Quality Improvement Teams: Moving from the Passionate Few to the Mandated Many.

Quality Improvement has gone from practice by practice piecework to an industry driven by expertise that lies within corporate offices rather than within patient care. Using for her 20 years of experience leading and teaching quality improvement as a lens, the author makes the case for quality improvement teams to ensure a key role for clinicians and direct care staff who are closest to the patients and the improvements that need to be made.

Practice level factors associated with enhanced engagement with practice facilitators; findings from the heart health now study.

BACKGROUND: Practice facilitation is a promising strategy to enhance care processes and outcomes in primary care settings. It requires that practices and their facilitators engage as teams to drive improvement. In this analysis, we explored the practice and facilitator factors associated with greater team engagement at the mid-point of a 12-month practice facilitation intervention focused on implementing cardiovascular prevention activities in practice. Understanding factors associated with greater engagement with facilitators in practice-based quality improvement can assist practice facilitation programs with planning and resource allocation. METHODS: One hundred thirty-six ambulatory care small to medium sized primary care practices that participated in the EvidenceNow initiative's NC Cooperative, named Heart Health Now (HHN), fit the eligibility criteria for this analysis. We explored the practice and facilitator factors associated with greater team engagement at the mid-point of a 12-month intervention using a retrospective cohort design that included baseline survey data, monthly practice activity implementation data and information about facilitator's experience. Generalized linear mixed-effects models (GLMMs) identified variables associated with greater odds of team engagement using an ordinal scale for level of team engagement. RESULTS: Among our practice cohort, over half were clinician-owned and 27% were Federally Qualified Health Centers. The mean number of clinicians was 4.9 (SD 4.2) and approximately 40% of practices were in Medically Underserved Areas (MUA). GLMMs identified a best fit model. The Model presented as odd ratios and 95% confidence intervals suggests greater odds ratios of higher team engagement with greater practice QI leadership 17.31 (5.24-57.19), [0.00], and practice location in a MUA 7.25 (1.8-29.20), [0.005]. No facilitator characteristics were independently associated with greater engagement. CONCLUSIONS: Our analysis provides information for practice facilitation stakeholders to consider when considering which practices may be more amendable to embracing facilitation services.

Meaningful Use in Chronic Care: Improved Diabetes Outcomes Using a Primary Care Extension Center Model.

BACKGROUND: The effect of practice facilitation that provides onsite quality improvement (QI) and electronic health record (EHR) coaching on chronic care outcomes is unclear. This study evaluates the effectiveness of such a program-similar to an agricultural extension center model-that provides these services. METHODS: Through the Health Information Technology for Economic and Clinical Health (HITECH) portion of the American Recovery and Reinvestment Act, the North Carolina Area Health Education Centers program became the Regional Extension Center for Health Information Technology (REC) for North Carolina. The REC program provides onsite technical assistance to help small primary care practices achieve meaningful use of certified EHRs. While pursuing meaningful use functionality, practices were also offered complementary onsite advice regarding QI issues. We followed the first 50 primary care practices that utilized both EHR and QI advice targeting diabetes care. RESULTS: The achievement of meaningful use of certified EHRs and performance of QI with onsite practice facilitation showed an absolute improvement of 19% in the proportion of patients who achieved excellent diabetes control (hemoglobin A1c < 7%) compared to baseline. In addition, the percentages of patients with poorly controlled diabetes (hemoglobin A1c > 9%) fell steeply in these practices. LIMITATIONS: No control group was available for comparison. CONCLUSION: Practice facilitation that provided EHR and QI coaching support showed important improvements in diabetes outcomes in practices that achieved meaningful use of their EHR systems. This approach holds promise as a way to help small primary care practices achieve excellent patient outcomes.

Advancing heart health in North Carolina primary care: the Heart Health NOW study protocol.

