Participatory logic modeling in a multi-site initiative to advance implementation science.

BACKGROUND: Logic models map the short-term and long-term outcomes that are expected to occur with a program, and thus are an essential tool for evaluation. Funding agencies, especially in the United States (US), have encouraged the use of logic models among their grantees. They also use logic models to clarify expectations for their own funding initiatives. It is increasingly recognized that logic models should be developed through a participatory approach which allows input from those who carry out the program being evaluated. While there are many positive examples of participatory logic modeling, funders have generally not engaged grantees in developing the logic model associated with their own initiatives. This article describes an instance where a US funder of a multi-site initiative fully engaged the funded organizations in developing the initiative logic model. The focus of the case study is Implementation Science Centers in Cancer Control (ISC3), a multi-year initiative funded by the National Cancer Institute. METHODS: The reflective case study was collectively constructed by representatives of the seven centers funded under ISC3. Members of the Cross-Center Evaluation (CCE) Work Group jointly articulated the process through which the logic model was developed and refined. Individual Work Group members contributed descriptions of how their respective centers reviewed and used the logic model. Cross-cutting themes and lessons emerged through CCE Work Group meetings and the writing process. RESULTS: The initial logic model for ISC3 changed in significant ways as a result of the input of the funded groups. Authentic participation in the development of the logic model led to strong buy-in among the centers, as evidenced by their utilization. The centers shifted both their evaluation design and their programmatic strategy to better accommodate the expectations reflected in the initiative logic model. CONCLUSIONS: The ISC3 case study demonstrates how participatory logic modeling can be mutually beneficial to funders, grantees and evaluators of multi-site initiatives. Funded groups have important insights about what is feasible and what will be required to achieve the initiative's stated objectives. They can also help identify the contextual factors that either inhibit or facilitate success, which can then be incorporated into both the logic model and the evaluation design. In addition, when grantees co-develop the logic model, they have a better understanding and appreciation of the funder's expectations and thus are better positioned to meet those expectations.

Diabetes and Hypertension Prevention and Control in Community Health Centers: Impact of the Affordable Care Act.

Access to care significantly improved following the implementation of the Patient Protection and Affordable Care Act. Since its implementation, the number of uninsured Americans has significantly decreased. Medicaid expansion played an important role in community health centers, who serve historically marginalized populations, leading to increased clinic revenue, and improved access to care. As the continuous Medicaid enrollment provision established during the pandemic ended, and states have to make decisions about their program eligibility, exploring the impact of Medicaid expansion on the detection, and management of hypertension and diabetes could inform these decisions. We summarized the effect of Medicaid expansion on community health centers and their patients specific to hypertension and diabetes from existing literature. These studies suggest the beneficial impact of the Affordable Care Act and acquiring insurance on diabetes and hypertension disease detection, treatment, and control for patients receiving care in community health centers. Overall, these studies suggest the clear importance of health insurance coverage, and notably insurance stability, on diabetes and hypertension control.

The Impact of the Affordable Care Act Medicaid Expansion on Acute Diabetes Complications Among Community Health Center Patients.

OBJECTIVE: This study evaluates whether patients residing in expansion states have a greater increase in outpatient diagnoses of acute diabetes complications than those living in non-expansion states following the implementation of the Affordable Care Act (ACA). METHODS: This retrospective cohort study uses electronic health records (EHR) from 10,665 non-pregnant patients, aged 19 to 64 years old who were diagnosed with diabetes in 2012 or 2013 from 347 community health centers (CHCs) across 16 states (11 expansion and 5 non-expansion states). Patients included had ≥1 outpatient ambulatory visit in each of these periods: pre-ACA: 2012 to 2013, post-ACA: 2014 to 2016, and post-ACA: 2017 to 2019. Acute diabetes-related complications were identified using International Classification Diseases (ICD-9-CM and ICD-10-CM) codes classification and could occur on or after diagnosis of diabetes. We performed difference-in-differences (DID) analysis using a generalized estimating equation to compare the change in rates of acute diabetes complications by year and by Medicaid expansion status. RESULTS: There was a greater increase after year 2015 in visits related to abnormal blood glucose among patient living in Medicaid expansion states than in non-expansion states (2017 DID = 0.041, 95% CI = 0.027-0.056). Although both visits due to any acute diabetes complications and infection-related diabetes complications were higher among patients living in Medicaid expansion states, there was no difference in the trend overtime between expansion and non-expansion states. CONCLUSION: We found a significantly greater rate of visits for abnormal blood glucose in patients receiving care in expansion states relative to patients in CHCs in non-expansion states starting in 2015. Additional resources for these clinics, such as the ability to provide blood glucose monitoring devices or mailed/delivered medications, could substantially benefit patients with diabetes.

