Adverse Events and Their Contributors Among Older Adults During Skilled Nursing Stays for Rehabilitation: A Scoping Review
Bibliographic record
Abstract
PURPOSE: To identify factors that contribute to adverse events among older adults during short stays at skilled nursing facilities (SNFs) for rehabilitation (ie, up to 100 resident days). Adults aged 65 years and older are at serious risk for adverse events throughout their continuum of care. Over 33% of older adults admitted to SNFs experienced an adverse event (eg, falls) within the first 35 days of their stay. DESIGN: A scoping review. SETTING AND PARTICIPANTS: Older adults admitted for short stays in SNFs. METHODS: Eligibility criteria were peer-reviewed original articles published between 1 January 2015 and 30 May 2021, written in English, and containing any of the following key terms and synonyms: "skilled nursing facilities", "adverse events", and "older adults". These terms were searched in PubMed, MEDLINE, CINAHL, EBSCOHost, and the ProQuest Nursing and Allied Health Database. We summarized the findings using the Joanna Briggs Institute and PRISMA-ScR reporting guidelines. We also used the Capability-Opportunity-Motivation-Behavior (COM-B) model of health behavioral change as a framework to guide the content, thematic, and descriptive analyses of the results. RESULTS: Eleven articles were included in this scoping review. Intrinsic and extrinsic contributors to adverse events (ie, falls, medication errors, pressure ulcers, and acute infections) varied for each COM-B domain. The most frequently mentioned capacity-related intrinsic contributors to adverse events were frailty and reduced muscle strength due to advancing age. Inappropriate medication usage and polypharmacy were the most common capacity-related extrinsic factors. Opportunity-related extrinsic factors contributing to adverse events included environmental hazards, poor communication among SNF staff, lack of individualized resident safety plans, and overall poor care quality owing to racial bias and organizational and administrative issues. CONCLUSION: These findings shed light on areas that warrant further research and may aid in developing interventional strategies for adverse events during short SNF stays.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".