Process evaluation of a data-driven quality improvement program within a cluster randomised controlled trial to improve coronary heart disease management in Australian primary care
Publication Details
Hafiz, N.,
Hyun, K.,
Tu, Q.,
Knight, A.,
Hespe, C.,
Chow, C.,
Briffa, T.,
Gallagher, R.,
Reid, C.,
Hare, D.,
Zwar, N.,
Woodward, M.,
Jan, S.,
Atkins, E.,
Laba, T.,
Halcomb, E.,
Johnson, T.,
Manandi, D.,
Usherwood, T.,
&
Redfern, J.
(2024).
Process evaluation of a data-driven quality improvement program within a cluster randomised controlled trial to improve coronary heart disease management in Australian primary care.
PLoS One, 19 (6).
Abstract
Background: This study evaluates primary care practices’ engagement with various features of a quality improvement (QI) intervention for patients with coronary heart disease (CHD) in four Australian states.
Methods: Twenty-seven practices participated in the QI intervention from November 2019 –November 2020. A combination of surveys, semi-structured interviews and other materials within the QUality improvement in primary care to prevent hospitalisations and improve Effectiveness and efficiency of care for people Living with heart disease (QUEL) study were used in the process evaluation. Data were summarised using descriptive statistical and thematic analyses for 26 practices.
Results: Sixty-four practice team members and Primary Health Networks staff provided feedback, and nine of the 63 participants participated in the interviews. Seventy-eight percent (40/54) were either general practitioners or practice managers. Although 69% of the practices selfreported improvement in their management of heart disease, engagement with the intervention varied. Forty-two percent (11/26) of the practices attended five or more learning workshops, 69% (18/26) used Plan-Do-Study-Act cycles, and the median (Interquartile intervals) visits per practice to the online SharePoint site were 170 (146–252) visits. Qualitative data identified learning workshops and monthly feedback reports as the key features of the intervention.
Conclusion: Practice engagement in a multi-featured data-driven QI intervention was common, with learning workshops and monthly feedback reports identified as the most useful features. A better understanding of these features will help influence future implementation of similar interventions.
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