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Cancer is the top leading cause of death among Latino people. Lack of health insurance is a significant contributor to inadequate cancer detection and treatment. Despite healthcare policy expansions such as the Affordable Care Act, Latino people persistently maintain the highest uninsured rate among any ethnic and racial group in the US, especially among Latino individuals who are immigrants or part of a mixed immigration status household. Recognizing that immigration status is a critical factor in the ability of Latino community members to seek health insurance and access healthcare services, a few US states and the District of Columbia have implemented policies that have expanded coverage to children and adults regardless of immigration status. Expansion of Medicaid eligibility regardless of immigration status may significantly benefit Latino communities, however the facilitators and barriers to enrolling in these programs need to be evaluated to ensure reach and achieve health equity across the cancer control continuum for all Latinos. [ABSTRACT FROM AUTHOR]

Objective: To describe telemedicine use patterns and understand clinic's approaches to shifting care delivery during the COVID-19 pandemic. Methods: We used electronic health record data from 203 community health centers across 13 states between 01/01/2019 and 6/31/2021 to describe trends in telemedicine visit rates over time. Qualitative data were collected from 13 of those community health centers to understand factors influencing adoption and implementation of telemedicine. Results: Most clinics in our sample were in urban areas (n = 176) and served a majority of uninsured and publicly insured patients (12.8% and 44.4%, respectively) across racial and ethnic minority groups (16.6% Black and 29.3% Hispanic). During our analysis period there was a 791% increase in telemedicine visits from before the pandemic (.06% pre- vs 47.5% during). A latent class growth analysis was used to examine differences in patterns of adoption of telemedicine across the 203 CHCs. The model resulted in 6 clusters representing various levels of telemedicine adoption. A mixed methods approach streamlined these clusters into 4 final groups. Clinics that reported rapid adoption of telemedicine attributed this change to leadership prioritization of telemedicine, robust quality improvement processes (eg, using PDSA processes), and emphasis on training and technology support. Conclusions: In response to the COVID-19 pandemic, telemedicine adoption rates varied across clinics. Our study highlight that organizational factors contributed to the clinic's ability to rapidly uptake and use telemedicine services throughout the pandemic. These approaches could inform future non-pandemic practice change and care delivery. [ABSTRACT FROM AUTHOR]

Abstract 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 .

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 . [ABSTRACT FROM AUTHOR]

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. The Affordable Care Act (ACA) provides coverage options for cancer survivors seen in community health centers, especially in states that have expanded Medicaid; unfortunately, 1 in 5 cancer survivors living in a state that has not expanded Medicaid coverage eligibility remains uninsured. The ACA Medicaid expansion provision change, likely in tandem with other ACA changes, has also contributed to modest improvements in rates of cardiovascular‐related screenings for cancer survivors. [ABSTRACT FROM AUTHOR]

Abstract This quasi-experimental study evaluated racial/ethnic disparities in health insurance and differences in visits post-versus pre-Affordable Care Act (ACA) Medicaid expansion. We utilized electronic health record data from a population of patients with diabetes aged 19–64 seen in community health centers (CHCs). We used generalized estimating equation Poisson models to estimate incidence rates of insurance type and visits post-(1/1/2014–12/31/2015) versus pre-(1/1/13–12/31/13) ACA, stratified by racial/ethnic group. We assessed difference-in-differences (DD) and difference-in-difference-in-differences (DDD). The relative disparity in uninsured visits increased between Hispanic and non-Hispanic Whites in expansion states (DD=1.93; 95% CI=1.41, 2.64); the magnitude was greater in expansion compared with non-expansion states (DDD=1.84, 95% CI=1.32, 2.56), yet uninsured rates were lower in expansion compared with non-expansion states. We found few changes in visits. Results suggest that the ACA Medicaid expansion increased health insurance coverage and that while some racial/ethnic disparities were improved, some remained. [ABSTRACT FROM AUTHOR]

