Ranking of healthcare programmes based on health outcome, health costs and safe delivery of care in hospital pharmacy practice
Bibliographic record
Abstract
OBJECTIVES: To establish a consensual and coherent ranking of healthcare programmes that involve the presence of ward-based and clinic-based clinical pharmacists, based on health outcome, health costs and safe delivery of care. METHODS: This descriptive study was derived from a structured dialogue (Delphi technique) among directors of pharmacy department. We established a quantitative profile of healthcare programmes at five sites that involved the provision of ward-based and clinic-based pharmaceutical care. A summary table of evidence established a unique quality rating per inpatient (clinic-based) or outpatient (ward-based) healthcare programme. Each director rated the perceived impact of pharmaceutical care per inpatient or outpatient healthcare programme on three fields: health outcome, health costs and safe delivery of care. They agreed by consensus on the final ranking of healthcare programmes. KEY FINDINGS: A ranking was assigned for each of the 18 healthcare programmes for outpatient care and the 17 healthcare programmes for inpatient care involving the presence of pharmacists, based on health outcome, health costs and safe delivery of care. There was a good correlation between ranking based on data from a 2007-2008 Canadian report on hospital pharmacy practice and the ranking proposed by directors of pharmacy department. CONCLUSIONS: Given the often limited human and financial resources, managers should consider the best evidence available on a profession's impact to plan healthcare services within an organization. Data are few on ranking healthcare programmes in order to prioritize which healthcare programme would mostly benefit from the delivery of pharmaceutical care by ward-based and clinic-based pharmacists.
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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 | 0.027 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".