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BackgroundA substantial percentage of the US population is not up to date on guideline-recommended cancer screenings. Identifying interventions that effectively improve screening rates would enhance the delivery of such screening. Interventions involving health IT (HIT) show promise, but much remains unknown about how HIT is optimized to support cancer screening in primary care. ObjectiveThis scoping review aims to identify (1) HIT-based interventions that effectively support guideline concordance in breast, cervical, and colorectal cancer screening provision and follow-up in the primary care setting and (2) barriers or facilitators to the implementation of effective HIT in this setting. MethodsFollowing scoping review guidelines, we searched MEDLINE, CINAHL Plus, Web of Science, and IEEE Xplore databases for US-based studies from 2015 to 2021 that featured HIT targeting breast, colorectal, and cervical cancer screening in primary care. Studies were dual screened using a review criteria checklist. Data extraction was guided by the following implementation science frameworks: the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework; the Expert Recommendations for Implementing Change taxonomy; and implementation strategy reporting domains. It was also guided by the Integrated Technology Implementation Model that incorporates theories of both implementation science and technology adoption. Reporting was guided by PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). ResultsA total of 101 studies met the inclusion criteria. Most studies (85/101, 84.2%) involved electronic health record–based HIT interventions. The most common HIT function was clinical decision support, primarily used for panel management or at the point of care. Most studies related to HIT targeting colorectal cancer screening (83/101, 82.2%), followed by studies related to breast cancer screening (28/101, 27.7%), and cervical cancer screening (19/101, 18.8%). Improvements in cancer screening were associated with HIT-based interventions in most studies (36/54, 67% of colorectal cancer–relevant studies; 9/14, 64% of breast cancer–relevant studies; and 7/10, 70% of cervical cancer–relevant studies). Most studies (79/101, 78.2%) reported on the reach of certain interventions, while 17.8% (18/101) of the included studies reported on the adoption or maintenance. Reported barriers and facilitators to HIT adoption primarily related to inner context factors of primary care settings (eg, staffing and organizational policies that support or hinder HIT adoption). Implementation strategies for HIT adoption were reported in 23.8% (24/101) of the included studies. ConclusionsThere are substantial evidence gaps regarding the effectiveness of HIT-based interventions, especially those targeting guideline-concordant breast and colorectal cancer screening in primary care. Even less is known about how to enhance the adoption of technologies that have been proven effective in supporting breast, colorectal, or cervical cancer screening. Research is needed to ensure that the potential benefits of effective HIT-based interventions equitably reach diverse primary care populations.

Abstract Broadly neutralizing monoclonal antibodies (mAbs) are being developed for HIV-1 prevention. Hence, these mAbs and licensed oral pre-exposure prophylaxis (PrEP) (tenofovir-emtricitabine) can be concomitantly administered in clinical trials. In 48 US participants (men and transgender persons who have sex with men) who received the HIV-1 mAb VRC01 and remained HIV-free in an antibody-mediated-prevention trial (ClinicalTrials.gov #NCT02716675), we conduct a post-hoc analysis and find that VRC01 clearance is 0.08 L/day faster (p = 0.005), and dose-normalized area-under-the-curve of VRC01 serum concentration over-time is 0.29 day/mL lower (p

Abstract 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.

