Protocol for the process evaluation of a cluster randomised controlled trial to determine the effectiveness and cost-effectiveness of independent pharmacist prescribing in care home: the CHIPPS study
Bibliographic record
Abstract
BACKGROUND: Prescribing, monitoring and administration of medicines in care homes could be improved. A cluster randomised controlled trial (RCT) is ongoing to evaluate the effectiveness of an independent prescribing pharmacist assuming responsibility for medicines management in care homes compared to usual care. AIMS AND OBJECTIVES: To conduct a mixed-methods process evaluation of the RCT, in line with Medical Research Council (MRC) process evaluation guidance, to inform interpretation of main trial findings and if the service is found to be effective and efficient, to inform subsequent implementation. OBJECTIVES: 1. To describe the intervention as delivered in terms of quality, quantity, adaptations and variations across triads and time. 2. To explore the effects of individual intervention components on the primary outcomes. 3. To investigate the mechanisms of impact. 4. To describe the perceived effectiveness of relevant intervention components [including pharmacist independent prescriber (PIP) training and care home staff training] from participant [general practitioner (GP), care home, PIP and resident/relative] perspectives. 5. To describe the characteristics of GP, care home, PIP and resident participants to assess reach. 6. To estimate the extent to which intervention delivery is normalised among the intervention healthcare professionals and related practice staff. METHODS: A mix of quantitative (surveys, record reviews) and qualitative (interviews) approaches will be used to collect data on the extent of the delivery of detailed tasks required to implement the new service, to collect data to confirm the mechanism of impact as hypothesised in the logic model, to collect explanatory process and final outcome data, and data on contextual factors which could have facilitated or hindered effective and efficient delivery of the service. DISCUSSION: Recruitment is ongoing and the trial should complete in early 2020. The systematic and comprehensive approach that is being adopted will ensure data is captured on all aspects of the study, and allow a full understanding of the implementation of the service and the RCT findings. With so many interrelated factors involved it is important that a process evaluation is undertaken to enable us to identify which elements of the service were deemed to be effective, explain any differences seen, and identify enablers, barriers and future adaptions. TRIAL REGISTRATION: ISRCTN17847169. Date registered: 15 December 2017.
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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 | 0.140 | 0.150 |
| Meta-epidemiology (narrow) | 0.012 | 0.006 |
| Meta-epidemiology (broad) | 0.018 | 0.012 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.012 | 0.022 |
| Insufficient payload (model declined to judge) | 0.146 | 0.033 |
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".