Patient-Reported Social Risks and Clinician Decision Making: Results of a Clinician Survey in Primary Care Community Health Centers.

PURPOSE: To assess the extent that patients' social determinants of health (SDOH) influence safety-net primary care clinicians' decisions at the point of care; examine how that information comes to the clinician's attention; and analyze clinician, patient, and encounter characteristics associated with the use of SDOH data in clinical decision making. METHODS: Thirty-eight clinicians working in 21 clinics were prompted to complete 2 short card surveys embedded in the electronic health record (EHR) daily for 3 weeks. Survey data were matched with clinician-, encounter-, and patient-level variables from the EHR. Descriptive statistics and generalized estimating equation models were used to assess relationships between the variables and the clinician reported use of SDOH data to inform care. RESULTS: Social determinants of health were reported to influence care in 35% of surveyed encounters. The most common sources of information on patients' SDOH were conversations with patients (76%), prior knowledge (64%), and the EHR (46%). Social determinants of health were significantly more likely to influence care among male and non-English-speaking patients, and those with discrete SDOH screening data documented in the EHR. CONCLUSIONS: Electronic health records present an opportunity to support clinicians integrating information about patients' social and economic circumstances into care planning. Study findings suggest that SDOH information from standardized screening documented in the EHR, combined with patient-clinician conversations, may enable social risk-adjusted care. Electronic health record tools and clinic workflows could be used to support both documentation and conversations. Study results also identified factors that may cue clinicians to include SDOH information in point-of-care decision-making. Future research should explore this topic further.

Creating research-ready partnerships: the initial development of seven implementation laboratories to advance cancer control.

BACKGROUND: In 2019-2020, with National Cancer Institute funding, seven implementation laboratory (I-Lab) partnerships between scientists and stakeholders in 'real-world' settings working to implement evidence-based interventions were developed within the Implementation Science Centers in Cancer Control (ISC3) consortium. This paper describes and compares approaches to the initial development of seven I-Labs in order to gain an understanding of the development of research partnerships representing various implementation science designs. METHODS: In April-June 2021, members of the ISC3 Implementation Laboratories workgroup interviewed research teams involved in I-Lab development in each center. This cross-sectional study used semi-structured interviews and case-study-based methods to collect and analyze data about I-Lab designs and activities. Interview notes were analyzed to identify a set of comparable domains across sites. These domains served as the framework for seven case descriptions summarizing design decisions and partnership elements across sites. RESULTS: Domains identified from interviews as comparable across sites included engagement of community and clinical I-Lab members in research activities, data sources, engagement methods, dissemination strategies, and health equity. The I-Labs use a variety of research partnership designs to support engagement including participatory research, community-engaged research, and learning health systems of embedded research. Regarding data, I-Labs in which members use common electronic health records (EHRs) leverage these both as a data source and a digital implementation strategy. I-Labs without a shared EHR among partners also leverage other sources for research or surveillance, most commonly qualitative data, surveys, and public health data systems. All seven I-Labs use advisory boards or partnership meetings to engage with members; six use stakeholder interviews and regular communications. Most (70%) tools or methods used to engage I-Lab members such as advisory groups, coalitions, or regular communications, were pre-existing. Think tanks, which two I-Labs developed, represented novel engagement approaches. To disseminate research results, all centers developed web-based products, and most (n = 6) use publications, learning collaboratives, and community forums. Important variations emerged in approaches to health equity, ranging from partnering with members serving historically marginalized populations to the development of novel methods. CONCLUSIONS: The development of the ISC3 implementation laboratories, which represented a variety of research partnership designs, offers the opportunity to advance understanding of how researchers developed and built partnerships to effectively engage stakeholders throughout the cancer control research lifecycle. In future years, we will be able to share lessons learned for the development and sustainment of implementation laboratories.

Social Care Recommendations in National Diabetes Treatment Guidelines.