Purpose: Health insurance coverage affects a patient's ability to access optimal care, the percentage of insured patients on a clinic's panel has an impact on the clinic's ability to provide needed health care services, and there are racial and ethnic disparities in coverage in the United States. Thus, we aimed to assess changes in insurance coverage at community health center (CHC) visits after the Patient Protection and Affordable Care Act (ACA) Medicaid expansion by race and ethnicity.Methods: We undertook a retrospective, observational study of visit payment type for CHC patients aged 19 to 64 years. We used electronic health record data from 10 states that expanded Medicaid and 6 states that did not, 359 CHCs, and 870,319 patients with more than 4 million visits. Our analyses included difference-in-difference (DD) and difference-in-difference-in-difference (DDD) estimates via generalized estimating equation models. The primary outcome was health insurance type at each visit (Medicaid-insured, uninsured, or privately insured).Results: After the ACA was implemented, uninsured visit rates decreased for all racial and ethnic groups. Hispanic patients experienced the greatest increases in Medicaid-insured visit rates after ACA implementation in expansion states (rate ratio [RR] = 1.77; 95% CI, 1.56-2.02) and the largest gains in privately insured visit rates in nonexpansion states (RR = 3.63; 95% CI, 2.73-4.83). In expansion states, non-Hispanic white patients had twice the magnitude of decrease in uninsured visits compared with Hispanic patients (DD = 2.03; 95% CI, 1.53-2.70), and this relative change was more than 2 times greater in expansion states compared with nonexpansion states (DDD = 2.06; 95% CI, 1.52-2.78).Conclusion: The lower rates of uninsured visits for all racial and ethnic groups after ACA implementation suggest progress in expanding coverage to CHC patients; this progress, however, was not uniform when comparing expansion with nonexpansion states and among all racial and ethnic minority subgroups. These findings suggest the need for continued and more equitable insurance expansion efforts to eliminate health insurance disparities. [ABSTRACT FROM AUTHOR]

Background: Understanding the impact of health insurance is critical, particularly in the era of Affordable Care Act Medicaid expansion. The electronic health record (EHR) provides new opportunities to quantify health outcomes.Objective: To assess changes in biomarkers of chronic disease among community health center (CHC) patients who gained Medicaid coverage with the Oregon Medicaid expansion (2008-2011).Design: Prospective cohort. Patients were followed for 24 months, and rate of mean biomarker change was calculated. Time to a controlled follow-up measurement was compared using Cox regression models.Setting/patients: Using EHR data from OCHIN (a non-profit network of CHCs) linked to state Medicaid data, we identified three cohorts of patients with uncontrolled chronic conditions (diabetes, hypertension, and hyperlipidemia). Within these cohorts, we included patients who gained Medicaid coverage along with a propensity score-matched comparison group who remained uninsured (diabetes n = 608; hypertension n = 1244; hyperlipidemia n = 546).Main Measures: Hemoglobin A1c (HbA1c) for the diabetes cohort, systolic and diastolic blood pressure (SBP and DBP, respectively) for the hypertension cohort, and low-density lipoprotein (LDL) for the hyperlipidemia cohort.Key Results: All cohorts improved over time. Compared to matched uninsured patients, adults in the diabetes and hypertension cohorts who gained Medicaid coverage were significantly more likely to have a follow-up controlled measurement (hazard ratio [HR] =1.26, p = 0.020; HR = 1.35, p < 0.001, respectively). No significant difference was observed in the hyperlipidemia cohort (HR = 1.09, p = 0.392).Conclusions: OCHIN patients with uncontrolled chronic conditions experienced objective health improvements over time. In two of three chronic disease cohorts, those who gained Medicaid coverage were more likely to achieve a controlled measurement than those who remained uninsured. These findings demonstrate the effective care provided by CHCs and the importance of health insurance coverage within a usual source of care setting.Clinical Trials Registration: NCT02355132 [ https://clinicaltrials.gov/ct2/show/NCT02355132 ]. [ABSTRACT FROM AUTHOR]

Using electronic health record data, we examined longitudinal changes in community health center (CHC) visit rates from 2013 through 2014 in Medicaid expansion versus nonexpansion states. Visits from 219 CHCs in 5 expansion states and 4 nonexpansion states were included. Rates were computed using generalized estimating equation Poisson models. Rates increased in expansion state CHCs for new patient, preventive, and limited-service visits (14%, 41%, and 23%, respectively, P < .01 for all), whereas these rates remained unchanged in nonexpansion states. One year after ACA Medicaid expansions, CHCs in expansion states saw an influx of new patients and provided increased preventive services. [ABSTRACT FROM AUTHOR]

