Improving the continuity of care following discharge of patients hospitalized with heart failure: is the discharge summary adequate?
Bibliographic record
Abstract
OBJECTIVE: To determine the adequacy of the discharge summary in reporting important investigative results and future management plans in patients hospitalized and discharged with a diagnosis of heart failure. DESIGN: During a six-month period, all patient charts were identified and reviewed in which heart failure had been the most responsible discharge diagnosis. Trained, independent chart reviewers recorded predefined key aspects of the typed and handwritten discharge summaries including measurement of left ventricular function, utilization of angiotensin-converting enzyme inhibitors (ACEI), management of risk factors, and instructions for follow-up treatment and appointments. SETTING: Single centre, tertiary care teaching hospital. MAIN RESULTS: One hundred and one patient charts meeting review criteria were identified. Eighty-two contained a typed (dictated) discharge summary and 82 contained a copy of a one-page preformatted but handwritten summary given to the patient at discharge with instructions to give to their primary care physician. Forty-one per cent of typed discharge summaries did not record any known evaluation of left ventricular ejection fraction (LVEF). Of patients with LVEF < or =40%, 34% were not prescribed an ACEI at time of discharge. Of these patients, a contraindication was documented in 26% but there was no documentation of a contraindication or reason in 24%. In patients with ischemic cardiomyopathy as the principal attributed cause of heart failure, 80% of discharge summaries had no specific instructions addressing modifiable risk factors. Follow-up instructions for family physician visits were not mentioned in 56% of typed discharge summaries. CONCLUSIONS: Substantial inadequacies exist in communicating to the community physician, at the time of discharge from an acute care teaching hospital, valuable patient management information of patients with heart failure. This may have implications for continuity of care and subsequent clinical outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.138 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".