PURPOSE OF REVIEW: An expanding body of research documents associations between socioeconomic circumstances and health outcomes, which has led health care institutions to invest in new activities to identify and address patients' social circumstances in the context of care delivery. Despite growing national investment in these "social care" initiatives, the extent to which social care activities are routinely incorporated into care for patients with type II diabetes mellitus (T2D), specifically, is unknown. We conducted a scoping review of existing T2D treatment and management guidelines to explore whether and how these guidelines incorporate recommendations that reflect social care practice categories. RECENT FINDINGS: We applied search terms to locate all T2D treatment and management guidelines for adults published in the US from 1977 to 2021. The search captured 158 national guidelines. We subsequently applied the National Academies of Science, Engineering, and Medicine framework to search each guideline for recommendations related to five social care activities: Awareness, Adjustment, Assistance, Advocacy, and Alignment. The majority of guidelines (122; 77%) did not recommend any social care activities. The remainder (36; 23%) referred to one or more social care activities. In the guidelines that referred to at least one type of social care activity, adjustments to medical treatment based on social risk were most common [34/36 (94%)]. Recommended adjustments included decreasing medication costs to accommodate financial strain, changing literacy level or language of handouts, and providing virtual visits to accommodate transportation insecurity. Ensuring that practice guidelines more consistently reflect social care best practices may improve outcomes for patients living with T2D.

Designing and Implementing an Electronic Health Record-Embedded Card Study in Primary Care: Methods and Considerations.

Card studies-short surveys about the circumstances within which patients receive care-are traditionally completed on physical cards. We report on the development of an electronic health record (EHR)-embedded card study intended to decrease logistical challenges inherent to paper-based approaches, including distributing, tracking, and transferring the physical cards, as well as data entry and respondent prompts, while simultaneously decreasing the complexity for participants and facilitating rich analyses by linking to clinical and demographic data found in the EHR. Developing the EHR-based programming and data extraction was time consuming, required specialized expertise, and necessitated iteration to rectify issues encountered during implementation. Nonetheless, future EHR-embedded card studies will be able to replicate many of the same processes as informed by these results. Once built, the EHR-embedded card study simplified survey implementation for both the research team and clinic staff, resulting in research-quality data, the ability to link survey responses to relevant EHR data, and a 79% response rate. This detailed accounting of the development and implementation process, including issues encountered and addressed, might guide others in conducting EHR-embedded card studies.

Strengthening methods for tracking adaptations and modifications to implementation strategies.

BACKGROUND: Developing effective implementation strategies requires adequate tracking and reporting on their application. Guidelines exist for defining and reporting on implementation strategy characteristics, but not for describing how strategies are adapted and modified in practice. We built on existing implementation science methods to provide novel methods for tracking strategy modifications. METHODS: These methods were developed within a stepped-wedge trial of an implementation strategy package designed to help community clinics adopt social determinants of health-related activities: in brief, an 'Implementation Support Team' supports clinics through a multi-step process. These methods involve five components: 1) describe planned strategy; 2) track its use; 3) monitor barriers; 4) describe modifications; and 5) identify / describe new strategies. We used the Expert Recommendations for Implementing Change taxonomy to categorize strategies, Proctor et al.'s reporting framework to describe them, the Consolidated Framework for Implementation Research to code barriers / contextual factors necessitating modifications, and elements of the Framework for Reporting Adaptations and Modifications-Enhanced to describe strategy modifications. RESULTS: We present three examples of the use of these methods: 1) modifications made to a facilitation-focused strategy (clinics reported that certain meetings were too frequent, so their frequency was reduced in subsequent wedges); 2) a clinic-level strategy addition which involved connecting one study clinic seeking help with community health worker-related workflows to another that already had such a workflow in place; 3) a study-level strategy addition which involved providing assistance in overcoming previously encountered (rather than de novo) challenges. CONCLUSIONS: These methods for tracking modifications made to implementation strategies build on existing methods, frameworks, and guidelines; however, as none of these were a perfect fit, we made additions to several frameworks as indicated, and used certain frameworks' components selectively. While these methods are time-intensive, and more work is needed to streamline them, they are among the first such methods presented to implementation science. As such, they may be used in research on assessing effective strategy modifications and for replication and scale-up of effective strategies. We present these methods to guide others seeking to document implementation strategies and modifications to their studies. TRIAL REGISTRATION: clinicaltrials.gov ID: NCT03607617 (first posted 31/07/2018).

