- Primary Care Landscape
- Practice Facilitation
- Practice Capacity for Quality Improvement
- Improving the ABCS of Heart Health
- Research Design and Methods
- Other Topics
Qualitative Evaluation of a Cardiovascular Quality Improvement Programme Reveals Sizable Data Inaccuracies in Small Primary Care Practices
The Midwest Cooperative reflected on lessons learned from EvidenceNOW using interviews from practice leaders and practice facilitators from practices that experienced the largest and smallest gains in quality scores. The cooperative found that the largest changes in heart health (ABCS) care delivery scores likely reflected improvements in documentation due to coaching or fixes to electronic health record (EHR) data “glitches” rather than changes in care. The authors concluded that small practices continue to struggle with EHRs, and some small practices continue to operate with limited or incorrect performance data.
McHugh M, Brown T, Liss DT, et al. Qualitative evaluation of a cardiovascular quality improvement programme reveals sizable data inaccuracies in small primary care practices. BMJ Open Quality 2019;8:e000702. https://bmjopenquality.bmj.com/content/8/4/e000702
Challenges to Electronic Clinical Quality Measurement Using Third-Party Platforms in Primary Care Practices: The Healthy Hearts in the Heartland Experience
The Midwest Cooperative examined the challenges of using third-party platforms to extract data from electronic health records (EHRs) for electronic clinical quality measures (eCQM) in small to medium-sized primary care practices. Researchers connected 116 practices with seven different EHRs to popHealth, an open source eCQM platform. They identified the following challenges with eCQM data for data extraction: (1) Lack of coded eCQM data; (2) Incorrectly categorized eCQM data; (3) Isosemantic data (data within the incorrect context); (4) Coding that could not be directly evaluated; (5) Errors in date assignment and labeled as historical values; and (6) Inadequate data to assign the correct code. The researchers concluded that enhancements are needed to EHR systems that can promote effective eCQM implementation.
Ahmad FS, Rasmussen LV, Persell SD, et al. Challenges to electronic clinical quality measurement using third-party platforms in primary care practices: the healthy hearts in the heartland experience. JAMIA Open Volume 2, Issue 4, 2019 Dec. https://doi.org/10.1093/jamiaopen/ooz038
Using Electronic Health Records to Measure Quality Improvement Efforts: Findings from a Large Practice Facilitation Initiative
The Midwest Cooperative describes primary care practices’ ability to obtain measures with reporting periods aligning with a large quality improvement (QI) initiative. Three quality measures were collected quarterly over one year: aspirin for ischemic vascular disease; blood pressure control for hypertension; and smoking screening/cessation from 107 practices. More than half of practices were able to obtain all measures with rolling 12-month reporting periods, but smaller practices were less likely to be able to do so. Barriers to data collection included practices lacking optional electronic health record (EHR) features, and EHRs’ inability to produce reporting periods across two calendar years. The researchers concluded that: 1) EHR vendors’ compliance with Federal reporting requirements is not necessarily sufficient to support real-world QI work, and 2) improvements are needed in the flexibility and usability of EHRs’ quality measurement functions, particularly for smaller practices.
Liss DT, Peprah YA, Brown T, et al. Using electronic health records to measure quality improvement efforts: findings from a large practice facilitation initiative. Jt Comm J Qual Patient Saf 2020 Jan; 46(1):11‐17. https://www.ncbi.nlm.nih.gov/31704159
Indicators of Workplace Burnout Among Physicians, Advanced Practice Clinicians, and Staff in Small to Medium-Sized Primary Care Practices
The Virginia Cooperative examined whether individual behaviors and attitudes, such as anxiety and withdrawal from work, in response to disruptive change, influence workplace burnout at small and medium-sized practices. Findings revealed that healthcare professional groups have high levels of anxiety. Primary care physicians reported higher rates of burnout than other healthcare professionals such as advanced practice clinicians, clinical support staff, and administrative staff. The authors concluded that programs should focus on strengthening the work environment to improve organizational capacity for change and address high levels of anxiety experienced by healthcare professionals.
Golberg G, Soylu TG, Grady VM, et al. Indicators of workplace burnout among physicians, advanced practice clinicians, and staff in small to medium-sized primary care practices. JABFM 2020 May 19; 33 (3) 378-385. https://www.jabfm.org/content/33/3/378
Correlates of Burnout in Small Independent Primary Care Practices in an Urban Setting
The New York Cooperative conducted a cross-sectional analysis of provider burnout by using data collected from 235 providers practicing in 174 small independent primary care practices in New York City. The rate of provider-reported burnout was 13.5 percent, which was relatively low compared with previous surveys that focused primarily on larger practices. Higher adaptive reserve scores were associated with lower odds of burnout (odds ratio, 0.12; 95% CI; 0.02-0.85; P=0.34). The researchers conclude that the independence and autonomy providers have in these small practices may provide some protection against symptoms of burnout. In addition, the relationship between adaptive reserve and lower rates of burnout point toward potential interventions for reducing burnout that include strengthening primary care practices’ learning and development capacity.
Blecher B, Jiang N, Cleland C, et al. Correlates of burnout in small independent primary care practices in an urban setting. JABFM 2018 Aug;31:4. DOI:10.3122/jabfm.2018.04.170360.
Burnout among Physicians, Advanced Practice Clinicians, and Staff in Smaller Primary Care Practices
Researchers from the EvidenceNOW national evaluation team analyzed survey data from a sample of 10,284 physicians, advanced practice clinicians (APCs), and staff of 1380 smaller primary care practices participating in EvidenceNOW to examine the association between physician-, APC- and staff-reported burnout and specific structural, organizational, and contextual characteristics of smaller primary care practices. Burnout was reported by 20.4% of respondents overall. In a multivariable analysis, burnout was slightly more common among physicians and APCs than staff. Other multivariable correlates of burnout included non-solo practice; health system affiliation vs. physician/APC-owned practice; and Federally Qualified Health Center status vs. physician/APC-owned practice. Neither the proportion of patients on Medicare or Medicaid, nor practice-level patient volume were significantly associated with burnout. Practice size was not associated with burnout for APCs, and participation in an accountable care organization was associated with burnout for clinical and non-clinical staff. The authors conclude that burnout is prevalent among physicians, APCs, and staff in smaller primary care practices, and practice-level autonomy may be a critical determinant of burnout.
Edwards ST, Marino M, Balasubramanian B, et al, Burnout among physicians, advanced practice clinicians, and staff in smaller primary care practices. J Gen Intern Med 2018; 33(12):2138-46. PMID:30276654; https://www.ncbi.nlm.nih.gov/pubmed/30276654
The Influence of a Place-Based Foundation and a Public University in Growing a Rural Health Workforce
The Southwest Cooperative worked with the University of New Mexico’s Office of Community Health, which hired local Health Extension Rural Officers (HEROs) in different regions of the State to link community health needs with university resources. Multi-party agreements involved the JF Maddox foundation, a local community college, local community hospitals, and the University to work together to recruit, support, and retain local health care professionals in an impoverished, rural area of the State. These partnerships significantly increased recruitment of key health care professionals, developed a more cohesive medical community, established a school-based clinic, and provided support for other community challenges. The University has since exported this model to other rural communities in the State.
Reid R, Rising E, Kaufman A, et al. The influence of place-based foundation and a public university in growing a rural health workforce. J Comm Hlth 2019; 44:292-296. Available at: https://doi.org/10.1007/s10900-018-0585-y
Use of Quality Improvement Strategies Among Small- to Medium-Size U.S. Primary Care Practices
The EvidenceNOW National Evaluation Team assessed the use of quality improvement strategies by small- to medium-sized primary care practices before participating in EvidenceNOW. Practices that participated in accountable care organizations, produced reports from electronic health records (EHRs), produced quality reports, or discussed clinical quality data in meetings use quality improvement (QI) strategies to a greater degree than other practices. Additionally, they found lower use of QI strategies among health-system owned practices and those experiencing a disruptive event.
Balasubramanian BA, Marino M, Cohen DJ, et al. (2018). Use of quality improvement strategies among small- to medium-size US primary care practices. Ann Fam Med 2018;16(Suppl 1):S35-S43. http://www.annfammed.org/content/16/Suppl_1/S35.