Precision Ecologic Medicine: Tailoring Care to Mitigate Impacts of Climate Change.

As recent extreme weather events demonstrate, climate change presents unprecedented and increasing health risks, disproportionately so for disadvantaged communities in the U.S. already experiencing health disparities. As patients in these frontline communities live through extreme weather events, socioeconomic and health stressors are compounded; thus, their healthcare teams will need tools to provide precision ecologic medicine approaches to their care. Many primary care teams are taking actionable steps to bring community-level socioeconomic data ("community vital signs") into electronic medical records, to facilitate tailoring care based on a given patient's circumstances. This work can be extended to include environmental risk data, thus equipping healthcare teams with an awareness of clinical and community vital signs and making them better positioned to mitigate climate impacts on health. For example, if healthcare teams can easily identify patients who have multiple chronic conditions and live in an urban heat island, they can proactively arrange to "prescribe" an air conditioner, heat pump, and/or air purifier. Or, when a severe storm/heat event/poor air quality event is predicted, they can take preemptive steps to get help to patients at high medical and socioeconomic risk, rather than waiting for them to arrive in the emergency department. Advances in health information technologies now make it technically feasible to integrate a wealth of publicly-available community-level data into EMRs. Efforts to bring this contextual data into clinical settings must be accelerated to equip healthcare teams to provide precision ecologic medicine interventions to their patients.

An observational study of health insured visits for children following Medicaid eligibility expansion for adults among a linked cohort of parents and children.

Despite its focus on adults, the Affordable Care Act (ACA) Medicaid expansion led to increased health insurance enrollment for children in the United States. Previous studies looked at parent and child insurance changes separately, or used a single survey response item to understand changes in health insurance for parents and children. It is, however, important to understand the connection between parent and child insurance changes together (not individually) using data sources that account for insurance over time. Therefore, to understand the association of parental health insurance on their children's coverage, leveraging a cohort of linked families seen in community health centers (CHCs), we used electronic health records to link a cohort of parents and children with ≥1 visit to a CHC in a Medicaid expansion state pre- (1/1/2012-12/31/2013) and ≥1 visit post-ACA (1/1/2014-12/31/2018) and determined primary payer type for all visits. This observational, cohort study assessed the rate of insured visits for children pre- to post-ACA across four parental insurance groups (always insured, gained Medicaid, discontinuously insured, never insured) using Poisson mixed effects models. We included 335 CHCs across 7 United States. Insurance rates were highest (~95 insured visits/100 visits) for children of parents who were always insured; rates were lowest for children of parents who were never insured (~83 insured visits/100 visits). Children with a parent who gained Medicaid had 4.4% more insured visits post- compared to pre-ACA (adjusted relative rates  = 1.044, 95% confidence interval: 1.014, 1.074). When comparing changes from pre- to post-ACA between parent insurance groups, children's insured visit rates were significantly higher for children of parents who gained Medicaid (reference) compared to children of parents who were always insured (adjusted ratio of rate ratio: 0.963, confidence interval: 0.935-0.992). Despite differences in Medicaid eligibility for children and adults, health insurance patterns were similar for linked families seen in CHCs. Findings suggest consideration should be paid to parent health insurance options when trying to increase children's coverage.

Diabetes And The Fragmented State Of US Health Care And Policy.

Progress in the prevention and treatment of type 2 diabetes-the dominant form of diabetes-appears to have stalled in the US over the past decade, and diabetes-related morbidity has increased nationally. The most geographically and socioeconomically disadvantaged segments of the population have been especially hard hit, and interventions that reduce the risk for diabetes have not reached these populations. In this overview article we lay out how fragmentation in health policy and governance, payers and reimbursement design, and service delivery in the US has contributed to low accountability and coordination, and thus stagnation and persistent inequities. We also review the evidence regarding past, ongoing, and new reforms that may help address fragmentation, lower diabetes burdens, and narrow disparities.