Background: Community health center (CHC) patients have high rates of smoking. Insurance coverage for smoking cessation assistance, such as that mandated by the Affordable Care Act, may aid in smoking cessation in this vulnerable population.Objective: We aimed to determine if uninsured CHC patients who gain Medicaid coverage experience greater primary care utilization, receive more cessation medication orders, and achieve higher quit rates, compared to continuously uninsured smokers.Design: Longitudinal observational cohort study using electronic health record data from a network of Oregon CHCs linked to Oregon Medicaid enrollment data.Patients: Cohort of patients who smoke and who gained Medicaid coverage in 2008-2011 after ≥ 6 months of being uninsured and with ≥ 1 smoking assessment in the 24-month follow-up period from the baseline smoking status date. This group was propensity score matched to a cohort of continuously uninsured CHC patients who smoke (n = 4140 matched pairs; 8280 patients).Intervention: Gaining Medicaid after being uninsured for ≥ 6 months.Main Measures: 'Quit' smoking status (baseline smoking status was 'current every day' or 'some day' and status change to 'former smoker' at a subsequent visit), smoking cessation medication order, and ≥ 6 documented visits (yes/no variables) at ≥ 1 smoking status assessment within the 24-month follow-up period.Key Results: The newly insured had 40 % increased odds of quitting smoking (aOR = 1.40, 95 % CI:1.24, 1.58), nearly triple the odds of having a medication ordered (aOR = 2.94, 95 % CI:2.61, 3.32), and over twice the odds of having ≥ 6 follow-up visits (aOR = 2.12, 95 % CI:1.94, 2.32) compared to their uninsured counterparts.Conclusions: Newly insured patients had increased odds of quit smoking status over 24 months of follow-up than those who remained uninsured. Providing insurance coverage to vulnerable populations may have a significant impact on smoking cessation. [ABSTRACT FROM AUTHOR]

Objective: To demonstrate use of the electronic health record (EHR) for health insurance surveillance and identify factors associated with lack of coverage.Materials and Methods: Using EHR data, we conducted a retrospective, longitudinal cohort study of adult patients (n = 279 654) within a national network of community health centers during a 2-year period (2012-2013).Results: Factors associated with higher odds of being uninsured (vs Medicaid-insured) included: male gender, age >25 years, Hispanic ethnicity, income above the federal poverty level, and rural residence (P < .01 for all). Among patients with no insurance at their initial visit (n = 114 000), 50% remained uninsured for every subsequent visit.Discussion: During the 2 years prior to 2014, many patients utilizing community health centers were unable to maintain stable health insurance coverage.Conclusion: As patients gain access to health insurance under the Affordable Care Act, the EHR provides a novel approach to help track coverage and support vulnerable patients in gaining and maintaining coverage. [ABSTRACT FROM AUTHOR]

Introduction: It is predicted that gaining health insurance via the Affordable Care Act will result in increased rates of preventive health services receipt in the U.S., primarily based on self-reported findings from previous health insurance expansion studies. This study examined the long-term (36-month) impact of Oregon's 2008 randomized Medicaid expansion ("Oregon Experiment") on receipt of 12 preventive care services in community health centers using electronic health record data.Methods: Demographic data from adult (aged 19-64 years) Oregon Experiment participants were probabilistically matched to electronic health record data from 49 Oregon community health centers within the OCHIN community health information network (N=10,643). Intent-to-treat analyses compared receipt of preventive services over a 36-month (2008-2011) period among those randomly assigned to apply for Medicaid versus not assigned, and instrumental variable analyses estimated the effect of actually gaining Medicaid coverage on preventive services receipt (data collected in 2012-2014; analysis performed in 2014-2015).Results: Intent-to-treat analyses revealed statistically significant differences between patients randomly assigned to apply for Medicaid (versus not assigned) for 8 of 12 assessed preventive services. In intent-to-treat analyses, Medicaid coverage significantly increased the odds of receipt of most preventive services (ORs ranging from 1.04 [95% CI=1.02, 1.06] for smoking assessment to 1.27 [95% CI=1.02, 1.57] for mammography).Conclusions: Rates of preventive services receipt will likely increase as community health center patients gain insurance through Affordable Care Act expansions. Continued effort is needed to increase health insurance coverage in an effort to decrease health disparities in vulnerable populations. [ABSTRACT FROM AUTHOR]