Role of Health Information Technology in Addressing Health Disparities: Patient, Clinician, and System Perspectives.

Over the last decade, health information technology (IT) has dramatically transformed medical practice in the United States. On May 11-12, 2017, the National Institute on Minority Health and Health Disparities, in partnership with the National Science Foundation and the National Health IT Collaborative for the Underserved, convened a scientific workshop, "Addressing Health Disparities with Health Information Technology," with the goal of ensuring that future research guides potential health IT initiatives to address the needs of health disparities populations. The workshop examined patient, clinician, and system perspectives on the potential role of health IT in addressing health disparities. Attendees were asked to identify and discuss various health IT challenges that confront underserved communities and propose innovative strategies to address them, and to involve these communities in this process. Community engagement, cultural competency, and patient-centered care were highlighted as key to improving health equity, as well as to promoting scalable, sustainable, and effective health IT interventions. Participants noted the need for more research on how health IT can be used to evaluate and address the social determinants of health. Expanding public-private partnerships was emphasized, as was the importance of clinicians and IT developers partnering and using novel methods to learn how to improve health care decision-making. Finally, to advance health IT and promote health equity, it will be necessary to record and capture health disparity data using standardized terminology, and to continuously identify system-level deficiencies and biases.

Bringing Social Context into Diabetes Care: Intervening on Social Risks versus Providing Contextualized Care.

PURPOSE OF REVIEW: Patient social and economic risk information can guide diabetes care through social risk-targeted care (directly intervening on social risk factors) or social risk-informed care (modifying or tailoring care to accommodate social risks). We review evidence supporting these approaches and highlight critical gaps in the current evidence. RECENT FINDINGS: Literature is scarce on isolated social care interventions and the impact on glycemic control is unclear, while blended social-behavioral interventions more consistently point to reductions in HbA1c. Social risk-informed care naturally occurs at low rates, yet holds potential to improve care. Momentum is building around programs designed to intervene on social risk factors and/or to contextualize care based on social context. Future work will need to isolate the impacts of these programs, clarify the pathways through which social care programs can improve outcomes, and identify provider barriers and facilitators to using social risk information in care.

Building Meaningful Patient Engagement in Research: Case Study From ADVANCE Clinical Data Research Network.

BACKGROUND: Strategies to engage patients to improve and enhance research and clinical care are increasingly being implemented in the United States, yet little is known about best practices for or the impacts of meaningful patient engagement. OBJECTIVE: We describe and reflect on our patient stakeholder groups, engagement framework, experiences, and lessons learned in engaging patients in research, from generating proposal ideas to disseminating findings. SETTING: The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network is the nation's largest clinical dataset on the safety net, with outpatient clinical data from 122 health systems (1109 clinics) in 23 states. RESULTS: Patients stakeholders codeveloped the ADVANCE engagement framework and its implementation in partnership with network leaders. In phase I of ADVANCE, patients were involved with designing studies (input on primary outcome measures and methods) and usability testing (of the patient portal). In phase II, the network is prioritizing research training, dissemination opportunities, an "ambassador" program to pair more experienced patient stakeholders with those less experienced, and evaluation of engagement activities and impacts. DISCUSSION: The ADVANCE framework for patient engagement has successfully involved a diverse group of patients in the design, implementation, and interpretation of comparative effectiveness research. Our experience and framework can be used by other organizations and research networks to support patient engagement activities.

Adoption of Social Determinants of Health EHR Tools by Community Health Centers.

