Virtual Practice Facilitation and Implementation of Cardiovascular Quality Improvement Strategies in Primary Care Clinics: A Descriptive Study.

BackgroundPractice facilitation is a key component of quality improvement in primary healthcare. Studies have reported the effectiveness of practice facilitation in improving quality management and care delivery. However, little has been published about practice facilitators’ training, facilitation activities, and their perceived role in quality improvement in primary healthcare. This study examined practice facilitators’ training and the perceptions of the practice facilitator role in a provincial primary healthcare learning collaborative quality improvement initiative in Ontario, Canada.MethodDescriptive and qualitative methods were used to outline the practice facilitator training as well as to look into the experiences and perceptions of practice facilitators and primary healthcare teams regarding the practice facilitation role in quality improvement. Data collection included training artifacts, activity logs, self-reflection reports, and semi-structured interviews with practice facilitators and primary healthcare participants. Reflections and interviews were analyzed to identify the role of the practice facilitators from their own experience, and from the perspective of the participants. Descriptive statistics were used to learn about categories of facilitation activities undertaken and frequency of these activities.ResultsSixteen practice facilitators and seven family healthcare teams participated in the study. Practice facilitators received a two-day intensive training workshop and continued training. Their time was spent mostly working directly with participating teams, continued learning and training, communications and administration. They served as coaches, resource providers, enablers and motivators. Participating teams expressed satisfaction with the practice facilitator role, although they had hoped this position would provide onsite and hands-on support in conducting activities of quality improvement at the practice level.ConclusionsPractice facilitators played a crucial role in the implementation of quality improvement in Ontario’s learning collaborative program. The practice facilitator role is perceived to be that of a coach, enabler and motivator. This study suggests that the practice facilitator successfully supported participating teams to undertake quality improvement activities in primary healthcare settings.

Evidence-based quality improvement (QI) interventions and strategies often require adaptation before implementation in new settings. The goal of this study was to describe the adaptation process of QI strategies from an evidence-based cardiovascular initiative, previously tested in community-based primary care clinics, for use in worksite health centers (WHC). Participating WHCs were located at large manufacturing plants. The adapted QI strategies were offered as part of the Healthy Hearts in Manufacturing initiative. Our team followed the ADAPT-ITT framework to adapt the QI strategies for twelve randomly selected WHCs. Meetings were held with WHC leaders, and semi-structured interviews were conducted with WHC clinicians and staff to understand current workflows and identify contextual factors that could help or hinder the implementation of the QI strategies. Data were analyzed using qualitative content analysis. Adaptations were then identified and developed by clinical experts and a practice facilitator, with input from an Advisory Panel. Proposed adaptations were shared with WHC leaders and clinicians for feedback before implementation protocols were finalized. Phase 1 (Assessment) showed that manufacturing communities had high rates of heart disease and its risk factors. Four QI interventions from the Million Hearts campaign were selected for implementation using evidence-based QI strategies during Phase 2 (Decision). Phase 3 (Administration) revealed helpful implementation factors, including strong patient-clinician relationships and leadership support, as well as hindering factors, including deficiencies of electronic health records systems, high staff turnover, and poor patient adherence to treatment. These factors informed the Phase 4 (Production) development of implementation materials, for example, tailored blood pressure measurement protocols and patient educational tools. During Phase 5 (Topical experts), clinicians and WHC leaders provided feedback on the adaptations, which were then integrated in Phase 6 (Integration) into a flexible implementation protocol for the practice facilitator. The final phase (Testing) is ongoing. This study describes the adaptation process of a primary care cardiovascular QI initiative to meet the unique clinical settings of WHCs. The findings suggest that with contextual adaptation of QI strategies, WHCs have the potential to implement evidence-based interventions to improve cardiovascular care, providing insights for future initiatives in non-traditional clinical care settings.