Affordable Care Act Medicaid expansion and access to primary-care based smoking cessation assistance among cancer survivors: an observational cohort study.

BACKGROUND: Smoking among cancer survivors can increase the risk of cancer reoccurrence, reduce treatment effectiveness and decrease quality of life. Cancer survivors without health insurance have higher rates of smoking and decreased probability of quitting smoking than cancer survivors with health insurance. This study examines the associations of the Affordable Care Act (ACA) Medicaid insurance expansion with smoking cessation assistance and quitting smoking among cancer survivors seen in community health centers (CHCs). METHODS: Using electronic health record data from 337 primary care community health centers in 12 states that expanded Medicaid eligibility and 273 CHCs in 8 states that did not expand, we identified adult cancer survivors with a smoking status indicating current smoking within 6 months prior to ACA expansion in 2014 and ≥ 1 visit with smoking status assessed within 24-months post-expansion. Using an observational cohort propensity score weighted approach and logistic generalized estimating equation regression, we compared odds of quitting smoking, having a cessation medication ordered, and having ≥6 visits within the post-expansion period among cancer survivors in Medicaid expansion versus non-expansion states. RESULTS: Cancer survivors in expansion states had higher odds of having a smoking cessation medication order (adjusted odds ratio [aOR] = 2.54, 95%CI = 1.61-4.03) and higher odds of having ≥6 office visits than those in non-expansion states (aOR = 1.82, 95%CI = 1.22-2.73). Odds of quitting smoking did not differ significantly between patients in Medicaid expansion versus non-expansion states. CONCLUSIONS: The increased odds of having a smoking cessation medication order among cancer survivors seen in Medicaid expansion states compared with those seen in non-expansion states provides evidence of the importance of health insurance coverage in accessing evidence-based tobacco treatment within CHCs. Continued research is needed to understand why, despite increased odds of having a cessation medication prescribed, odds of quitting smoking were not significantly higher among cancer survivors in Medicaid expansion states compared to non-expansion states.

Effectiveness of an insurance enrollment support tool on insurance rates and cancer prevention in community health centers: a quasi-experimental study.

BACKGROUND: Following the ACA, millions of people gained Medicaid insurance. Most electronic health record (EHR) tools to date provide clinical-decision support and tracking of clinical biomarkers, we developed an EHR tool to support community health center (CHC) staff in assisting patients with health insurance enrollment documents and tracking insurance application steps. The objective of this study was to test the effectiveness of the health insurance support tool in (1) assisting uninsured patients gaining insurance coverage, (2) ensuring insurance continuity for patients with Medicaid insurance (preventing coverage gaps between visits); and (3) improving receipt of cancer preventive care. METHODS: In this quasi-experimental study, twenty-three clinics received the intervention (EHR-based insurance support tool) and were matched to 23 comparison clinics. CHCs were recruited from the OCHIN network. EHR data were linked to Medicaid enrollment data. The primary outcomes were rates of uninsured and Medicaid visits. The secondary outcomes were receipt of recommended breast, cervical, and colorectal cancer screenings. A comparative interrupted time-series using Poisson generalized estimated equation (GEE) modeling was performed to evaluate the effectiveness of the EHR-based tool on the primary and secondary outcomes. RESULTS: Immediately following implementation of the enrollment tool, the uninsured visit rate decreased by 21.0% (Adjusted Rate Ratio [RR] = 0.790, 95% CI = 0.621-1.005, p = .055) while Medicaid-insured visits increased by 4.5% (ARR = 1.045, 95% CI = 1.013-1.079) in the intervention group relative to comparison group. Cervical cancer preventive ratio increased 5.0% (ARR = 1.050, 95% CI = 1.009-1.093) immediately following implementation of the enrollment tool in the intervention group relative to comparison group. Among patients with a tool use, 81% were enrolled in Medicaid 12 months after tool use. For the 19% who were never enrolled in Medicaid following tool use, most were uninsured (44%) at the time of tool use. CONCLUSIONS: A health insurance support tool embedded within the EHR can effectively support clinic staff in assisting patients in maintaining their Medicaid coverage. Such tools may also have an indirect impact on evidence-based practice interventions, such as cancer screening. TRIAL REGISTRATION: This study was retrospectively registered on February 4th, 2015 with Clinicaltrials.gov (#NCT02355262). The registry record can be found at https://www.clinicaltrials.gov/ct2/show/NCT02355262 .

