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. 2020 Sep-Oct;33(5):655-664.
doi: 10.3122/jabfm.2020.05.200058.

Identifying Practice Facilitation Delays and Barriers in Primary Care Quality Improvement

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Free article

Identifying Practice Facilitation Delays and Barriers in Primary Care Quality Improvement

Jiancheng Ye et al. J Am Board Fam Med. 2020 Sep-Oct.
Free article

Abstract

Objective: Practice facilitation is an effective approach to implementing quality improvement (QI) interventions in practice-based research networks (PBRNs). Regular facilitator-practice interactions are necessary for successful facilitation, and missed engagements may hinder the process of practice improvement. This study employs a mixed-methods approach to characterize the dynamics of practice facilitation and examine facilitation delays and barriers, as well as their association with the achievement of QI program goals in a PBRN initiative.

Methods: This study presents a secondary analysis of data from 226 primary care practices that participated in the Healthy Hearts in the Heartland (H3) initiative. We performed a time series analysis to identify delays in facilitation activities, and then qualitatively analyzed practice facilitators' notes (n = 4358) to uncover facilitation barriers. Finally, we assessed the relationship between delays, barriers, and QI intervention completion.

Results: While most facilitation activities occurred at regular, practice-specific tempos, nearly all practices experienced at least 1 delay. Practices with more delays had lower QI intervention completion rates. Practices with more delays were more likely to have encountered barriers such as lack of time and staff, lack of staff engagement, technical issues, and staff turnover.

Discussion and conclusion: This study is the first to quantify irregular intervals between facilitation activities and demonstrate their negative association with project completion. The analytic method can be applied to identify at-risk practices and to accelerate timely interventions in future studies. Our delay detection algorithm could inform the design of a decision support system that notifies facilitators which practices may benefit from timely attention and resources.

Keywords: Cardiovascular Diseases; Personnel Turnover; Practice Facilitation; Practice-Based Research; Primary Health Care; Quality Improvement; Regression Analysis; Time series algorithms; Work Engagement; Workforce.

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Conflicts of interest: None.

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