BACKGROUND: The objective of Heart Health NOW (HHN) is to determine if primary care practice support-a comprehensive evidence-based quality improvement strategy involving practice facilitation, academic detailing, technology support, and regional learning collaboratives-accelerates widespread dissemination and implementation of evidence-based guidelines for cardiovascular disease (CVD) prevention in small- to medium-sized primary care practices and, additionally, increases practices' capacity to incorporate other evidence-based clinical guidelines in the future. METHODS/DESIGN: HHN is a stepped wedge, stratified, cluster randomized trial to evaluate the effect of primary care practice support on evidence-based CVD prevention, organizational change process measures, and patient outcomes. Each practice will start the trial as a control, receive the intervention at a randomized time point, and then enter a maintenance period 12 months after the start of the intervention. The intervention will be randomized to practices in one of four strata defined by region of the state (east or west) and degree of practice readiness for change. Seventy-five practices in each region with a high degree of readiness will be randomized 1:1:1 in blocks of 3 sometime prior to month 8 to receive the intervention at month 9, 11, or 12. An additional 75 practices within each region that have a low degree of readiness or are recruited later will be randomized 1:1 in blocks of 2 prior to month 13 to receive the intervention at month 14 or 16. The sites will be ordered within each strata based on time of enrollment with the blocking based on this ordering. Evaluation will examine the effect of primary care practice support on (1) practice-level delivery of evidence-based CVD prevention, (2) patient-level health outcomes, (3) practice-level implementation of clinical and organizational changes that support delivery of evidence-based CVD prevention, and (4) practice-level capacity to implement future evidence-based clinical guidelines. DISCUSSION: Results will indicate whether primary care practice support is an effective strategy for widespread dissemination and implementation of evidence-based clinical guidelines in primary care practices. Discernible reductions in cardiovascular risk in 300 practices covering over an estimated 900,000 adult patients would likely lead to prevention of thousands of cardiovascular events within 10 years. TRIAL REGISTRATION: ClinicalTrials.gov NCT02585557.

Tackling the triple aim in primary care residencies: the I3 POP Collaborative.

BACKGROUND AND OBJECTIVES: The I3 POP Collaborative's goal is to improve care of populations served by primary care residencies in North Carolina, South Carolina, and Virginia by dramatically improving patients' experience, quality of care, and cost-effectiveness. We examine residency baseline triple aim measures, compare with national benchmarks, and identify practice characteristics associated with data reporting. METHODS: We used a cross-sectional design, with 27 primary care residency programs caring for over 300,000 patients. Outcome measures were obtained via data pulls from electronic health records and practice management system submitted by residencies; they include quality measure sets for chronic illness and prevention, patient experience (usual provder continuity and time to third available), and utilization (emergency visits, hospitalizations, referrals, high-end radiology). RESULTS: Thirteen practices (48%) reported all required baseline measures. We found associations between data reporting ability with registry use (59% versus 0%) and having a faculty member involved in data management (69% versus 29%). Reported measures varied widely; examples include colorectal cancer screening (median: 61%, range: 28%--80%), provider continuity (median: 52%, range: 1%--68%), subspecialty referral rate (median: 24%, range: 10%--51%). Seventy percent of patient-centered medical homes (PCMH) recognized practices had usual provider continuity (UPC) > or = collaborative median versus 0% of non-PCMH recognized practices. Median data were similar to national comparisons for chronic disease measures, lower for prevention and better for utilization. CONCLUSIONS: Baseline triple aim data are highly variable among residencies, but residency care is comparable to available national standards. Registry use and faculty leadership in data management are critical success factors for assessing practice performance.

More extensive implementation of the chronic care model is associated with better lipid control in diabetes.

OBJECTIVE: Chronic disease collaboratives help practices redesign care delivery. The North Carolina Improving Performance in Practice program provides coaches to guide implementation of 4 key practice changes: registries, planned care templates, protocols, and self-management support. Coaches rate progress using the Key Drivers Implementation Scales (KDIS). This study examines whether higher KDIS scores are associated with improved diabetes outcomes. METHODS: We analyzed clinical and KDIS data from 42 practices. We modeled whether higher implementation scores at year 1 of participation were associated with improved diabetes measures during year 2. Improvement was defined as an increase in the proportion of patients with hemoglobin A1C values <9%, blood pressure values <130/80 mmHg, and low-density lipoprotein (LDL) levels <100 mg/dL. RESULTS: Statistically significant improvements in the proportion of patients who met the LDL threshold were noted with higher "registry" and "protocol" KDIS scores. For hemoglobin A1C and blood pressure values, none of the odds ratios were statistically significant. CONCLUSIONS: Practices that implement key changes may achieve improved patient outcomes in LDL control among their patients with diabetes. Our data confirm the importance of registry implementation and protocol use as key elements of improving patient care. The KDIS tool is a pragmatic option for measuring practice changes that are rooted in the Chronic Care Model.

The role of academic health centers and their partners in reconfiguring and retooling the existing workforce to practice in a transformed health system.

