INTRODUCTION: The most crucial step in forming a set of key performance indicators (KPI) for emergency department's (ED) staff is deciding the appropriate items for the KPI. This article demonstrates Fuzzy Delphi Method (FDM) as a scientific approach to consolidate consensus agreement within a panel of experts pertaining to each service related KPI item's appropriateness for ED. We aimed to develop framework of service key performance indicators for emergency departments of tertiary centres by using FDM. MATERIALS AND METHODS: The panel consists of ten experts from ED that was randomly chosen from list of specialists obtained from the National Specialist Registry for Emergency Medicine. A set of questionnaires that contains item constructs related to KPI based on structure, outcome and process was developed from initial literature search from Pubmed Central, Google Scholar, Cochrane Database and Public Library of Sciences. The construct then used for FDM session in second phase of the study. In FDM phase, the experts will rank each of the items created from nominal group technique (NGT) session by using Likert Scale ranged from 1 to 5 ("1" totally disagree and "5" extremely agree). FDM prerequisite must include threshold value (d) ≤0.2, expert consensus of >75% and average fuzzy numbers ("A" value) of >0.5. RESULTS: The initial item construct has produced 22 items proposed for the service KPI. Post FDM analysis for service KPI, 16 out of the 22 (72%) satisfied first prerequisite "d" value ≤0.2. For the second prerequisite, ten items (45%) from service KPI domain had expert consensus of more than 75%. For the third prerequisite, 16 out of the 22 (73%) fit the criteria of average fuzzy number ("A" value) of more than 0.5. In final model of FDM, 13 items (59%) were discarded and the remaining (n=9 items) that fulfilled all three prerequisites were retained for the final draft for content validation process. CONCLUSION: This study introduces that FDM can be used to obtain experts' opinion and consensus in order to achieve a decision. The experts' consensus on the suitability of the pre-selected items on the KPI set were obtained, hence it is now ready for further applicability in the clinical setting in ED.
INTRODUCTION: The most crucial step in forming a set of key performance indicators (KPI) for emergency department's (ED) staff is deciding the appropriate items for the KPI. This article demonstrates Fuzzy Delphi Method (FDM) as a scientific approach to consolidate consensus agreement within a panel of experts pertaining to each service related KPI item's appropriateness for ED. We aimed to develop framework of service key performance indicators for emergency departments of tertiary centres by using FDM. MATERIALS AND METHODS: The panel consists of ten experts from ED that was randomly chosen from list of specialists obtained from the National Specialist Registry for Emergency Medicine. A set of questionnaires that contains item constructs related to KPI based on structure, outcome and process was developed from initial literature search from Pubmed Central, Google Scholar, Cochrane Database and Public Library of Sciences. The construct then used for FDM session in second phase of the study. In FDM phase, the experts will rank each of the items created from nominal group technique (NGT) session by using Likert Scale ranged from 1 to 5 ("1" totally disagree and "5" extremely agree). FDM prerequisite must include threshold value (d) ≤0.2, expert consensus of >75% and average fuzzy numbers ("A" value) of >0.5. RESULTS: The initial item construct has produced 22 items proposed for the service KPI. Post FDM analysis for service KPI, 16 out of the 22 (72%) satisfied first prerequisite "d" value ≤0.2. For the second prerequisite, ten items (45%) from service KPI domain had expert consensus of more than 75%. For the third prerequisite, 16 out of the 22 (73%) fit the criteria of average fuzzy number ("A" value) of more than 0.5. In final model of FDM, 13 items (59%) were discarded and the remaining (n=9 items) that fulfilled all three prerequisites were retained for the final draft for content validation process. CONCLUSION: This study introduces that FDM can be used to obtain experts' opinion and consensus in order to achieve a decision. The experts' consensus on the suitability of the pre-selected items on the KPI set were obtained, hence it is now ready for further applicability in the clinical setting in ED.
Authors: Asana Hosseini Dolatabad; Hannan Amoozad Mahdiraji; Ali Zamani Babgohari; Jose Arturo Garza-Reyes; Ahad Ai Journal: Environ Dev Sustain Date: 2022-07-04 Impact factor: 4.080