three published papers.

Secondly, I worked at a research institute where I studied mice that were genetically modified to show signs of anthrax toxin exposure. These modified toxins could be controlled to specifically target tumor cells in the body. I dedicated 40 hours a week to this research, and as a result, we have two research papers in progress for publication

How did you prepare to apply to MD-PhD programs?

Eli: Since I had played varsity baseball throughout college (which was impactful training in its own right,) I had limited time for research as an undergraduate. So, I decided to pursue an extended research position before applying to MD-PhD programs. After sending several emails to laboratories across the US and applying to many formal postbacc research programs, I took a two-year job as a postgraduate researcher at an academic research institute. During my time working on a project in a laboratory, I also volunteered at the connected hospital. This allowed me to experience what it was like to conduct independent research during the first part of my day, and care for patients in the afternoon. This experience only confirmed my deeply held passions for both medicine and science, but also exposed me to the challenges that both careers entailed. I felt much more confident in my decision to pursue a dual-degree knowing these insights.

What is your favorite part about being an MD-PhD student?

Eli: Thus far, my favorite part of my training has been directly experiencing the intersection of clinical care and research. During the first two years of the MD-PhD, I was mainly focused on medical school courses and preparing for the first board exam. But now, as I am beginning my Ph.D., I am realizing how medical school has broadened my perspective. When I read research papers or craft a plan to tackle a hypothesis, I feel empowered with the knowledge I learned in my didactic medical school courses. For example, during one of my Ph.D. research rotations, a scientist was having difficulty delivering a therapeutic to the brains of the mice they were studying. Immediately I recalled from my medical school courses how mannitol could be co-infused to transiently open the blood-brain barrier for drug delivery. It could easily be translated to this scenario. Similarly, my experiences with clinic patients have benefited from my MD-PhD training. Often, it can be as simple as the ability to explain to a patient or their family, the exact mechanism of a drug and the reason it could be effective for their ailment. Or, informing them about current basic science efforts in the field or current clinical trials they might be eligible for. As I advance further into my training, I am eager to see how clinical care and laboratory research can become even more intertwined. Sreya:  I am very excited to learn new techniques and approaches to my field of interest. I am also glad that for MD-PhD students in my program, there is a huge emphasis on lifestyle and work/life balance. Many students in my program have become engaged, or married, and are starting families, while many medical students may feel pressure to push these milestones off. Being an MD-PhD student is a huge commitment, so I am especially grateful for all of the personal and professional support my program has to offer.

What do you wish you’d known before you started the program?

Eli: I wish I had known how important it would be to keep an open mind about the research topics that interested me most. I began the MD-PhD program with a rigid focus on a certain topic, thinking that it was the only topic that gave me real excitement. It was also the topic I was most versed in and comfortable in. But during my medical school courses, I was suddenly overwhelmed with several fascinating questions and problems, that all seemed equally thrilling. It took a fair bit of mental wrestling with myself to broaden my own research interests and muster up the courage to explore a field I was fascinated with even if I didn’t have the most experience in it quite yet. Luckily, MD-PhD programs are usually quite supportive of students exploring new topics of interest and are eager to see you follow your motivations.

Sreya:  One of the most important aspects to consider for MD-PhD students is the idea that this path is a marathon, not a sprint. There is a lot of temptation to overload on clubs, leadership, research, etc., to keep pace with MD colleagues, but in the long run, an MD-PhD is about the quality and depth of training. It’s important to build healthy habits, strong social relationships, and enjoy activities in a sustainable manner since MD-PhD students have to do another graduate degree on top of medical training.

What advice would you give a student considering an MD-PhD program?

Eli:  My advice is to accrue as many experiences as you can in medicine and research before applying. Through these, you can understand if pursuing both an MD and a PhD is the best fit for you, or, if you’d be completely satisfied pursuing a career with only training in one discipline. If you can, shadow physicians at both large academic hospitals and private practices. This can teach you if you’d enjoy treating patients daily and give you insight into how your experience will vary based on the setting. Seek out research experiences as early as possible. This may be difficult to procure, but having a longitudinal research experience that encompasses the successes and failures of science will inform you if this should be your future career. If you can, ask for opportunities to experience what it’s like to write a grant or an academic research article. These are not easy to write, yet they encompass a significant amount of time for professional physician-scientists, so, it is important to learn if you’d enjoy (or at least tolerate) the academic writing load. Lastly, don’t be intimidated by the amount time it takes to complete an MD-PhD. Yes, it is longer than most post-graduate training and takes up a significant portion of your early life. But it is a unique and worthy career path that is much needed in service to society. Sreya:  My advice to anyone considering an MD-PhD would be to get both a variety and depth of research experiences. As a student, it’s very easy to continue down a path you already started, but you must try to explore before you commit to any one approach. MD-PhD programs appreciate students who know what they would like to research and the only way to discover this is to pursue broad research experiences. That said, once you find what drives and excites you, it’s important to stick with it and maintain good relationships with your PIs and mentors. It’s a small world among physician-scientists, so depth of work and networking will help you achieve and further your goals. Above all, remember that an MD-PhD is not necessary to do research as a physician. The goal of an MD-PhD is to provide the specific training needed to conduct research above and beyond what a physician alone can do. In this case, you must really be sure that research is fulfilling and allows you to achieve your career goals when applying to programs, as they will ask you about your aspirations.

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Translating Pre-Medical Experiences into Clinical Skills

Michael Foster | May 3, 2023

Your time before medical school is golden. It is a unique time to explore where your passions lie (both within and beyond medicine) and lay a strong foundation of the inter- and intrapersonal skills needed for you to be the best physician you can be. The best advice is simple: challenge yourself, be honest, and have fun! […]

The AAMC offers trusted resources and services to help you navigate the journey from premed to residency and beyond.

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Why a PhD in Medical Sciences?

Our Ph.D. program in Medical Sciences provides advanced training with the goal of preparing students for research-based careers. Areas of in-depth study are driven by faculty research and encompass clinically related fields such as diabetes mellitus, obesity, immunology and infectious disease, oncology, and other chronic health conditions.

Read abstracts of recent graduate student research projects .

Admissions Information

Program prerequisites.

• BS, MS or equivalent degree from an accredited college of university
• GRE scores of at least 148 on quantitative reasoning and at least 150 on verbal reasoning
• An undergraduate GPA of 3.0 or higher
• Written statement of goals and objectives that identifies the applicant’s research and curriculum interests and explains how admission to the program will facilitate his/her professional objectives
• Current resume and three letters of recommendation
• If English is not the first language, the University requires a paper-based TOEFL score of at least 570, or at least 90 on the Internet-based TOEFL, or 6.5 on the IELTS

Admissions is selective and competitive, based on the number of available positions in the department laboratories and available faculty and facilities.

Degree Requirements

The Doctor of Philosophy in Medical Sciences requires a minimum of 43 credits including 9 credits of dissertation. The program is designed to be completed in 4 to 5 years. Program educational goals and courses can be viewed in the Course Catalog .

Required Courses (37 credits):

•  MMSC800 Preparing Research Proposals (2 cr)
• MMSC650 Medical Biochemistry (4 cr)
• MMSC691 Human Medical Genetics (3 cr)
• MMSC868 Research (12 cr)
• MMSC603 Research Design (3 cr)
• MMSC803/804 Seminar (4 cr) (taken 8 semesters: 4 semesters for 1 credit [803] and 4 semesters for 0 credit [804])
• MMSC969 Dissertation (9 cr)

Science Core Elective Courses (6 credits)

A preliminary exam is taken at end of year 1 that tests the student’s general knowledge base in Medical Sciences and their ability to critically evaluate scientific literature. The preliminary examination includes a written component followed by an oral component on a separate day.

A candidacy exam is taken at the end of year 2. The student will prepare a written and oral proposal for dissertation research that meets the requirements for an external grant proposal. The oral proposal meeting will include both a defense of the student's proposed research and an in-depth examination of the student's knowledge of their research specialization.

When the dissertation research is complete, all Medical Sciences faculty and students will be invited to attend the oral dissertation defense meetings. Following the oral presentation and questions from faculty in attendance, the Dissertation Committee will meet separately and vote on the outcome. The outcome will be presented to the student, along with any conditions or requirements for proposal or dissertation revisions. 

Tuition Rates

The 2023-2024 UD graduate student tuition rate per credit hour is $1,028. Research Assistant awards will be made for students that best fit the needs of the sponsoring faculty member. Teaching Assistant awards will be made for students prepared to teach and otherwise assist with undergraduate instruction. Students can also apply for internal funding, such as the competitive awards offered through the UD Research and Graduate Studies Office. Students can also apply for pre-doctoral support from funding agencies such as the American Heart Association. The sponsoring faculty member will work with the student to develop the proposal.

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Everything you need to know about pursuing a Ph.D. in Medical Science

Blog summary.

Ph.D. in medical sciences is a vast field of study that equips MBBS graduates with the skills and knowledge base required to diagnose and treat medical conditions in the human body. A medical professional takes a patient through an entire journey of treating a disease, right from its consultation, identification, diagnosis, treatment, and surgery (if required). The subspecialties available in the program are many and can be preferred according to each student's career interest. The subdisciplines include Public Health, Biomedicine, Dentistry, Nursing, Nutrition, Health Management, Veterinary Science, and many more. A Ph.D. in medicine degree will teach you to identify diseases and treat them promptly. 

Ph.D. in Medicine

Why consider a ph.d. in medical sciences, career opportunities after completion of phd, ph.d. program overview, ph.d. in medicine eligibility requirements, ph.d. in medicine enrollment, best ways to get admission to the ph.d. program.

Many might wonder what is a Doctorate in Medical Sciences. A Ph.D. in Medicine is crucially designed and structured in a way most suitable for aspiring doctors inclined toward research and academia. The subspecialties from which one can choose to do a doctorate are vast, and it purely depends on the interests and preferences of the students. The curriculum of each may vary on the specialization chosen and may include clinical research, independent study, group work, and lab work. The varied focus areas may include microbiology, immunology, pharmacology, reproductive issues, brain disorders, genetics, orthopedics, development disorders, etc. 

A Ph.D. in medical science means that the student gets exposure to other skills besides academic knowledge, like analytical skills, lateral thinking, technological abilities, accuracy, and attention to detail that will significantly help them in their career life. This Doctorate in Medicine, when obtained from Texila American University in academic partnership with the University of Central Nicaragua, helps students gain a comprehensive view of the subject wherein all the major components of medical science are covered. 

The program is offered for three years and may extend to five years, depending on the specialization chosen. It is aimed at individuals who have a zeal for expertise and conduct research in the field of medicine. It helps them gain 360-degree knowledge and a broader perspective of the science involved. Along with the academic skills, the students get the opportunity to polish their research and analytical and innovative skills that will significantly help them in their research work.

One might have heard the saying, "Jack of all Trades, but Master of None." A Ph.D. in medicine means the other way around. You get to master expertise in the field of medical science. It is meticulously designed to cover all the primary and essential criteria involved in medicine and seamlessly puts you on the path of research, dissertation, and thesis. It includes all the clinical and non-clinical streams, including neurology, genetics, and epidemics. Ultimately the students of the program get to choose their field of specialization in the third year of study upon completion of successful clinical work study in the initial years. 

The program aims to deliver the students with core competencies required to show excellence in research and development. The industrial demand for doctors who have completed a doctorate in medical sciences is very compelling in hospitals, pharmacies, research & development, biomedical, and pharmacology. The ultimatum is to equip the students with the requisite communicative, analytical, and competent skills for the amicable completion of the research work.

The profession of being a doctor is a tough and engaging one; however, the profile is advantageous and satisfactory. Doctors with academic knowledge are expected to have empathy, passion, good communication, and cooperation with patients and their peers. Graduates get lucrative opportunities in research & development, scientific study, the biomedical industry, and government-aided and initiated schemes for medical health.

Doctors who complete the doctorate program can become one of the below-mentioned career profiles based on their area of interest and focus of study.

• Diagnostic molecular scientist
• Epidemiologist
• Biostatistician
• Biomedical chemist
• Health information specialist
• Allied health manager
• Pediatrician
• Health psychologist
• Orthopedist
• Radiologist
• Occupational therapist

A Ph.D. in medical sciences program envisions its students transforming into competent physicians and skilled scientists. Becoming a successful doctor after completing the program depends on various factors:

• Clinical requirements
• Progress of your research work
• Time is taken to mold yourself into an independent investigator and
• Other Ph.D. requirements

The initial years of the course cover mastering basic sciences, followed by an intense and rigorous Ph.D. and clinical training period. A typical Ph.D. training involves the completion of coursework, performing dissertation research, completing comprehensive exams, and thesis defense. In this course, you will be expected to conduct a lot of research and thesis writing. It will also offer networking opportunities through workshops, seminars, discussion sessions, and student retreats. 