Primary Care Practices’ Abilities and Challenges Using Electronic Health Record Data for Quality Improvement
An analysis of the challenges primary care practices face in generating and using data reports from their electronic health records (EHRs) to conduct quality improvement activities. The EvidenceNOW National Evaluation Team found that meaningful-use participation was associated with the ability to generate reports on clinical quality measures, but the reports did not necessarily support quality improvement initiatives. Practices reported numerous challenges in generating adequate reports, including functionality limitations, differences between clinical guidelines and measures available in EHR-generated reports, and questionable data quality. Findings from this large study of smaller primary care practices demonstrate that the promise of using EHRs for quality improvement remains largely unfulfilled.
Cohen, DJ et al. (2018). Health Affairs 37(4). https://www.healthaffairs.org/doi/full/10.1377/hlthaff.2017.1254.
Effect of Practice Ownership on Work Environment, Learning Culture, Psychological Safety, and Burnout
The Virginia Cooperative examines effects of practice ownership on self-reported work environment, culture of learning, psychological safety, and burnout at small- and medium-size primary care practices. Hospital ownership was associated with more positive perceptions of practice work environment, psychological safety, and lower staff burnout, though the effect was largely driven by clinic staff rather than clinicians.
Cuellar A, Krist AH, Nichols LM, Kuzel AJ. (2018). Association between primary care practice ownership, work environment, learning culture, and burnout. Ann Fam Med 2018;16(Suppl 1):S44-S51. http://www.annfammed.org/content/16/Suppl_1/S44.
Organizational Leadership and Adaptive Reserve in Blood Pressure Control: The Heart Health NOW Study
The North Carolina Cooperative examines small primary care practices’ performance on blood pressure control goals before practices’ participation in EvidenceNOW and the relationship to organizational quality improvement (QI) characteristics. Adaptive reserve and leadership capability in QI were not associated with achieving the target blood pressure goal.
Henderson KH, DeWalt DA, Halladay J, et al. (2018). Organizational leadership and adaptive reserve in blood pressure control: The Heart Health NOW Study. Ann Fam Med 2018;16(Suppl 1):S29-S34. http://www.annfammed.org/content/16/Suppl_1/S29.
EvidenceNOW: Balancing Primary Care Implementation and Implementation Research
AHRQ describes the research design decisions made for the EvidenceNOW initiative, including the focus on small- and medium-sized practices, the specific intervention and research strategies, the evaluation, and use of learning communities. The article also addresses the trade-offs between research goals and real-world implementation of quality improvement strategies.
Meyers D, Miller T, Genevro J, et al. (2018). EvidenceNOW: Balancing primary care implementation and implementation research. Ann Fam Med 2018;16(Suppl 1):S5-S11. http://www.annfammed.org/content/16/Suppl_1/S5.
The Alarming Rate of Major Disruptive Events in Primary Care Practices in Oklahoma
The Oklahoma Cooperative explores major disruptive events in small- to medium-sized primary care practices in Oklahoma, such as practice relocation, changes in ownership and key staff, and implementation of new systems—events that can affect quality and continuity of care. During the practices’ first year participating in EvidenceNOW, nearly one in two practices experienced at least one major disruptive event.
Mold JW, Walsh M, Chou A, Homco J. (2018). The alarming rate of major disruptive events in primary care practices in Oklahoma. Ann Fam Med 2018;16(Suppl 1):S52-S57. http://www.annfammed.org/content/16/Suppl_1/S52.
Quality of Cardiovascular Disease Care in Small Urban Practices
This paper by the New York City Cooperative captures the performance of small, urban primary care practices on the four EvidenceNOW heart health care (ABCS) measures before the practices participated in EvidenceNOW. At these practices, performance on goals for the ABCS of heart health varied. Researchers also found that solo clinician primary care practices were more likely to meet the aspirin and cholesterol goal than practices with more than one clinician.
Shelley D, Blechter B, Siman N, et al. (2018). Quality of cardiovascular disease care in small urban practices. Ann Fam Med 2018;16(Suppl 1):S21-S28. http://www.annfammed.org/content/16/Suppl_1/S21.
AHRQ’s EvidenceNOW: A Snapshot of Participating Primary Care Practices
An infographic showing diversity among primary care practices participating in EvidenceNOW across characteristics such as practice size, location, ownership, and patient characteristics.
Agency for Healthcare Research and Quality. (September 2017). Available at: http://www.ahrq.gov/evidencenow/evaluation/practice-snapshot.html.
Measuring Implementation Strategy Fidelity in HealthyHearts NYC: A Complex Intervention Using Practice Facilitation in Primary Care
The New York City Cooperative assessed the fidelity of practice facilitation as an implementation strategy. Fidelity was measured using data from a web-based tracking system using four categories: intervention frequency, duration, content, and coverage. Results revealed that almost all of the 257 participating practices received at least 13 practice facilitation visits. Facilitators spent an average of 26 hours at each site conducting on-site facilitation. Most practices completed a set of standardized activities designed to facilitate adoption of the ABCS of heart health care and were educated on all Chronic Care Model strategies. Most practices also received the full intervention.
Berry CA, Nguyen AM, Cuthel AM, et al. Measuring implementation strategy fidelity in HealthyHearts NYC: A complex intervention using practice facilitation in primary care. American Journal of Medical Quality, 2020 September 23. https://doi.org/10.1177/1062860620959450
Using a Customer Relationship Management System to Manage a Quality Improvement Intervention
The New York City Cooperative evaluated the impact of practice facilitation on implementation of the Million Hearts guidelines for cardiovascular disease prevention and treatment. A customizable customer relationship management system (CRMS) was implemented to support the quality improvement intervention that included 257 participating practices. Features of the CRMS were customized to optimize program management, practice facilitation tracking and supervision, and data collection for performance feedback to practices and for research. The authors concluded that CRMS can effectively track practice facilitation activities with the detail needed to optimize implementation and provides a data source for both research and practice.
Pham-Singer H, Onakomaiya M, Cuthel A, et al. Using a customer relationship management system to manage a quality improvement intervention. American Journal of Medical Quality. 2020 September 13. https://doi.org/10.1177/1062860620953214
Identifying Practice Facilitation Delays and Barriers in Primary Care Quality Improvement
The Midwest Cooperative analyzed practice-specific delays and barriers to practice facilitation during EvidenceNOW. Results revealed that most facilitation activities occurred at regular tempos, but nearly all practices experienced at least one delay. Practices with more delays had lower quality improvement intervention completion rates and were more likely to encounter barriers such as lack of time and staff, lack of staff engagement, technical issues, and staff turnover.
Ye J, Zhang R, Bannon JE, et al. Identifying practice facilitation delays and barriers in primary care quality improvement. Journal of the American Board of Family Medicine, September 2020, 33 (5), 655-664. https://doi.org/10.3122/jabfm.2020.05.200058
A Cross-Cutting Workforce Solution for Implementing Community-Clinical Linkage Models
This editorial proposes that small, independently owned practices should strategically employ practice facilitators to integrate community health workers (CHWs) into their primary care teams to support the effective implementation of community–clinical linkage models. The authors concluded that the strong evidence that CHWs are effective and that practice facilitation can optimize implementation of evidence-based care models should inform decisions about future funding of practice facilitation to support CHW integration in small, independently owned practices.
Islam N, Rogers ES, Schoenthaler A, et al. A cross-cutting workforce solution for implementing community-clinical linkage models. Am J Public Health. 2020 July; 110(S2): S191-S193. http://doi.org/10.2105/AJPH.2020.305692
How Practice Facilitation Strategies Differ by Practice Context
The New York City Cooperative looked at how practice facilitation strategies are tailored to different primary care contexts, using interviews with practice facilitators working in small independent practices (SIPs) or Federally Qualified Health Centers (FQHCs). Interviews revealed four facilitation strategies used: 1) Remain flexible to align with practice and organizational priorities; 2) Build relationships; 3) Provide value through information technology expertise; and 4) Build capacity and create efficiencies. Facilitators in SIPs and FQHCs described using the same strategies, often in combination, but tailored to their specific practice environments. The authors concluded that facilitators require multidisciplinary skills to support sustainable practice improvement in different healthcare delivery settings.