Aims: Children of parents with substance use and/or other mental health (SU/MH) diagnoses are at increased risk for health problems. It is unknown whether these children benefit from receiving primary care at the same clinic as their parents. Thus, among children of parents with >1 SU/MH diagnosis, we examined the association of parent-child clinic concordance with rates of well-child checks (WCCs) and childhood vaccinations. Design: Retrospective cohort study using electronic health record (EHR) data from the OCHIN network of community health organizations (CHOs), 2010-2018. Setting: 280 CHOs across 17 states. Participants/Cases: 41,413 parents with >1 SU/MH diagnosis, linked to 65,417 children aged 0 to 17 years, each with >1 visit to an OCHIN clinic during the study period. Measurements: Dependent variables: rates of WCCs during (1) the first 15 months of life, and (2) ages 3 to 17 years; vaccine completeness (3) by the age of 2, and (4) before the age of 18. Estimates were attained using generalized estimating equations Poisson or logistic regression. Findings: Among children utilizing the same clinic as their parent versus children using a different clinic (reference group), we observed greater WCC rates in the first 15 months of life [adjusted rate ratio (aRR) = 1.06; 95% confidence interval (CI) = 1.02-1.10]; no difference in WCC rates in ages 3 to 17; higher odds for vaccine completion before age 2 [adjusted odds ratio (aOR) = 1.12; 95% CI = 1.03-1.21]; and lower odds for vaccine completion before age 18 (aOR = 0.88; 95% CI = 0.81-0.95). Conclusion: Among children whose parents have at least one SU/MH diagnosis, parent-child clinic concordance was associated with greater rates of WCCs and higher odds of completed vaccinations for children in the youngest age groups, but not the older children. This suggests the need for greater emphasis on family-oriented healthcare for young children of parents with SU/MH diagnoses; this may be less important for older children.

Previous reviews of strategies to increase cervical cancer screening are more than 10 years old, the U.S. continues to fall short of the Healthy People 2030 cervical cancer screening goal, and guidelines were revised in 2018, therefore an updated review of the existing literature is needed. We conducted a scoping review using electronic databases PubMed, Scopus, and Ovid Medline that included publication dates between 2012 and 2021 to answer the question, “Which strategies implemented in U.S. primary care settings have been most successful in increasing rates of cervical cancer screening since the 2012 US Preventative Services Task Force cervical cancer screening guidelines were published?” We mapped findings to pre-specified implementation strategy categories. After initially identifying 399 articles, we excluded 350 due to duplicates or not meeting review criteria, leaving 49 articles for full review. We excluded 37 of these during full-text review and identified 2 additional articles from the manual search of reference lists for a total of 14 studies for abstraction. Eleven articles reported on strategies resulting in increased cervical cancer screening, and 3 did not. Clinic workflow re-design strategies showed the greatest promise in improving cervical cancer screening rates, education strategies for patients had mixed results, and quality management strategies were not effective. These findings suggest clinical workflow re-structures and patient education strategies can increase cervical cancer screening in primary care settings. Results are particularly important in settings that care for underserved populations, as these settings may need additional implementation strategies to decrease cervical cancer screening disparities.

Monoclonal antibodies are commonly engineered with an introduction of Met428Leu and Asn434Ser, known as the LS mutation, in the fragment crystallizable region to improve pharmacokinetic profiles. The LS mutation delays antibody clearance by enhancing binding affinity to the neonatal fragment crystallizable receptor found on endothelial cells. To characterize the LS mutation for monoclonal antibodies targeting HIV, we compared pharmacokinetic parameters between parental versus LS variants for five pairs of anti-HIV immunoglobin G1 monoclonal antibodies (VRC01/LS/VRC07-523LS, 3BNC117/LS, PGDM1400/LS PGT121/LS, 10-1074/LS), analyzing data from 16 clinical trials of 583 participants without HIV. We described serum concentrations of these monoclonal antibodies following intravenous or subcutaneous administration by an open two-compartment disposition, with first-order elimination from the central compartment using non-linear mixed effects pharmacokinetic models. We compared estimated pharmacokinetic parameters using the targeted maximum likelihood estimation method, accounting for participant differences. We observed lower clearance rate, central volume, and peripheral volume of distribution for all LS variants compared to parental monoclonal antibodies. LS monoclonal antibodies showed several improvements in pharmacokinetic parameters, including increases in the elimination half-life by 2.7- to 4.1-fold, the dose-normalized area-under-the-curve by 4.1- to 9.5-fold, and the predicted concentration at 4 weeks post-administration by 3.4- to 7.6-fold. Results suggest a favorable pharmacokinetic profile of LS variants regardless of HIV epitope specificity. Insights support lower dosages and/or less frequent dosing of LS variants to achieve similar levels of antibody exposure in future clinical applications.