The curriculum has balanced coverage of theory and practical projects, resulting in the best understanding of the courseware. The subjects mainly involve the study of:

• Research Methodology
• Advances in Physiology and Microbiology
• Advances in Medicines
• Advances in Pharmacology and Anatomy
• Stem Cells and Regeneration
• Hospital Waste and Disposal management
• Biochemistry 
• Application of medical sciences 
• Research Thesis

A student who wants to pursue a Ph.D. doctorate has to complete the following requirements:

• Candidates must have completed an MD/ MS with a decent score from a university recognized and approved by the Medical Council of India.
• Candidates who have secured a Diploma in National Board (DNB) in any subject related to medical science are also eligible for admission.
• Candidates who have graduated with a PG degree like an M. Optometry or M. Sc from any recognized university with the streams of pharmacology, microbiology, anatomy, physiology, biochemistry, or any related stream are considered eligible for admission.
• Candidates may also be required to be registered with the Medical Council of their locality.
• Candidates must possess work experience in their specialty after completing their PG degree.

A medical Ph.D. program is gaining more recognition for the convenience it offers with the perfect blend of knowledge. You must successfully clear the All-India Entrance examination that tests applicants' research and medical science skills. Upon passing the test, you will have to impress the panel of judges who will interview you based on your research interest and medical specialty. Once you are through with the program's eligibility requirements, you can proceed with the admission process to start a fast-paced and rewarding career. 

• Gain substantive research experience by doing quality research. The thesis and research projects you worked on will impress your interview committee to know why you chose to do a Ph.D.
• Avail of considerable clinical experience in the research and medicine field you choose to pursue. Clinical exposure and lab technicality knowledge is a must-haves to prove your efficiency in handling the Ph.D. courseware and curriculum.
• Shadowing experience is requisite that can be effectively done by passively observing a doctor who does clinical practice. This will help you gain knowledge that can later be put to great use while doing your research work.

When you choose to do a Ph.D. in Medical Sciences , you are about to get a chance to be part of one of the most demanded and compelling career choices globally. Join the team that holds the platform for medical exploration, scientific discovery, and medical intervention. It will land you in a career that blends research and medicine. It also implies that you will gain extensive research experience, contribute widely to publications, be mentored by industry experts, and gain valuable shadowing experience. Register with Texila American University in academic partnership with the University of Central Nicaragua for your Ph.D. in medical sciences and experience your career reaching maximum heights.

Ph.D. in medical sciences is a vast field of study that equips MBBS graduates with the skills and knowledge base required to diagnose and treat medical conditions in the human body. Read more: https://t.co/45SCANPCKr #PhD #MedicalScience #Medicine #TexilaAmericanUniversity #UCN pic.twitter.com/L0UCKbZ0mS — Texila American University - Post Graduate (@TexilaPG) October 6, 2022

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The AIM PhD track prepares the next generation of leaders at the intersection of artificial intelligence and medicine. The program’s mission is to train exceptional computational students, harnessing large-scale biomedical data and cutting-edge AI methods, to create new technologies and clinically impactful research that transform medicine around the world, increasing both the quality and equity of health outcomes.

The BIG PhD track trains the next generation of leaders in the field of bioinformatics and genomics. Our mission is to provide BIG graduate students with the tools to conduct original research and the ability to develop novel approaches and new technologies to address fundamental biological questions, many of which will facilitate translation solutions to challenging problems in biomedicine and health. (68 Students | 78 Faculty)

The BBS graduate research training is interdisciplinary, with a concentration in one or more of the following areas: biochemistry and proteomics, cell and molecular biology, computational biology, developmental biology, genetics and genomics, human biology and disease, microbial biology and pathogenesis, molecular neurosciences, physiology, pharmacology, regenerative biology and structural biology. The methods and experimental approaches used to address questions within these areas range from the techniques of molecular biology, protein chemistry, cell biology and biophysics to those of molecular and developmental genetics.

Our goal is to educate scientists in investigative and academic medicine, preparing them to contribute to immunological research with a full awareness of the potential impact of immunology. Our program combines an education in basic biology, a sophisticated training in immunology, and exposure to the immunological and non-immunological problems of disease. (70 Students | 142 Faculty)

Researchers at Harvard University are working on all these biomedical problems. They conduct basic research defining new molecular structures of viruses and virus-encoded enzymes, new mechanisms within cells for molecular and organelle trafficking and function, and new mechanisms that control cell growth. Harvard researchers are among the world leaders in the design and testing of AIDS, genital herpes, and smallpox vaccines. The Harvard Program in Virology provides extraordinary opportunities to conduct graduate study for the Ph.D. degree in these exciting areas of biomedical science. (61 Students | 49 Faculty)

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We adapt our curriculum, resources and mentoring styles to the individual needs of a diverse next generation of scientists, who are shaping the world through scientific discovery, policy and health.

Welcome from RAJESH C. MIRANDA, PhD

On behalf of the Texas A&M School of Medicine’s graduate faculty and the Graduate Program Executive Committee, welcome to the Medical Sciences Office of Graduate Studies! We are a collegial team of faculty, students, staff and administration—all committed to fostering an exceptional, inclusive and rewarding research and training environment.

The graduate program in Medical Sciences equips each new generation of aspiring scientists with the skills to identify and solve important health problems. Under faculty guidance, our trainees will engage in rigorous and original scholarship supplemented by coursework tailored to fit individual needs. Trainees have an opportunity to focus their scholarly efforts on many important biomedical problems including infectious diseases, cancer, neuro-degenerative diseases and trauma, substance use and psychiatric disorders, heart and lymphatic disease, to name a few. It is expected that this original scholarship of our trainees will be disseminated in rigorous, peer-reviewed scientific journals and have an impact on the trainee’s scientific discipline. Trainees are also expected to participate in national and international scientific conferences, build professional networks, and seek leadership roles, both within TAMU and in professional scientific societies. An active and vibrant graduate student organization (GSO) engages in a program of professional development activities, research retreats and symposia and also provides a robust mechanism for shared governance and a conduit for feedback to the graduate program and to the faculty.

The School of Medicine at Texas A&M University is part of a vibrant group of 17 schools and colleges and 92 doctoral programs on a contiguous campus. Annual research expenditures at TAMU exceed $1.1 billion, making this central Texas land grant university a research powerhouse. An undergraduate enrollment of ~53,000 students provides ample opportunity for graduate students to work with and train teams of undergraduates, and to develop their own skills as educators and mentors.

Former trainees are scientists at academic institutions as well as pharmaceutical and biotechnology companies, educators, entrepreneurs, engaged in advocacy and health policy and scientific writing. Trainees find professional advancement in increasingly diverse arenas that need the analytic and communications skills of trained biomedical scientists.

I hope you find all the resources you are looking for in this website. If you have any questions, please do not hesitate to reach out to us. We look forward to hearing from you!.

Best Regards,

Rajesh C Miranda, PhD Shelton Professor of Neuroscience Director, Medical Sciences Graduate Program Chair, MED Graduate Program Executive Committee

Research Areas

There are six areas of research across the School of Medicine  departments (Bryan/College Station) and the Institute of Biosciences and Technology  (Houston) that students can choose from to specialize in areas of expertise while expanding their knowledge and touching other interdisciplinary research groups. The School of Medicine is an academic unit of Texas A&M University (TAMU), and students in the Medical Sciences PhD program have access to all the resources, facilities, and courses of both the School of Medicine and the university. The Medical Sciences PhD Program branch in Houston is located in the Texas Medical Center, the nation's fourth largest city and the largest medical center complex in the world. The PhD program is housed within the Institute of Biosciences and Technology, a research institute focused on translational medical research, and features a close-knit community of investigators and students, with close connections to both the TAMU main campus, neighboring institutions, and universities in the Texas Medical Center. When applying for the PhD program in Medical Sciences, be sure to specify which campus you are interested in, either Bryan/College Station or Houston.

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Research related to normal neural development and neurodevelopmental disorders, behavior, adaptation to injury and disease, psychiatric disorders.

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Research that explores the potential of somatic stem cells to ameliorate and cure a broad range of diseases.

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Research related to the regulation of development, including processes dysregulated in cancer, such as control of cell cycle, cell survival and cell death; the role of innate and adaptive immunity in cancer and immunotherapy, molecular and cellular mechanisms of cancer initiation and pathogenesis; metabolic dysregulation in cancer, lymphatics in cancer progression; and design and application of mouse models of human cancer.

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Research related to the investigations of cardiac function, blood vessel circulation of organs; lymphatic vessel physiology, lymphatic control of inflammation and immune responses; underlying pathophysiology of obesity, diabetes, aging, heart disease, hypertension, lymphedema, inflammatory bowel disease, kidney and liver injury, eye conditions, and cancer.

Genetic, Genomic and Network Biology

Research using model organisms to study physiology in health and disease; quantitative, systems-based approaches to gain insight into the molecular, cellular and biochemical networks that underlie biological phenomena.

Infection, Immunity and Inflammation

Research related to infection and subsequent host response; innate and adaptive immunity; inflammatory responses; genetic evaluation of virulence that affect colonization of tissues and systems; disease pathologies related to inflammation and immune dysfunction; e.g., diabetes, neurodegenerative disease; mesenchymal stem cells differentiation for immune function and wound healing.

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Texas A&M University is ranked among the top 10 public universities in the United States and number one in Texas for research expenditures, according to the National Science Foundation. Our graduate faculty exemplify the highest standards of teaching, research and scholarship. By joining the Texas A&M School of Medicine, you will not only be immersed in exciting research but also become part of the Aggie family, a unique and life-long experience, full of traditions and a network of leaders around the world.

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With 170 full time faculty, 75 graduate students and more than 100 postdoctoral fellows, the School of Medicine has a combined total of 39.8 M of external funding from federal grant agencies (NIH, NSF, USDA, and DOD) and the private sector. Our scientists are continuously improving medicine in the areas of cancer, cellular and molecular biology, environmental and genetic medicine, infectious and inflammatory diseases, microbial pathogenesis, neuroscience, stem cell biology, cardiovascular and lymphatic biology and many more.

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Our diverse student body comes from across the nation and the world to become independent scientists and develop professional and transferable skills through top research projects, professional development, and other campus resources that prepare them to become leaders in a broad range of scientific fields.

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Have access to the student handbook, Texas A&M and School of Medicine forms, policies and procedures, as well as other sources to support student wellness and success.

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Get to know better our most recent cohort.

Rajesh C. Miranda, PhD [email protected] Program Director, Medical Sciences Graduate Program Shelton Professor of Neuroscience- Department of Neuroscience and Experimental Therapeutics (NeXT) Chair, COM Graduate Program Execuative Committee

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Everything You Need to Know About MD-PhD Programs

Posted in: Applying to Medical School

Table of Contents

MD-PhD programs are dual-degree programs for pre-medical students who want to both practice medicine and conduct extensive research.

In an MD-PhD program, the medical education of the MD program is combined with the in-depth research training of a PhD program. Students learn to practice medicine, diagnosing and treating patients all while gaining research experience to investigate medical conditions and diseases.

These programs are more intense than standard medical school. Students take additional coursework, typically in the biomedical sciences, graduate training, rotations in different laboratories, and intensive research.

The extra education gives students the tools to advance in the medical field after graduation. If you are interested in investigating diseases as you treat patients and developing innovative ways to provide care, an MD-PhD path may be for you!

What are MD-PhD programs?

MD-PhD programs are unique dual-degree programs designed for students who have an interest in both patient care and research. In these programs, students complete both a medical degree (MD) and a doctorate (PhD). This prepares graduates to function as physician-scientists, seamlessly bridging the gap between the laboratory and the clinical setting.

What is the difference between an MD and an MD-PhD? The difference between MD and MD-PhD graduates is that while both degrees are conferred to medical doctors, MD programs focus on clinical practice. MD-PhD programs, on the other hand, combine medical education with extensive biomedical research training. 

Is MD-PhD easier than MD? MD-PhD programs are not easier than MD programs. They require a longer time commitment, but in the end, provide graduates with a broader skill set to pursue careers that integrate medicine and scientific research.

How rare is an MD-PhD? Only about 3% of students that enroll in medical school are in MD-PhD programs. There are 122 MD-PhD programs in the U.S. and 13 in Canada listed on the AAMC MD-PhD Degree Programs by State directory .

Graduate programs aren’t confined to a specific area of study. Each school with this type of program has its own options for its PhD degree. PhD students commonly choose to specialize in topics such as:

• Cell biology
• Biochemistry
• Pharmacology
• Neuroscience
• Biomedical engineering

Upon completion of an MD-PhD program, graduates are awarded the dual degree for their proficiency in both clinical practice and research. 

MD-PhD Program Duration

A significant commitment of time is necessary to complete an MD-PhD program, but the career path is rewarding and well-compensated. 

How many years are MD-PhD programs ? Students can expect to spend 7-8 years total between graduate school and med school, but there is no strict timeline for completing an MD-PhD. Some students complete their programs in as little as six years, and others take as long as 10.

Students usually start with the first year to two years of medical school, followed by 3-5 years of research, then finish with another two years of medical training and clinicals. Current students entering into MD-PhD programs are older , on average, than when these programs first began, and many take longer to complete their studies.

