Integrating a focus on health equity in implementation science: Case examples from the national cancer institute's implementation science in cancer control centers (ISC3) network.

Background: A Health Equity Task Force (HETF) of members from seven Centers funded by the National Cancer Institute's (NCI) Implementation Science in Cancer Control Centers (ISC3) network sought to identify case examples of how Centers were applying a focus on health equity in implementation science to inform future research and capacity-building efforts. Methods: HETF members at each ISC3 collected information on how health equity was conceptualized, operationalized, and addressed in initial research and capacity-building efforts across the seven ISC3 Centers funded in 2019-2020. Each Center completed a questionnaire assessing five health equity domains central to implementation science (e.g., community engagement; implementation science theories, models, and frameworks (TMFs); and engaging underrepresented scholars). Data generated illustrative examples from these five domains. Results: Centers reported a range of approaches focusing on health equity in implementation research and capacity-building efforts, including (1) engaging diverse community partners/settings in making decisions about research priorities and projects; (2) applying health equity within a single TMF applied across projects or various TMFs used in specific projects; (3) evaluating health equity in operationalizing and measuring health and implementation outcomes; (4) building capacity for health equity-focused implementation science among trainees, early career scholars, and partnering organizations; and (5) leveraging varying levels of institutional resources and efforts to engage, include, and support underrepresented scholars. Conclusions: Examples of approaches to integrating health equity across the ISC3 network can inform other investigators and centers' efforts to build capacity and infrastructure to support growth and expansion of health equity-focused implementation science.

A Practice-Based Research Network (PBRN) Roadmap for Evaluating COVID-19 in Community Health Centers: A Report From the OCHIN PBRN.

BACKGROUND: Primary care practice-based research networks (PBRNs) are critical laboratories for generating evidence from real-world settings, including studying natural experiments. Primary care's response to the novel coronavirus-19 (COVID-19) pandemic is arguably the most impactful natural experiment in our lifetime. EVALUATING THE IMPACT OF COVID-19: We briefly describe the OCHIN PBRN of community health centers (CHCs), its partnership with implementation scientists, and how we are leveraging this infrastructure and expertise to create a rapid research response evaluating how CHCs across the country responded to the COVID-19 pandemic. COVID-19 RESEARCH ROADMAP: Our research agenda focuses on asking: How has care delivery in CHCs changed due to COVID-19? What impact has COVID-19 had on the delivery of preventive services in CHCs? Which PBRN services (e.g., data surveillance, training, evidence synthesis) are most impactful to real-world practices? What decision-making strategies were used in the PBRN and its practices to make real-time changes in response to the pandemic? What critical factors in successfully and sustainably transforming primary care are illuminated by pandemic-driven changes? DISCUSSION AND CONCLUSIONS: PBRNs enable real-world evaluation of practice change and natural experiments, and thus are ideal laboratories for implementation science research. We present a real-time example of how a PBRN Implementation Laboratory activated a response to study a historic natural experiment, to help other PBRNs charting a course through this pandemic.

The Affordable Care Act improved health insurance coverage and cardiovascular-related screening rates for cancer survivors seen in community health centers.

BACKGROUND: This study assessed the impact of Affordable Care Act (ACA) Medicaid expansion on health insurance rates and receipt of cardiovascular-related preventive screenings (body mass index, glycated hemoglobin [HbA1c], low-density lipoproteins, and blood pressure) for cancer survivors seen in community health centers (CHCs). METHODS: This study identified cancer survivors aged 19 to 64 years with at least 3 CHC visits in 13 states from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE). Via inverse probability of treatment weighting multilevel multinomial modeling, insurance rates before and after the ACA were estimated by whether a patient lived in a state that expanded Medicaid, and changes between a pre-ACA time period and 2 post-ACA time periods were assessed. RESULTS: The weighted estimated sample size included 409 cancer survivors in nonexpansion states and 2650 in expansion states. In expansion states, the proportion of uninsured cancer survivors decreased significantly from 20.3% in 2012-2013 to 4.5%in 2016-2017, and the proportion of those with Medicaid coverage increased significantly from 38.8% to 55.6%. In nonexpansion states, there was a small decrease in uninsurance rates (from 33.6% in 2012-2013 to 22.5% in 2016-2017). Cardiovascular-related preventive screening rates increased over time in both expansion and nonexpansion states: HbA1c rates nearly doubled from the pre-ACA period (2012-2013) to the post-ACA period (2016-2017) in expansion states (from 7.2% to 12.8%) and nonexpansion states (from 9.3% to 16.8%). CONCLUSIONS: This study found a substantial decline in uninsured visits among cancer survivors in Medicaid expansion states. Yet, 1 in 5 cancer survivors living in a state that did not expand Medicaid remained uninsured. Several ACA provisions likely worked together to increase cardiovascular-related preventive screening rates for cancer survivors seen in CHCs.

Measuring Preventive Care Delivery: Comparing Rates Across Three Data Sources.

INTRODUCTION: Preventive care delivery is an important quality outcome, and electronic data reports are being used increasingly to track these services. It is highly informative when electronic data sources are compared to information manually extracted from medical charts to assess validity and completeness. METHODS: This cross-sectional study used a random sample of Medicaid-insured patients seen at 43 community health centers in 2011 to calculate standard measures of correspondence between manual chart review and two automated sources (electronic health records [EHRs] and Medicaid claims), comparing documentation of orders for and receipt of ten preventive services (n=150 patients/service). Data were analyzed in 2015. RESULTS: Using manual chart review as the gold standard, automated EHR extraction showed near-perfect to perfect agreement (κ=0.96-1.0) for services received within the primary care setting (e.g., BMI, blood pressure). Receipt of breast and colorectal cancer screenings, services commonly referred out, showed moderate (κ=0.42) to substantial (κ=0.62) agreement, respectively. Automated EHR extraction showed near-perfect agreement (κ=0.83-0.97) for documentation of ordered services. Medicaid claims showed near-perfect agreement (κ=0.87) for hyperlipidemia and diabetes screening, and substantial agreement (κ=0.67-0.80) for receipt of breast, cervical, and colorectal cancer screenings, and influenza vaccination. Claims showed moderate agreement (κ=0.59) for chlamydia screening receipt. Medicaid claims did not capture ordered or unbilled services. CONCLUSIONS: Findings suggest that automated EHR and claims data provide valid sources for measuring receipt of most preventive services; however, ordered and unbilled services were primarily captured via EHR data and completed referrals were more often documented in claims data.