Summary: Background: The phase 2b proof-of-concept Antibody Mediated Prevention (AMP) trials showed that VRC01, an anti-HIV-1 broadly neutralising antibody (bnAb), prevented acquisition of HIV-1 sensitive to VRC01. To inform future study design and dosing regimen selection of candidate bnAbs, we investigated the association of VRC01 serum concentration with HIV-1 acquisition using AMP trial data. Methods: The case–control sample included 107 VRC01 recipients who acquired HIV-1 and 82 VRC01 recipients who remained without HIV-1 during the study. We measured VRC01 serum concentrations with a qualified pharmacokinetic (PK) Binding Antibody Multiplex Assay. We employed nonlinear mixed effects PK modelling to estimate daily-grid VRC01 concentrations. Cox regression models were used to assess the association of VRC01 concentration at exposure and baseline body weight, with the hazard of HIV-1 acquisition and prevention efficacy as a function of VRC01 concentration. We also compared fixed dosing vs. body weight-based dosing via simulations. Findings: Estimated VRC01 concentrations in VRC01 recipients without HIV-1 were higher than those in VRC01 recipients who acquired HIV-1. Body weight was inversely associated with HIV-1 acquisition among both placebo and VRC01 recipients but did not modify the prevention efficacy of VRC01. VRC01 concentration was inversely correlated with HIV-1 acquisition, and positively correlated with prevention efficacy of VRC01. Simulation studies suggest that fixed dosing may be comparable to weight-based dosing in overall predicted prevention efficacy. Interpretation: These findings suggest that bnAb serum concentration may be a useful marker for dosing regimen selection, and operationally efficient fixed dosing regimens could be considered for future trials of HIV-1 bnAbs. Funding: Was provided by the National Institutes of Health, National Institute of Allergy and Infectious Diseases (NIAID) (UM1 AI068614, to the HIV Vaccine Trials Network [HVTN]; UM1 AI068635, to the HVTN Statistical Data and Management Center [SDMC], Fred Hutchinson Cancer Center [FHCC]; 2R37 054165 to the FHCC; UM1 AI068618, to HVTN Laboratory Center, FHCC; UM1 AI068619, to the HPTN Leadership and Operations Center; UM1 AI068613, to the HIV Prevention Trials Network [HPTN] Laboratory Center; UM1 AI068617, to the HPTN SDMC; and P30 AI027757, to the Center for AIDS Research, Duke University (AI P30 AI064518) and University of Washington (P30 AI027757) Centers for AIDS Research; R37AI054165 from NIAID to the FHCC; and OPP1032144 CA-VIMC Bill & Melinda Gates Foundation.

Abstract Background Cancer survivors face increased risk for chronic diseases resulting from cancer, preexisting conditions, and cancer treatment. Having an established primary care clinic or health insurance may influence patients’ receipt of recommended preventive care necessary to manage, treat, or diagnose new conditions. This study sought to understand receipt of healthcare in community health centers (CHCs) before and after cancer diagnosis among cancer survivors. We also examined the type of care received and assessed whether being established with a CHC or the type of health insurance affected the use of services. Methods Using electronic health record data and linked cancer registries from 5,649 CHC patients in three states from 2012 through 2018, we obtained monthly rates of primary care and mental health/behavioral health (MHBH) visits and the probability of receipt of care before and after a cancer diagnosis. Results Seventy‐five percent of CHC patients diagnosed with cancer returned to their primary CHC for care within 2‐years of their diagnosis. Among those who returned, there was a sharp increase in primary and MHBH care shortly before their diagnosis. Significantly more primary care (pre: 19.6%, post: 21.9%, p