PURPOSE: This pilot study assessed the feasibility of implementing electronic health record (EHR) tools for collecting, reviewing, and acting on patient-reported social determinants of health (SDH) data in community health centers (CHCs). We believe it is the first such US study. METHODS: We implemented a suite of SDH data tools in 3 Pacific Northwest CHCs in June 2016, and used mixed methods to assess their adoption through July 2017. We modified the tools at clinic request; for example, we added questions that ask if the patient wanted assistance with SDH needs. RESULTS: Social determinants of health data were collected on 1,130 patients during the study period; 97% to 99% of screened patients (n = 1,098) had ≥1 SDH need documented in the EHR, of whom 211 (19%) had an EHR-documented SDH referral. Only 15% to 21% of patients with a documented SDH need indicated wanting help. Examples of lessons learned on adoption of EHR SDH tools indicate that clinics should: consider how to best integrate tools into existing workflow processes; ensure that staff tasked with SDH efforts receive adequate tool training and access; and consider that timing of data entry impacts how and when SDH data can be used. CONCLUSIONS: Our results indicate that adoption of systematic EHR-based SDH documentation may be feasible, but substantial barriers to adoption exist. Lessons from this study may inform primary care providers seeking to implement SDH-related efforts, and related health policies. Far more research is needed to address implementation barriers related to SDH documentation in EHRs.

Electronic health record tools to assist with children's insurance coverage: a mixed methods study.

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.

Cardiovascular care guideline implementation in community health centers in Oregon: a mixed-methods analysis of real-world barriers and challenges.

BACKGROUND: Spreading effective, guideline-based cardioprotective care quality improvement strategies between healthcare settings could yield great benefits, particularly in under-resourced contexts. Understanding the diverse factors facilitating or impeding such guideline implementation could improve cardiovascular care quality and outcomes for vulnerable patients. METHODS: We sought to identify multi-level factors affecting uptake of cardioprotective care guidelines in community health centers (CHCs), within a successful trial of cross-setting implementation of an effective intervention. Quantitative analyses used multivariable logistic regression to examine in-person patient encounters at 10 CHCs from June 2011-May 2014. At these encounters, a point-of-care alert flagged adults with diabetes who were clinically indicated for, but not currently prescribed, cardioprotective medications. The main outcome measure was the rate of relevant prescriptions issued within two days of encounters. Qualitative analyses focused on CHC providers and staff, and, guided by the constant comparative method, were used to enhance understanding of the factors that influenced this prescribing. RESULTS: Recommended prescribing occurred at 13-16% of encounters with patients who were indicated for such prescribing. The odds of this prescribing were higher when the patient was male, had HbA1c ≥7, was previously prescribed a similar medication, gave diabetes as the chief complaint, saw a mid-level practitioner, or saw their primary care provider. The odds were lower when the patient was insured, had ≥1 clinic visits in the past year, had kidney disease, or was prescribed certain other medications. Additional factors were associated with prescribing of each medication class. Qualitative results both supported and challenged the quantitative findings, illustrating important tensions involved in guideline-based prescribing. Clinic staff stressed the importance of the provider-patient relationship in guiding prescribing decisions in the face of competing priorities and care needs, and the impact of rapidly changing guidelines. CONCLUSIONS: Diverse factors associated with guideline-concordant prescribing illuminate the complexity of delivering evidence-based care in CHCs. We present possible strategies for addressing barriers to guideline-based prescribing. CLINICAL TRIALS REGISTRATION: This trial was registered retrospectively. Currently Controlled Trials NCT02299791 . Retrospectively registered 10 November 2014.

Health Care Utilization Rates After Oregon's 2008 Medicaid Expansion: Within-Group and Between-Group Differences Over Time Among New, Returning, and Continuously Insured Enrollees.