Background Despite expansions in public health insurance, many children remain uninsured or experience gaps in coverage. Community health centers (CHCs) provide primary care to many children at risk for uninsurance and are well-positioned to help families obtain and retain children's coverage. Recent advances in health information technology (HIT) capabilities provide the means to create tools that could enhance CHCs' insurance outreach efforts. Objective To present the study design, baseline patient characteristics, variables, and statistical methods for the Innovative Methods for Parents And Clinics to Create Tools for Kids' Care (IMPACCT Kids' Care) study. Methods/design In this mixed methods study, we will design, test and refine health insurance outreach HIT tools through a user-centered process. We will then implement the tools in four CHCs and evaluate their effectiveness and barriers and facilitators to their implementation. To measure effectiveness, we will quantitatively assess health insurance coverage continuity and utilization of healthcare services for pediatric patients in intervention CHCs compared to matched control sites using electronic health record (EHR) and Oregon Medicaid administrative data over 18 months pre- and 18 months post-implementation (n = 34,867 children). We will also qualitatively assess the implementation process to understand how the tools fit into the clinics' workflows and the CHC staff experiences with the tools. Conclusions This study creates, implements, and evaluates health insurance outreach HIT tools. The use of such tools will likely improve care delivery and health outcomes, reduce healthcare disparities for vulnerable populations, and enhance overall healthcare system performance. ClinicalTrials.gov Identifier: NCT02298361 . [ABSTRACT FROM AUTHOR]

Objective To validate electronic health record (EHR) insurance information for low-income pediatric patients at Oregon community health centers (CHCs), compared to reimbursement data and Medicaid coverage data. Materials and Methods Subjects Children visiting any of 96 CHCs (N=69 189) from 2011 to 2012. Analysis The authors measured correspondence (whether or not the visit was covered by Medicaid) between EHR coverage data and (i) reimbursement data and (ii) coverage data from Medicaid. Results Compared to reimbursement data and Medicaid coverage data, EHR coverage data had high agreement (87% and 95%, respectively), sensitivity (0.97 and 0.96), positive predictive value (0.88 and 0.98), but lower kappa statistics (0.32 and 0.49), specificity (0.27 and 0.60), and negative predictive value (0.66 and 0.45). These varied among clinics. Discussion/Conclusions EHR coverage data for children had a high overall correspondence with Medicaid data and reimbursement data, suggesting that in some systems EHR data could be utilized to promote insurance stability in their patients. Future work should attempt to replicate these analyses in other settings. [ABSTRACT FROM AUTHOR]

Purpose: The Affordable Care Act of 2010 supports marked expansions in Medicaid coverage in the United States. As of January 1, 2014, a total of 25 states and the District of Columbia expanded their Medicaid programs. We tested the hypothesis that rates of uninsured safety net clinic visits would significantly decrease in states that implemented Medicaid expansion, compared with states that did not.Methods: We undertook a longitudinal observational study of coverage status for adult visits in community health centers, from 12 months before Medicaid expansion (January 1, 2013 to December 31, 2013) through 6 months after expansion (January 1, 2014 to June 30, 2014). We analyzed data from 156 clinics in the OCHIN practice-based research network, with a shared electronic health record, located in 9 states (5 expanded Medicaid coverage and 4 did not).Results: Analyses were based on 333,655 nonpregnant adult patients and their 1,276,298 in-person billed encounters. Overall, clinics in the expansion states had a 40% decrease in the rate of uninsured visits in the postexpansion period and a 36% increase in the rate of Medicaid-covered visits. In contrast, clinics in the nonexpansion states had a significant 16% decline in the rate of uninsured visits but no change in the rate of Medicaid-covered visits.Conclusions: There was a substantial decrease in uninsured community health center visits and a significant increase in Medicaid-covered visits in study clinics in states that expanded Medicaid in 2014, whereas study clinics in states opting out of the expansion continued to have a high rate of uninsured visits. These findings suggest that Affordable Care Act-related Medicaid expansions have successfully decreased the number of uninsured safety net patients in the United States. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop methodologies for creating child-parent 'links' in two healthcare-related data sources. We linked children and parents who were patients in a network of Oregon clinics with a shared electronic health record (EHR), using data that reported the child's emergency contact information or the 'guarantor' for the child's visits. We also linked children and parents enrolled in the Oregon Health Plan (OHP; Oregon's public health insurance programs), using administrative data; here, we defined a 'child' as aged <19 years and identified potential 'parents' from among adults sharing the same OHP household identification (ID) number. In both data sources, parents had to be 12-55 years older than the child. We used OHP individual client ID and EHR patient ID numbers to assess the quality of our linkages through cross-validation. Of the 249,079 children in the EHR dataset, we identified 62,967 who had a 'linkable' parent with patient information in the EHR. In the OHP data, 889,452 household IDs were assigned to at least one child; 525,578 with a household ID had a 'linkable' parent (272,578 households). Cross-validation of linkages revealed 99.8 % of EHR links validated in OHP data and 97.7 % of OHP links validated in EHR data. The ability to link children and their parents in healthcare-related datasets will be useful to inform efforts to improve children's health. Thus, we developed strategies for linking children with their parents in an EHR and a public health insurance administrative dataset. [ABSTRACT FROM AUTHOR]