How much does an MD-PhD program cost?

Most MD-PhD programs offer enrolled students tuition-free training and a stipend to cover living expenses.

The cost of an MD-PhD program varies widely depending on the institution, but the stipend and tuition-free training makes many of these programs significantly less burdensome financially compared to standalone MD or PhD programs.

Financial support is available through the Medical Scientist Training Program (MSTP) funded by the National Institutes of Health (NIH). Scholarships are offered that cover tuition and provide a stipend for living expenses, making these intensive dual degree programs more attainable.

Not all MD-PhD programs are funded by the MSTP, but some schools offer similar financial support to their MD-PhD students. For any school you plan to apply to, double-check their program website or call an admissions counselor to see if there are options for financial aid. 

MD-PhD Residencies

MD-PhD residencies provide a unique opportunity to bridge the gap between patient care and research. Graduates often enter residency programs to acquire hands-on training in a particular medical specialty. Some even opt for a fellowship in a subspecialty after that. This training phase can range from 3 -7 years, depending on the specialty.

Although they can enter any medical specialty, they frequently gravitate towards specialties with a strong research component. Here are a few common residencies that MD-PhDs typically enter:

• Internal Medicine: This field covers a broad range of diseases in adults and often involves solving complex medical problems. It’s a popular choice for MD-PhD graduates because of the diversity of patients and conditions, which provides many opportunities for research.
• Neurology: The complexity and the largely untapped understanding of the nervous system provide abundant research opportunities. Advances in neuroimaging, AI , and genetics also offer tools for physician-scientists to explore the nervous system in unprecedented ways.
• Psychiatry: Studying the pathophysiology of mental disorders, exploring new therapeutic interventions, and examining the genetic basis of psychiatric conditions are just a sample of the ways an MD-PhD can continue research in this specialty.
• Pathology: Pathologists often work behind the scenes in medicine, studying the causes and effects of diseases. This field is deeply rooted in medical research, which makes it a good fit for many MD-PhD graduates.
• Pediatrics : Pediatric physician-scientists research a wide array of topics, including childhood diseases, growth and development, pediatric therapies, and many other areas related to child health.

The choice of residency program should align with each graduate’s clinical interests, research interests, and career goals. There is great flexibility in the MD-PhD pathway, and physician-scientists span all specialties in medicine.

MD-PhD Career Path & Salary

Careers for MD-PhD’s often sit at the intersection of healthcare, academic medicine, and industry. Roles vary from practicing physicians, medical researchers, educators, and policy advisors to leaders in biotech and pharmaceutical companies.

After completing their residency, MD-PhDs typically divide their professional time between research and clinical practice. They often work in academic medical centers or research institutions where they can see patients and conduct research. Their research may be basic, translational, or clinical, depending on their interests and training.

MD-PhDs may also grow to take on teaching roles, educating the next generation of physicians and scientists. This path can bring them to leadership roles such as department chair, dean of a medical college, or even hospital CEO with their unique understanding of both medicine and research.

The salary for MD-PhDs does vary depending on the chosen career path. Earning potential is generally high due to the advanced and specialized nature of their training.

On average, physician-scientists in the US earn a median salary that is well above the national average for all occupations. According to Doximity’s 2023 Physician’s Compensation Report , the average salary for physicians in the Pharmaceutical/Industry employment setting is highest at $392,534.

Those working in academia or research may have different salary scales. These salaries are frequently dependent on research grants, but still typically fall within a comfortable range.

An MD-PhD opens up a wide range of career options, particularly in the intersecting areas of healthcare and research. Below are careers someone with an MD-PhD might pursue:

• Academic Physician: They divide their time between seeing patients, conducting research, and teaching students and residents. These professionals usually work at medical schools or teaching hospitals.
• Biomedical Researcher: MD-PhDs often find employment as researchers in the field of biomedical sciences. They can work in research institutions, pharmaceutical companies, or government organizations such as the NIH.
• Clinical Investigator: These are physicians who conduct research involving human subjects (clinical trials). They develop and implement studies to understand the effects of new drugs or therapeutic strategies.
• Pharmaceutical/Biotech Industry Professional : Many MD-PhDs work in the pharmaceutical or biotechnology industry. They may be involved in drug development, clinical trials, regulatory affairs, or medical affairs.
• Medical Director: In this role, an individual would oversee the medical aspect of a healthcare facility, biotech company, or department in a hospital. This position often requires both a medical and research background.
• Science Policy Analyst/Advisor: They can work in government or nonprofit organizations, helping to shape policies that affect scientific research and healthcare.
• Public Health Official: Some MD-PhDs choose to work in the public sector, addressing health issues at the population level. They may work for entities like the Centers for Disease Control and Prevention (CDC) or World Health Organization (WHO).
• Medical Science Liaison: This role often involves serving as a bridge between pharmaceutical companies and healthcare professionals, explaining new therapies and scientific findings to physicians, researchers, and other stakeholders.
• Medical Educator: MD-PhDs are uniquely qualified to educate future doctors and researchers, teaching in areas such as pharmacology, pathology, genetics, or any other medical specialty. They may design and implement courses, advise students, and contribute to the educational mission of their institution.

These are just a few of the potential career paths. A career choice often depends on an individual’s specific interests, such as which medical specialties they are drawn to, whether they prefer working with patients or in a laboratory, and how they want to contribute to advancing medical science.

Medical Science Training Programs

Some MD-PhD programs in the United States are funded by the National Institutes of Health (NIH) through the Medical Scientist Training Program (MSTP). This means that students receive full tuition remission, health insurance, and a living stipend throughout their training.

Because of this financial support, admission to an MSTP is very competitive. Many schools have financial support available to MD-PhD students even if they are not part of the Medical Scientist Training Program to allow them to focus on their studies and research.

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4 Benefits of Becoming an MD-PhD

Earning dual degrees in medicine and research is an ambitious endeavor, but the impacts you can make on patient care and scientific research are significant and valuable to public health. An MD-PhD degree comes with some great benefits.

1. Interdisciplinary Perspective

The duality of the MD-PhD training allows graduates the ability to translate clinical observations into research questions, then taking research findings to enhance patient care. You will essentially be a bridge to the gap between the laboratory and the clinic.

2. Career Flexibility

Graduates can become practicing physicians, medical researchers, educators, and/or policy advisors. They may also take on leadership roles within academic institutions, hospitals, biotech companies, or pharmaceutical firms. 

The wide range of possible careers allows the flexibility to pursue a path that aligns with your passion.

3. Influential Impact 

The rigorous training in MD-PhD programs allows graduates to drive innovation in healthcare and medical science. This advanced education will have you asking critical questions and finding answers that can change the course of medical treatment and patient care. 

The potential to make significant contributions to the field of medicine is a rewarding and prestigious aspect of this career path.

4. Community and Mentorship

During their training, MD-PhD students join a tight-knit community of fellow dual-degree students, mentors, and faculty. This network can provide valuable support, guidance, and camaraderie during the demanding years of study. 

Post-graduation, this network continues to serve as a resource for collaboration, mentorship, and career advancement.

Are MD-PhD programs more competitive than MD programs?

In general, yes, MD-PhD programs are more competitive than MD programs. 

The statistics here can be a little confusing, though. 10% of applicants are accepted to an MD-PhD program, which is higher than the 3% that get accepted into MD programs. Acceptance rates are nearly the same as traditional medical programs, too.

But the quality of application for MD-PhD programs is inherently higher than traditional pre-meds. Your GPA and MCAT need to be higher, with well-developed extracurricular experiences and glowing letters of recommendation to have a chance at an MD-PhD program. 

Learn more about how we can help you boost your MCAT score.

Preparing to Apply to MD-PhD Programs

Applying for an MD-PhD program is done through AMCAS, just like MD programs. Preparation is key in the application process .

Being proactive, getting relevant experiences, understanding the requirements, and applying to multiple programs will significantly enhance your chances of success in securing a spot in an MD-PhD program. Applicants must be prepared to showcase themselves as doctor material and make a case for their desire to take part in research.

Here are a few tips for increasing your chances at acceptance.

Make sure you have the right extracurriculars under your belt.

Gaining relevant experiences beyond the classroom is crucial to showcase your commitment to a career in medical research. Admissions committees are looking for candidates with experience in research projects. 

It is absolutely necessary to have taken part in research to have a chance at getting into an MD-PhD program.

Check application requirements well in advance.

You’ll be required to meet all the AMCAS application requirements of MD programs. This includes the prerequisite coursework, your MCAT score and GPA, letters of evaluation, and personal statement . 

There are also two additional essays that are required on MD-PhD applications, which we’ll cover later.

We advise checking with each specific medical school on the requirements for their applications . Non-medical graduate programs may ask for your GRE scores. You want to make sure you’ve taken this test well in advance of the AMCAS open date. 

Our advisors can help you craft a personal statement for your MD-PhD that will stand out.

Apply to several programs.

Because of the limited number of programs and the competitive nature of MD-PhD programs, you should apply to multiple programs. Students who have gotten into these programs report applying to as many as 30 programs for the best chance to be accepted. 

Along with MD-PhD programs, we also recommend applying to some MD programs as well. On your AMCAS application, you can easily designate as an MD candidate or MD-PhD candidate.

Even if you don’t make it into the MD-PhD program of a medical school, you will still have the opportunity to be considered for their MD program.

MD-PhD Application Timeline

Get your medical school application in early — the same goes for MD-PhD applications. In fact, it’s even more important to have your primary application in as soon as possible to give yourself plenty of time to write your secondary essays. 

The MD-PhD application process follows the AMCAS application timeline :

• May: AMCAS application opens. You’ll receive your secondary application shortly after you submit your primary. 
• July-August: Submit your supplemental application within two weeks.
• October-March: Prepare for and attend all scheduled interviews.
• December-March: Application committees make final decisions. For schools with rolling admissions, this may happen shortly after an interview. Other institutions wait until after all interviews are complete to make decisions.
• March-April: Applicant decisions are made.
• June-August: Your MD-PhD begins.

Additional Essays in the MD-PhD Application

The MD-PhD application process includes two additional essays that showcase your commitment to a career as a physician-scientist. 

MD-PhD Essay

The MD-PhD Essay is your opportunity to express why you have chosen the dual-degree path and how it aligns with your career goals. Discuss your motivation for pursuing the ambitious MD-PhD degree. You should explain why both clinical practice and research are integral to your career vision and share personal experiences that ignite your interest in this path.

Describe your career goals and how integrating clinical practice and scientific research will allow you to achieve those goals. If you’re interested in a particular field, discuss how the blend of clinical and research training in the MD-PhD program will enhance your contributions to this field.

Significant Research Experience Essay

This essay is your chance to elaborate on your research experiences and demonstrate your scientific curiosity, perseverance, and ability to work independently. You’ll explain the objectives of the research project you have been involved in, your role in achieving these objectives, and the significance of the research.

You can also write about instances where you faced challenges and had to use your problem-solving skills, perseverance, and critical thinking to overcome them. Highlight your ability to learn from others, like your mentors, how you can collaborate, and contribute to a team-oriented goal.

If your work led to any significant findings, presentations, or publications, be sure to include this. Use this opportunity to communicate your passion for research and how these experiences have prepared you for a career that combines patient care and scientific investigation.

MD-PhD: The career path that moves medicine forward.

MD-PhD candidates have a commitment to both medical practice and research on this path. The journey is long and at times challenging, but for those driven by a passion for both clinical medicine and biomedical research, the reward lies in the unique ability to contribute to the advancement of healthcare as a physician-scientist.

Speak with a member of our enrollment team who can help you prepare your MD-PhD application.

Kachiu Lee, MD

Dr. Lee specializes in BS/MD admissions. She was accepted into seven combined bachelor-medical degree programs. She graduated Summa Cum Laude from Northwestern University and proceeded to Northwestern University’s Feinberg School of Medicine in Chicago, IL. After completing a dermatology residency at Brown University, Dr. Lee pursued a fellowship in Photomedicine, Lasers, and Cosmetics at Massachusetts General Hospital and was a Clinical Fellow at Harvard Medical School. Academically, she has over 100 peer-reviewed publications and lectures internationally.

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The Bioinformatics PhD Program is well established, with a long history of successful graduates in both academia and industry.  

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To apply for the Bioinformatics PhD Program, you must submit complete applications by December 1 for admission the following Fall term. Early applications are not allowed and will not be considered. 

Please visit the Rackham Graduate School web pages for additional information on applying. There you will also find information on how to respond to an offer of admission, plus tips and materials required for international applicants and incoming students.

If you are certain about pursuing a Bioinformatics PhD, then applications should be submitted directly to the Bioinformatics PhD Program ; there are more than 100 diverse affiliated faculty to choose from.

Applicants should be U.S. citizens or permanent residents. In addition, applicants with a background in quantitative sciences should consider applying directly. Separately, if you are transferring from another University of Michigan Program or have obtained an established University of Michigan mentor affiliated with the program, a direct application is most appropriate.

