학술논문

Identifying contextually relevant improvement measures, illustrated by a case of executive walkrounds
Document Type
Journal
Source
International Journal of Health Care Quality Assurance, 2020, Vol. 33, Issue 4/5, pp. 345-361.
Subject
research-article
Research paper
cat-HSC
Health & social care
cat-HSQ
Health service quality
cat-HSD
Health service delivery
cat-HPL
Heathcare policy & law
Performance measurement
Mixed methods
Quality improvement
Rounding
Driver diagrams
Delphi technique
Language
English
ISSN
0952-6862
Abstract
PurposeA method to engage salient organisational stakeholders in identifying and ranking measures of healthcare improvement programs is described. The method is illustrated using Executive WalkRounds (EWRs) in a multi-site Australian Health District.Design/methodology/approachSubject matter experts (SMEs) conducted document analysis, identified potential EWRs measures, created driver diagrams and then eliminated weak measures. Next, a panel of executives skilled in EWRs ranked and ratified the potential measures using a modified Delphi technique.FindingsEWRs measurement selection demonstrated the feasibility of the method. Of the total time to complete the method 79% was contributed by SMEs, 14% by administration personnel and 7% by executives. Document analysis revealed three main EWRs aims. Ten of 28 potential measures were eliminated by the SME review. After repeated Delphi rounds the executive panel achieved consensus (75% cut-off) on seven measures. One outcome, one process and one implementation fidelity metric were selected to measure and monitor the impact of EWRs in the health district.Practical implicationsPerceptions of weak relationships between measures and intended improvements can lead to practitioner scepticism. This work offers a structured method to combine the technical expertise of SMEs with the practical knowledge of healthcare staff in selecting improvement measures.Originality/valueThis research describes and demonstrates a novel method to systematically leverage formal and practical types of expertise to select measures that are strongly linked to local quality improvement goals. The method can be applied in diverse healthcare settings.