Adverse events experienced by homecare patients: a scoping review of the literature
Bibliographic record
Abstract
PURPOSE: The paper summarizes the results of a scoping review that focused on the occurrence of adverse events experienced by homecare patients. DATA SOURCES: The literature search covered published and grey literature between 1998 and 2007. Databases searched included: MEDLINE, EMBASE, CINAHL and EBM REVIEWS including the Cochrane Library, AGELINE, the National Patient Safety Foundation Bibliography, Agency for Healthcare Research and Quality and the Patient Safety Net bibliography. STUDY SELECTION: Papers included research studies, review articles, policy papers, opinion articles and legal briefs. Inclusion criteria were: (i) homecare directed services provided in the home by healthcare professionals or caregivers; (ii) addressed a characteristic relevant to patient experienced adverse events (e.g. occurrences, rates, definitions, prevention or outcomes); and (iii) were in English. Data extraction A pool of 1007 articles was reduced to 168 after analysis. Data were charted according to six categories: definitions, rates, causes, consequences, interventions and policy. RESULTS: Eight categories emerged: adverse drug events, line-related, technology-related, infections and urinary catheters, wounds, falls, studies reporting multiple rates and other. Reported overall rates of adverse events ranged from 3.5 to 15.1% with higher rates for specific types. Few intervention studies were found. Adverse events were commonly associated with communication problems. Policy suggestions included the need to improve assessments, monitoring, education, coordination and communication. CONCLUSION: A standardized definition of adverse events in the homecare setting is needed. Prospective cohort studies are needed to improve estimates and intervention studies should be undertaken to reduce the risk that homecare patients will experience adverse events.
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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 | 0.031 | 0.097 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.033 | 0.032 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".