BackgroundThe past decade has seen increasing opportunities and efforts to integrate quality improvement into health care. Practice facilitation is a proven strategy to support redesign and improvement in primary care practices that focuses on building organizational capacity for continuous improvement. Practice leadership, staff, and practice facilitators all play important roles in supporting quality improvement in primary care. However, little is known about their perspectives on the context, enablers, barriers, and strategies that impact quality improvement initiatives.ObjectiveThis study aimed to develop a framework to enable assessment of contextual factors, challenges, and strategies that impact practice facilitation, clinical measure performance, and the implementation of quality improvement interventions. We also illustrated the application of the framework using a real-world case study.MethodsWe developed the TITO (task, individual, technology, and organization) framework by conducting participatory stakeholder workshops and incorporating their perspectives to identify enablers and barriers to quality improvement and practice facilitation. We conducted a case study using a mixed methods approach to demonstrate the use of the framework and describe practice facilitation and factors that impact quality improvement in a primary care practice that participated in the Healthy Hearts in the Heartland study.ResultsThe proposed framework was used to organize and analyze different stakeholders’ perspectives and key factors based on framework domains. The case study showed that practice leaders, staff, and practice facilitators all influenced the success of the quality improvement program. However, these participants faced different challenges and used different strategies. The framework showed that barriers stemmed from patients’ social determinants of health, a lack of staff and time, and unsystematic facilitation resources, while enablers included practice culture, staff buy-in, implementation of effective practice facilitation strategies, practice capacity for change, and shared complementary resources from similar, ongoing programs.ConclusionsOur framework provided a useful and generalizable structure to guide and support assessment of future practice facilitation projects, quality improvement initiatives, and health care intervention implementation studies. The practice leader, staff, and practice facilitator all saw value in the quality improvement program and practice facilitation. Practice facilitators are key liaisons to help the quality improvement program; they help all stakeholders work toward a shared target and leverage tailored strategies. Taking advantage of resources from competing, yet complementary, programs as additional support may accelerate the effective achievement of quality improvement goals. Practice facilitation–supported quality improvement programs may be opportunities to assist primary care practices in achieving improved quality of care through focused and targeted efforts. The case study demonstrated how our framework can support a better understanding of contextual factors for practice facilitation, which could enable well-prepared and more successful quality improvement programs for primary care practices. Combining implementation science and informatics thinking, our TITO framework may facilitate interdisciplinary research in both fields.

Background: In the face of rising healthcare costs and constrained budgets, primary care systems are increasingly being asked to achieve more with fewer resources. This financial reality places a significant strain on practices striving to deliver high-quality, comprehensive care while meeting complex patient needs. To address these challenges, practice facilitators have emerged as a valuable resource in primary care, offering targeted support to build practice capacity, enhance efficiency, and drive quality improvement efforts. By collaborating directly with practice teams, facilitators help to streamline workflows, implement evidence-based interventions, and foster a culture of continuous improvement. As healthcare systems continue to face financial pressures, the role of practice facilitators in optimizing primary care performance is more critical than ever. Approach: The Health Innovation Group developed a training program to grow the practice facilitator workforce across multiple jurisdictions within Canada. The program focuses on building core competencies in Quality Improvement, Facilitation, Primary Care Context, Patient’s Medical Home, Information for Action, and Leadership. The program's design was guided by a scientific planning committee with an international membership of physicians, nurses, academics, clinicians, and practice facilitators. Patient/public insights and involvement in developing the Patient’s Medical Home model of care were significant and informed the core elements of continuity, respect for preferences, and commitment to shared decision-making. This training has been accessed by medical associations, health authorities, and other healthcare organizations to build their organizational capacity to improve the sustainability of primary care. Results: Health Innovation Group has trained over 100 practice facilitators and supported them with ongoing coaching and networking opportunities. These practice facilitators have been able to report the following results in building a more sustainable primary care system: Nova Scotia – reduction of over 10000 patients from the unattached patient registry Newfoundland – 380 patients added to primary care providers panels Ontario – currently deploying practice facilitators to enhance team integration of primary care teams Alberta – 15% increase in patients receiving recommended screening and preventive care, impacting over 1.6 million patients Results achieved without additional resources provided to primary care teams demonstrate increased system capacity, capability, and sustainability. Implications: Integrating trained practice facilitators into primary care has demonstrated measurable improvements in patient access, preventive care, and system capacity across multiple Canadian jurisdictions, even without additional financial resources. This approach offers a scalable solution for building a more sustainable primary care system, enhancing efficiency, and addressing the increasing demand for high-quality care in an environment of constrained budgets. Future opportunities to deploy practice facilitators include decreasing the carbonization of primary care practices or introducing strategies for primary care to be more inclusive to patient populations. The success of this training, support, and deployment underscores the critical role of practice facilitators in strengthening primary care infrastructure and supporting the long-term sustainability of healthcare delivery.

