Assessment of Risk in Medication-Use Systems: Learning from the Medication Safety Self-Assessment
Bibliographic record
Abstract
INTRODUCTION Interest in tools for enhancing patient safety has grown with the patient safety movement. The Medication Safety Self-Assessment (MSSA), a comprehensive assessment program originally developed by the Institute for Safe Medication Practices (ISMP) in the United States, is one such tool. The MSSA was adapted for use in Canada in 2001 and has been used by individual hospitals, regional health authorities, and provincial governments to identify and prioritize areas for improvement in medication-use systems.1 The Canadian MSSA program is administered by ISMP Canada, independent of ISMP (US), and includes additional features not available with the US version. The MSSA assists interdisciplinary hospital teams to evaluate the safety of medication practices in their institutions and to heighten awareness of the characteristics of a safe medication system. The MSSA consists of a series of safe medication practice characteristics, which are grouped into 10 key elements of medication-use systems (Table 1). Each key element is defined by one or more core distinguishing characteristics. Several self-assessment items describing safe medication practices are then used to determine the level of success for each of the key elements. Some of the items purposely represent innovative practices and system enhancements that are not widely implemented in Canadian hospitals but that are grounded in scientific research and expert analysis of medication errors and their causes. When completing the self-assessment, respondents must select 1 of 5 responses, ranging from no activity or discussion about a particular item to full implementation throughout the organization. Although ISMP Canada is not itself a standardssetting organization, several items are under consideration for inclusion in the new standards of the Canadian Council on Health Services Accreditation. The principal values of the MSSA are the ability of individual hospitals to identify opportunities for improvement and to track their improvement efforts over time. These values are enabled through a unique feature of the Canadian MSSA, whereby a Web-based program allows participants to immediately compare their current results to the aggregate national, provincial, and regional results, as well as to their own previous results in real time, as soon as responses have been electronically submitted. This functionality is not available for the US version. At the time of writing, in late 2006, a total of 273 Canadian hospitals had completed at least one self-assessment. This article describes one hospital’s experience with the MSSA program.
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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 | 0.013 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| 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".