Shared Language for Shared Work in Population Health.

People working on behalf of population health, community health, or public health often experience confusion or ambiguity in the meaning of these and other common terms-the similarities and differences and how they bear on the tasks and division of labor for care delivery and public health. Shared language must be clear enough to help, not hinder people working together as they ultimately come to mutual understanding of roles, responsibilities, and actions in their joint work. Based on an iterative lexicon development process, the authors developed and propose a definitional framework as an aid to navigating among related population and community health terms. These terms are defined, similarities and differences clarified, and then organized into 3 categories that reflect goals, realities, and ways to get the job done. Goals include (a) health as well-being for persons, (b) population health as that goal expressed in measurable terms for groups, and (c) community health as population health for particular communities of interest, geography, or other defining characteristic-groups with shared identity and particular systemic influences on health. Realities are social determinants as influences, health disparities as effects, and health equity as both a goal and a design principle. Ways to get the job done include health care delivery systems for enrollees and public health in population-based civic activities-with a broad zone of collaboration where streams of effort converge in partnership with served communities. This map of terms can enable people to move forward together in a broad zone of collaboration for health with less confusion, ambiguity, and conflict.

Rates of Undiagnosed Hypertension and Diagnosed Hypertension Without Anti-hypertensive Medication Following the Affordable Care Act.

BACKGROUND: The Affordable Care Act (ACA) Medicaid expansion improved access to health insurance and health care services. This study assessed whether the rate of patients with undiagnosed hypertension and the rate of patients with hypertension without anti-hypertensive medication decreased post-ACA in community health center (CHC). METHODS: We analyzed electronic health record data from 2012 to 2017 for 126,699 CHC patients aged 19-64 years with ≥1 visit pre-ACA and ≥1 post-ACA in 14 Medicaid expansion states. We estimated the prevalence of patients with undiagnosed hypertension (high blood pressure reading without a diagnosis for ≥1 day) and the prevalence of patients with hypertension without anti-hypertensive medication by year and health insurance type (continuously uninsured, continuously insured, gained insurance, and discontinuously insured). We compared the time to diagnosis or to anti-hypertensive medication pre- vs. post-ACA. RESULTS: Overall, 37.3% of patients had undiagnosed hypertension and 27.0% of patients with diagnosed hypertension were without a prescribed anti-hypertensive medication for ≥1 day during the study period. The rate of undiagnosed hypertension decreased from 2012 through 2017. Those who gained insurance had the lowest rates of undiagnosed hypertension (2012: 14.8%; 2017: 6.1%). Patients with hypertension were also more likely to receive anti-hypertension medication during this period, especially uninsured patients who experienced the largest decline (from 47.0% to 8.1%). Post-ACA, among patients with undiagnosed hypertension, time to diagnosis was shorter for those who gained insurance than other insurance types. CONCLUSIONS: Those who gained health insurance were appropriately diagnosed with hypertension faster and more frequently post-ACA than those with other insurance types. CLINICAL TRIALS REGISTRATION: Trial Number NCT03545763.

New hypertension and diabetes diagnoses following the Affordable Care Act Medicaid expansion.