Effective quality improvement (QI) strategies are needed for small practices. The objective of this study was to compare practice facilitation implementing point-of-care (POC) QI strategies alone versus facilitation implementing point-of-care plus population management (POC+PM) strategies on preventive cardiovascular care. Two arm, practice-randomized, comparative effectiveness study. Small and mid-sized primary care practices. Practices worked with facilitators on QI for 12 months to implement POC or POC+PM strategies. Proportion of eligible patients in a practice meeting "ABCS" measures: (Aspirin) Aspirin/antiplatelet therapy for ischemic vascular disease, (Blood pressure) Controlling High Blood Pressure, (Cholesterol) Statin Therapy for the Prevention and Treatment of Cardiovascular Disease, and (Smoking) Tobacco Use: Screening and Cessation Intervention, and the Change Process Capability Questionnaire. Measurements were performed at baseline, 12, and 18 months. A total of 226 practices were randomized, 179 contributed follow-up data. The mean proportion of patients meeting each performance measure was greater at 12 months compared with baseline: Aspirin 0.04 (95% confidence interval: 0.02-0.06), Blood pressure 0.04 (0.02-0.06), Cholesterol 0.05 (0.03-0.07), Smoking 0.05 (0.02-0.07); P<0.001 for each. Improvements were sustained at 18 months. At 12 months, baseline-adjusted difference-in-differences in proportions for the POC+PM arm versus POC was: Aspirin 0.02 (-0.02 to 0.05), Blood pressure -0.01 (-0.04 to 0.03), Cholesterol 0.03 (0.00-0.07), and Smoking 0.02 (-0.02 to 0.06); P>0.05 for all. Change Process Capability Questionnaire improved slightly, mean change 0.30 (0.09-0.51) but did not significantly differ across arms. Facilitator-led QI promoting population management approaches plus POC improvement strategies was not clearly superior to POC strategies alone.

2005 APA Gold Award: Improving Treatment Engagement and Integrated Care of Veterans

Primary care physicians, office-based practice, and the meaning of quality improvement

Age-friendly care, addressing what matters most, medications, mentation, and mobility, is a successful model for improving older adult care. We describe the initial outcomes of age-friendly care implementation in five primary care clinics in an academic health system. In partnership with a regional quality improvement (QI) organization, we used practice facilitation to implement age-friendly care from July 2020 to June 2023. Clinic workflows and electronic health record (EHR) templates were modified to capture six QI measures for patients ≥65 years: Documenting what matters most to patients Advance care planning (ACP) Annual cognitive screening Caregiver referral to dementia community resources Fall-risk screening Co-prescription of opioid and sedative-hypnotic drugs Providers were alerted if patients had positive screens and given support tools for clinical decision-making. QI measures from January-June 2023 were compared to the year prior to implementation. Providers and staff were interviewed about implementation barriers and facilitators. All six measures improved in Geriatrics and and other clinics showed improvement in ACP and cognitive screening. All clinics had high fall-risk screening rates (≥85%). The least improved measure was co-prescription of opioids and sedative-hypnotics with co-prescription rates ranging from 7% to 39%. Implementation hinged on leadership prioritization, practice facilitator guidance, clinical team buy-in, EHR functionality, and clinical performance review. Three clinics received Age-Friendly Health System recognition. A QI approach using practice facilitation and EHR templates improved some but not all age-friendly care measures. Future interventions will focus on training in high-risk medication tapering and elicitation of health goals.