Background and Objective: Cancer screening rates remain low in rural, racial and ethnic minority, low-income, and uninsured populations. Prior studies showed that cancer screening recommendations vary based on clinicians’ factors. We conducted an exploratory study on primary care clinicians’ beliefs about new or updated cancer screening guidelines according to clinician demographics. Methods: This cross-sectional study involved administering a web-based survey in July and August of 2021 to primary care clinicians practicing in diverse ambulatory settings in the Pacific Northwest belonging to the same health system. The survey assessed clinician demographics, attitudes about the impact of cancer screening on mortality, and how clinicians stay up-to-date with guidelines. Results: Of the 191 clinicians, 81 responded (42.4%), after removing 13 incomplete surveys, we analyzed 68 (35.6%). The majority agreed/strongly agreed that breast (76.1%), colorectal (95.5%), and cervical (90.9%) cancer screening, and HPV vaccination (85.1%) prevent early cancer mortality: there were no differences according to clinician gender or years in practice. Female compared to male clinicians were more likely to agree/strongly agree that tobacco smoking cessation (female: 100% vs male: 86.4%, P = .01) prevents early cancer mortality, whereas male compared to female clinicians were more likely to agree/strongly agree that lung cancer screening (male: 86.4% vs female: 57.8%, P = .04) prevents early cancer mortality. One-third (33.3%) of clinicians were unaware of the 2021 update on lung cancer screening and females were more likely than males to say they did not know about this change (females: 43.2% vs males: 13.6%, P = .02). Conclusions: This study suggests that clinicians’ attitudes are not likely the primary factor affecting low cancer screening rates in some populations and that few differences exist in beliefs based on gender, and none based on years in practice.

Abstract Background Multi-center research initiatives offer opportunities to develop and strengthen connections among researchers. These initiatives often have goals of increased scientific collaboration which can be examined using social network analysis. Methods The National Cancer Institute (NCI)-funded Implementation Science Centers in Cancer Control (ISC3) initiative conducted an online social network survey in its first year of funding (2020) to (1) establish baseline network measures including the extent of cross-center collaboration and (2) assess factors associated with a network member’s access to the network such as one’s implementation science (IS) expertise. Members of the seven funded centers and NCI program staff identified collaborations in planning/conducting research, capacity building, product development, scientific dissemination, and practice/policy dissemination. Results Of the 192 invitees, 182 network members completed the survey (95%). The most prevalent roles were faculty (60%) and research staff (24%). Almost one-quarter (23%) of members reported advanced expertise in IS, 42% intermediate, and 35% beginner. Most members were female (69%) and white (79%). One-third (33%) of collaboration ties were among members from different centers. Across all collaboration activities, the network had a density of 14%, suggesting moderate cohesion. Degree centralization (0.33) and betweenness centralization (0.07) measures suggest a fairly dispersed network (no single or few central member(s) holding all connections). The most prevalent and densely connected collaboration was in planning/conducting research (1470 ties; 8% density). Practice/policy dissemination had the fewest collaboration, lowest density (284 ties’ 3% density), and the largest number of non-connected members (n=43). Access to the ISC3 network varied significantly depending on members’ level of IS expertise, role within the network, and racial/ethnic background. Across all collaboration activities, most connected members included those with advanced IS expertise, faculty and NCI staff, and Hispanic or Latino and white members. Conclusions Results establish a baseline for assessing the growth of cross-center collaborations, highlighting specific areas in need of particular growth in network collaborations such as increasing engagement of racial and ethnic minorities and trainees or those with less expertise in IS.

Abstract 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.

Background: Parental factors are associated with children's receipt of recommended care but not adequately described. Methods: We conducted a qualitative study of patients with at least two visits who were a primary caregiver for a child who also had at least two visits at the same clinic in 1/2018–12/2019 from two Oregon family medicine clinics. We stratified patients by child age and number of caregiver visits and randomly selected caregivers. Participants were interviewed in accordance with approval by our Institutional Review Board between 12/2020 and 4/2021. The data were analyzed using a grounded theory approach. Results: 12 caregivers (termed parents) were interviewed; half were single parents and three-quarters had a history of substance use disorder and/or a mental health condition. Parents focused on the importance of keeping themselves healthy to keep their families healthy. They described similar reasons for choosing to initiate and continue care for themselves and their children at the same clinic, including: convenience, trust, relationships, and receiving whole-person and whole-family care. Many valued having a healthcare “home” for their entire family. We developed a figure that highlights three themes that capture the interrelated factors parents identified as supporting healthcare use for themselves and their families. These overarching themes included: healthcare initiation; healthcare engagement and continuity; and parent bringing child to the same clinic for healthcare. Conclusion: Our data suggests that long-standing patient-clinic relationships for parents and children can support family-focused healthcare.

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.