OBJECTIVE: To assess the Affordable Care Act (ACA) Medicaid expansion's impact on new hypertension and diabetes diagnoses in community health centres (CHCs). DESIGN: Rates of new hypertension and diabetes diagnoses were computed using generalised estimating equation Poisson models and we tested the difference-in-difference (DID) pre-ACA versus post-ACA in states that expanded Medicaid compared with those that did not. SETTING: We used electronic health record data (pre-ACA: 1 January 2012-31 December 2013-post-ACA: 1 January 2014-31 December 2016) from the Accelerating Data Value Across a National Community Health Center Network clinical data network. We included clinics with ≥50 patients contributing to person-time-at risk in each study year. PARTICIPANTS: Patients aged 19-64 with ≥1 ambulatory visit in the study period were included. We then excluded patients who were pregnant during the study period (N=127 530). For the hypertension outcome, we excluded individuals with a diagnosis of hypertension prior to the start of the study period, those who had a hypertension diagnosis on their first visit to a clinic or their first visit after 3 years without a visit, and those who had a diagnosis more than 3 years after their last visit (pre-ACA non-expansion N=130 973; expansion N=193 198; post-ACA non-expansion N=186 341; expansion N=251 015). For the diabetes analysis, we excluded patients with a diabetes diagnosis prior to study start, on their first visit or first visit after inactive patient status, and diagnosis while not an active patient (pre-ACA non-expansion N=145 435; expansion N=198 558; post-ACA non-expansion N=215 039; expansion N=264 644). RESULTS: In non-expansion states, adjusted hypertension diagnosis rates saw a relative decrease of 6%, while in expansion states, the adjusted rates saw a relative increase of 7% (DID 1.14, 95% CI 1.11 to 1.18). For diabetes diagnosis, adjusted rates in non-expansion states experienced a significant relative increase of 28% and in expansion states the relative increase was 25%; yet these differences were not significant pre-ACA to post-ACA comparing expansion and non-expansion states (DID 0.98, 95% CI 0.91 to 1.05). CONCLUSION: There was a differential impact of Medicaid expansion for hypertension and diabetes diagnoses. Moderate increases were found in diabetes diagnosis rates among all patients served by CHCs post-ACA (both in expansion and non-expansion states). These increases suggest that ACA-related opportunities to gain health insurance (such as marketplaces and the Medicaid expansion) may have facilitated access to diagnostic tests for this population. The study found a small change in hypertension diagnosis rates from pre-ACA to post-ACA (a decrease in non-expansion and an increase in expansion states). Despite the significant difference between expansion and non-expansion states, the small change from pre-ACA to post-ACA suggests that the diagnosis of hypertension is likely documented for patients, regardless of health insurance availability. Future studies are needed to understand the impact of the ACA on hypertension and diabetes treatment and control.

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.

Uptake of Preventive Services Among Patients With and Without Multimorbidity.

INTRODUCTION: Patients with multiple chronic conditions (multimorbidity) are seen commonly in primary care practices and often have suboptimal uptake of preventive care owing to competing treatment demands. The complexity of multimorbidity patterns and their impact on receiving preventive services is not fully understood. This study identifies multimorbidity combinations associated with low receipt of preventive services. METHODS: This was a retrospective cohort study of U.S. community health center patients aged ≥19 years. Electronic health record data from 209 community health centers for the January 1, 2014-December 31, 2017 study period were analyzed in 2018-2019. Multimorbidity patterns included physical only, mental health only, and physical and mental health multimorbidity patterns, with no multimorbidity as a reference category. Electronic health record-based preventive ratios (number of months services were up-to-date/total months the patient was eligible for services) were calculated for the 14 preventive services. Negative binomial regression models assessed the relationship between multimorbidity physical and/or mental health patterns and the preventive ratio for each service. RESULTS: There was a variation in receipt of preventive care between multimorbidity groups: individuals with mental health only multimorbidity were less likely to be up-to-date with cardiometabolic and cancer screenings than the no multimorbidity group or groups with physical health conditions, and the physical only multimorbidity group had low rates of depression screening. CONCLUSIONS: This study provided critical insights into receipt of preventive service among adults with multimorbidity using a more precise method for measuring up-to-date preventive care delivery. Findings would be useful to identify target populations for future intervention programs to improve preventive care.

A Medicaid Alternative Payment Model Program In Oregon Led To Reduced Volume Of Imaging Services.

The patient-centered medical home model aspires to fundamentally restructure care processes, but a volume-based payment system may hinder such transformations. In 2013 Oregon's Medicaid program changed its reimbursement of traditional primary care services for selected community health centers (CHCs) from a per visit to a per patient rate. Using Oregon claims data, we analyzed the price-weighted volume of care for five service areas: traditional primary care services, including imaging, tests, and procedures; other services provided by CHCs that were carved out from the payment reform; emergency department visits; inpatient services; and other services of non-CHC providers. We further subdivided traditional primary care services using Berenson-Eggers Type of Service categories of care. We compared participating and nonparticipating CHCs in Oregon before and after the payment model was implemented. The payment reform was associated with a 42.4 percent relative reduction in price-weighted traditional primary care services, driven fully by decreased use of imaging services. Other outcomes remained unaffected. Oregon's initiative could provide lessons for other states interested in using payment reform to advance the patient-centered medical home model for the Medicaid population.

Primary Care Is an Essential Ingredient to a Successful Population Health Improvement Strategy.