Despite the current evidence of preventive screening effectiveness, rates of breast, cervical, and colorectal cancer in the United States fall below national targets. We evaluated the efficacy and feasibility of combining practice facilitation and academic detailing quality improvement (QI) strategies to help primary care practices increase breast, cervical, and colorectal cancer screening among patients. Practices received a 1-hour academic detailing session addressing current cancer screening guidelines and best practices, followed by 6 months of practice facilitation to implement evidence-based interventions aimed at increasing patient screening. One-way repeated measures analysis of variance compared screening rates before and after the intervention, provider surveys, and TRANSLATE model scores. Qualitative data were gathered via participant focus groups and interviews. Twenty-three practices enrolled in the project: 4 federally qualified health centers, 10 practices affiliated with larger health systems, 4 physician-owned practices, 4 university hospital clinics, and 1 nonprofit clinic. Average screening rates for breast cancer increased by 13% (P = .001), and rates for colorectal cancer increased by 5.6% (P = .001). Practices implemented a mix of electronic health record data cleaning workflows, provider audits and feedback, reminder systems streamlining, and patient education and outreach interventions. Practice facilitators assisted practices in tailoring interventions to practice-specific priorities and constraints and in connecting with community resources. Practices with resource constraints benefited from the engagement of all levels of staff in the quality improvement processes and from team-based adaptations to office workflows and policies. Many practices aligned quality improvement interventions in this project with patient-centered medical home and other regulatory reporting targets. Combining practice facilitation and academic detailing is 1 method through which primary care practices can achieve systems-level changes to better manage patient population health.

Machine learning (ML)-a field of study dedicated to the principled extraction of knowledge from complex data-can benefit implementation science, quality improvement (QI), and primary care research. Given the general complexity of implementation research and the need to develop strategies for understanding relationships among practice characteristics and practice facilitation strategies, we chose the Implementation Research Logic Model (IRLM) as an underlying structure for the data and to identify relationships that might be associated with outcomes. This study illustrates this novel method involving ML and an IRLM in the context of a practice facilitation-supported QI program in primary care. We applied advanced statistical methods within a machine learning framework to data from the Healthy Hearts in the Heartland (H3) study, including practice facilitation data and practice and staff participation survey, to assess the relationship between practice attributes and practice facilitator strategies and their impact on successful implementation of QI interventions. We used PCA for feature selection, incorporated practice facilitators' knowledge for contextual factor validation, and employed Structural Equation Modeling (SEM) to analyze relationships among contextual factors, latent variables, practice facilitation strategies, and outcomes. We selected 20 contextual factors and identified practice facilitation strategies and mapped them to the IRLM. Cronbach's alphas of contextual factors in the five domains (Intervention characteristics, outer setting, inner setting, characteristics of individuals, and implementation process) are 0.71, 0.82, 0.72, 0.89, 0.86, respectively. We used structural equation modeling to analyze the relationships among contextual factors, latent variables, practice facilitation strategies (Doing Tasks, Project Management, Consulting, Teaching, and Coaching), and outcomes (number of implemented QI interventions and Change Process Capability Questionnaire (CPCQ) score). All five facilitation strategies had statistically significant associations with the implementation of QI interventions (all P < 0.05). The combination of ML and the theory behind the IRLM can be used to identify relationships between inner and outer context determinants and implementation strategies and study outcomes in pragmatic research study datasets. All the proposed strategies in H3 were statistically associated with completed QI interventions; and the strategies had more impact on the implementation of interventions than CPCQ change. By understanding the relationship between outcomes, practice determinants and coaching strategies, practice facilitators can better help primary care practices adapt and implement interventions and build capacity to adapt to change.

