Evidence‐Based Approaches to Quality Improvement: A Narrative Review of Integrating Bayesian Adaptive Trials Into Health Services.
Rationale: Quality improvement (QI) in health service programmes aims to make small, incremental changes to increase reach and efficiency. Simple, low‐risk programmatic changes can improve services, particularly when supported by robust evidence. However, in health service contexts, there is tension...
| Publicado en: | Journal of Evaluation in Clinical Practice Vol. 31; no. 5; pp. 1 - 12 |
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| Autores principales: | , , , , , , |
| Formato: | review Journal Article |
| Publicado: |
Wiley-Blackwell
Aug2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=187574766&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 187574766 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13561294 EV1 jtl: Journal of Evaluation in Clinical Practice issn: 13561294 maglogo: Y pubinfo: dt: Aug2025 vid: 31 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 187574766 187574766 187574766 10.1111/jep.70197 187574766 ppf: 1 ppct: 11 formats: tig: atl: Evidence‐Based Approaches to Quality Improvement: A Narrative Review of Integrating Bayesian Adaptive Trials Into Health Services. aug: au: Kim, Min Jung Prieto‐Merino, David Nicholas, Jennifer Allen, Luke Burton, Matthew J. Bastawrous, Andrew Macleod, David affil: Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK sug: subj: Quality Improvement Health Services Research Implementation Science Probability Medical Practice, Evidence-Based Study Design Clinical Trials ab: Rationale: Quality improvement (QI) in health service programmes aims to make small, incremental changes to increase reach and efficiency. Simple, low‐risk programmatic changes can improve services, particularly when supported by robust evidence. However, in health service contexts, there is tension between the need for swift decision‐making and the high research standards for conducting methodologically rigorous trials. Randomized trials are rarely used to evaluate these changes due to high costs and long timelines, especially when the changes are expected to result in marginal improvements. Instead, health service programmes frequently introduce changes informed by anecdotal evidence or less robust evaluation methods such as before‐and‐after comparisons. Aims: In this paper, we present a narrative review of the concepts underlying Bayesian adaptive trial designs for conducting QI research, highlighting their use in the commercial sector and exploring opportunities for cross‐industry learning and future application in healthcare settings. Methods: Relevant studies were selected based on their contextual relevance to the topic, in keeping with the narrative review approach. Results: Given that programmatic changes typically yield modest improvements, we recommend that adaptive trial designs can strike a balance between obtaining reliable results and avoiding overly large sample sizes. We review how interim analysis and early stopping can be integrated into trials, allowing the level of rigour to be adjusted according to the proramme specifications. Conclusion: Adaptive trial designs hold significant promise for enhancing the QI efforts. To ensure that adaptive trial designs can be successfully integrated into health service contexts, tradeoffs should be made between methodological rigour and resource constraints. pubtype: Academic Journal doctype: review Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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