Nguyen AM, Cuthel A., Padgett DK, et al. How practice facilitation strategies differ by practice context. J Gen Intern Med 35, 824–831 (2020). https://doi.org/10.1007/s11606-019-05350-7
Effects of 2 Forms of Practice Facilitation on Cardiovascular Prevention in Primary Care
The Healthy Hearts in the Heartland Cooperative compared practice facilitation implementing point-of-care (POC) quality improvement (QI) strategies alone versus facilitation implementing point-of-care plus population management (POC+PM) strategies on preventive cardiovascular care. The authors randomized 226 small and mid-sized primary care practices who worked with facilitators on QI for 12 months to implement POC or POC+PM strategies. The researchers measured the proportion of eligible patients in a practice meeting “ABCS” measures: (aspirin for eligible patients, blood pressure control, Cholesterol control, Smoking cessation counseling), as well as the Change Process Capability Questionnaire at baseline, 12 months, and 18 months. The mean proportion of patients meeting each performance measure was slightly (.04 to .05) greater at 12 months, with improvements sustained at 18 months. At 12 months, baseline-adjusted differences 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. The Change Process Capability Questionnaire improved slightly, mean change 0.30 (0.09–0.51), but did not significantly differ across arms. The authors conclude that facilitator-led QI promoting population management approaches plus POC improvement strategies was not clearly superior to POC strategies alone.
Persell S, Liss D, Walunas T, et al. Effects of 2 forms of practice facilitation on cardiovascular prevention in primary care. Medical Care 2020; 58(4): 344-351. Available at: https://doi.org/10.1097/MLR.0000000000001260.
Cardiovascular Disease Guideline Adherence: An RCT Using Practice Facilitation
This study by the Healthy Hearts New York City Cooperative examined whether practice facilitation (PF) is effective in increasing the proportion of patients meeting the Million Hearts ABCS outcomes: (A) aspirin when indicated, (B) blood pressure control, (C) cholesterol management, and (S) smoking screening and cessation intervention. Researchers randomized 257 small independent primary care practices in New York City into 1 of 4 waves that determined when they would start receiving the 1-year PF intervention. The intervention consisted of practice facilitators conducting at least 13 practice visits over 1 year, focused on capacity building and implementing system and workflow changes to meet the cardiovascular disease care guidelines. Data were extracted for 13 quarters between January 1, 2015 and March 31, 2018, which encompassed the control, intervention, and follow-up periods for all waves, and analyzed in 2019. PF was associated with improvements in the 2 smoking-related outcomes only, the smoking composite (screening for tobacco use and counseling) and smokers counseled. The follow-up smoking measure improved compared with the control period (incidence rate ratio=1.152, 95% CI=1.072, 1.238, p<0.001) and the intervention period (incidence rate ratio=1.060, 95% CI=1.013, 1.109, p=0.007). Smokers counseled also improved when comparing the intervention period with control period (incidence rate ratio=1.121, 95% CI=1.037, 1.211, p=0.002). The researchers conclude that increasing the impact of PF programs that target multiple risk factors may require a longer, more intense intervention and greater attention to external policy and practice contextual factors that may hinder the facilitation process and practice improvement goals.
Shelley DR, Gepts T, Siman N, et al. Cardiovascular disease guideline adherence: An RCT using practice facilitation. Am J Prev Med 2020; Feb 14. Available at: https://www.ncbi.nlm.nih.gov/pubmed/32067871
Dedicated Workforce Required to Support Large-Scale Practice Improvement
EvidenceNOW funded seven Cooperatives, each working with over 200 primary care practices, advised by practice facilitators, to rapidly disseminate and implement improvements in cardiovascular preventive care: aspirin in high-risk individuals, blood pressure control, cholesterol management, and smoking cessation. This study by the EvidenceNOW national evaluation team identified the organizational elements and infrastructures Cooperatives used to support practice facilitators by reviewing facilitator logs, online diary data, semi-structured interviews with facilitators, and field notes from facilitator observations. Results revealed that each Cooperative partnered with 2 to 16 organizations, piecing together 16 to 35 facilitators, often from other quality improvement projects. Quality assurance strategies by Cooperatives included establishing initial and ongoing training, processes to support facilitators, and monitoring to assure consistency and quality. Cooperatives developed facilitator toolkits, implemented initiative-specific training, and developed processes for peer-to-peer learning and support. The evaluation team found that supporting a large-scale facilitation workforce requires creating an infrastructure, including initial training, and ongoing support and monitoring, often borrowing from other ongoing initiatives. Few regions have facilitation organizations at this scale. The researchers conclude that a dedicated workforce is required to support large-scale practice improvement and would be more efficient and effective than this fragmented approach to quality improvement.
Sweeney SM, Hemler JR, Baron AN, et al. Dedicated workforce required to support large-scale practice improvement J Am Bd Fam Med 2020; 33 (2): 230-239. DOI: https://doi.org/10.3122/jabfm.2020.02.190261
Disseminating, Implementing, and Evaluating Patient-Centered Outcomes to Improve Cardiovascular Care Using a Stepped-Wedge Design: Healthy Hearts for Oklahoma
This paper describes how the Healthy Hearts for Oklahoma Cooperative partnered with public health agencies and communities to construct a sustainable Oklahoma Primary Care Healthcare Improvement Collaborative (OPHIC) to support dissemination and implementation (D&I) of quality improvement (QI) methods to promote implementation of ABCS (aspirin therapy, blood pressure control, cholesterol management, and smoking cessation) measures and provide QI support to primary care practices (PCPs) to better manage patients at risk for cardiovascular disease events. A total of 263 small PCPs across Oklahoma received the bundled QI intervention to improve ABCS performance. A stepped-wedge design was used to evaluate D&I of QI support. Changes in ABCS measures will be estimated as a function of various components of the QI support and capacity and readiness of PCPs to change. Notes from academic detailing and practice facilitation sessions will be analyzed to help interpret findings on ABCS performance. Lessons learned from this project will guide future strategies for D&I of evidence-based practices in PCPs. The authors conclude that trained practice facilitators will continue to serve as critical resource to assist small, rural PCPs in adapting to the ever-changing health environment and continue to deliver quality care to their communities.
Chou AF, Homco JB, Nagykaldi Z, et al. Disseminating, implementing, and evaluating patient-centered outcomes to improve cardiovascular care using a stepped-wedge design: healthy hearts for Oklahoma. BMC Health Serv Res. 2018 Jun 4;18(1):404. doi: 10.1186/s12913-018-3189-4; https://www.ncbi.nlm.nih.gov/pubmed/29866120
Practice Facilitator Strategies for Addressing Electronic Health Record Data Challenges for Quality Improvement: EvidenceNOW
The EvidenceNOW national evaluation team analyzed qualitative data from online diaries, site visit field notes, and interviews to discover how practice facilitators worked with practices on electronic health record (EHR) data challenges to obtain and use data for quality improvement (QI). They examined data from about 1500 small- to medium-sized primary care practices and 136 facilitators in EvidenceNOW. They found that facilitators faced practice-level EHR data challenges, such as a lack of clinical performance data, partial or incomplete clinical performance data, and inaccurate clinical performance data. Facilitators responded to these challenges, respectively, by using other data sources or tools to fill in for missing data, approximating performance reports and generating patient lists, and teaching practices how to document care and confirm performance measures. In addition, facilitators helped practices communicate with EHR vendors or health systems in requesting data they needed. Overall, facilitators tailored strategies to fit the individual practice and helped build data skills and trust. The authors conclude that support is necessary to help practices, particularly those with EHR data challenges, build their capacity for conducting data-driven QI, which is required to participate in practice transformation and performance-based payment programs.