Organization of Diabetes Care

Little is known about what determines strategy implementation around quality improvement (QI) in small- and medium-sized practices. Key questions are whether QI strategies are associated with practice readiness and practice characteristics. Grounded in organizational readiness theory, we examined how readiness and practice characteristics affect QI strategy implementation. The study was a component of a larger practice-level intervention, Heart of Virginia Healthcare, which sought to transform primary care while improving cardiovascular care. This observational study analyzed practice correlates of QI strategy implementation in primary care at 3 and 12 months. Data were derived from surveys completed by clinicians and staff and from assessments by practice coaches. A total of 175 small- and medium-sized primary care practices were included. Outcome was QI strategy implementation in three domains: (1) aspirin, blood pressure, cholesterol, and smoking cessation (ABCS); (2) care coordination; and (3) organizational-level improvement. Coaches assessed implementation at 3 and 12 months. Readiness was measured by baseline member surveys, 1831 responses from 175 practices, a response rate of 73%. Practice survey assessed practice characteristics, a response rate of 93%. We used multivariate regression. QI strategy implementation increased from 3 to 12 months: the mean for ABCS from 1.20 to 1.59, care coordination from 2.15 to 2.75, organizational improvement from 1.37 to 1.78 (95% CI). There was no statistically significant association between readiness and QI strategy implementation across domains. Independent practice implementation was statistically significantly higher than hospital-owned practicesat 3 months for ABCS (95% CI, P = 0.01) and care coordination (95% CI, P = 0.03), and at 12 months for care coordination (95% CI, P = 0.04). QI strategy implementation varies by practice ownership. Independent practices focus on patient care-related activities. FQHCs may need additional time to adopt and implement QI activities. Practice readiness may require more structural and organizational changes before starting a QI effort.

Health Care Reform and Care at the Behavioral Health--Primary Care Interface

Practice transformation efforts in healthcare, like the patient-centred medical home model in primary care, have spurred the development of multiple quality improvement (QI) and implementation strategies to support effective change....

Despite substance use disorders (SUD) being a leading cause of preventable death in the US, most people who visit primary care in the US are not screened for SUD. There are multiple barriers to screening for, identifying, and managing SUD in primary care. However, there are also promising strategies available to address these barriers, including practice facilitation (PF), learning collaboratives (LC), and performance incentives (PI). This study is a 48-site cluster-randomized 2 × 2 factorial implementation trial that aims to compare the effectiveness of several strategies for implementing evidence-based screening and interventions for SUDs in primary care. Practices will be randomized to one of four implementation strategies: (1) PF only, (2) PF + LC, (3) PF + PI, or (4) all three strategies. An estimated 144 participants from 48 primary care practices will be enrolled. All participants will receive PF to guide them in making changes to implement screening for SUD, focusing on a defined change package and associated tools. PF includes quality improvement (QI) coaching, as well as electronic health record (EHR) support, training, and expert consultation. LC includes monthly virtual education sessions led by content experts to support practice improvement and innovation with didactics on key topics as well as facilitating participant interactions to share experiences. PI includes financial incentives for performance. Primary care practices will be the unit of analysis for both the primary outcome (rate of SUD screening) and secondary outcomes (rates of evidence-based interventions for SUD). Assessments will be conducted during a 12-month implementation phase and 12-month sustainment phase. This study will produce evidence regarding the comparative effectiveness of several strategies on implementation and sustainment of evidence-based screening and interventions for SUD within primary care. It will also generate knowledge about mechanisms of change in primary care settings. The results are expected to have a positive impact by providing a nuanced understanding of the incremental benefits of LC and/or PI to inform primary care practices, health systems, policymakers, and payers about optimal implementation strategies for SUD screening and evidence-based interventions. ClinicalTrials.gov NCT06524232. July 23, 2024 -registered.