Health insurance coverage facilitates access to preventive screenings and other essential health care services, and is linked to improved health outcomes; therefore, it is critical to understand how well coverage information is documented in the electronic health record (EHR) and which characteristics are associated with accurate documentation. Our objective was to evaluate the validity of EHR data for monitoring longitudinal Medicaid coverage and assess variation by patient demographics, visit types, and clinic characteristics. We conducted a retrospective, observational study comparing Medicaid status agreement between Oregon community health center EHR data linked at the patient-level to Medicaid enrollment data (gold standard). We included adult patients with a Medicaid identification number and ≥1 clinic visit between 1/1/2013–12/31/2014 [>1 million visits (n = 135,514 patients)]. We estimated statistical correspondence between EHR and Medicaid data at each visit (visit-level) and for different insurance cohorts over time (patient-level). Data were collected in 2016 and analyzed 2017–2018. We observed excellent agreement between EHR and Medicaid data for health insurance information: kappa (>0.80), sensitivity (>0.80), and specificity (>0.85). Several characteristics were associated with agreement; at the visit-level, agreement was lower for patients who preferred a non-English language and for visits missing income information. At the patient-level, agreement was lower for black patients and higher for older patients seen in primary care community health centers. Community health center EHR data are a valid source of Medicaid coverage information. Agreement varied with several characteristics, something researchers and clinic staff should consider when using health insurance information from EHR data. Keywords: Electronic health records, Medicaid, Health policy, Health insurance

Community-level factors have significant impacts on health. There is renewed enthusiasm for integrating these data with electronic health record (EHR) data for use in primary care to improve health equity in the USA. Thus, it is valuable to reflect on what has been published to date. Specifically, we comment on: (1) recommendations about combining community-level factors in EHRs for use in primary care; (2) examples of how these data have been combined and used; and (3) the impact of using combined data on healthcare, patient health and health equity. We found publications discussing the potential of combined data to inform clinical care, target interventions, track population health and spark community partnerships with the goal of reducing health disparities and improving health equity. Although there is great enthusiasm and potential for using these data to inform primary care, there is little evidence of improved healthcare, patient health or health equity.

Abstract Background Children with health insurance have increased access to healthcare and receive higher quality care. However, despite recent initiatives expanding children’s coverage, many remain uninsured. New technologies present opportunities for helping clinics provide enrollment support for patients. We developed and tested electronic health record (EHR)-based tools to help clinics provide children’s insurance assistance. Methods We used mixed methods to understand tool adoption, and to assess impact of tool use on insurance coverage, healthcare utilization, and receipt of recommended care. We conducted intent-to-treat (ITT) analyses comparing pediatric patients in 4 intervention clinics (n = 15,024) to those at 4 matched control clinics (n = 12,227). We conducted effect-of-treatment-on-the-treated (ETOT) analyses comparing intervention clinic patients with tool use (n = 2240) to intervention clinic patients without tool use (n = 12,784). Results Tools were used for only 15% of eligible patients. Qualitative data indicated that tool adoption was limited by: (1) concurrent initiatives that duplicated the work associated with the tools, and (2) inability to obtain accurate insurance coverage data and end dates. The ITT analyses showed that intervention clinic patients had higher odds of gaining insurance coverage (adjusted odds ratio [aOR] = 1.32, 95% confidence interval [95%CI] 1.14–1.51) and lower odds of losing coverage (aOR = 0.77, 95%CI 0.68–0.88), compared to control clinic patients. Similarly, ETOT findings showed that intervention clinic patients with tool use had higher odds of gaining insurance (aOR = 1.83, 95%CI 1.64–2.04) and lower odds of losing coverage (aOR = 0.70, 95%CI 0.53–0.91), compared to patients without tool use. The ETOT analyses also showed higher rates of receipt of return visits, well-child visits, and several immunizations among patients for whom the tools were used. Conclusions This pragmatic trial, the first to evaluate EHR-based insurance assistance tools, suggests that it is feasible to create and implement tools that help clinics provide insurance enrollment support to pediatric patients. While ITT findings were limited by low rates of tool use, ITT and ETOT findings suggest tool use was associated with better odds of gaining and keeping coverage. Further, ETOT findings suggest that use of such tools may positively impact healthcare utilization and quality of pediatric care. Trial registration ClinicalTrials.gov, NCT02298361; retrospectively registered on November 5, 2014.

