Ten tips for advancing a culture of improvement in primary care

Kiran, Tara; Ramji, Noor; Derocher, Mary Beth; Girdhari, Rajesh; Davie, Samantha; Lam-Antoniades, Margarita

doi:10.1136/bmjqs-2018-008451

Cited by 17 publications

(19 citation statements)

References 11 publications

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“…Primary care practices are undergoing care-improving changes within an evolving health care context, and for some practices this means participating in some kind of QI activity. 21-25 Turnover is one of many impediments practices experience that limits their ability to engage in QI. Turnover needs to be understood and addressed because, as the present study shows, turnover influenced practices’ ability to engage in QI; it slowed momentum for making quality-improving changes by limiting staff capacity, strained staff dynamics, and contributed to loss of institutional memory.…”

Section: Discussionmentioning

confidence: 99%

Effects of Practice Turnover on Primary Care Quality Improvement Implementation

et al. 2019

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Primary care practices often engage in quality improvement (QI) in order to stay current and meet quality benchmarks, but the extent to which turnover affects practices’ QI ability is not well described. The authors examined qualitative data from practice staff and external facilitators participating in a large-scale QI initiative to understand the relationship between turnover and QI efforts. The examination found turnover can limit practices’ ability to engage in QI activities in various ways. When a staff member leaves, remaining staff often absorb additional responsibilities, and QI momentum slows as new staff are trained or existing staff are reengaged. Turnover alters staff dynamics and can create barriers to constructive working relationships and team building. When key practice members leave, they can take with them institutional memory about QI purpose, processes, and long-term vision. Understanding how turnover affects QI may help practices, and those helping them with QI, manage the disruptive effects of turnover.

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Section: Discussionmentioning

confidence: 99%

Effects of Practice Turnover on Primary Care Quality Improvement Implementation

et al. 2019

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“…SMHAFHT has developed a strong quality improvement (QI) program that includes an interprofessional steering committee, local QI teams at each of the six clinics, and paid QI physician leads [ 12 ]. The team tracks quality of care using a dashboard of over 25 quality measures reported at the team-level and prioritizes specific areas for improvement through development of an annual QI plan.…”

Section: Methodsmentioning

confidence: 99%

Unpacking the intention to action gap: a qualitative study understanding how physicians engage with audit and feedback

et al. 2021

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Background Audit and feedback (A&F) often successfully enhances health professionals’ intentions to improve quality of care but does not consistently lead to practice changes. Recipients often cite data credibility and limited resources as barriers impeding their ability to act upon A&F, suggesting the intention-to-action gap manifests while recipients are interacting with their data. While attention has been paid to the role feedback and contextual variables play in contributing to (or impeding) success, we lack a nuanced understanding of how healthcare professionals interact with and process clinical performance data. Methods We used qualitative, semi-structured interviews guided by Normalization Process Theory (NPT). Questions explored the role of data in quality improvement, experiences with the A&F report, perceptions of the data, and interpretations and reflections. Interviews were audio-recorded and transcribed verbatim. Data were analyzed using a combination of inductive and deductive strategies using reflexive thematic analysis informed by a constructivist paradigm. Results Healthcare professional characteristics (individual quality improvement capabilities and beliefs about data) seem to influence engagement with A&F to a greater degree than feedback variables (i.e., delivered by peers) and observed contextual factors (i.e., strong quality improvement culture). Most participants lacked the capabilities to interpret practice-level data in an actionable way despite a motivation to engage meaningfully. Reasons for the intention-to-action gap included challenges interpreting longitudinal data, appreciating the nuances of common data sources, understanding how aggregate data provides insights into individualized care, and identifying practice-level actions to improve quality. These factors limited effective cognitive participation and collective action, as outlined in NPT. Conclusions A well-designed A&F intervention is necessary but not sufficient to inform practice changes. A&F initiatives must include co-interventions to address recipient characteristics (i.e., beliefs and capabilities) and context to optimize impact. Effective strategies to overcome the intention-to-action gap may include modelling how to use A&F to inform practice change, providing opportunities for social interaction relating to the A&F, and circulating examples of effective actions taken in response to A&F. More broadly, undergraduate medical education and post-graduate training must ensure physicians are equipped with QI capabilities, with an emphasis on the skills required to interpret and act on practice-level data.

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“…4 Numerous case examples illustrate the impact of codesign on organizational service delivery, including in our own work, where it led to improved patientreported afterhours access in primary care. 5 Moreover, patient engagement leads to new and important insights. For example, patient involvement in reporting of safety incidents highlighted safety concerns that organizations' tradi tional safety reporting systems overlooked.…”

mentioning

confidence: 99%

“…6 Patients in our prac tice helped us reframe our own concepts of timely access in pri mary care and how we measure it. 5 Crucially, patient engagement can help us develop and test ideas for improving care. For example, we recently tried to improve cancer screening rates for patients liv ing with a low income.…”

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confidence: 99%