Objective: This study compared the preventive service utilization of uninsured patients receiving care at Oregon community health centers (CHCs) in 2008 through 2011 with that of continuously insured patients at the same CHCs in the same period, using electronic health record (EHR) data.Methods: We performed a retrospective cohort analysis, using logistic mixed effects regression modeling to calculate odds ratios and rates of preventive service utilization for patients without insurance, or with continuous insurance.Results: CHCs provided many preventive services to uninsured patients. Uninsured patients were less likely than continuously insured patients to receive 5 of 11 preventive services, ranging from OR 0.52 (95% CI: 0.35-0.77) for mammogram orders to 0.75 (95% CI: 0.66-0.86) for lipid panels. This disparity persisted even in patients who visited the clinic regularly.Conclusion: Lack of insurance is a barrier to preventive service utilization, even in patients who can access care at a CHC. Policymakers in the United States should continue to address this significant prevention disparity. [ABSTRACT FROM AUTHOR]

Background: Patients with gaps in health insurance coverage often defer or forgo cancer prevention services. These delays in cancer detection and diagnoses lead to higher rates of morbidity and mortality and increased costs. Recent advances in health information technology (HIT) create new opportunities to enhance insurance support services that reduce coverage gaps through automated processes applied in healthcare settings. This study will assess the implementation of insurance support HIT tools and their effectiveness at improving patients' insurance coverage continuity and cancer screening rates.Methods/design: This study uses a hybrid cluster-randomized design-a combined effectiveness and implementation trial-in community health centers (CHCs) in the USA. Eligible CHC clinic sites will be randomly assigned to one of two groups in the trial's implementation component: tools + basic training (Arm I) and tools + enhanced training + facilitation (Arm II). A propensity score-matched control group of clinics will be selected to assess the tools' effectiveness. Quantitative analyses of the tools' impact will use electronic health record and Medicaid data to assess effectiveness. Qualitative data will be collected to evaluate the implementation process, understand how the HIT tools are being used, and identify facilitators and barriers to their implementation and use.Discussion: This study will test the effectiveness of HIT tools to enhance insurance support in CHCs and will compare strategies for facilitating their implementation in "real-world" practice settings. Findings will inform further development and, if indicated, more widespread implementation of insurance support HIT tools.Trial Registration: Clinical trial NTC02355262. [ABSTRACT FROM AUTHOR]

Churning on and off and/or experiencing coverage gaps is common among public health insurance recipients. Although Affordable Care Act provisions to extend parental coverage for adolescents transitioning to young adulthood on private insurance plans were implemented in 2010, no such protection was mandated for adolescents with public health insurance. Oregon public health insurance enrollment and electronic health record data from community health centers were used to conduct a retrospective, observational cohort study of Oregon adolescents (17-19 years of age) with public coverage [January 1, 2011- December 31, 2013 (n=51,988)] to assess loss. Time-to-event methods determined the association of coverage loss with sociodemographic characteristics. Although adolescents are vulnerable to coverage loss as they age out of child public health insurance coverage, >35% of 19 year olds in this study kept their coverage for up to one year after their 19th birthday. Our findings suggest that the support many community health centers offer to help their patients maintain insurance coverage may be having an impact, especially during this important transition period. Additional research to understand how these 19 year olds were able to keep coverage will provide recommendations for future adolescents as they transition to young adulthood. [ABSTRACT FROM AUTHOR]