Hemler JR, Hall JD, Cholan RA, et al. Practice facilitator strategies for addressing electronic health record data challenges for quality improvement: EvidenceNOW. JABFM 2018;31(3):398-409. PubMed PMID: 29743223; https://www.ncbi.nlm.nih.gov/pubmed/29743223
Facilitating Practice Transformation in Frontline Health Care
This editorial by EvidenceNOW grantees notes that many featured papers in this supplement on primary care transformation are the early products of nearly $800 million invested by AHRQ and other Federal health agencies to test facilitation of transformation in thousands of practices across the United States. It notes that most small practices lack the time, energy, and resources for quality improvement and lack examples from which they can learn. Farmers were in this position a century ago when the U.S. Department of Agriculture Cooperative Extension Program revolutionized farming in the United States. Agricultural experts worked with farmers to test and disseminate innovative agricultural practices that farming is still benefitting from today. AHRQ has developed a similar extension model using practice facilitators and other consultants and resources to transform primary care, which is described in several supplement articles by EvidenceNOW researchers in this supplement.
Phillips Jr, RL, Cohen DJ, Kaufman A, et al. (2019).Facilitating practice transformation in frontline health care. Ann Fam Med 2019; 17 (Suppl 1):S2-S5. http://www.annfammed.org/content/17/Suppl_1/S2.full
Clinician Perspectives on the Benefits of Practice Facilitation for Small Primary Care Practices
The Healthy Hearts New York City Cooperative interviewed 19 small independent primary care practices (SIPs) about how the benefits of practice facilitation (PF) differed based on the availability of internal staff for quality improvement. Providers perceived three central PF benefits: creating awareness of quality gaps; connecting practices to information, resources, and strategies to improve care; and optimizing the EHR for quality improvement goals. SIPS with more than three office staff felt PF provided benefits primarily through teaching, while SIPs with three or fewer staff felt that PF also provided hands-on support.
Rogers ES, Cuthel AM, Berry CA, et al. Clinician perspectives on the benefits of practice facilitation for small primary care practices. Ann Fam Med 2019; 17 (Suppl 1):S17-S23. http://www.annfammed.org/content/17/Suppl_1/S17.full
A Randomized Trial of External Practice Support to Improve Cardiovascular Risk Factors in Primary Care
The Northwest Cooperative compared the effectiveness of adding enhanced external support to practice facilitation (PF) on primary care practices’ performance on cardiovascular clinical quality measures. In this randomized trial, Practices received either PF alone or enhanced practice support that included: PF with shared learning opportunities, PF with educational outreach visits, or PF with both shared learning opportunities and educational outreach visits. The researchers found no significant differences in clinical quality measure improvements between practices receiving only PF and those receiving enhanced support. However, they found that practices that received both shared learning opportunities and educational outreach were two times more likely to achieve a blood pressure performance goal of 70 percent compared to those receiving PF alone.
Parchman ML, Anderson ML, Dorr DA, et al. A randomized trial of external practice support to improve cardiovascular risk factors in primary care. Ann Fam Med 2019; 17 (Suppl 1):S40-S49. http://www.annfammed.org/content/17/Suppl_1/S40.full
Practice Facilitators’ and Leaders’ Perspectives on a Facilitated Quality Improvement Program
A qualitative look by the Midwest Cooperative at methods for improving quality improvement approaches, using detailed interviews from primary care practice leaders and the practice facilitators assigned to those practices. Interviews indicated that targeted practice facilitator-supported efforts may be easier to implement in primary care than larger, more extensive quality improvement projects.
McHugh M, Brown T, Liss DT, Walunas T, Persell S. (2018). Practice facilitators' and leaders' perspectives on a facilitated quality improvement program. Ann Fam Med 2018;16(Suppl 1):S65-S71. http://www.annfammed.org/content/16/Suppl_1/S65.
A Framework to Guide Practice Facilitators in Building Capacity
A discussion from the North Carolina Cooperative of a new framework for practice facilitators to apply the most appropriate mechanism for providing information to primary care practices, with a goal of building practices’ capacity to sustain improvement in their care delivery.
Baker N, Lefebvre A, Sevin C. (August 2017). J Family Med Community Health 4(6):1126. Available at: https://www.jscimedcentral.com/FamilyMedicine/familymedicine-4-1126.pdf.
Practice Transformation Support and Patient Engagement to Improve Cardiovascular Care: From EvidenceNOW Southwest (ENSW)
The Southwest Cooperative examined how primary care practices can improve cardiovascular care through adoption of evidence-based guidelines. The Cooperative compared two practice transformation support interventions: standard practice support and standard support plus patient engagement support. These interventions were compared to an external group of practices that received no support. Results revealed no difference between the two interventions. However, participating practices saw greater improvement compared to the external comparison group, including improvement in team-based care, patient-team partnership, and population management in the enhanced intervention group. The authors concluded that practice transformation support can assist practices with improving quality of care, and patient engagement can further enhance practices' implementation of new models of care.
Dickinson WP, Nease DE, Rhyne RL, et al. Practice transformation support and patient engagement to improve cardiovascular care: From EvidenceNOW Southwest (ENSW). The Journal of the American Board of Family Medicine, September 2020, 33 (5), 675-686. https://doi.org/10.3122/jabfm.2020.05.190395
Readiness and Implementation of Quality Improvement Strategies Among Small- and Medium-Sized Primary Care Practices: An Observational Study
The Virginia Cooperative examined how readiness and practice characteristics affect quality improvement (QI) strategy implementation. Results revealed that QI strategy implementation increased at 12 months compared to 3 months. There was no statistically significant association between readiness and QI strategy implementation. However, independent practice implementation was significantly higher than hospital-owned practices at 3 months for aspirin, blood pressure control, cholesterol management, smoking cessation, and care coordination, and at 12 months for care coordination. The authors concluded that QI strategy implementation varies by practice ownership, and practice readiness may require more structural and organizational changes before starting a QI effort.
Soylu TG, Cuellar AE, Goldberg DG, et al. Readiness and implementation of quality improvement strategies among small- and medium-sized primary care practices: An observational study. J Gen Intern Med, 2020 August 10. https://doi.org/10.1007/s11606-020-05978-w
Exemplary Practices in Cardiovascular Care: Results on Clinical Quality Measures from the EvidenceNOW Southwest Cooperative
The Southwest Cooperative identified practice characteristics associated with high performance on four cardiovascular disease clinical quality measures (CQMs). Quarterly CQM reports were obtained from 178 practices; among these practices, 39 were high performers. These practices were more likely to be a Federally Qualified Health Center, have an underserved designation, and have a higher percentage of Medicaid patients. Additionally, these practices reported greater use of cardiovascular disease registries, standing orders or electronic health record prompts, were more likely to have medical home recognition, and reported greater implementation of building blocks of high-performing primary care. Practices with high improvement showed greater improvement implementing team-based care and population management. The authors concluded that multiple strategies were associated with delivering high-quality cardiovascular care over time.
Fernald DH, Mullen R, Hall T, et al. Exemplary practices in cardiovascular care: Results on clinical quality measures from the EvidenceNOW Southwest Cooperative. J Gen Intern Med, 2020 August 17. https://doi.org/10.1007/s11606-020-06094-5
Practice Level Factors Associated with Enhanced Engagement with Practice Facilitators; Findings from The Heart Health Now Study
The North Carolina Cooperative explored if there are practice characteristics and practice facilitator factors associated with greater levels of engagement between the facilitators and the practices they served. Half of the 136 participating practices were clinician-owned, 27% were Federally Qualified Health Centers, and approximately 40% were in medically underserved areas. The researchers found greater engagement with facilitators was associated with practices that have leaders who support quality improvement implementation and practices located in medically underserved areas.
Halladay JR, Weiner BJ, Kim J, et al. Practice level factors associated with enhanced engagement with practice facilitators; findings from the heart health now study. BMC Health Serv Res 20,695;2020 July 28. https://doi.org/10.1186/s12913-020-05552-4
The Ability of Practices to Report Clinical Quality Measures: More Evidence of the Size Paradox?
The Northwest Cooperative examined whether primary care practices with and without support from a larger organization differ in their ability to produce timely reports on cardiovascular disease quality measures. Researchers used data from 205 practices from a baseline practice survey and clinical quality measure (eCQM) data from electronic health records. Findings revealed that practices without central quality improvement (QI) support had higher rates of eCQM submission at 30 days and 60 days than practices with central QI support. Practices with central QI support took longer to submit data compared with practices without centralized support. The authors concluded that the ability of smaller practices without centralized QI support to report their eCQMs more quickly may have implications for their ability to improve these measures.