PIBS is an umbrella program that offers first-year PhD students flexibility in exploring opportunities in bioinformatics and thirteen other graduate programs. Through PIBS, students have the opportunity to rotate in, and potentially join the lab of a faculty mentor in another program; there are more than 500 diverse faculty to select from. PIBS students who list Bioinformatics as their primary choice must complete at least one rotation with a Bioinformatics-affiliated faculty member. After 10 months in PIBS, students officially join Bioinformatics (or one of the other programs). You can visit the PIBS website for more information.

Please note that reviewing admissions faculty for both PIBS and direct applications are the same. In addition, admitted applicants take the same Bioinformatics-specific courses and activities. See below for details on program diversity outreach, application materials, and funding.

Students who will have an MS in a relevant field (e.g. computer science, statistics, biostatistics, biology) from another university may request to have up to 6 credit-hours (two classes) waived. These classes may be used to help fulfill the core PhD requirements for biology (1 course), statistics (2 courses), and/or computing (1 course). To obtain approval, students need to send a detailed syllabus of the class(es) they took to the PhD directors along with their grade(s), which must be a B or better. The other PhD course requirements, including BIOINF-529 and two advanced bioinformatics courses, cannot be waived.

Most international Bioinformatics PhD applicants should apply through PIBS. However, some who are already embedded in a University of Michigan mentor lab affiliated with the program may be an appropriate fit for the direct Bioinformatics PhD program.

The TOEFL or IELTS exam is required unless Rackham Graduate School waiver requirements have been met. Criteria for English proficiency exemption can be found on the Rackham website . In addition, a list of required credentials from non-U.S. institutions for an application can be found here.

The Bioinformatics Graduate Program encourages applications from traditionally underrepresented minorities, students with disabilities, and those from disadvantaged backgrounds. There are numerous funding opportunities and resources on campus to contribute to students overall well-being while pursuing studies. Several resources available to students can be found on the Rackham Graduate School Diversity, Equity, and Inclusion website .

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All application materials should be submitted electronically when possible. Applicants must meet  Rackham's Minimum Requirements for Admission . The  online application form  can be found on the Rackham Admissions webpages. The application is available in early September through the deadline. 

• GPA, minimum 3.2/4.0 (exceptions may be made if deemed appropriate)
• Letters of recommendation (3 required): Please be aware that submitting only the Rackham Recommendation for Admission Form is insufficient; forms must be accompanied by a letter from the recommender. All letters are due by the application deadline. Without them, applications will not be considered complete or reviewed by the Program Admissions Committee.
• Statement of Purpose: The Statement of Purpose should be a concise, well-written statement about your academic and research background, your career goals, and how Michigan's graduate program will help you meet your career and educational objectives.
• Personal Statement: The Personal Statement should be a concise, well-written statement about how your personal background and life experiences, including social, cultural, familial, educational, or other opportunities or challenges, motivated your decision to pursue a graduate degree at the University of Michigan. This is not an Academic Statement of Purpose, but a discussion of the personal journey that has led to your decision to seek a graduate degree.
• Transcripts: Please submit unofficial transcripts electronically with your online application
• GRE scores are no longer included as part of admission
• Applicants whose native language is not English must demonstrate English proficiency via either the TOEFL or IELTS exam. The institution code is 1839. Other exams may not be substituted. Rackham Graduate School offers a full explanation of this requirement , including exemption criteria. Please contact Rackham directly ( [email protected] ) with questions.

Diversity is a key component of excellence, especially for solving the complex biomedical challenges that our field of computational medicine and bioinformatics faces. We believe that all people—regardless of background, race, religion, sexual/gender orientation, age or disability—deserve an equitable opportunity to pursue the education and career of their choice.

The Bioinformatics Graduate Program will provide tuition, healthcare coverage, and a stipend on a 12-month basis. This level of support will be maintained throughout a student's tenure in the Program, provided s/he remains in good academic standing and makes reasonable progress towards the degree as determined by the Graduate Directors, with faculty input. It is expected that the student will be supported directly by the mentor's laboratory, beginning in the second year. The expected time to degree is typically 5-6 years.

The U-M MS program is a terminal degree program. If you are interested in the Bioinformatics PhD Program, you must submit a new application. If you are a Bioinformatics MS student who is in good academic standing and has identified a Bioinformatics affiliated faculty mentor, you may apply for admission directly to the PhD Bioinformatics Program for the Winter term. Reviewing faculty take all application components into account and mentors are prepared to take both academic and financial responsibility for their trainees.

Eligibility: Only current or recently graduated University of Michigan Master’s students are eligible. Before applying, students must have completed more than half of all required courses, with at least six credits from the Bioinformatics Program.

Application deadline: October 1

The online application form can be found on the Rackham Admissions webpages. The application is available in early September through the deadline.

• Letters of recommendation: Please be aware that submitting only the Rackham Recommendation for Admission Form is insufficient; forms must be accompanied by a letter from the recommender. If you wish to include three letters from your original application, only one additional letter is needed. It must be from the DCMB faculty member who will serve as your primary mentor. The letter should state clearly that the mentor takes responsibility for your funding upon admission. Alternatively, you may wish to obtain three new letters of recommendation. The Admissions Committee strongly encourages you to include letters from those familiar with your research and coursework obtained while pursuing your Master’s degree. Of these, one must be from the faculty member who will serve as your primary mentor. The letter should state clearly that the mentor takes responsibility for your funding upon admission.
• Statement of Purpose: The Statement of Purpose should be a concise, well-written statement about your academic and research background, your career goals, and how the PhD Program will help you meet your career and educational objectives.
• Transcripts: Only a current, unofficial U-M transcript is necessary. You do not need to re-submit materials included with your Master’s application.
• TOEFL: If you submitted TOEFL scores when applying to the Master’s Program, additional test scores are not needed.

Bioinformatics consists of a mathematical and/or statistical analysis of a biomedical problem using computation. We define bioinformatics widely and include traditional bioinformatics areas such as for examples, systems biology, genomics, proteomics, plus statistical and evolutionary genetics, clinical informatics, and protein modeling.

As an interdisciplinary field, Bioinformatics attracts graduate students from mathematics, statistics, physics, computer science, biomedical engineering, chemistry, biochemistry and biology. Most incoming students have both a major in one and a minor in another discipline. In recent years students have entered with undergraduate training in bioinformatics or computational biology.

Each student obtains individual counseling by one of the two graduate program directors upon arrival and throughout their academic career. As Bioinformatics is still developing, new courses are added all the time. Current students are encouraged to contact the Program Directors about courses that may be relevant to their studies and are not listed on the website (esp. if they are new or infrequently offered).

In most cases, we recommend you apply to the PIBS program, as it provides flexibility in classes, funding, and a central admission for many biomedical programs. If you have no or very little biology background, please contact our Student Services Representative as to whether a direct application would be better. Current student who are considering transferring areas of study should also contact the Bioinformatics Graduate Office.

There is no need to apply both direct and through PIBS, as the same committee sees your applications.

For most students, thesis work includes computing, reading, and writing. A small group also participates in wet laboratory work. Please check both the research areas and student webpages for an overview of the varied subjects addressed in research and student theses.

Many of our graduate students obtain academic postdoctoral fellowships and go on to faculty positions. Quite a significant number of graduates go into non-academic professions such as small or large biotech companies. Some have founded their own business, and others apply their analytical skills in companies unrelated to bioinformatics. For a current list of graduate placement, please visit the alumni pages.

No. If you want to get a PhD, directly apply to the PhD Program.

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The PhD in Health Policy is a highly interdisciplinary program that will develop the specialized skills you need for a research and teaching career in health policy.

The program is collaborative at its core, with its curriculum drawing from six Harvard schools:

• Harvard Business School
• Harvard Kenneth C. Griffin Graduate School of Arts and Sciences
• Harvard Kennedy School
• Harvard Law School
• Harvard Medical School
• Harvard T.H. Chan School of Public Health

With more than 100 Harvard faculty members from these schools integrated in the program, you have access to the insights of leading experts across the full academic and professional spectrum.

Balance broad and specialized knowledge.

As a PhD in Health Policy student, you take courses throughout Harvard’s specialized schools. This allows you to become familiar with the conceptual frameworks, vernacular and perspectives of researchers from other disciplines.

At the same time, developing specialized skills in a discipline is a hallmark of the program, which is why you specialize in one of five concentrations:

• Decision Sciences
• Methods for Policy Research
• Political Analysis

The PhD in Health Policy degree is awarded by the  Harvard Kenneth C. Griffin Graduate School of Arts and Sciences (Harvard Griffin GSAS). Our graduates leave the program well equipped to make an impact in academia, government agencies, research institutes, think tanks, foundations, and multinational corporations. 

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Explore the graduate programs

Aspiring biomedical scientists must acquire a broad background of knowledge and expertise, as well as develop in-depth understanding of their primary area of research interest.

During your graduate studies, you’ll discover a unique research training environment of academic inquiry and scientific discovery, combined with exceptional intellectual and technological resources designed to help you achieve your highest scientific career goals.

Our Ph.D. Program in biomedical science offers eight areas of specialization, known as tracks. Learn more about the ways you can specialize during your graduate studies.

Biochemistry and Molecular Biology

Biochemistry and structural biology, cell biology and genetics, cancer biology

Biomedical Engineering and Physiology

Biomechanics, biomedical imaging, molecular biophysics, physiology

Clinical and Translational Science

Laboratory-based, patient-based and population-based translational science

Mechanisms of immunity and inflammation, immune-mediated disease, vaccines and immune-based therapies, regenerative immunity

Molecular Pharmacology and Experimental Therapeutics

Cancer biology and therapy, regenerative medicine, pharmacogenomics and genetics, drug discovery, neurobiology and genetics of addiction, cardiovascular biology and therapy

Neuroscience

Neurodegeneration, neuroregeneration, neurogenetics, neuroengineering, neuroimaging

Regenerative Sciences

Regenerative diagnostics and therapeutics, molecular and cell biology, biomedical engineering, translational science

Virology and Gene Therapy

Molecular biology of viruses, mechanisms of virus-host interactions, gene therapy, oncolytic virotherapy, cancer immunotherapy, vaccine development, tissue and genetic engineering using viruses

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Underlying Medical Conditions and Severe Illness Among 540,667 Adults Hospitalized With COVID-19, March 2020-March 2021

Affiliations.

• 1 COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia.
• 2 Centers for Disease Control and Prevention, 4770 Buford Hwy, MS S107-5, Atlanta GA 30341. Email: [email protected].
• 3 US Public Health Service Commissioned Corps, Rockville, Maryland.
• 4 Epidemic Intelligence Service, Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, Georgia.
• PMID: 34197283
• PMCID: PMC8269743
• DOI: 10.5888/pcd18.210123

Introduction: Severe COVID-19 illness in adults has been linked to underlying medical conditions. This study identified frequent underlying conditions and their attributable risk of severe COVID-19 illness.

Methods: We used data from more than 800 US hospitals in the Premier Healthcare Database Special COVID-19 Release (PHD-SR) to describe hospitalized patients aged 18 years or older with COVID-19 from March 2020 through March 2021. We used multivariable generalized linear models to estimate adjusted risk of intensive care unit admission, invasive mechanical ventilation, and death associated with frequent conditions and total number of conditions.

Results: Among 4,899,447 hospitalized adults in PHD-SR, 540,667 (11.0%) were patients with COVID-19, of whom 94.9% had at least 1 underlying medical condition. Essential hypertension (50.4%), disorders of lipid metabolism (49.4%), and obesity (33.0%) were the most common. The strongest risk factors for death were obesity (adjusted risk ratio [aRR] = 1.30; 95% CI, 1.27-1.33), anxiety and fear-related disorders (aRR = 1.28; 95% CI, 1.25-1.31), and diabetes with complication (aRR = 1.26; 95% CI, 1.24-1.28), as well as the total number of conditions, with aRRs of death ranging from 1.53 (95% CI, 1.41-1.67) for patients with 1 condition to 3.82 (95% CI, 3.45-4.23) for patients with more than 10 conditions (compared with patients with no conditions).

Conclusion: Certain underlying conditions and the number of conditions were associated with severe COVID-19 illness. Hypertension and disorders of lipid metabolism were the most frequent, whereas obesity, diabetes with complication, and anxiety disorders were the strongest risk factors for severe COVID-19 illness. Careful evaluation and management of underlying conditions among patients with COVID-19 can help stratify risk for severe illness.

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• PhD vs MD – Differences explained
• Types of Doctorates

A MD is a Doctor of Medicine, whilst a PhD is a Doctor of Philosophy. A MD program focuses on the application of medicine to diagnose and treat patients. A PhD program research focuses on research (in any field) to expand knowledge.

Introduction

This article will outline the key differences between a MD and a PhD. If you are unsure of which degree is suitable for you, then read on to find out the focuses and typical career paths of both. Please note this article has been written for the perspective of a US audience.

What is a MD?

MD (also seen stylized as M.D and M.D.) comes from the Latin term Medicīnae Doctor and denotes a Doctor of Medicine.