Background: Lack of insurance is associated with suboptimal receipt of diabetes preventive care. One known reason for this is an access barrier to obtaining healthcare visits; however, little is known about whether insurance status is associated with differential rates of receipt of diabetes care during visits. Purpose: To examine the association between health insurance and receipt of diabetes preventive care during an office visit. Methods: This retrospective cohort study used electronic health record and Medicaid data from 38 Oregon community health centers. Logistic regression was used to test the association between insurance and receipt of four diabetes services during an office visit among patients who were continuously uninsured (n=1,117); continuously insured (n=1,466); and discontinuously insured (n=336) in 2006-2007. Generalized estimating equations were used to account for within-patient correlation. Data were analyzed in 2013. Results: Overall, continuously uninsured patients had lower odds of receiving services at visits when due, compared to those who were continuously insured (AOR=0.73, 95% CI=0.66, 0.80). Among the discontinuously insured, being uninsured at a visit was associated with lower odds of receipt of services due at that visit (AOR=0.77, 95% CI=0.64, 0.92) than being insured at a visit. Conclusions: Lack of insurance is associated with a lower probability of receiving recommended services that are due during a clinic visit. Thus, the association between being uninsured and receiving fewer preventive services may not be completely mediated by access to clinic visits. [ABSTRACT FROM AUTHOR]

Prevention is critical to optimizing health, yet most people do not receive all recommended preventive services. As the complexity of preventive recommendations increases, there is a need for new measurements to capture the degree to which a person is up to date, and identify individual-level barriers and facilitators to receiving needed preventive care. We used electronic health record data from a national network of community health centers (CHCs) in the United States (US) during 2014-2017 to measure patient-level up-to-date status with preventive ratios (measuring up-to-date person-time denoted as a percent) for 12 preventive services and an aggregate preventive index. We use negative binomial regression to identify factors associated with up-to-date preventive care. We assessed 267,767 patients across 165 primary care clinics. Mean preventive ratios ranged from 8.7% for Hepatitis C screening to 83.3% for blood pressure screening. The mean aggregate preventive index was 43%. Lack of health insurance, smoking, and homelessness were associated with lower preventive ratios for most cancer and cardiovascular screenings (p < 0.05). Having more ambulatory visits, better continuity of care, and enrollment in the patient portal were positively associated with the aggregate preventive index (p < 0.05) and higher preventive ratios for all services (p < 0.05) except chlamydia and HIV screening. Overall, receipt of preventive services was low. CHC patients experience many barriers to receiving needed preventive care, but certain healthcare behaviors - regular visits, usual provider continuity, and patient portal enrollment - were consistently associated with more up-to-date preventive care. These associations should inform future efforts to improve preventive care delivery. [ABSTRACT FROM AUTHOR]

Community health centers (CHCs) play an important role in providing care for the safety net population. After implementation of the Affordable Care Act, many patients gained insurance through state and federal marketplaces. Using electronic health record data from 702,663 patients in 257 clinics across 20 states, we sought to explore the following differences between Medicaid expansion and non-expansion state CHCs: (1) trends in private/marketplace insurance post-expansion, and (2) whether CHC patients retain private/marketplace insurance. We found that patients in non-expansion state CHCs relied more heavily on private/marketplace insurance than patients in expansion states and had increases in private/marketplace-insured visits from 2014 through 2018. Additionally, there appeared to be seasonal variation in private/marketplace-insured visits that were more pronounced in non-expansion states. While a greater percentage of patients in non-expansion states retained private/marketplace insurance than in expansion states, a greater percentage of those who did not retain it became uninsured. In comparison, a greater percentage of patients in expansion states who lost private/marketplace insurance gained other types of health insurance. CHCs' ability to provide adequate care for vulnerable populations relies, in part, on federal grants as well as reimbursement from insurers: decreases in either could result in reduced capacity or quality of care for patients seen in CHCs. [ABSTRACT FROM AUTHOR]