BACKGROUND: Although past research demonstrated that Medicaid expansions were associated with increased emergency department (ED) and primary care (PC) utilization, little is known about how long this increased utilization persists or whether postcoverage utilization is affected by prior insurance status. OBJECTIVES: (1) To assess changes in ED, PC, mental and behavioral health care, and specialist care visit rates among individuals gaining Medicaid over 24 months postinsurance gain; and (2) to evaluate the association of previous insurance with utilization. METHODS: Using claims data, we conducted a retrospective cohort analysis of adults insured for 24 months following Oregon's 2008 Medicaid expansion. Utilization rates among 1124 new and 1587 returning enrollees were compared with those among 5126 enrollees with continuous Medicaid coverage (≥1 y preexpansion). Visit rates were adjusted for propensity score classes and geographic region. RESULTS: PC visit rates in both newly and returning insured individuals significantly exceeded those in the continuously insured in months 4 through 12, but were not significantly elevated in the second year. In contrast, ED utilization rates were significantly higher in returning insured compared with newly or continuously insured individuals and remained elevated over time. New visits to PC and specialist care were higher among those who gained Medicaid compared with the continuously insured throughout the study period. CONCLUSIONS: Predicting the effect of insurance expansion on health care utilization should account for the prior coverage history of new enrollees. In addition, utilization of outpatient services changes with time after insurance, so expansion evaluations should allow for rate stabilization.

Healthcare Utilization After a Children's Health Insurance Program Expansion in Oregon.

OBJECTIVE: The future of the Children's Health Insurance Program (CHIP) is uncertain after 2017. Survey-based research shows positive associations between CHIP expansions and children's healthcare utilization. To build on this prior work, we used electronic health record (EHR) data to assess temporal patterns of healthcare utilization after Oregon's 2009-2010 CHIP expansion. We hypothesized increased post-expansion utilization among children who gained public insurance. METHODS: Using EHR data from 154 Oregon community health centers, we conducted a retrospective cohort study of pediatric patients (2-18 years old) who gained public insurance coverage during the Oregon expansion (n = 3054), compared to those who were continuously publicly insured (n = 10,946) or continuously uninsured (n = 10,307) during the 2-year study period. We compared pre-post rates of primary care visits, well-child visits, and dental visits within- and between-groups. We also conducted longitudinal analysis of monthly visit rates, comparing the three insurance groups. RESULTS: After Oregon's 2009-2010 CHIP expansions, newly insured patients' utilization rates were more than double their pre-expansion rates [adjusted rate ratios (95 % confidence intervals); increases ranged from 2.10 (1.94-2.26) for primary care visits to 2.77 (2.56-2.99) for dental visits]. Utilization among the newly insured spiked shortly after coverage began, then leveled off, but remained higher than the uninsured group. CONCLUSIONS: This study used EHR data to confirm that CHIP expansions are associated with increased utilization of essential pediatric primary and preventive care. These findings are timely to pending policy decisions that could impact children's access to public health insurance in the United States.

An early look at rates of uninsured safety net clinic visits after the Affordable Care Act.

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.

Community Health Center Use After Oregon's Randomized Medicaid Experiment.

PURPOSE: There is debate about whether community health centers (CHCs) will experience increased demand from patients gaining coverage through Affordable Care Act Medicaid expansions. To better understand the effect of new Medicaid coverage on CHC use over time, we studied Oregon's 2008 randomized Medicaid expansion (the "Oregon Experiment"). METHODS: We probabilistically matched demographic data from adults (aged 19-64 years) participating in the Oregon Experiment to electronic health record data from 108 Oregon CHCs within the OCHIN community health information network (originally the Oregon Community Health Information Network) (N = 34,849). We performed intent-to-treat analyses using zero-inflated Poisson regression models to compare 36-month (2008-2011) usage rates among those selected to apply for Medicaid vs not selected, and instrumental variable analyses to estimate the effect of gaining Medicaid coverage on use. Use outcomes included primary care visits, behavioral/mental health visits, laboratory tests, referrals, immunizations, and imaging. RESULTS: The intent-to-treat analyses revealed statistically significant differences in rates of behavioral/mental health visits, referrals, and imaging between patients randomly selected to apply for Medicaid vs those not selected. In instrumental variable analyses, gaining Medicaid coverage significantly increased the rate of primary care visits, laboratory tests, referrals, and imaging; rate ratios ranged from 1.27 (95% CI, 1.05-1.55) for laboratory tests to 1.58 (95% CI, 1.10-2.28) for referrals. CONCLUSIONS: Our results suggest that use of many different types of CHC services will increase as patients gain Medicaid through Affordable Care Act expansions. To maximize access to critical health services, it will be important to ensure that the health care system can support increasing demands by providing more resources to CHCs and other primary care settings.