MDs practice allopathic medicine (they use modern medicine to treat symptoms and diseases). A common example would be your physician, though there are numerous types of medical doctors, with different areas of speciality and as such may be referred to differently.

What is a PhD?

A PhD (sometimes seen stylized as Ph.D.) comes from the Latin term Philosophiae Doctor and denotes a Doctor of Philosophy.

A PhD can be awarded for carrying out original research in any field, not just medicine. In comparison to an MD, a PhD in a Medicinal field is focused on finding out new knowledge, as opposed to applying current knowledge.

A PhD in Medicine therefore does not require you to attend medical school or complete a residency program. Instead, you are required to produce a thesis (which summarizes your research findings) and defend your work in an oral examination.

What is the difference between a MD and a PhD?

Both are Doctoral Degrees, and someone with either degree can be referred to as a doctor. But for clarity, MDs are awarded to those with expertise in practicing medicine and are therefore more likely to be found in clinical environments. PhDs are awarded to researchers, and are therefore more likely to be found in academic environments.

This does not mean that MDs cannot pursue a research career, nor does it mean that a PhD cannot pursue clinical practice. It does mean, however, that PhDs are more suited to those who would wish to pursue a career in research, and that MDs are more suited to those who prefer the clinical aspects of medicine or aspire to become a practicing physician.

It should also be noted that a medical PhD doctorates possess transferable skills which make them desirable to various employers. Their familiarity with the scientific method and research experience makes them well suited to industry work beyond medical research.

Program structure and time

The standard MD program structure sees students undertake 2 years of coursework and classroom-based learning, before undertaking 2 years of rotational work in a clinical environment (such as a hospital). Getting an MD requires attending a medical school (accredited by the Liaison Committee on Medical Education) and completing a residency program. Both of which prepare students to diagnose patients and practice clinical medicine.

The standard PhD program lasts 5 to 7 years and sees students undertake original research (monitored by a supervisor). Getting a PhD requires the contribution of novel findings, which leads to the advancement of knowledge within your field of research. With the exception of some clinical PhDs, a PhD alone is not enough to be able to prescribe medicine.

PhD doctorates are required to summarize the purpose, methodology, findings and significance of their research in a thesis. The final step is the ‘ Viva Voce ’ where the student must defend their thesis to a panel of examiners.

To summarize, a MD program usually lasts 4 years, whilst a PhD program lasts 5 to 7 years. Before being licensed to practice medicine, however, you must first complete a residency program which can last between 3 to 7 years.

What is a MD/PhD?

A MD/PhD is a dual doctoral degree. The program alternates between clinical focused learning and research focused work. This is ideal for those who are interested in both aspects of medicine. According to the Association of American Medical Colleges, an estimated 600 students matriculate into MD-PhD programs each year .

The typical length of a MD/PhD program is 7 to 8 years, almost twice the length of a MD alone. As with a MD, MD/PhDs are still required to attend medical school and must complete a residency program before being able to practice medicine.

In comparison to PhD and MD programs, MD/PhD positions in the United States are scarce and consequently more competitive. The tuition fees for MD/PhD positions are typically much lower than MD and PhD positions are sometimes waived completely.

Those who possess a MD/PhD are commonly referred to as medical scientists. The ability to combine their medical knowledge with research skills enables MD/PhDs to work in a wide range of positions from academia to industrial research.

Finding a PhD has never been this easy – search for a PhD by keyword, location or academic area of interest.

Browse PhDs Now

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What is the Real Difference between an MD and PhD?

Phds advance knowledge, whereas mds merely apply existing knowledge..

Posted March 7, 2011 | Reviewed by Kaja Perina

If you ask someone in the psychology world how people with PhDs (Doctor of Philosophy ) differ from those with MD (Doctor of Medicine) you may get an answer like "MDs can prescribe medication , whereas PhDs cannot." That is true. Another difference is that MDs generally make more money in the United States.

MDs are consider by many to be the "real doctors" because they can help with physiological medical problems. That too is true. I certainly don't refer to myself as "Dr. Kelly" in any context other than an academic setting, because people might get the false impression that I could jump in and help in the event of a broken foot or migraine headache.

All that sounds pretty bad for the PhD. But here's the most essential difference between the two degrees: PhDs advance knowledge, whereas MDs merely apply existing knowledge. Unlike the MD who does not need to produce any original research, the person earning a PhD must produce original research and write it up in a thesis or dissertation. Then a committee of experts must deem that thesis as offering an acceptable advancement of knowledge before the PhD is conferred. It typically takes a couple of years longer to earn a PhD than an MD. Part of the reason it takes so long is that the person earning the PhD is being trained on how to think critically about existing knowledge, and it can take a while to find one's niche and fill a gap in the knowledge base.

If you yourself want to make important scientific discoveries and then tell the world about them, you will be much better prepared by getting a PhD than an MD. You also will be much better prepared to criticize studies you read about in virtually any field because you will be trained in critical thinking and writing.

If you are deciding which degree is right for you, ask yourself if you will be content with applying the knowledge you learn (MD) from other people, or if you would like to get in on the action of making the discoveries yourself (PhD). For instance, would you like to be one of the scientists who are figuring out how to reverse the aging process (PhD)? Would you like to see if giving aging mice a particular the enzyme (one that you discover) makes their hair shiny again and restores their fertility (PhD)? Or would you be content giving your future medical patients the proper dose of the medications that arise from this research and then seeing the signs of youth return in your patients (MD)? These are the kinds of questions that college students everywhere should be asking themselves, and yet I have never seen them do so.

This difference in training also means that if you want to know what the cutting -edge knowledge is in a given field, you have to ask a PhD in that field, not an MD. So for instance, let's say you or your mate is having trouble getting pregnant . If you just ask your local obstetrician or gynecologist what the cutting edge discoveries are regarding fertility, that MD is not likely to know. That MD can give you fertility treatments that he or she has learned about and tried with other patients. It should be noted, however, that many MDs make an effort to remain abreast of scientific research long after their degree has been conferred.

The upshot of my message is this: We need both kinds of people, those who apply existing knowledge (such as the MD does in the medical field) and those who advance it (PhDs). But if you think a PhD is less qualified than an MD when it comes to having cutting-edge knowledge, you have that backwards.

Anita E. Kelly, Ph.D., is a Professor of Psychology at the University of Notre Dame. She is author of The Clever Student and The Psychology of Secrets.

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Congratulations Kelsey Pinson, M.D., a PGY-7 maternal fetal medicine (MFM) fellow who was selected as House Officer of the Year. Recognized for her compassion and empathy with patients, as well as her dedication, innovation and leadership, she profoundly influenced the practice of medicine within the Department of Obstetrics, Gynecology and Reproductive Sciences.

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Population and Health Data Science: Fully Funded Health Data Research UK PhD Scholarship: Use of Real-World Evidence in Health Technology Assessment for Multiple Long-term Conditions (RS600)

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Closing date: 12 May 2024

Key Information

Funding provider:   Health Data Research (HDR) UK

Subject areas:   Population Data Science

Project start date:

• 1  October 202 4 ( Enrolment open from mid-September )

Project supervisors:

• Professor Rhiannon Owen ( r.k.owen @swansea.ac.uk )
• Dr James Rafferty
• Professor Hamish Laing
• Professor Keith Abrams (University of Warwick)

Aligned programme of study: PhD in Population and Health Data Science

Mode of study: Full-time

Project description:

Healthcare decision-making has previously focussed on developing recommendations for single conditions. However, standardised care for each chronic condition in isolation can be inappropriate for individuals living with multiple long-term conditions known as multimorbidity, and may lead to unnecessary polypharmacy. This PhD studentship aims to develop a modelling framework to estimate the natural history of disease in individuals living with multiple long-term conditions using population-scale, linked, electronic health records from the Secure Anonymised Information Linkage (SAIL) Databank Wales Multimorbidity e-Cohort ( Lyons et al , 2021 ). This approach will allow estimation of the potential adverse effects (such as hospitalisations) of drug-on-drug interactions for the treatment of multiple conditions and associated genetic, environmental, or demographic risk factors. Further this PhD project will compare the efficacy of different combinations of treatments used in people with multiple long-term conditions, and assess potential health inequalities.   

Facilities 

The PhD student will be based in Population Data Science at Swansea University with visiting PhD Student Status at the Department of Statistics at the University of Warwick, benefiting from the stimulating and supportive environment and bespoke training programmes. The successful candidate will receive training to develop their knowledge and expertise in statistical modelling, epidemiology, population data science and health technology assessment, with the opportunity for their research to directly inform healthcare policy and practice. The successful student will have the opportunity to present their work at national and international conferences and workshops.  

This PhD is funded as part of the HDR UK Medicines in Acute and Chronic Care Driver Programme, which is a national collaboration that aims to understand and transform the use of medicines for patient benefit, and reduce medicines-associated harm. The Driver Programme has a particular focus on vulnerable populations including people living with multiple long-term conditions and those experiencing health inequalities. The successful candidate will be one of several PhD students contributing to the wider HDR UK Driver Programmes and will have the opportunity to collaborate with the wider HDR UK Driver Programme Team as well as access additional training and associated events hosted by HDR UK. 

Eligibility

Candidates must hold an Upper Second Class (2.1) honours degree. Candidates  will need an MSc in Statistics/Biostatistics or Epidemiology/Health Data Science (with a strong analytical component ) plus programming and data analysis skills/experience in R and/or Python.  

Experience of analysing large-scale linked electronic health record data and k nowledge of Bayesian methods would be an advantage.

If you are eligible to apply for the scholarship but do not hold a UK degree, you can check our comparison entry requirements (see  country specific qualifications ). Please note that you may need to provide evidence of your English Language proficiency. 

This scholarship is open to candidates of any nationality.

If you have any questions regarding your academic or fee eligibility based on the above, please email  [email protected]  with the web-link to the scholarship(s) you are interested in. 

This scholarship covers the full cost of tuition fees and an annual stipend of £ 19,237.

Additional research expenses will also be available.

How to Apply

To apply, please  complete your application online   with the following information:

In the event you have already applied for the above programme previously, the application system may issue a warning notice and prevent application, in this event, please email [email protected] where staff will be happy to assist you in submitting your application.

• Start year  – please select  2024
• Funding (page 8)  –
• ‘Are you funding your studies yourself?’ – please select  No
• ‘Name of Individual or organisation providing funds for study’ – please enter  ‘RS600 - Health Technology Assessment'

*It is the responsibility of the applicant to list the above information accurately when applying, please note that applications received without the above information listed will not be considered for the scholarship award.

One application is required per individual Swansea University led research scholarship award ; applications cannot be considered listing multiple Swansea University led research scholarship awards.

We encourage you to complete the following to support our commitment to providing an environment free of discrimination and celebrating diversity at Swansea University: 

• Equality, Diversity and Inclusion (EDI) Monitoring Form  (online form)  

As part of your online application, you MUST upload the following documents (please do not send these via e-mail).  We strongly advise you to provide the listed supporting documents by the advertised application closing date.  Please note that your application may not be considered without the documents listed:

• Degree certificates and transcripts  (if you are currently studying for a degree, screenshots of your grades to date are sufficient)
• A cover letter  including a ‘Supplementary Personal Statement’ to explain why the position particularly matches your skills and experience and how you choose to develop the project.
• Two references  (academic or previous employer) on headed paper or using the  Swansea University reference form . Please note that we are not able to accept references received citing private email accounts, e.g. Hotmail. Referees should cite their employment email address for verification of reference.
• Evidence of meeting  English Language requirement  (if applicable).
• Copy of  UK resident visa  (if applicable)
• C onfirmation of EDI form submission (optional)

Informal enquiries are welcome, please contact Professor  Rhiannon Owen  ( r.k.owen @swansea.ac.uk ).

*External Partner Application Data Sharing  – Please note that as part of the scholarship application selection process, application data sharing may occur with external partners outside of the University, when joint/co- funding of a scholarship project is applicable.

• Open access
• Published: 19 April 2024

Causes and outcomes of at-risk underperforming pharmacy students: implications for policy and practice

• Alice Campbell 1 ,
• Tina Hinton 1 , 2 ,
• Narelle C. da Costa 1 ,
• Sian E. O’Brian 1 ,
• Danielle R. Liang 1 &
• Nial J. Wheate 1  

BMC Medical Education volume  24 , Article number:  421 ( 2024 ) Cite this article

136 Accesses

Metrics details

This study aimed to understand the key determinants for poor academic performance of students completing a Bachelor of Pharmacy (BPharm), Bachelor of Pharmacy and Management (BPharmMgmt), or Master of Pharmacy (MPharm) degree.

Data were collected on pharmacy students who had not met academic progression requirements between 2008 and 2018 at The University of Sydney, Australia. This included: age at the start of pharmacy degree; gender; whether they transferred from another university; whether they were a domestic or international student; Australian Tertiary Admissions Rank upon entry, previous studies in biology, chemistry, or mathematics; show cause triggers (units of study failed); number of show causes; students’ written show cause responses; weighted average mark at last show cause or graduation; whether they graduated and were a registered pharmacist; and, the number of years they spent studying the degree. Descriptive studies were used to analyse student characteristics using SPSS software, and student self-reported reasons for poor performance were analysed reflexively using thematic analysis procedures using NVivo.