Parchman ML, Anderson ML, Penfold RB, et al. The ability of practices to report clinical quality measures: More evidence of the size paradox? JABFM 2020 July; 33(4), 620-625. https://www.jabfm.org/content/33/4/620/tab-article-info
Contrasting Perspectives of Practice Leaders and Practice Facilitators May Be Common in Quality Improvement Initiatives
The Midwest Cooperative interviewed practice leaders and practice facilitators to identify contrasting perspectives on quality improvement (QI) implementation issues and factors that contribute to them. Contrasting perspectives were related to the easiest or hardest QI interventions and practices’ success implementing the interventions. Employee turnover was often reported by practice leaders and facilitators with contrasting perspectives. The authors concluded that those who are planning QI initiatives using practice facilitation should take steps to minimize contrasting perspectives by addressing turnover challenges and encouraging opportunities to share perspectives.
McHugh M, Brown T, Walunas TL, et al. Contrasting perspectives of practice leaders and practice facilitators may be common in quality improvement initiatives. J Healthc Qual 2020 May;42(3):e32‐e38. https://www.ncbi.nlm.nih.gov/31634207
The Role of Organizational Learning and Resilience for Change in Building Quality Improvement Capacity in Primary Care
The Northwest Cooperative examined the association of adaptive reserve (AR) and development of primary care practices’ capacity for quality improvement (QI). The cooperative randomized 142 primary care practices and evaluated them at baseline and 12 months. AR was measured using a staff survey, and QI capacity was measured using the QI capacity assessment (QICA). Findings revealed that baseline AR was positively associated with both baseline and follow-up QI capacity, but there was no association between change in AR and change in the QICA. The researchers concluded that AR may be necessary for practices to increase their QI capacity, and developing AR may be a valuable step before undertaking QI-related growth.
Schuttner L, Coleman K, Ralston J, et al. The role of organizational learning and resilience for change in building quality improvement capacity in primary care. Health Care Manage Rev, 2020 April 3. https://www.ncbi.nlm.nih.gov/32251020
What Do We Know and Need to Know About Transforming Primary Care?
This commentary by a member of the national evaluation team for AHRQ’s EvidenceNOW initiative identifies some of what we know, and still need to know, in order to guide and support primary care transformation. He notes that it requires both internal culture change and a supportive external environment, including aligned financial incentives. He points out that while external facilitation will likely help, transformation is even more dependent on active support from visionary internal leadership and an infrastructure for managing change. But without access to accurate, timely and repeatable measurement data, even a practice with all the other pieces in place will find it hard to identify and improve priority areas. Clinicians and other personnel, plus patients must be engaged in the changes to ensure that they are made in a way that also serves their needs. Finally, it is very unlikely that one size will fit all practice settings, either in approach to change or in what changes each practice chooses to make. More information is needed for many questions, which he raises here in the hope that others will provide evidence-based answers.
Solberg LI. What do we know and need to know about transforming primary care? Family Practice, August 2017; 34(4): 371-372. PMID: 28475721 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5808872/
Effects of Practice Turnover on Primary Care Quality Improvement Implementation
The EvidenceNOW national evaluation team examined qualitative data from practice staff and external practice facilitators participating in EvidenceNOW, a large-scale quality improvement (QI) initiative, to understand the relationship between practice turnover and QI efforts. They found that turnover can limit practices' ability to engage in QI activities in various ways. For example, when a staff member leaves, remaining staff often must take on additional responsibilities. What’s more, QI momentum slows as new staff are trained or existing staff are reengaged. Turnover also 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. The authors conclude that understanding how staff turnover affects QI may help practices, and those helping them with QI, manage the disruptive effects of turnover.
Baron A HJ, Sweeney S, Woodson T, et al. Effects of practice turnover on primary care quality improvement implementation. Am J Med Qual 2019 Apr; 29. PMID:31030525 https://www.ncbi.nlm.nih.gov/pubmed/31030525
Does Ownership Make a Difference in Primary Care Practice?
The EvidenceNOW national evaluation team used electronic health record and survey data from September 2015 to April 2017 to assess differences in structural characteristics, quality improvement (QI) processes, and cardiovascular preventive care by ownership type among 989 small to medium primary care practices. The team compared physician-owned practices, health system or medical group practices, and Federally Qualified Health Centers (FQHC) by using 15 survey-based practice characteristic measures, 9 survey-based QI process measures, and 4 electronic health record-based cardiovascular disease prevention quality measures, namely, aspirin prescription, blood pressure control, cholesterol management, and smoking cessation support (ABCS). ABCS performance was similar across ownership type, with the exception of smoking cessation support (51.0% for physician-owned practices vs 67.3% for health system practices and 69.3% for FQHCs). Primary care practice ownership was associated with differences in QI process measures, with FQHCs reporting the highest use of QI strategies followed by health system practices. ABCS were mostly unrelated to ownership, suggesting a complex path between QI strategies and outcomes.
Liindner S, Solberg LJ, Miller WL, et al. Does ownership make a difference in primary care practice? JABFM 2019 May; 32(3):398-407. PMID:31068404 https://www.ncbi.nlm.nih.gov/pubmed/31068404
The Capacity of Primary Care for Improving Evidence-Based Care: Early Findings from AHRQ’s EvidenceNOW
This paper introduces the journal supplement on AHRQ’s EvidenceNOW initiative to improve primary care. The supplement consists of 8 original research articles representing all 7 EvidenceNOW regional cooperatives and the national evaluation team. The authors note that at the outset of the program, the cooperatives and national evaluation team harmonized a number of metrics, especially for the ABCS (aspirin prescribing , blood pressure control, cholesterol management, and smoking cessation), and practice capacity for quality improvement. In addition, each cooperative, as part of its own robust evaluation plan, has been collecting some unique metrics specific to its own study aims. The supplement also includes an overview and rationale for the initiative from AHRQ and two commentaries from nationally recognized experts in the field of primary care research and practice transformation. The authors of this introduction to the supplement note that although the articles report early findings that represent a range of topics and empirical approaches, together they expand our understanding of the current performance and capacity of primary care for improving evidence-based care and how to provide external quality improvement support to primary care practices.
Shoemaker SJ, McNellis RJ, and DeWalt DA. The capacity of primary cfare for improving evidence-based care: Early findings from AHRQ’s EvidenceNOW. Ann Fam Med 2018; 16(Suppl 1):S2-S-4. PMID: 29632218 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5891306/
Assessing Quality Improvement Capacity in Primary Care Practices
Healthy Hearts Northwest developed a Quality Improvement Capacity Assessment (QICA) survey that identified seven domains of QI capacity, such as embedding clinical evidence into daily work and using data to improve clinical performance measures. As part of the study intervention, each of the 209 participating practices met with a practice facilitator (PF) to discuss their survey responses and calculate a QICA score. The researchers examined the association between the QICA scores, practice characteristics, their prior experience with managing practice change, and performance on clinical quality measures for three cardiovascular (CVD) risk factors. The QICA score was associated with prior experience managing change and moderately associated with two of three CVD risk factors. Rural practices and those with 2 to 5 clinicians had lower QICA scores. The authors conclude that the QICA is useful for assessing QI capacity within a practice and may serve as a guide for both PFs and practices to improve QI capacity and clinical performance.
Parchman ML, Anderson ML, Coleman K, et al. Assessing quality improvement capacity in primary care practices. BMC Family Practice 2019; 20:103. Available at: https://doi.org/10.1186/s12875-019-1000-1
AHRQ’s EvidenceNOW: Helping Small Primary Care Practices Build Capacity for Quality Improvement
An infographic highlighting participating EvidenceNOW practices’ capacity at baseline to implement new evidence into practice. Capacity refers to the attitudes, skills, structures, and processes that enable a primary care practice to improve systematically.
Agency for Healthcare Research and Quality. (January 2018). Available at: http://www.ahrq.gov/sites/default/files/wysiwyg/evidencenow/evaluation/evidence-now-improving-capacity.pdf.
A Framework to Guide Practice Facilitators in Building Capacity
A discussion from the North Carolina Cooperative of a new framework for practice facilitators to apply the most appropriate mechanism for providing information to primary care practices, with a goal of building practices’ capacity to sustain improvement in their care delivery.
