Publications by authors named "Katie Dambrun"

Objective: Increased social risk data collection in health care settings presents new opportunities to apply this information to improve patient outcomes. Clinical decision support (CDS) tools can support these applications. We conducted a participatory engagement process to develop electronic health record (EHR)-based CDS tools to facilitate social risk-informed care plan adjustments in community health centers (CHCs).

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Background: The fee-for-service reimbursement system that dominates health care throughout the United States links payment to a billable office visit with a physician or advanced practice provider. Under Oregon's Alternative Payment and Advanced Care Model (APCM), initiated in 2013, participating community health centers (CHCs) received per-member-per-month payments for empaneled Medicaid patients in lieu of standard fee-for-service Medicaid payments. With Medicaid revenue under APCM no longer tied solely to the volume of visits, the Oregon Health Authority needed a way to document the full range of care and services that CHCs were providing to their patients, including nontraditional patient encounters taking place outside of traditional face-to-face visits with a billable provider.

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Only half of the United States population regularly receives recommended preventive care services. Alternative payment models (e.g.

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Importance: Responding to the substantial research on the relationship between social risk factors and health, enthusiasm has grown around social risk screening in health care settings, and numerous US health systems are experimenting with social risk screening initiatives. In the absence of standard social risk screening recommendations, some health systems are exploring using publicly available community-level data to identify patients who live in the most vulnerable communities as a way to characterize patient social and economic contexts, identify patients with potential social risks, and/or to target social risk screening efforts.

Objective: To explore the utility of community-level data for accurately identifying patients with social risks by comparing the social deprivation index score for the census tract where a patient lives with patient-level social risk screening data.

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Purpose: In an age of value-based payment, primary care providers are increasingly scrutinized on performance metrics that assess quality of care, including the outcomes of their patient population in key areas such as diabetes control. Although such measures often adjust for patient clinical risk factors or clinical complexity, most do not account for the social complexity of patient populations, despite research demonstrating the strong association between social factors and health.

Methods: Using patient electronic health record data from 2 large community health center networks serving safety net patients, we assessed the effect of both clinical and social risk factors on poor glucose control among diabetics.

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Successfully incorporating social determinants of health (SDH) screening into clinic workflows can help care teams provide targeted care, appropriate referrals, and other interventions to address patients' social risk factors. However, integrating SDH screening into clinical routines is known to be challenging. To achieve widespread adoption of SDH screening, we need to better understand the factors that can facilitate or hinder implementation of effective, sustainable SDH processes.

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Introduction: This paper describes the adoption of an electronic health record-based social determinants of health screening tool in a national network of more than 100 community health centers.

Methods: In 2016, a screening tool with questions on 7 social determinants of health domains was developed and deployed in the electronic health record, with technical instructions on how to use the tool and suggested clinical workflows. To understand adoption patterns, the study team extracted electronic health record data for any patient with a community health center visit between June 2016 and May 2018.

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Background: National leaders recommend documenting social determinants of health and actions taken to address social determinants of health in electronic health records, and a growing body of evidence suggests the health benefits of doing so. However, little evidence exists to guide implementation of social determinants of health documentation/action.

Methods: This paper describes a 5-year, mixed-methods, stepped-wedge trial with realist evaluation, designed to test the impact of providing 30 community health centers with step-by-step guidance on implementing electronic health record-based social determinants of health documentation.

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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.

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Little is known about how health care organizations are developing tools for identifying/addressing patients' social determinants of health (SDH). We describe the processes recently used by 6 organizations to develop SDH screening tools for ambulatory care and the barriers they faced during those efforts. Common processes included reviewing literature and consulting primary care staff.

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