This study included 164 pharmacy students enrolled in a BPharm (79.3%, n  = 130), BPharmMgmt (1.2%, n  = 2), or MPharm (19.5%, n  = 32). Of the students, 54% ( n  = 88) were men, 81% ( n  = 133) were domestic students, 15% ( n  = 24) transferred from another degree program, and 38% ( n  = 62) graduated from the course. Show cause students were less likely to graduate if they transferred from another degree program ( P  = 0.0002) or failed more than three units of study (UoS; P  < 0.0001). The most commonly failed UoS were related to organic or pharmaceutical chemistry, and the top student self-reported reasons for poor performance was stress/anxiety, physical health, and depression.

Pharmacy schools should aim to address student foundational knowledge in chemistry, identify at-risk students early using pre-subject testing, and provide better services to address student mental health.

Peer Review reports

Introduction

A student’s academic performance in higher education is typically defined by their achievement of learning outcomes and demonstration of their ability to apply the concepts taught. Measurement of these attributes can include assessments, quizzes, role plays, field work, practical placements, workshops, tutorials, laboratories, and examinations. In most higher education programs, a minimum standard of academic achievement is required in order to progress through the course, to ensure the student has gained adequate knowledge and skills, and that they have achieved the specified learning outcomes. In this regard, poor academic performance can be defined by instances where a student fails to meet the expected minimum academic standard. Usually this comprises a minimum overall score in a subject and/or passing a specific barrier assessment, which is ultimately linked to their retention or attrition.

Understanding the key determinants of student success, failure, retention, and attrition has become increasingly important for higher education institutions, and has been the subject of extensive research over the past few decades. Early studies on student attrition focused primarily on student characteristics [ 1 ], before attention shifted to interactions between the student and their institutions. Prominent researchers, including Spady [ 2 , 3 ], Tinto [ 4 , 5 ], and Bean [ 6 ] proposed models to explain the interplay between academic and social integration leading to underperformance, and eventually, attrition. More recently, interest has increased in examining student engagement [ 7 , 8 , 9 ], where the student and institutions have a joint responsibility for academic success. To be successful, a student needs to participate, and higher education institutions need to provide an appropriate learning environment, opportunities, and support [ 10 ].

Studies on the key determinants of student underperformance reveal an array of contributing factors. Recent systematic reviews on underperformance and dropout rates show that key determinants fall into categories relating to the institution, personal life, demographics, and social integration [ 11 , 12 ]. Within higher education institutions, studies have found that an academic’s professional knowledge and pedagogical skills, along with the institution’s learning resources, course structure, and environment, are key factors that influence academic performance and non-completion [ 13 , 14 , 15 , 16 , 17 ]. Teaching methods that higher institutions adopt have also been evaluated, with student-centered approaches that encourage active learning resulting in better performance when compared with a traditional teacher-centered approach [ 15 , 16 ].

In terms of individual factors, studies have found a lack of effort, distraction, poor time management, and no longer being interested in the course as having a negative impact on academic performance [ 14 , 15 , 18 , 19 ]. Active learning (e.g. self-quizzes, completing problem sets, and explaining concepts) has been found to yield better academic outcomes when compared with passive learning (e.g. reading lecture slides or class notes, watching lecture videos, and reading textbooks) [ 20 , 21 ]. In the same study, how early a student studied in relation to their exam did not affect their outcome, whereas students who were more distracted during the time they allocated for study, performed worst [ 20 , 22 ]. Education-related stress, poor mental health, exam anxiety, and sleep quality are also factors found to cause poor performance [ 23 , 24 , 25 , 26 , 27 ]. Other studies have shown that part-time students and those who have previously failed subjects are at risk of further poor performance and attrition [ 17 , 28 , 29 ]. Social factors including cyberbullying [ 30 ], homesickness for international students [ 31 ], and excessive socialising [ 16 ] also have a negative effect on academic performance.

Working status was found to negatively impact academic performance [ 27 ], where poor academic outcomes were correlated with a longer time spent at work [ 16 , 28 , 32 ]. Many studies have associated the lower socioeconomic status of students and their family, or financial strain with poor academic performance [ 27 , 28 , 29 ]; whereas, other studies have shown that students in families where one parent has attended higher education tend to achieve higher grades [ 31 ]. Some studies have found men and minority students are more at risk of poor performance [ 31 , 33 ]. Part-time students are much more likely cite work and family responsibilities as reasons for stopping their studies [ 17 ]. Research on students whose first language is not that of the higher education institution is mixed, with some confirming it to be a key attributor to underperformance [ 34 , 35 , 36 ], along with students with a migrant background or who are first-generation university attendees (commonly referred to as first-in-family) [ 31 , 37 , 38 ]. In contrast, other studies have found that academic performance of international students was similar, or better, than domestic students [ 39 , 40 ].

A government panel in Australia reported that the leading drivers for non-completion in higher education are both institution-related (learning environment, an academic’s ability to teach, student to staff ratios, student engagement, and support services) and student-related (health, finance, and personal responsibilities) [ 41 ]. A survey conducted by the Australian Bureau of Statistics (ABS) identified the top three reasons for attrition for students studying a bachelors degree to be: loss of interest, employment/financial reasons, and personal reasons (health, family, or other personal reasons). For postgraduate courses, reasons for attrition were highest in the order of personal reasons, employment/financial, followed by loss of interest [ 42 ].

Where a student has underperformed, they may be offered remediation assessments; to re-enroll and attempt the entire subject again, which may result in a delay in degree completion; or in some cases, be excluded from reenrolling into the same course for a period of time [ 43 , 44 ].

Consequences of poor performance vary across higher education institutions and may depend on the reasoning provided, extent of underperformance, and number of failed subjects. Key stake holders impacted by poor performance and attrition from higher education can include the students and their families, the higher education institution they are enrolled in, their community workforce, and government. Non-completion directly impacts the funding and reputation of an institution [ 17 , 45 , 46 ]. In Australia, where the cost of higher education for domestic students is subsidised by the federal government, non-completion incurs a direct cost to both the student and the tax-payer. The cost to the student includes lost time, psychological health, student debt, and forgone income [ 9 ]. From the perspective of workforce planning, a delay or non-completion of study reduces the number of employees entering into the workforce, and can lead to workforce shortages and place a burden on those currently in the field.

There are many studies that have examined the key determinants for student success or underperformance and attrition in health; however, most have focused on nursing or medical education [ 13 , 15 , 47 , 48 , 49 , 50 ]. Consequently there are limited studies that have examined the rate and reasons for attrition within pharmacy degrees. Being a degree known to be difficult in technical content, and which requires students to achieve a high level of competence, it is important to investigate reasons for attrition and potential opportunities for improvement in student teaching and engagement.

In this study we analysed 10 years of demographic data and responses to why academic progression requirements had not been met in a cohort of students enrolled in a Bachelor of Pharmacy (BPharm), Bachelor of Pharmacy and Management (BPharmMgmt), or Master of Pharmacy (MPharm) degree at The University of Sydney. Our aim was to understand the key determinants for poor performance within this group of students and identify opportunities for policy and practice to reduce underperformance in the future.

Approval for this study was granted by the Human Research Ethics Committee of The University of Sydney (2022/815).

Data collection

The inclusion criteria for this study were students enrolled in a BPharm, BPharmMgmt, or MPharm degree between the period of 2008 and 2018 (inclusive), who were required to provide a minimum of one show cause at any stage of their study. Data collected on each student included: age at the start of pharmacy degree; gender; whether they transferred from another university; whether they were a domestic or international student; Australian Tertiary Admissions Rank (ATAR) upon entry, which is a percentile score that ranks Australian students finishing secondary school in relation to their academic achievement [ 51 ]; previous studies in biology, chemistry, or mathematics; show cause triggers (units of study failed); number of show causes; students’ written show cause responses; weighted average mark (WAM) at last show cause or graduation (WAM is an average grade score indicating a student’s overall academic performance over the course of their degree and is similar to a grade point average) [ 52 ]; whether they graduated; and, the number of years they spent studying the degree. Whether those students who had graduated were currently registered as a pharmacist in Australia was retrieved using the Australian Health Practitioner Regulation Agency online registry list [accessed in 2023].

Data analysis

Researchers Da Costa, O’Brien, and Liang collected, screened, and de-identified the data, and researchers Campbell, Hinton, and Wheate analysed the data. Descriptive statistics, including mean ± SD, median, and frequencies (count and percentage) were calculated using Microsoft Excel. Mann-Whitney U tests were undertaken in GraphPad Prism 9.0 (GraphPad Software, Boston, MA, USA) to ascertain any differences between ATAR scores. Chi Square analyses were undertaken in GraphPad Prism 9.0 to compare categorical data including differences between men and women, domestic and international students, transferring and non-transferring students, and graduating and non-graduating students.

Written show cause responses were transcribed by Campbell and uploaded into NVivo (1.5.1) software (QSR International, Massachussets USA). The show cause responses were analysed reflexively using inductive thematic analysis procedures [ 53 ].This involved manually reviewing each show cause response to identify emerging themes relating to the reasons stated by the student for their poor performance. From the themes identified, a total of 43 codes were generated based on the ideas, trends, and content. Coding was conducted in a theory-driven manner, seeking to code information referencing the specific themes arising from the show cause response [ 53 ]. Themes were guided by the frequency of mention, and reported in the results if there was more than a single mention. The frequency of the subthemes was analysed to demonstrate the prevalence of stated factors that the student believed led to their poor performance.

Show cause process

Pharmacy students who do not meet the progression requirements of their degree enter one of three stages of academic intervention (Fig.  1 ). Triggers for a student not meeting the requirements for progression include: awarded a fail grade in over 50% of total units of study (subjects; UoS) taken in a semester or teaching period; an average grade (WAM) less than 50 across all UoS in a semester or teaching period; failing one, or more, barrier or compulsory UoS which includes CHEM1611, CHEM1612, PHAR2822, and any 3000 or 4000 level UoS for BPharm/BPharmMgmt; and any single UoS for MPharm; any practical component (e.g. field work or clinical work), failing the same UoS twice, having unsatisfactory attendance, or exceeding the maximum time limit allowed for the degree to be completed.

Students who fail to meet progression requirements for the first time are placed on Stage 1 of the at-risk register at which point they receive a letter from the Faculty of Medicine and Health, and are advised to complete a ‘Stay on Track’ survey and information session. At the discretion of the Associate Dean of Education, some students at Stage 1 may be required to consult an academic adviser. If a student is enrolled in a degree with a duration of less than two years full-time (e.g. MPharm), they are advised that should they fail to meet progression requirements in the following semester, they would be asked to ‘show good cause’ in order to be allowed to re-enrol in the same program; that is, they would be excluded from the degree for two years unless they could give reasons for why they should be allowed to remain studying. They are also recommended to speak to an academic advisor.

Stage 2 is triggered for a student in a 4 or 5 year undergraduate degree program (e.g. BPharm and BPharmMgmt) if they fail to meet progression requirements after being placed on Stage 1 in the previous semester, at which point the faculty sends a letter, advising the student to complete the ‘Staying on Track’ survey if they had not yet done so, and to consult an academic adviser. Stage 3 is triggered if a student fails to meet progression requirements a third time, or fails the same compulsory or barrier UoS, or any practical component twice. Students on Stage 3 are required to ‘show good cause’ and provide reasonable evidence to be allowed to re-enrol into the degree program.

The three at-risk stages of academic intervention for students who fail to meet course progression requirements. Show cause is required at Stage 2 (MPharm) or Stage 3 (BPharm/BPharmMgmt) in order to re-enrol

Demographics

In total, 164 pharmacy students received at least one show cause notification between the period of 2008 to 2018 (inclusive) and were enrolled in a BPharm (79.3%, n  = 130), BPharmMgmt (1.2%, n  = 2), or MPharm (19.5%, n  = 32) degree (Table  1 ). Of the students, 54% ( n  = 88) were men, and 81% ( n  = 133) were domestic students.

Students who transferred from another degree program made up 15% ( n  = 24) of the sample, and were a median two years older than those who did not transfer (median age 21, range 19–43 years). All students who transferred from another degree, were enrolled in the BPharm. Ninety-two percent of transfer students ( n  = 22) were domestic and 71% ( n  = 17) were women.

The age of students at the start of their degree was positively skewed, with a median age of 19 years for BPharm and BPharmMgmt (range 17–43 years). For MPharm, the median age at commencement was 24 (range 20–24) years. The median age of domestic students at the start of their BPharm or BPharmMgmt degree was 19 (range 17–43) years compared with international students at 22 (range 18–33) years. For MPharm, the median age for domestic students at commencement was 24 (range 20–54) years while for international students it was 24.5 (range 22–38) years.