Maintaining continuous health insurance coverage is important. With recent expansions in access to coverage in the United States after “Obamacare,” primary care teams have a new role in helping to track and improve coverage rates and to provide outreach to patients. We describe efforts to longitudinally track health insurance rates using data from the electronic health record (EHR) of a primary care network and to use these data to support practice-based insurance outreach and assistance. Although we highlight a few examples from one network, we believe there is great potential for doing this type of work in a broad range of family medicine and community health clinics that provide continuity of care. By partnering with researchers through practice-based research networks and other similar collaboratives, primary care practices can greatly expand the use of EHR data and EHR-based tools targeting improvements in health insurance and quality health care.

Low-income families struggle to obtain and maintain public health insurance. We identified strategies used by Community Health Centers (CHCs) to assist patients with insurance applications, and assessed patients’ receptivity to these efforts. Observational cross-case comparative study with four CHCs in Oregon. We observed insurance assistance processes, and interviewed 26 clinic staff and 18 patients/family members. Qualitative data were analyzed using a grounded theory approach. Patients’ understanding of eligibility status, reapplication schedules, and how to apply, were major barriers to insurance enrollment. Clinic staff addressed these barriers by reminding patients when applications were due, assisting with applications as needed, and tracking submitted applications to ensure approval. Families trusted clinic staff with insurance enrollment support, and appreciated it. CHCs are effective at helping patients with public health insurance. Access to insurance expiration data, tools enabling enrollment activities, and compensation are needed to support enrollment services in CHCs.

Background: It is crucial to understand the impact of the Affordable Care Act (ACA). This study assesses changes in insurance status of patients visiting community health centers (CHCs) comparing states that expanded Medicaid to those that did not. Methods: Electronic health record data on 875,571 patients aged 19 to 64 years with ≥ 1 visit between 2012 and 2015 in 412 primary care CHCs in 9 expansion and 4 nonexpansion states. We assessed changes in rates of total, uninsured, Medicaid-insured, and privately insured primary care and preventive care visits; immunizations administered, and medications ordered. Results: Rates of uninsured visits decreased pre- to post-ACA, with greater drops in expansion (−57%) versus nonexpansion (−20%) states. Medicaid-insured visits increased 60% in expansion states while remaining unchanged in nonexpansion states. Privately insured visits were 2.7 times higher post-ACA in nonexpansion states with no increase in expansion states. Comparing 2015 with 2014: Uninsured visit rates continued to decrease in expansion (−28%) and nonexpansion states (−19%), Medicaid-insured rates did not significantly increase, and privately insured visits increased in nonexpansion states but did not change in expansion states. Conclusions: Medicaid expansion and subsidies to purchase private coverage likely increased the accessibility of health insurance for patients who had previously not been able to access coverage.

Background: Changes in health insurance policies have increased coverage opportunities, but enrollees are required to annually reapply for benefits which, if not managed appropriately, can lead to insurance gaps. Electronic health records (EHRs) can automate processes for assisting patients with health insurance enrollment and re-enrollment. Objective: We describe community health centers' (CHC) workflow, documentation, and tracking needs for assisting families with insurance application processes, and the health information technology (IT) tool components that were developed to meet those needs. Method: We conducted a qualitative study using semi-structured interviews and observation of clinic operations and insurance application assistance processes. Data were analyzed using a grounded theory approach. We diagramed workflows and shared information with a team of developers who built the EHR-based tools. Results: Four steps to the insurance assistance workflow were common among CHCs: 1) Identifying patients for public health insurance application assistance; 2) Completing and submitting the public health insurance application when clinic staff met with patients to collect requisite information and helped them apply for benefits; 3) Tracking public health insurance approval to monitor for decisions; and 4) assisting with annual health insurance reapplication. We developed EHR-based tools to support clinical staff with each of these steps. Conclusion: CHCs are uniquely positioned to help patients and families with public health insurance applications. CHCs have invested in staff to assist patients with insurance applications and help prevent coverage gaps. To best assist patients and to foster efficiency, EHR based insurance tools need comprehensive, timely, and accurate health insurance information.