Using multi-criteria decision analysis to describe stakeholder preferences for new quality improvement initiatives that could optimise prescribing in England

Khanal, Saval ORCID: https://orcid.org/0000-0001-5201-0612, Schmidtke, Kelly Ann, Talat, Usman, Turner, Alice M. and Vlaev, Ivo (2023) Using multi-criteria decision analysis to describe stakeholder preferences for new quality improvement initiatives that could optimise prescribing in England. Frontiers in Health Services, 3. ISSN 2813-0146

[thumbnail of frhs-03-1155523]
Preview
PDF (frhs-03-1155523) - Published Version
Available under License Creative Commons Attribution.

Download (2MB) | Preview

Abstract

Background: Hospital decision-makers have limited resources to implement quality improvement projects. To decide which interventions to take forward, trade-offs must be considered that inevitably turn on stakeholder preferences. The multi-criteria decision analysis (MCDA) approach could make this decision process more transparent.  Method: An MCDA was conducted to rank-order four types of interventions that could optimise medication use in England's National Healthcare System (NHS) hospitals, including Computerised Interface, Built Environment, Written Communication, and Face-to-Face Interactions. Initially, a core group of quality improvers (N = 10) was convened to determine criteria that could influence which interventions are taken forward according to the Consolidated Framework for Implementation Research. Next, to determine preference weightings, a preference survey was conducted with a diverse group of quality improvers (N = 356) according to the Potentially All Pairwise Ranking of All Possible Alternatives method. Then, rank orders of four intervention types were calculated according to models with criteria unweighted and weighted according to participant preferences using an additive function. Uncertainty was estimated by probabilistic sensitivity analysis using 1,000 Monte Carlo Simulation iterations.  Results: The most important criteria influencing what interventions were preferred was whether they addressed "patient needs" (17.6%)' and their financial "cost (11.5%)". The interventions' total scores (unweighted score out of 30 | weighted out of 100%) were: Computerised Interface (25 | 83.8%), Built Environment (24 | 79.6%), Written Communication (22 | 71.6%), and Face-to-Face (22 | 67.8%). The probabilistic sensitivity analysis revealed that the Computerised Interface would be the most preferred intervention over various degrees of uncertainty.  Conclusions: An MCDA was conducted to rank order intervention types that stand to increase medication optimisation across hospitals in England. The top-ranked intervention type was the Computerised Interface. This finding does not imply Computerised Interface interventions are the most effective interventions but suggests that successfully implementing lower-ranked interventions may require more conversations that acknowledge stakeholder concerns.

Item Type: Article
Additional Information: Funding information: This work received support from the Health Foundation's Behavioural Insights Research programme (Award 807263) and the NIHR ARC West Midlands (NIHR200165). Ivo Vlaev was further supported by the National Institute for Health Research (NIHR) through the Policy Research Unit in Behavioural Science (PR-PRU-1217-20501). The views expressed are those of the author(s) and not necessarily the funders. The funders had no role in the design of the study.
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
Depositing User: LivePure Connector
Date Deposited: 11 Jul 2023 08:30
Last Modified: 11 Jul 2023 08:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/92582
DOI: 10.3389/frhs.2023.1155523

Downloads

Downloads per month over past year

Actions (login required)

View Item View Item