Performance on entry and exit of the degree

The ATAR scores of the students in either the BPharm or BPharmMgmt were not normally distributed ( n  = 78, mean ATAR 88.8 ± 4.8) (Supplementary Figure S1 ). The average ATAR required for entry into BPharm and BPharm/Mgmt at the University of Sydney is around 90. Of the 24 students who transferred from another degree program, the ATAR score was available for four students, with an average of 78.8 ± 9.8, including two outliers who had ATAR scores of 67.80 and 74.15. The average ATAR on entry to the degree of the students who graduated was 89.4 ± 3.4, which was similar to those who did not graduate, 88.5 ± 5.4. A Mann-Whitney U test showed this difference was not statistically significant (W = 702.5, p  = 0.937).

The proportion of students who graduated after receiving at least one show cause was 37.8% ( n  = 62), of which 77.4% ( n  = 48) were registered as pharmacists at the time of data collection (Fig.  2 ). One student did not graduate their BPharm; however, they did return and complete the MPharm degree and was registered as a pharmacist at the time of data collection. The median time taken to graduation was 7 (range 1–9) years for students enrolled in the BPharm and 3 (range 2.5-8) years for those enrolled in the MPharm. During the study period, 188 students were enrolled in the BPharmMgmt degree but only two (1.1%) were required to show cause due to poor performance. Neither of those two students graduated.

A WAM score was available for all but three of the 164 students. The overall average WAM either at last show cause, if the student had not graduated, or at degree completion was 52.1 ± 12.0. For students who graduated (38.5%, n  = 62), the average WAM was 62.2 ± 5.1, while for those who did not graduate (61.5%, n  = 99), the average WAM was 45.7 ± 10.5.

When the proportion of students who graduated was compared across the ATAR bands (Table S1 ), it was evident that show cause students who entered their degree with an ATAR between 85 and 89.99 were more likely to graduate (44%) when compared with those who entered their degree with lower (27%) and higher (25–35%) ATAR scores.

Units failed

Across the cohort, show cause students received between 1 and 8 show cause notifications (Fig.  1 ). When the proportion of students who graduated was compared across the number of show causes received for those who received 1–5 show causes, the rate of graduation ranged from 36 to 50%, while none of the students who received six or more show causes graduated.

Percentage of students who graduated (black) and did not graduate (grey) by number of show causes received

Number of failed UoS

The median number of UoS failed across the three degree programs was 8 (BPharm, range 2–33), 9 (BPharmMgmt, range 5–13), and 5 (MPharm, range 2–12), respectively. In total, 8.5% ( n  = 14) students were required to show cause because they failed 2 or 3 UoS, 19.5% ( n  = 32) students failed 4 or 5 UoS and 72% ( n  = 118) students failed more than 6 UoS. Of the 14 students who failed 2 or 3 UoS, 86% were studying the MPharm degree and the remaining were BPharm students. Students who failed 4 or 5 UoS, were studying a BPharm (66%), BPharmMgmt (3%), or MPharm (31%) degree. The majority of students who failed more than 6 units were studying BPharm (91%), followed by MPharm (8%), and BPharmMgmt (1%). Students who failed 2 or 3 UoS were significantly more likely to graduate when compared with those who failed 4 or 5 UoS, or more than 6 UoS \( (X_2^2=21.86, \text{P}<0.0001)\) (Supplementary Figure S2 ).

Type of failed UoS

The most failed UoS that triggered a show cause across students in the BPharm and BPharmMgmt degrees were a mix of pharmaceutical sciences, chemistry and biology, across the first and second years of the degree programs (Table  2 ). The top five UoS failed were Basic Pharmaceutical Sciences (8.8%, 116/1314 fails; unit code: PHAR1812), Chemistry 1B (Pharmacy) (6.9%, 91/1314 fails; unit code: CHEM1612), Drug Discovery and Design 1 (6.7%, 88/1465 fails; unit code: PHAR2811), Molecular Biology and Genetics (6.5%, 86/1314 fails; unit Code: MBLG1001), and Chemistry 1A (6.2%, 81/1314 fails; unit code: CHEM1611).

For students studying the MPharm, the majority of UoS failed were for pharmaceutical sciences in first year and one specific pharmacy practice unit (PHAR5717) in the second year. The top three UoS failed for MPharm were Pharmaceutical Chemistry 1A (12.6% 19/151 fails; unit code: PHAR5513), Pharmaceutical Science (7.9%, 12/151 fails; unit code: PHAR5515), and Pharmaceutical Chemistry 1B (7.9%, 12/151 fails; unit code: PHAR5516) (Table  3 ).

Gender, transfer and international students

There was no significant difference between the number of men and women who graduated after receiving at least one show cause \( (X_1^2=0.056, \text{P}=0.813)\) . There was also no significant difference in the number of UoS failed \( (X_2^2=2.249, \text{P}\hspace{0.17em}=\hspace{0.17em}0.325)\) or number of show causes received \( (X_6^2=2.829, \text{P}=0.830)\) between men and women.

Students who transferred from another degree program were significantly less likely to graduate \( (X_1^2=13.53, \text{P}\hspace{0.17em}=\hspace{0.17em}0.0002)\) . The likelihood of graduating was not statistically significant different between domestic and international students who received a show cause \( (X_1^2=0.88, \text{P}<0.348)\) (Supplementary Figure S3 ).

Student responses to show causes

There were 293 show causes in total, of which only 141 show cause response letters were available. Reasons given by students for their poor performance could be classified under four major themes: personal life matters, institutional aspects, social integration, and interest in the course (Fig.  3 ). Personal life matters could be further sub-divided into health, study familiarity, responsibilities, and other personal life matters.

The majority of show cause responses attributed poor performance to personal life reasons (87%, 396 responses), followed by institution-related (8.8%, 40 responses), lack of interest in the degree (2.2%, 10 responses), and social integration (2%, 9 responses). The five most mentioned personal life reasons that led to poor performance were stress and anxiety ( n  = 63, 45%), physical health ( n  = 51, 36%), and depression ( n  = 39 28%). This was followed by family health, mentioned 37 times (26%), and reasons relating to employment or financial health, mentioned 33 times (23%). Reasons that related to the institution totalled 40, interest of the course totalled 10, and social reasons totalled 9. Personal life health-related reasons accounted for 41% of show cause responses. These included a combination of physical, mental, and unspecified health issues.

All show cause responses provided by students could be categorised into four major themes. Personal life was subcategorised into health, study skills, responsibilities, and other personal life

Some students identified a lack of study-related skills and study familiarity as a source of underperformance. Reasons included: carelessness in exams, poor study habits, language barrier, being an international student or mature age student, misjudging the course difficulty, overloading, burning out after high school, and being unaware of opportunities to apply for special consideration. Another set of reasons provided for underperformance included: needing to meet responsibilities and commitments for family, friendships, and romantic relationships. A variety of other personal life reasons were provided, which included: employment, finance, transition to independent living or a new country, living environment, distance to travel to the university, needing to relocate, and being physically unable to attend classes.

Student show cause responses that attributed poor performance to inefficiencies within the institution included UoS changes, error or poor timing of exams, dissatisfaction with the course and staff, and unhelpful support. Some students found the UoS content too difficult. Social reasons that lead to poor performance included: bullying, stigma from peers once failing, and homesickness (for those studying abroad). Another reason provided was no longer being interested or committed to the course.

This study investigated the key determinants of underperformance by pharmacy students at an Australian higher education institution. Our findings indicate that across the students enrolled in BPharm, BPharmMgmt, and MPharm degrees, those who had failed more UoS overall, were less likely to graduate. The types of UoS failed were weighted towards chemistry-based subjects, and the most frequent student-reported reasons for poor performance were related to personal health.

Our study also found that students who transferred from another higher education institution were less likely to graduate compared with students who had not transferred. Some studies in the US have found that students who transfer to bachelors programs from similar institutions or community colleges, which are US institutions that only offer two year undergraduate associate degrees that lead to a specific skilled job or can be used to transfer into a bachelor course [ 54 ], experience ‘transfer shock’ where grade point average (GPA) declines at the post transfer institution, which can eventually result in attrition [ 55 , 56 ]. In contrast, other studies have found no significant effects from transfers, and an overall lack of consensus on this as a universal experience [ 57 , 58 ]. A study that examined transferring engineering students found that students who transferred from similar degrees were more likely to graduate when compared with students who transferred from less comprehensive degrees [ 56 ]. A literature review that examined transferring student performance found factors that negatively influenced persistence and course completion included: a lack of social integration, limited transferrable credits, lower GPAs, lack of funding, distance from institution, academic rigour, and personal work/life balance [ 57 ].

Our analysis also found that students failing more than three UoS were more likely to not graduate when compared with those who failed fewer UoS. This finding parallels many studies that show students with poor academic outcomes are more likely to not complete their degree [ 59 , 60 ]. A recent study on student attrition, found that students who failed one subject were more likely to fail more subjects, and also had a four-fold higher likelihood of not graduating [ 27 ]. The Grattan Institute presents similar statistics, where students who consistently fail to meet academic progression requirements eventually decide to leave or are excluded from re-enrolling by the university [ 61 ].

The high occurrence of underperformance in relation to chemistry is consistent with other studies [ 62 , 63 ]. Pancyk et al. found that chemistry marks were correlated with attrition while biology marks predicted likelihood of delayed graduation for Master of Science (in Pharmacy) students. Another study found that the prior attainment of a Bachelor of Science degree to be a predictor of performance in a Doctor of Pharmacy program [ 64 ]. In countries, such as the US, where a specialised pre-admissions pharmacy test (Pharmacy College Admissions Test; PCAT) is used for entrance into a pharmacy program, the PCAT score correlated with student academic performance in the pharmacy course [ 65 ]. There are five areas examined by the PCAT, including: writing, biological processes, chemical processes, critical reading, and quantitative reasoning [ 66 ]. There is also evidence that better outcomes attained in pre-pharmacy biology and mathematics GPA [ 67 , 68 ], or having completed a four-year bachelor course, contributes to student performance in American pharmacy colleges [ 64 , 69 , 70 ]. Another study found prior academic achievement in secondary school, or pre-university study, can predict performance in an UK MPharm course; however, not the likelihood of graduation [ 71 ]. Other studies have found that pre-tests, for certain UoS, like biochemistry and pharmaceutical calculations conducted before starting a subject are correlated with overall subject performance, which makes these tests a good predictor for at-risk students [ 67 , 68 ].

The most common reasons reported by students for their underperformance in the present study were stress and anxiety, personal health, and depression. This is consistent with current literature [ 17 , 23 , 24 , 25 , 26 , 27 ], and the 2022 Australian Student Experience Survey [ 72 ], which reported that health or stress, followed by work/life balance were the leading causes for students attrition. A specific study in pharmacy students found that exam anxiety had a negative impact on student performance in pharmacy practical exams [ 26 ]. Psychological distress among students completing a higher education degree in Norway showed negative impacts on their self-perceived academic ability, and course progression [ 73 ]. Another study investigating students’ self-reported explanations for their poor academic performance found mental health as a contributing factor, and vice versa, where poor performance intensified mental distress [ 27 ]. Although the Australian Bureau of Statistics also reported personal health reasons as a major contributor for non-completion in bachelor programs between 2018 and 2019, the leading reason was that students were no longer interested in their chosen degree. In the same report, non-completion of masters degrees was driven by family, health, or other personal reasons [ 42 ]. Student mental health is a significant driver of attrition and is common across both private and public higher institutions in Australia [ 41 ]. The mental health burden on students is recognised at The University of Sydney and so significant mental health support is offered. All students are able to access free counselling and psychological support sessions, there is a 24/7 mental health support telephone line, and additional self-help resources (like mindfulness and relaxation) are provided through the university’s website. Mental health first health training is also included in the curricula for all pharmacy degree programs at the university.

Successful completion of a pharmacy degree requires not only academic ability, but a certain level of pre-knowledge, in particular, biology and chemistry, to decrease failure rates in these subjects, avoid delays in degree completion, and possible attrition. Institutions should aim to address these barriers by introducing pre-requisite subjects or mandate compulsory bridging courses if a prior level of knowledge attainment in these subject areas is not provided. Alternatively, pre-tests for certain UoS can be conducted prior to the course commencement to identify at-risk students, and additional academic support services can be offered.

With student poor mental health found as the most common self-reported reason for poor performance in this study, often exacerbated by academic performance pressures, institutions should implement policies for early detection and support for students going through challenging times. Such policies could include more frequent reminders for students to self-assess their mental health, and information on where to seek support services. This could take form in programs being introduced prior to lectures, access to support portals made more prominent on online learning platforms, or self-check surveys to be taken at a frequency deemed appropriate.

Limitations

The present study had a number of limitation. Not all student’s ATAR scores (or equivalent) were available. The method of collecting whether a student was registered as a pharmacist was based on them not having changed their last name which may be the case for some students who changed their name after graduation (e.g. upon marriage). Students who may be registered as a pharmacist in countries other than Australia could not be determined. Not all student show cause reasons were available because of the change from physical to electronic filing over the period studied. The limited number of students who received five or more show causes also meant the study was not powered to establish a cut-off whereby after receiving a certain number of show causes, the chance of graduating is highly unlikely.