The Association Between Medicaid Coverage for Children and Parents Persists: 2002-2010.

To assess the association between a child's and their parent's public health insurance status during a time when children had access to coverage independent of policies that impacted adults' access. Secondary data from the Oregon Health Plan (OHP) [Oregon's Medicaid and Children's Health Insurance Programs] for families with at least one parent and one child with OHP coverage at any time during the study period (2002-2010). We linked children to their parents in the OHP data set and examined longitudinal associations between the coverage patterns for children and their parents, controlling for several demographic and economic confounders. We tested for differences in the strength of associations in monthly coverage status in five time periods throughout the nine-year study period. The odds of a child being insured by the OHP in months in which at least one parent had OHP coverage were significantly higher than among children whose parents were not enrolled at that time. Children with at least one parent who maintained or gained OHP coverage in a given month had a much higher probability of being enrolled in the OHP in that month, compared to children who had no covered parents in the given month or the month prior. Despite implementation of policies that differentially affected eligibility requirements for children and adults, strong associations persisted between coverage continuity for parents and children enrolled in Oregon public health insurance programs.

Using electronic health record data to evaluate preventive service utilization among uninsured safety net patients.

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.

Health information technology: an untapped resource to help keep patients insured.

The recent confluence of: (1) changing state and national insurance-related policies, and (2) the rapid growth in electronic health record (EHR) use, yields an unprecedented opportunity for patient-centered medical homes (PCMHs) and other primary care practices or care settings to use health information technology (HIT) and health information exchange (HIE) in novel ways to impact patient health. We propose that HIT is an untapped resource for supporting clinic-based efforts to help eligible patients obtain and maintain insurance coverage. This commentary presents a conceptual model and guiding principles for this idea. Additionally, it describes insurance support tools that could be used to conduct 'inreach' and 'outreach' with patients around health insurance, similar to how HIT is used to manage chronic disease and panels of patients, and to improve population health outcomes.

Understanding how low-income families prioritize elements of health care access for their children via the optimal care model.

BACKGROUND: Insurance coverage alone does not guarantee access to needed health care. Few studies have explored what "access" means to low-income families, nor have they examined how elements of access are prioritized when availability, affordability, and acceptability are not all achievable. Therefore, we explored low-income parents' perspectives on accessing health care. METHODS: In-depth interviews with a purposeful sample of 29 Oregon parents who responded to a previously administered statewide survey about health insurance. Transcribed interviews were analyzed by a multidisciplinary team using a standard iterative process. RESULTS: Parents highlighted affordability and limited availability as barriers to care; a continuous relationship with a health care provider helped them overcome these barriers. Parents also described the difficult decisions they made between affordability and acceptability in order to get the best care they could for their children. We present a new conceptual model to explain these experiences accessing care with health insurance: the Optimal Care Model. The model shows a transition from optimal care to a breaking point where affordability becomes the driving factor, but the care is perceived as unacceptable because it is with an unknown provider. CONCLUSIONS: Even when covered by health insurance, low-income parents face barriers to accessing health care for their children. As the Affordable Care Act and other policies increase coverage options across the United States, many Americans may experience similar barriers and facilitators to health care access. The Optimal Care Model provides a useful construct for better understanding experiences that may be encountered when the newly insured attempt to access available, acceptable, and affordable health care services.