Baker N, Lefebvre A, Sevin C. (August 2017). Journal of Family Medicine and Community Health 4(6):1126. Available at: https://www.jscimedcentral.com/FamilyMedicine/familymedicine-4-1126.pdf.
Validity of Medical Record Abstraction and Electronic Health Record-Generated Reports to Assess Performance on Cardiovascular Quality Measures in Primary Care
The Oklahoma Cooperative examined whether medical record abstraction and electronic health record (EHR)–generated reports are valid methods to determine performance scores for common cardiovascular care. Results revealed that medical record abstraction resulted in higher performance scores compared with EHR–generated reports. In some cases, misclassification-adjusted performance scores were more similar to EHR–generated performance scores. The findings suggest that meeting a performance target may depend on the method used to estimate performance, which has implications for quality improvement efforts and value-based payment models.
Homco J, Carabin H, Nagykaldi Z, et al. Validity of medical record abstraction and electronic health record–generated reports to assess performance on cardiovascular quality measures in primary care. JAMA Netw Open 2020; 3(7). http://doi.org/10.1001/jamanetworkopen.2020.9411
AHRQ’s EvidenceNOW: Setting the Target for Improving Heart Health in America
An infographic summarizing participating primary care practices’ performance delivering heart health services to their patients at baseline (as of January 2017).
Agency for Healthcare Research and Quality. (February 2017). Available at: http://www.ahrq.gov/evidencenow/evaluation/before-evidencenow.html.
Implementation of Systematic Community Resource Referrals at Small Primary Care Practices to Promote Cardiovascular Disease Self-Management
The Midwest Cooperative describes the implementation of a community resource referral system in small clinical practices to reduce cardiovascular disease (CVD) risk. Practices completed an inventory of local CVD-related resources, which was then used to create a list of printed resources for patients. Half of the participating practices completed the inventory. The cooperative found that it was feasible to create practice-specific resources, but digital distribution was not feasible due to inconsistent use of electronic health record (EHR) systems, workflow variation, and lacking data-sharing infrastructure. The researchers concluded that successful implementation of quality improvement strategies to systematize community resource referral solutions is feasible at small practices, but more research is needed to understand what motivates small practices to participate in implementation of these solutions.
Makelarski JA, DePumpo M, Boyd K, et al. Implementation of systematic community resource referrals at small primary care practices to promote cardiovascular disease self-management. J Healthc Qual, 2019 Nov 20. https://www.ncbi.nlm.nih.gov/31764248
Accounting for Blood Pressure Seasonality Alters Evaluation of Practice-Level Blood Pressure Control Intervention
The New York City Cooperative examined methods to address seasonal variation in blood pressure. In this randomized stepped-wedge design, interventions consisted of 13 visits from practice facilitators trained in improving blood pressure control. To determine the interventions’ effects, two models were used—one that did not account for seasonality and one that did. The researchers found that accounting for seasonality did affect outcomes related to blood pressure control. The cooperative concluded that studies evaluating blood pressure control should compare outcome measures across similar seasons, and the length of the measurement period should account for seasonal effects.
Gepts T, Nguyen AM, Cleland C, Wu W, Pham-Singer H, Shelley D. Accounting for blood pressure seasonality alters evaluation of practice-level blood pressure control intervention. Am J Hypertens 2020 March 13;33(3):220‐222. https://www.ncbi.nlm.nih.gov/31711219
A Qualitative Analysis of Implementing EvidenceNOW to Improve Cardiovascular Care
Using in-depth interviews, the Virginia Cooperative found that strengths of EvidenceNOW implementation in the region included diverse team member skills and areas of expertise, a well-received kick-off event, and a comprehensive set of practice improvement resources. Implementation challenges included recruiting primary care practices, varying types and capabilities of electronic health records, and working with practices at different transformation stages. The authors concluded that future large-scale primary care practice improvement efforts may benefit from a narrower focus on either clinical intervention or practice transformation and/or required organizational structures and processes before clinical intervention efforts start.
Goldberg DG, Haghighat S, Kavalloor S, et al. A qualitative analysis of implementing EvidenceNOW to improve cardiovascular care. JABFM 2019 September; 32 (5) 705-714. https://www.jabfm.org/content/32/5/705
Barriers and Facilitators in the Recruitment and Retention of More Than 250 Small Independent Primary Care Practices for EvidenceNOW
The New York City Cooperative used a stepped-wedge randomized controlled trial to look at factors that facilitate recruitment of small independent primary care practices and influence retention. Researchers analyzed qualitative data from recruiters’ field notes, diary entries, and provider interviews to identify barriers and facilitators encountered in recruiting and retaining 257 practices in New York City. They found that three main factors facilitated rapid recruitment: (1) a prior well-established relationship with the local health department, (2) alignment of project goals with practice priorities, and (3) providing appropriate monetary incentives. They also found that retention was facilitated in similar ways using a multifaceted communication strategy.
Cuthel A, Rogers E, Daniel F, et al. Barriers and facilitators in the recruitment and retention of more than 250 small independent primary care practices for EvidenceNOW. Am J Med Qual, 2019 Dec 22. https://www.ncbi.nlm.nih.gov/31865749
Design of Healthy Hearts in the Heartland (H3): A Practice-Randomized, Comparative Effectiveness Study
The Midwest Cooperative randomized 112 and 114 practices to Point of Care ( POC) and POC + Population Management (POC + PM), respectively, to test the feasibility of implementing these two quality improvement strategies to improve ABCS (aspirin use for eligible patients, blood pressure control, cholesterol management, and smoking cessation) at practices in Illinois, Indiana, and Wisconsin. Randomization ensured baseline comparability for all nine key variables, including the ABCS measures indicating proportion of patients at the practice level meeting each quality measure. Surrogate estimates for the true ABCS at baseline, coupled with the unique randomization logic, achieved adequate baseline balance on these outcomes. Similar practice- or cluster-randomized trials may consider adaptations of this design. Final analyses on 12- and 18-month ABCS outcomes for the H3 study are forthcoming.
Ciolino JD, Jackson KL, Liss DT, et al. (2018). Design of healthy hearts in the heartland (H3): a practice-randomized comparative effectiveness study. Contemp Clin Trials. 2018 Aug;71:47-54. Doi: 10.101/j.cct.2018.06.004. Epub 2018 Jun 2. PMID:29870868.
From Concepts and Codes to Healthcare Quality Measurement: Understanding Variations in Value Set Vocabularies for a Statin Therapy Clinical Quality Measure
In the Northwest Cooperative’s development of a statin therapy clinical quality measure (CQM), independent measure developers created two unique value sets for the same global concepts. They first identified differences between the two value set specifications of the same CQM. They then implemented the various versions in a quality measure calculation registry to understand how the differences affected calculated prevalence of risk and measure performance. Global performance rates only differed by 0.8%, but there were up to 2.3 times as many patients included with key conditions, and differing performance rates of 7.5% for patients with ‘myocardial infarction’ and 3.5% for those with ‘ischemic vascular disease’. They concluded that the decisions CQM developers make about which concepts and code groups to include or exclude in value set vocabularies can lead to inaccuracies in the measurement of quality of care. One solution is that developers could provide rationale for these decisions.
Cholan RA, Rhoton D, Sacheva B, et al. From concepts and codes to healthcare quality measurement: Understanding variations in value set vocabularies for a statin therapy clinical quality Measure. eGEMS (Washington DC). 2017;5(1):19. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983064/
Understanding the Impact of Variations in Measurement Period Reporting for Electronic Clinical Quality Measures.
Electronic Clinical Quality Measures (eCQMs) have increased in importance in value-based programs, but accurate and timely measurement has been slow. Northwest cooperative researchers asked 209 practices to extract and submit four eCQMs from their electronic health records on a quarterly basis using a 12-month measurement period. The measurement periods of the survey data were categorized into non-standard (3, 6, 9 months and other) and standard periods (12 months). For comparison, patient-level data from three clinics were collected and calculated in an eCQM registry to measure the impact of varying measurement periods. Differences between measures with standard versus non-standard periods ranged from –3.3 percent to 14.2 percent between clinics. Variations in measurement periods were associated with variation in performance between clinics for 3 of the 4 eCQMs, but did not have significant differences when calculated within clinics. The researchers conclude that variations from standard measurement periods may reflect poor data quality and accuracy.