Conclusions

This study investigated the key determinants for poor academic performance in a cohort of pharmacy students enrolled in a BPharm, BPharmMgmt, and MPharm degree. The key factors that influenced whether a show cause student completed their studies included whether they transferred from another institution, and failed more than three UoS. The UoS with the highest fail rates were chemistry based, and the most frequent student self-reported reason for poor performance was personal stress and anxiety. The results indicate that pharmacy schools should aim to address student foundation knowledge in chemistry, identify at-risk students early using pre-subject testing, and provide better access and knowledge of available services to address student mental burden. Future studies should investigate whether students who have completed chemistry and biology pre-requisites perform better in their pharmacy degree.

Data availability

The data that support the findings of this study are available on request from the corresponding author, N.J.W.

Aljohani O. A comprehensive review of the major studies and theoretical models of student retention in higher education. High Educ Stud. 2016;6:1–18.

Article   Google Scholar  

Spady WG. Dropouts from higher education: an interdisciplinary review and synthesis. Interchange 1984. 1970;1(1):64–85.

Spady WG. Dropouts from higher education: toward an empirical model. Interchange. 1971;2(3):38–62.

Tinto V. Dropout from higher education: a theoretical synthesis of recent research. Rev Educ Res. 1975;45(1):89–125.

Tinto V. Leaving college: rethinking the causes and cures of student attrition. 2nd ed. Chicago: University of Chicago Press; 1993.

Google Scholar  

Bean JP. Dropouts and turnover: the synthesis and test of a causal model of student attrition. Res High Educ. 1980;12(2):155–87.

Tight M. Student retention and engagement in higher education. J Furth High Educ. 2020;44(5):689–704.

Carini RM, Kuh GD, Klein SP. Student engagement and student learning: testing the linkages. Res High Educ. 2006;47(1):1–32.

Thomas L, Kift S, Shah M. Student retention and success in higher education. Cham: Springer International Publishing; 2021. pp. 1–16.

Book   Google Scholar  

Coates H. The value of student engagement for higher education quality assurance. Qual High Educ. 2005;11(1):25–36.

Al-Tameemi RAN, Johnson C, Gitay R, Abdel-Salam A-SG, Hazaa KA, BenSaid A, et al. Determinants of poor academic performance among undergraduate students—A systematic literature review. Int J Educ Res. 2023;4:100232.

Lorenzo-Quiles O, Galdón-López S, Lendínez-Turón A. Factors contributing to university dropout: a review. Front Educ Res. 2023;8.

Wilkinson TJ, McKenzie JM, Ali AN, Rudland J, Carter FA, Bell CJ. Identifying medical students at risk of underperformance from significant stressors. BMC Med Educ. 2016;16:43.

Le HTTN, La HTT, Le TP, Nguyen TTT, Nguyen NT, Tran TP. Factors affecting academic performance of first-year university students: a case of a Vietnamese university. Int J Educ Prac. 2020;8(2):221–32.

Sharma P, Singh P, Kalhan S, Garg S. Analysis of factors affecting academic performance of MBBS students in pathology. Ann Int Med Dent Res. 2017;2.

Mascolo M, Castillo J. The origins of underperformance in higher education in America: proximal systems of influence. Pedgog Hum Sci. 2015;5(1):1–40.

Norton AC, I. and, Mackey W. Dropping out: the benefits and costs of trying university. The Grattan Institute, 2018. p. 1–65.

van Rooij E, Jansen EPWA, Van de Grift W. First-year university students’ academic success: the importance of academic adjustment. Eu J Psychol Educ. 2017;33:1–19.

Arshad M, Zaidi SM, Mahmood D. Self-esteem and academic performance among university students. J Educ Pract. 2015;6:2015.

Walck-Shannon EM, Rowell SF, Frey RF. To what extent do study habits relate to performance? CBE - Life Sci Educ. 2021;20(1):ar6.

Roick J, Ringeisen T. Students’ math performance in higher education: examining the role of self-regulated learning and self-efficacy. Learn Individ Differ. 2018;65:148–58.

Nonis SA, Hudson GI. Performance of college students: impact of study time and study habits. J Educ Bus. 2010;85(4):229–38.

Jevons C, Lindsay S. The middle years slump: addressing student-reported barriers to academic progress. High Educ Res Dev. 2018;37(6):1156–70.

Pascoe MC, Hetrick SE, Parker AG. The impact of stress on students in secondary school and higher education. Int J Adolesc Youth. 2020;25(1):104–12.

May RW, Bauer KN, Seibert GS, Jaurequi ME, Fincham FD. School burnout is related to sleep quality and perseverative cognition regulation at bedtime in young adults. Learn Individ Differ. 2020;78:101821.

Hadi MA, Ali M, Haseeb A, Mohamed MMA, Elrggal ME, Cheema E. Impact of test anxiety on pharmacy students’ performance in Objective Structured Clinical examination: a cross-sectional survey. Int J Pharm Pract. 2018;26(2):191–4.

Ajjawi R, Dracup M, Zacharias N, Bennett S, Boud D. Persisting students’ explanations of and emotional responses to academic failure. High Educ Res Dev. 2020;39(2):185–99.

Rodríguez-Hernández CF, Cascallar E, Kyndt E. Socio-economic status and academic performance in higher education: a systematic review. Educ Res Rev. 2019;29:100305.

Tomul E, Polat G. The effects of socioeconomic characteristics of ctudents on their academic achievement in higher education. Am J Educ Res. 2013;1:449–55.

Peled Y. Cyberbullying and its influence on academic, social, and emotional development of undergraduate students. Heliyon. 2019;5(3):e01393.

Sun J, Hagedorn L, Zhang Y. Homesickness at college: its impact on academic performance and retention. J Coll Stud Dev. 2016;57:943–57.

Triventi M. Does working during higher education affect students’ academic progression? Econ Educ Rev. 2014;41:1–13.

Voyer D, Voyer SD. Gender differences in scholastic achievement: a meta-analysis. Psychol Bull. 2014;140(4):1174–204.

Dafouz E, Camacho-Miñano MM. Exploring the impact of English-medium instruction on university student academic achievement: the case of accounting. Engl Specif Purp. 2016;44:57–67.

Civan A, Coskun A. The effect of the medium of instruction language on the academic success of university students. Educ Sci: Theory Prac. 2016;16:1981–2004.

Sawir E. Language difficulties of international students in Australia: the effects of prior learning experience. Int Educ J. 2005;6:567–80.

Mishra S. Social networks, social capital, social support and academic success in higher education: a systematic review with a special focus on ‘underrepresented’ students. Educ Res Rev. 2020;29:100307.

López MJ, Santelices MV, Carmen Maura T. Academic performance and adjustment of first-generation students to higher education: a systematic review. Cogent Educ. 2023;10(1).

Zheng RX, Everett B, Glew P, Salamonson Y. Unravelling the differences in attrition and academic performance of international and domestic nursing students with English as an additional language. Nurse Educ Today. 2014;34(12):1455–9.

Rienties B, Beausaert S, Grohnert T, Niemantsverdriet S, Kommers P. Understanding academic performance of international students: the role of ethnicity, academic and social integration. High Educ. 2012;63(6):685–700.

Final Report -. Improving retention, completion and success in higher education. Higher Education Standards Panel; Australian Government Department of Education; 2017.

Qualifications. and Work, 2018-19. Australian Bureau of Statistics; 2020.

Academic Progression. The University of Sydney [updated 31 March 2023; cited 2023 September ]. Available from: https://www.sydney.edu.au/students/academic-progression.html .

Failed. withheld and invalid units: Monash University; [updated 2023; cited 2023 September]. Available from: https://www.monash.edu/students/admin/enrolments/change/failed-withheld-invalid-units .

OCED. Education at a Glance 2023. Organisation for Economic Co-operation and Development Publishing 2023 [Available from: https://www.oecd-ilibrary.org/content/publication/e13bef63-en .

Yorke M, Longden B. Retention and student success in higher education. McGraw-Hill Education (UK); 2004.

Faisal R, Shinwari L, Hussain S. Academic performance of male in comparison with female undergraduate medical students in pharmacology examinations. J Pak Med Assoc. 2017;67:204–8.

van Moppes NM, Willems S, Nasori M, Bont J, Akkermans R, van Dijk N et al. Ethnic minority GP trainees at risk for underperformance assessments: a quantitative cohort study. Br J Gen Pract Open. 2023;7(1).

Liu XL, Wang T, Bressington D, Nic Giolla Easpaig B, Wikander L, Tan JB. Factors influencing retention among regional, rural and remote undergraduate nursing students in Australia: a systematic review of current research evidence. Int J Environ Res Public Health. 2023;20(5).

Caponnetto V, Dante A, Masotta V, La Cerra C, Petrucci C, Alfes CM, et al. Examining nursing student academic outcomes: a forty-year systematic review and meta-analysis. Nurse Educ Today. 2021;100:104823.

Australian Tertiary Admission Rank. Universities Admission Centre; [cited 2023 November ]. Available from: https://www.uac.edu.au/future-applicants/atar .

Weighted Average Mark (WAM). The University of Sydney; 2023 [cited 2023 November]. Available from: https://www.sydney.edu.au/students/weighted-average-mark.html .

Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.

Community College. Education USA; [cited 2023 November ]. Available from: https://educationusa.state.gov/ .

Ivins T, Copenhaver K, Koclanes A. Adult transitional theory and transfer shock in higher education: practices from the literature. Ref Serv Rev. 2017;45(2):244–57.

Smith NL, Grohs JR, Van Aken EM. Comparison of transfer shock and graduation rates across engineering transfer student populations. J Eng Educ. 2022;111(1):65–81.

Aulck L, West J. Attrition and performance of community college transfers. PLoS ONE. 2017;12:e0174683.

Diaz PE. Effects of transfer on academic performance of community college students at the four-year institution community. Coll J Res Prac. 1992;16(3):279–91.

Li I, Carroll D. Factors influencing university student satisfaction, dropout and academic performance: an Australian higher education equity perspective. Perth: National Centre for Student Equity in Higher Education, Curtin University;; 2017. p. 56.

Sosu EM, Pheunpha P. Trajectory of university dropout: investigating the cumulative effect of academic vulnerability and proximity to family support. Front Educ. 2019;4.

Cherastidtham I, Norton A, Mackey W. University attrition: what helps and what hinders university completion? Grattan Institute; 2018.

Panczyk M, Rebandel H, Belowska J, Zarzeka A, Gotlib J. Risk of attrition from master of science in pharmacy degree program: 15-year predictive evaluation. Ind J Pharm Educ Res. 2016;50(1):70–9.

Houglum JE, Aparasu RR, Delfinis TM. Predictors of academic success and failure in a pharmacy professional program. Am J Pharm Educ. 2005;69(1–5):283–9.

McCall KL, Allen DD, Fike DS. Predictors of academic success in a doctor of pharmacy program. Am J Pharm Educ. 2006;70(5):106.

Meagher DG, Pan T, Perez CD. Predicting performance in the first-year of pharmacy school. Am J Pharm Educ. 2011;75(5):81.

Pharmacy College Admission Test American Association of Colleges of Pharmacy. [updated 2023; cited 2023 October]. Available from: https://www.aacp.org/resource/pharmacy-college-admission-test .

Vinall R, Khansari P, McDowell J, Ried LD, Kreys E. Impact of completion of a pre-pharmacy biochemistry course and competency levels in pre-pharmacy courses on pharmacy student performance. Pharm 2019;7(3).

Aronson BD, Eddy E, Long B, Welch OK, Grundey J, Hinson JL. Identifying low pharmaceutical calculation performers using an algebra-based pretest. Am J Pharm Educ. 2022;86(1):8473.

Chisholm MA, Cobb HH, DiPiro JT, Lauthenschlager GJ. Development and validation of a model that predicts the academic ranking of first-year pharmacy students. Am J Pharm Educ. 1999;63(4):388–93.

Chisholm MA, Cobb HH, Kotzan JA. Significant factors for predicting academic success of first-year pharmacy students. Am J Pharm Educ. 1995;59(4):364–70.

Bush J. Entry characteristics and academic performance of students in a master of pharmacy degree program in the United Kingdom. Am J Pharm Educ. 2012;76(7).

2022 Student Experience Survery. National Report. 2023.

Grøtan K, Sund ER, Bjerkeset O. Mental health, academic self-efficacy and study progress among college students - the SHoT Study, Norway. Front Psychol. 2019;10:45.

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ND, SO, and DL collated and de-identified the data. AC, TH, and NW analysed the data and wrote the manuscript.

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Campbell, A., Hinton, T., da Costa, N.C. et al. Causes and outcomes of at-risk underperforming pharmacy students: implications for policy and practice. BMC Med Educ 24 , 421 (2024). https://doi.org/10.1186/s12909-024-05327-z

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DOI : https://doi.org/10.1186/s12909-024-05327-z

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