Primary care teams bridge health care to other sectors, making effective connections between health care and health. For health care systems to improve patient and population health, the important role of primary care must be recognized, celebrated, and strengthened. This commentary explores several of the current hot topics in policy discussions (eg, social determinants of health, population health) and gives examples of how these theoretical discussions are relevant to the real world of patient care. It concludes with a few key points on how the system can better support the important population health improvement work done by primary care teams. Changes in the way primary care is delivered, reimbursed, and measured are needed to support the health promoting and healing work that happens continuously, not just during a clinic visit or inside the clinic walls. Renewed investments must be made to strengthen delivery models that enable longitudinal, trusting relationships to develop between patients and primary care teams. Payment systems must shift away from fee-for-service models to new holistic reimbursement methods that reflect the value of a comprehensive scope of primary care practice and continuity of care. Measuring what matters in primary care will help to realign our focus on health.

Using Electronic Health Records in Longitudinal Studies: Estimating Patient Attrition.

BACKGROUND: Electronic health records (EHRs) provide rich data on many domains not routinely available in other data, as such, they are a promising source to study changes in health outcomes using longitudinal study designs (eg, cohort studies, natural experiments, etc.). Yet, patient attrition rates in these data are unknown. OBJECTIVE: The objective of this study was to estimate overall and among adults with diabetes or hypertension: (1) patient attrition over a 3-year period at community health centers; and (2) the likelihood that patients with Medicaid permanently switched their source of primary care. RESEARCH DESIGN: A retrospective cohort study of 2012-2017 data from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) Clinical Data Research Network of community health centers were used to assess EHR data attrition. Oregon Medicaid enrollment and claims data were used to estimate the likelihood of changing the source of primary care. SUBJECTS: A total of 827,657 patients aged 19-64 with ≥1 ambulatory visit from 76 community health center systems across 20 states. In all, 232,891 Oregon Medicaid enrollees (aged 19-64) with a gap of ≥6 months following a claim for a visit billed to a primary care source. MEASURES: Percentage of patients not returning within 3 years of their qualifying visit (attrition). The probability that a patient with Medicaid permanently changed their primary care source. RESULTS: Attrition over the 3 years averaged 33.5%; attrition rates were lower (<25%) among patients with diabetes and/or hypertension. Among Medicaid enrollees, the percentage of provider change after a 6-month gap between visits was 12% for community health center patients compared with 39% for single-provider practice patients. Over 3 years, the likelihood of a patient changing to a new provider increased with length of time since their last visit but remained lowest among community health center patients. CONCLUSION: This study demonstrates the use of the EHR dataset is a reliable source of data to support longitudinal studies while highlighting variability in attrition by primary care source and chronic conditions.

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.

Payment for Contraceptive Services in Safety Net Clinics: Roles of Affordable Care Act, Title X, and State Programs.

OBJECTIVES: We describe payor for contraceptive visits 2013-2014, before and after Medicaid expansion under the Affordable Care Act (ACA), in a large network of safety-net clinics. We estimate changes in the proportion of uninsured contraceptive visits and the independent associations of the ACA, Title X, and state family planning programs. METHODS: Our sample included 237 safety net clinics in 11 states with a common electronic health record. We identified contraception-related visits among women aged 10-49 years using diagnosis and procedure codes. Our primary outcome was an indicator of an uninsured visit. We also assessed payor type (public/private). We included encounter, clinic, county, and state-level covariates. We used interrupted time series and logistic regression, and calculated multivariable absolute predicted probabilities. RESULTS: We identified 162,666 contraceptive visits in 219 clinics. There was a significant decline in uninsured contraception-related visits in both Medicaid expansion and nonexpansion states, with a slightly greater decline in expansion states (difference-in-difference: -1.29 percentage points; confidence interval: -1.39 to -1.19). The gap in uninsured visits between expansion and nonexpansion states widened after ACA implementation (from 2.17 to 4.1 percentage points). The Title X program continues to fill gaps in insurance in Medicaid expansion states. CONCLUSIONS: Uninsured contraceptive visits at safety net clinics decreased following Medicaid expansion under the ACA in both expansion and nonexpansion states. Overall, levels of uninsured visits are lower in expansion states. Title X continues to play an important role in access to care and coverage. In addition to protecting insurance gains under the ACA, Title X and state programs should continue to be a focus of research and advocacy.