Colin NV, Cholan RA, Sachdeva B, et al. Understanding the impact of variations in measurement period reporting for electronic clinical quality measures. eGMS (Washington DC) 2018;6(1):17. Epub 2018/08/11. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6078150/
Primary Care Practices’ Ability to Report Electronic Clinical Quality Measures in the EvidenceNOW Southwest Initiative to Improve Heart Health
EvidenceNOW Southwest researchers determined how quickly primary care practices can report electronic clinical quality measures (eCQMs) and the practice characteristics associated with faster reporting. A total of 211 primary care practices in Colorado and New Mexico participated. Practices were instructed on eCQM specifications that could be produced by an electronic health record, a registry, or a third-party platform. Practices received 9 months of support from a practice facilitator, a clinical health information technology advisor, and the research team. Practices were instructed to report their baseline ABCS (aspirin for eligible patients, blood pressure control, cholesterol management, and smoking cessation) CQMs as soon as possible. Time to report eCQMs varied by measure and practice type, with very few practices reporting quickly. The median time to report any baseline electronic clinical quality measure was 8.2 months. Practices took longer to report a new cholesterol measure than other measures. The researchers conclude that programs that require eCQM reporting should consider the time and effort practices must exert to produce reports, and that practices may benefit from additional support to succeed in new programs that require eCQM reporting.
Knierim KE, Hall TL, Dickinson LM, et al. Primary care practices’ ability to report electronic clinical quality measures in the EvidenceNOW Southwest initiative to improve heart health. JAMA Network Open. In press. PMID:31390033; DOI:10.1001/jamanetworkopen.2019.856
Specifying and Comparing Implementation Strategies across Seven Large Implementation Interventions: A Practical Application of Theory
ESCALATES, the EvidenceNOW national evaluation team, used empirical data to test how the Expert Recommendations for Implementing Change (ERIC) taxonomy applies to the EvidenceNOW dissemination and implementation initiative aimed at taking cardiac prevention to scale in primary care practice. The researchers used ERIC to identify the implementation strategies of the seven cooperatives involved in the initiative, and specified the actor, action, target, dose, temporality, justification, and expected outcome for each. They then grouped implementation strategies by outcomes and justifications. Thirty-three ERIC strategies were used by cooperatives. The researchers identified a range of revisions to the ERIC taxonomy to improve the practical application of these strategies. They also organized ERIC implementation strategies into four functional groupings based on the way they observed how they were applied in practice. The findings suggest revisions to the ERIC implementation strategies to reflect their use in real-work dissemination and implementation efforts. The researchers conclude that the functional groupings of the ERIC implementation strategies that emerged from on-the-ground implementers will help guide others in choosing among and linking multiple implementation strategies when planning small- and large-scale implementation efforts.
Perry CK, Damschroder LJ, Hemler JR, et al. Specifying and comparing implementation strategies across seven large implementation interventions: a practical application of theory. Implementation Science 2019; 14(32). Open access: https://implementationscience.biomedcentral.com/articles/10.1186/s13012-019-0876-4
A Population Approach Using Cholesterol Imputation to Identify Adults with High Cardiovascular Risk: A Report from AHRQ’s EvidenceNow Initiative
Using two different methods for estimating patients’ risk for cardiovascular disease, when cholesterol data are missing, can quickly and accurately identify high-risk patients, according to this study by AHRQ EvidenceNOW researchers in North Carolina. Using these methods could help clinicians avoid delays in implementing strategies to help reduce the cardiovascular risk for these patients.
Cykert S, DeWalt, DA, Weiner BJ, Pignone M, Fine J, and Kim, JI (2018). A population approach using cholesterol imputation to identify adults with high cardiovascular risk: A report from AHRQ’s EvidenceNow initiative.
Journal of the American Medical Informatics Association, November 29, 2018. https://doi.org/10.1093/jamia/ocy151
A Community Engagement Method to Design Patient Engagement Materials for Cardiovascular Health
The Southwest Cooperative describes research design challenges and findings from the use of a community-based intervention called Boot Camp Translation. This intervention focuses on translating evidence-based heart disease prevention strategies into messaging and materials that are relevant and understandable for community members. Findings indicate that this technique yielded messages and materials tailored to different communities, suggesting that heart disease prevention programs are not one-size-fits-all.
English A, Dickinson L, Zittleman L, et al. (2018). A community engagement method to design patient engagement materials for cardiovascular health. Ann Fam Med 2018;16(Suppl 1):S58-S64. http://www.annfammed.org/content/16/Suppl_1/S58.
Engaging Primary Care Practices in Studies of Improvement: Budgeting for Practice Recruitment
In this article, the Northwest and Midwest Cooperatives describe the approach, cost, and resources needed to recruit and enroll 500 primary care practices for EvidenceNOW. The recruitment effort required a total of 22,430 hours and $2.675 million, or $5,529 per enrolled practice. Prior relationships with practices or “warm hand-offs” predicted recruitment success.
Fagnan LJ, Walunas T, Parchman ML, et al. (2018). Engaging primary care practices in studies of improvement: budgeting for practice recruitment. Ann Fam Med 2018;16(Suppl 1):S72-S79. http://www.annfammed.org/content/16/Suppl_1/S72.
Recruiting Practices for Change Initiatives Is Hard: Findings from EvidenceNOW
A cross-cooperative analysis conducted by the EvidenceNOW National Evaluation Team of strategies used to recruit primary care practices into EvidenceNOW. The analysis explores important elements of primary care practice today that highlight the need for ever-changing recruitment methods.
Sweeney, S et al. (September 2017). American Journal of Medical Quality. Available at: http://journals.sagepub.com/eprint/sktm6QrtsVRTST5dgKgM/full#articleCitationDownloadContainer.
Study Protocol for “Healthy Hearts Northwest”: a 2x2 Randomized Factorial Trial to Build Quality Improvement Capacity in Primary Care
A description of the EvidenceNOW Northwest Cooperative’s study protocol. The study targeted the enrollment of 250 smaller primary care practices across Washington, Oregon, and Idaho to assess four combinations of practice support—practice facilitation alone, practice facilitation with educational outreach, practice facilitation with shared learning opportunities, or practice facilitation with both—and their effectiveness in building quality improvement capacity in primary care.
Parchman, ML et al. (October 2016). Implementation Science 1(1):138. Available at: http://implementationscience.biomedcentral.com/articles/10.1186/s13012-016-0502-7.
Testing the Use of Practice Facilitation in a Cluster Randomized Stepped Wedge Design Trial to Improve Adherence to Cardiovascular Disease Prevention Guidelines: HealthyHearts NYC
A description of the EvidenceNOW New York City Cooperative’s study protocol. The study tested the use of a stepped-wedge cluster randomized control trial in evaluating the impact of practice facilitation versus usual care on the outcome of ABCS measures in 250 small- to medium-sized primary care practices in New York City.
Shelley, DR et al. (July 2016). Published in Implementation Science 11(1):88. Available at: http://implementationscience.biomedcentral.com/articles/10.1186/s13012-016-0450-2.
A National Evaluation of a Dissemination and Implementation Initiative to Enhance Primary Care Practice Capacity and Improve Cardiovascular Disease Care: the ESCALATES Study Protocol
An overview of the EvidenceNOW national evaluation research design. The observational study is examining quantitative and qualitative data across the seven EvidenceNOW cooperatives. Data collected will include information from online implementation diaries, interviews with practice staff, organizational characteristics, and performance on clinical quality measures (ABCS).
Cohen, DJ et al. (June 2016). Implementation Science 11(1): 86. Available at: https://implementationscience.biomedcentral.com/articles/10.1186/s13012-016-0449-8.
Advancing Heart Health in North Carolina Primary Care: the Heart Health NOW Study Protocol
A description of the EvidenceNOW North Carolina Cooperative’s study protocol. The study used a stepped wedge, stratified, cluster randomized trial to determine the effect of a comprehensive, evidence-based practice support strategy—including practice facilitation, expert consultation, technology support, and regional learning collaboratives—on the implementation of evidence-based heart disease prevention among patients in 300 primary care practices.