Inspired by the Affordable Care Act and health care payment models that reward value over volume, health care delivery systems are redefining the work of the health professionals they employ. Existing workers are taking on new roles, new types of health professionals are emerging, and the health workforce is shifting from practicing in higher-cost acute settings to lower-cost community settings, including patients' homes. The authors believe that although the pace of health system transformation has accelerated, a shortage of workers trained to function in the new models of care is hampering progress. In this Perspective, they argue that urgent attention must be paid to retraining the 18 million workers already employed in the system who will actually implement system change.Their view is shaped by work they have conducted in helping practices transform care, by extensive consultations with stakeholders attempting to understand the workforce implications of health system redesign, and by a thorough review of the peer-reviewed and gray literature. Through this work, the authors have become increasingly convinced that academic health centers (AHCs)-organizations at the forefront of innovations in health care delivery and health workforce training-are uniquely situated to proactively lead efforts to retrain the existing workforce. They recommend a set of specific actions (i.e., discovering and disseminating best practices; developing new partnerships; focusing on systems engineering approaches; planning for sustainability; and revising credentialing, accreditation, and continuing education) that AHC leaders can undertake to develop a more coherent workforce development strategy that supports practice transformation.

Natural history of practice transformation: development and initial testing of an outcomes-based model.

PURPOSE: Practice transformation is the cornerstone of the future of family medicine and health care reform, but little is known about how the process occurs. We sought to develop and test a model of the natural history of practice transformation. METHODS: We developed an outcomes-based model of how a practice moves through practice transformation in 2 phases: (1) initial model created through meetings with collaborative experts and practice facilitators, and (2) clinical and practice systems change reports examined from the first group of participating North Carolina Improving Performance In Practice practices to test and further refine the model. RESULTS: The resultant model described motivators and supports to transformation. Three emerging practice patterns were identified with the model: transformed practices experiencing robust improvement, activated practices with moderate change, and engaged practices with minimal change in measured quality over a 2-year period. Transformed practices showed broad-based improvement; some reached a threshold and others continued to improve. These practices had highly engaged leadership and used data to drive decisions. Activated practices had a slower improvement trajectory, usually encountering a barrier that took time to overcome (eg, extracting population data, spreading practice changes). Engaged practices did not improve or were unable to sustain change; despite good intentions, multiple competing distractions interfered with practice transformation. CONCLUSIONS: Practice transformation is a continuous and long-term process. Internal and external practice motivations and specific practice supports provided by a community-based quality improvement program appear to have an impact on engagement, rate of quality improvement, and long-term sustainability. Early successes play a key role as practices learn how to change their performance.

It takes a community: The North Carolina Division of Public Health and the North Carolina area health education center program partner to reduce strokes and heart attacks.

The North Carolina Division of Public Health is leading a statewide project using a combination of approaches to address cardiovascular risk factors including obesity, hypertension, diabetes, and cigarette smoking. The objectives are to decrease tobacco use, increase physical activity, improve nutrition, and increase access to evidence-based clinical preventive services targeting hypertension, hypercholestrolemia, tobacco use, and weight management.

Regional extension coordinators: use of practice support and electronic health records to improve quality and efficiency.

The North Carolina Regional Extension Center for Health Information Technology provides onsite consultation to primary care practices to help them implement electronic health records then use these systems to optimize care through measurement, rapid cycle quality improvement, and application of medical home functionalities. Services are available from all 9 regional North Carolina Area Health Education Centers.

Infrastructure for large-scale quality-improvement projects: early lessons from North Carolina Improving Performance in Practice.

INTRODUCTION: Little is known regarding how to accomplish large-scale health care improvement. Our goal is to improve the quality of chronic disease care in all primary care practices throughout North Carolina. METHODS: Methods for improvement include (1) common quality measures and shared data system; (2) rapid cycle improvement principles; (3) quality-improvement consultants (QICs), or practice facilitators; (4) learning networks; and (5) alignment of incentives. We emphasized a community-based strategy and developing a statewide infrastructure. Results are reported from the first 2 years of the North Carolina Improving Performance in Practice (IPIP) project. RESULTS: A coalition was formed to include professional societies, North Carolina AHEC, Community Care of North Carolina, insurers, and other organizations. Wave One started with 18 practices in 2 of 9 regions of the state. Quality-improvement consultants recruited practices. Over 80 percent of practices attended all quarterly regional meetings. In 9 months, almost all diabetes measures improved, and a bundled asthma measure improved from 33 to 58 percent. Overall, the magnitude of improvement was clinically and statistically significant (P = .001). Quality improvements were maintained on review 1 year later. Wave Two has spread to 103 practices in all 9 regions of the state, with 42 additional practices beginning the enrollment process. DISCUSSION: Large-scale health care quality improvement is feasible, when broadly supported by statewide leadership and community infrastructure. Practice-collected data and lack of a control group are limitations of the study design. Future priorities include maintaining improved sustainability for practices and communities. Our long-term goal is to transform all 2000 primary-care practices in our state.