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Association of Early Physician Follow-up With Readmission Among Patients Hospitalized for Acute Myocardial Infarction, Congestive Heart Failure, or Chronic Obstructive Pulmonary Disease

2022· article· en· W4285078476 on OpenAlexafffundabout
Farah E. Saxena, Arlene S. Bierman, Richard H. Glazier, Xuesong Wang, Jun Guan, Douglas S. Lee, Thérèse A. Stukel

Bibliographic record

VenueJAMA Network Open · 2022
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreTed Rogers Centre for Heart ResearchInstitute for Clinical Evaluative SciencesUniversity of TorontoSt. Michael's HospitalCanadian Partnership Against Cancer
FundersCanadian Institutes of Health ResearchUniversity of TorontoOntario Ministry of Health and Long-Term Care
KeywordsMedicineHeart failureMyocardial infarctionInternal medicineCardiologyPulmonary disease

Abstract

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Importance: A better understanding of the association between early physician follow-up after discharge and adverse outcomes among hospitalized patients may inform interventions aimed at reducing readmission for common chronic conditions. Objective: To assess whether hospitalized patients with early physician follow-up after discharge had lower rates of overall and condition-specific readmissions within 30 days and 90 days of discharge. Design, Setting, and Participants: This cohort study was conducted among Ontario, Canada, adults with first admission for acute myocardial infarction (AMI), congestive heart failure (CHF), or chronic obstructive pulmonary disease (COPD) during 2005 to 2019. The exposure was follow-up visit with a primary care physician or relevant specialist within 7 days of discharge. Cox proportional hazards models were used to compare patients with vs without early follow-up, adjusting for sociodemographic factors and comorbidities, weighting by propensity score-based overlap weights. Data were analyzed from January through July 2021. Main Outcomes and Measures: Primary outcomes were 30-day and 90-day readmissions, cardiac readmissions (readmission for AMI, CHF, or angina) for patients with cardiac conditions, and COPD-related readmissions for patients with COPD. Mortality at 30 days and 90 days was a secondary outcome. All percentages reported in Results are unweighted. Results: The study cohort comprised 450 746 patients, including 198 854 patients with AMI, 133 058 patients with CHF, and 118 834 patients with COPD; the median (IQR) age was 66 (56-77) years for AMI, 78 (68-85) years for CHF, and 73 (64-81) years for COPD, and there were 64 339 (32.35%) women, 62 575 (47.03%) women, and 59 179 (49.80%) women, respectively. There were 91 182 patients (45.85%), 56 491 patients (42.46%), and 40 159 patients (33.79%), respectively, who received an early follow-up visit. Overall, patients with early follow-up had higher rates of collaborative care (eg, CHF: 20 931 patients [37.85%] vs 11 101 of 76 567 patients [14.85%]) and visits to a specialist within 30 days (eg, CHF: 25 797 patients [45.67%] vs 20 548 patients [26.84%]). Those with early follow-up had lower 90-day readmission rates among patients with CHF (15 934 patients [28.21%] vs 23 121 patients [30.20%]; adjusted hazard ratio [aHR], 0.98; 95% CI, 0.96-0.99) and among those with COPD (8784 patients [21.87%] vs 18 097 of 78 675 patients [23.00%]; aHR, 0.95; 95% CI, 0.93-0.98). Among patients with COPD, those with early follow-up had lower 90-day COPD-related readmission rates (4015 patients [10.00%] vs 8449 patients [10.74%]; aHR, 0.93; 95% CI, 0.89-0.96), and among patients with CHF, those with early follow-up had lower 90-day mortality rates (4044 patients [7.16%] vs 6281 patients [8.20%]; aHR, 0.93; 95% CI, 0.90-0.97). There were no significant benefits at 30 days or for patients with AMI. Conclusions and Relevance: These findings suggest that early follow-up in conjunction with a comprehensive transitional care strategy for hospitalized patients with medically complex conditions coupled with ongoing effective chronic disease management may be associated with reduced 90-day readmissions.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.259
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations47
Published2022
Admission routes3
Has abstractyes

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