Weiner, BJ et al. (November 2015). Implementation Science 10:160. Available at: http://implementationscience.biomedcentral.com/articles/10.1186/s13012-015-0348-4.
Diffusion of Community Health Workers Within Medicaid Managed Care: A Strategy to Address Social Determinants of Health
Addressing social determinants of health (SDH) in clinical settings under the current incentive system is a challenge, note the authors of this blog. While primary care providers recognize that social needs are as important as medical needs, they feel ill-equipped to address them. The authors note the benefit of an expanded role for community health workers (CHWs). They cite New Mexico as a successful model. The diffusion of clinically integrated CHWs throughout New Mexico’s Medicaid system was sustained by incorporating the cost into the capitated payment to the managed care organizations (MCOs). Moreover, hiring and incorporating CHWs into clinical care became a required component within the contracts of state Medicaid with MCOs. Acknowledging the success of the CHW model, in 2017, New Mexico Medicaid required all MCOs to increase their CHW contacts with clients by 20 percent. Because three of the four MCOs are national, the CHW model begun in New Mexico has been deployed in 12 States. The authors conclude that screening for social determinants at the beginning of every visit uncovers important needs otherwise missed. Immediate referral to a CHW, skilled in assisting the patient in addressing such uncovered needs, expands a primary care clinic’s ability to care for patients.
Nkouaga C, Kaufman A, Alfero C, et al. Diffusion of community health workers within Medicaid managed care: A strategy to address social determinants of health. Health Affairs Blog. July 2017. DOI: 10.10377/hblog20170725.061194
Health Extension and Clinical and Translational Science: An Innovative Strategy for Community Engagement
This paper describes how Health Extension Regional Officers (HEROs) through the University of New Mexico Health Sciences Center (UNMHSC) help to facilitate university-community engagement throughout New Mexico. HEROs, based in communities across the state, link priority community health needs with university resources in education, service, and research. The UNM Clinical and Translational Science Center (CTSC) provides partial funding for HEROs to bridge the divide between research priorities of UNMHSC and health priorities of the State's communities. The establishment of a bidirectional partnership between HEROs and CTSC researchers led to: enhanced community-engaged studies through the CTSC, the HERO model itself as a subject of research, a HERO-driven boost in local capacity in scholarship and grant writing, and development of training modules for investigators and community stakeholders on community-engaged research. The upshot of these efforts were 5 grants submitted, 4 of which were funded, totaling $7,409,002.00, and 3 research articles that were published.
Kaufman A, Rhyne RL, Anastasoff J, et al. Health extension and clinical and translational science: An innovative strategy for community engagement. Journal of the American Board of Family Medicine; January-February 2017; 30(1):94-99. DOI:10.3122/jabfm.2017.01.160119
Primary Care Practices’ Implementation of Patient-Team Partnerships: Findings from EvidenceNOW Southwest
EvidenceNOW Southwest provided 9 months of practice facilitation and information technology support to 211 Colorado and New Mexico primary care practices. The researchers analyzed surveys from participating practices on patient-team partnership activities of self-management support, patient social needs assessment, community resource linkages, and patient input to examine relationships between practice characteristics and patient-team partnership. They found that practices that used patient registries, were in a medically underserved area, had a multispecialty staff mix, and were using clinical cardiovascular disease management guidelines were significantly associated with greater patient-team partnerships. However, practices reported only partial implementation of patient-team partnership strategies, and could improve their assessment of patients’ social needs, incorporating patient expectations, and linking patients to community resources.
Hall TL, Knierim KE, Nease Jr. D, et al. Primary care practices’ implementation of patient-team partnerships: Findings from EvidenceNOW Southwest. JABFM July 2019; 32(4): 490-504. Available at: https://www.jabfm.org/content/32/4/490.full
The Role of Health Extension in Practice Transformation and Community Health Improvement: Lessons from 5 Case Studies
The Northwest, Southwest, and Oklahoma Cooperatives examined the effects of incorporating technical assistance for practices and their communities to address social determinants of health in five States: New Mexico, Oklahoma, Oregon, Colorado, and Washington. They interviewed the leaders of health extension initiatives in these States to describe case studies that stretched the boundaries of the primary care extension model. The findings reveal the importance of building sustained relationships with practices and community coalitions, documenting success in broad terms as well as achieving diverse outcomes of meaning to different stakeholders, understanding that health extension is a function that can be carried out by an individual or group depending on resources, and the importance of being prepared for political struggles over “turf” and “ownership” of extension. All authors saw the need for long-term sustained funding beyond grants for sustainability of quality improvement.
Kaufman A, Dickinson WP, Fagnan LJ, et al. The role of health extension in practice transformation and community health improvement: Lessons from 5 case studies. Ann Fam Med 2019; 17 (Suppl 1):S67-S72. http://www.annfammed.org/content/17/Suppl_1/S67.full
Virtual Educational Outreach Intervention in Primary Care Based on the Principles of Academic Detailing
This article describes the development by Healthy Hearts Northwest of a tailored virtual educational outreach program using principles of traditional academic detailing (AD). The program was adapted and deployed with small- and medium-sized rural and urban primary care practices across three States. The aim of the program was to increase practices' use of cardiovascular disease risk calculation and prescription of statins for primary prevention, when appropriate. The adapted virtual program has general application to the implementation of educational outreach interventions into geographically dispersed practices and can help overcome the limitations posed by more traditional resource-intensive AD programs.
Baldwin L-M, Fischer MA, Powell J, et al. (2018). Virtual educational outreach intervention in primary care based on the principles of academic detailing. JCEHP 2018; a38(4):269-275. Available at: https://www.ncbi.nlm.nih.gov/pubmed/30346338.
Data-Driven Diffusion of Innovations: Successes and Challenges in 3 Large-Scale Innovative Delivery Models
A paper by the Northwest Cooperative exploring barriers and solutions for diffusing data-driven innovations in primary care. The authors found that many health care organizations are using technologies necessary for health care innovation, such as electronic health records. However, for a variety of reasons, organizations encounter challenges with using data from those sources to drive innovations in care. Proposed solutions to these challenges include facilitating peer-to-peer technical assistance, providing data feedback reports to clinicians, and working with practice facilitators who are skilled in using data technology for quality improvement.
Dorr, D, Cohen, DJ, and Adler-Milstein, J. (2018). Health Affairs 37(2):257–265. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5810405/.
Taking Innovation to Scale in Primary Care Practices: The Functions of Healthcare Extensions
The EvidenceNOW National Evaluation team describes how EvidenceNOW cooperatives varied in their approaches to health care extension—a way of providing external support to primary care practices with the goal of spreading innovations. This paper provides early evidence that health care extension is a feasible and potentially useful approach for providing coordinated quality improvement support to primary care practices.
Ono, S et al. (2018). Health Affairs 37(2):222-230. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5805471/.
Lessons in Advancing Evidence-Based Primary Care from the Heart of Virginia Healthcare EvidenceNOW Cooperative
This brief from the Virginia Cooperative shares challenges and successful strategies for implementing primary care quality improvement interventions, with lessons learned from EvidenceNOW. Major challenges included recruiting busy practices and extracting data on heart health measures. Successful strategies included leveraging and strengthening key relationships, as well as aligning quality improvement initiatives with other ongoing priorities for a practice.
Reck, J and Bacon, O. (2018). Published by the National Academy for State Health Policy. Available at: https://nashp.org/wp-content/uploads/2018/01/VCU-Brief-No-2.pdf.
Primary Care Provider Burnout: Implications for States & Strategies for Mitigation
A paper on the experiences of primary care practices participating in the EvidenceNOW Virginia Cooperative, which point to a number of practice challenges contributing to burnout including scope of practice, payment reform, reporting requirements, and electronic health records. This brief outlines a range of strategies and policy options that States have for mitigating burnout.
Reck, J. (2017). Published by the National Academy for State Health Policy. Available at: http://nashp.org/primary-care-provider-burnout-implications-for-states-strategies-for-mitigation.