187 Improving departmental quality improvement plans through standardization, structured peer-to-peer feedback, and building improvement capacity and culture
Bibliographic record
Abstract
The lead author has seen and agreed to the license applied to conference abstracts published by BMJ.Introduction Quality Improvement Plans (QIPs) can improve healthcare quality by raising awareness and providing focus around improvement efforts. 1 Meanwhile, physician leadership and participation in an organization’s quality agenda is required to improve patient safety and quality of care, and to attain organizational quality goals.2–8 The physician-led quality committee at our institution set out to improve the previously heterogenous quality and content of medical department QIPs and increase alignment between medical department and hospital quality improvement (QI) priorities. We describe these initiatives and assess their impact on the quality of departmental QIPs.Methods The Physician Quality Committee at our academic tertiary care hospital implemented a series of interventions, including a peer-to-peer feedback mechanism, longitudinal education and coaching, standardized QI project templates, and efforts to facilitate culture change. The QIPs from 13 medical departments were reviewed for the academic years before (2018–2019) and after the interventions (2022–2023) and scored according to a structured rubric, created by consensus from physician quality leads. Data are reported as means and median [interquartile range]. A Wilcoxon signed-rank test was used to evaluate for statistical significance. A Likert-scale survey was used to assess the physician QI leads perception of the impact of the initiatives.Results The mean score on the structured rubric was 4.4/12 for the QIPs from 2018–2019 and 8.0/12 for the QIPs from 2022–2023 (Z=3.06, p=0.0005). The median score [25th, 75th percentile] in 2018–2019 was 4.5 [3.5, 5.13], which increased to 8.5 [7.0, 9.0] in 2022–2023 [ figure 1]. The survey response for physician QI leads was 10/13 (76.9%). The most positive response was the QI lead’s knowledge and understanding of how to structure a QI project (mean score of 4.4/5); the least positive response was related to departmental focus and clarity regarding QI priorities (mean score of 3.9/5) [figure 2].Multifaceted physician-led interventions resulted in improvements in the quality and content of medical department QIPs, improved physician knowledge of QI methodology, enhanced focus and clarity around departmental QI priorities, and improved awareness of hospital-wide improvement efforts.Abstract 187 Figure 1Change in departmental QIP rubric score pre- and post-interventionAbstract 187 Figure 2Mean score on likert scale survey of medical department physician QI leads. Figure Legend: Dots represent mean score; error bars represent range of survey results.References Chan Y-CL, Hsu SH. Target-setting, pay for performance, and quality improvement: a case study of ontario hospitals’ quality-improvement plans. Canadian Journal of Administrative Sciences/Revue Canadienne des Sciences de l’Administration 2019;36(1):128–144.Reinertsen J, Gosfield A, Rupp W, Whittington J. Engaging Physicians in a Shared Quality Agenda. IHI Innovation Series white paper. Cambridge, Massachusetts: Institute for Healthcare Improvement;2007.Hayes C, Yousefi V, Wallington T, Ginzburg A. Case study of physician leaders in quality and patient safety, and the development of a physician leadership network. Healthcare Quarterly 2010;13(Sp):68–73.Fisher E, Berwick D, Davis K. Achieving health care reform--how physicians can help. The New England journal of medicine 2009;360(24):2495–2497.Pronovost PJ, Miller MR, Wachter RM, Meyer GS. Perspective: physician leadership in quality. Academic medicine : journal of the Association of American Medical Colleges 2009;84(12):1651–1656.McGonigal M, Bauer M, Post C. Physician engagement: a key concept in the journey for quality improvement. Crit Care Nurs Q. 2019;42(2):215–219.Dhalla IA, Tepper J. Improving the quality of health care in Canada. Canadian Medical Association Journal 2018;190(39):E1162-E1167.Digby GC DS, Hobbs H. Strategies for emerging physician leaders in quality improvement to advance the quality agenda and increase organizational alignment. Physician Leadership Journal 2021;8(4):30–37.
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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 | 0.033 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".