Tools for Assessing Medication Safety Processes in Nursing Homes: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: This systematic review aimed to identify tools for measuring the quality of medication safety-related processes in nursing homes. METHODS: We systematically searched Medline, Embase, and CINAHL databases to identify studies describing tools for measuring medication safety-related processes or systems supporting medication safety in nursing homes. Databases were searched from their inception to June 2022. For each tool, the individual items included in the tool were mapped to the 9 steps and 3 background processes of the medication management pathway and the methodological quality was assessed using the Appraisal of Indicators through Research and Evaluation (AIRE) Instrument. RESULTS: Four tools for assessing medication safety-related processes or systems in the nursing home setting were identified. The tools varied substantially in terms of development, content (number of key elements and items), focus and quality. Only one tool, the Canadian Medication Safety Self-Assessment for Long-Term Care (MSSA-LTC), addressed all 9 steps and 3 background processes of the medication management pathway and had a high overall quality rating as per the AIRE instrument. CONCLUSIONS: While the Canadian MSSA-LTC tool had the widest focus and highest quality of the 4 tools identified, the choice of a tool by an individual nursing home or care organization will depend on the purpose of the assessment and processes of interest as well as the validity of the tool in the jurisdiction in which it is being used. Awareness of the differences and limitations of each tool in the relevant context should facilitate this endeavour.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".