Patient Complexity, Social Factors, and Hospitalization Outcomes at Academic and Community Hospitals
Bibliographic record
Abstract
Importance: There have been limited evaluations of the patients treated at academic and community hospitals. Understanding differences between academic and community hospitals has relevance for the design of clinical models of care, remuneration for clinical services, and health professional training programs. Objective: To evaluate differences in complexity and clinical outcomes between patients admitted to general medical wards at academic and community hospitals. Design, Setting, and Participants: This retrospective cohort study of patients admitted to general medicine at 28 hospitals in Ontario, Canada, was conducted between April 2015 and December 2021. All patients admitted to or discharged from general medicine during the study period who were older than 18 years were included. Data analysis occurred between February 2023 and June 2024. Exposures: Patient admission to a general medicine inpatient service at an academic or community hospital. Main Outcomes and Measures: Demographic and clinical characteristics (age, sex, modified Laboratory-based Acute Physiology Score [mLAPS], discharge diagnosis, Charlson Comorbidity Index, frailty risk score, and disability), social factors (neighborhood-level markers of income, material deprivation, immigrant status, and racial and ethnic minority status) and clinical outcomes and processes (patient volume per physician, in-hospital mortality, length of stay, readmission rates, and intensive care unit [ICU] admission rates). Results: There were 947 070 admissions, including 609 696 at 17 community hospitals (median [IQR] age, 73 [58-84] years) and 337 374 at 11 academic hospitals (median [IQR] age, 70 [56-82] years). Baseline clinical characteristics were similar at community and academic hospitals, including female sex (307 381 [50.4%] vs 168 033 [49.8%]; standardized mean difference [SMD] = 0.012), median (IQR) mLAPS (21 [11-36] vs 21 [10-34]; SMD = 0.001), and Charlson Comorbidity Index score of 2 or greater (182 171 [29.9%] vs 105 502 [31.3%]; SMD = 0.038). Social characteristics, including income, education, and neighborhood proportion of racial and ethnic minority and immigrant residents were also similar. The number of unique discharge diagnoses was similar at academic and community hospitals. Patient volumes per attending physician were higher at academic hospitals (median [IQR] daily census, 20 [19-22] vs 17 [15-19]; SMD = 1.086). After multivariable regression adjusting for baseline factors, mortality (adjusted odds ratio [aOR], 0.96; 95% CI, 0.78 to 1.17), ICU admission rate (aOR, 1.20; 95% CI, 0.80 to 1.79) and length of stay (β = -0.001; 95% CI, -0.10 to 0.10) were not significantly different, while 7-day readmission (aOR, 1.25; 95% CI, 1.10 to 1.43) and 30-day readmission (aOR, 1.25; 95% CI, 1.10 to 1.42) were significantly higher at academic hospitals than community hospitals. Conclusions and Relevance: In this cohort study, patients admitted to general medicine at academic and community hospitals had similar baseline clinical characteristics and generally similar clinical outcomes, with greater readmission rates in academic hospitals. These findings suggest that the patient case mix in general internal medicine that trainees would be exposed to during their residency training at academic hospitals is largely representative of the case mix they would encounter at community hospitals, and has important implications for health services planning and funding.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".