Partner-developed electronic health record tools to facilitate social risk-informed care planning.

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). MATERIALS AND METHODS: We identified potential care plan adaptations through systematic reviews of hypertension and diabetes clinical guidelines. The results were used to inform an engagement process in which CHC staff and patients provided feedback on potential adjustments identified in the guideline reviews and on tool form and functions that could help CHC teams implement these suggested adjustments for patients with social risks. RESULTS: Partners universally prioritized tools for social risk screening and documentation. Additional high-priority content included adjusting medication costs and changing follow-up plans based on reported social risks. Most content recommendations reflected partners' interests in encouraging provider-patient dialogue about care plan adaptations specific to patients' social needs. Partners recommended CDS tool functions such as alerts and shortcuts to facilitate and efficiently document social risk-informed care plan adjustments. DISCUSSION AND CONCLUSION: CDS tools were designed to support CHC providers and staff to more consistently tailor care based on information about patients' social context and thereby enhance patients' ability to adhere to care plans. While such adjustments occur on an ad hoc basis in many care settings, these are among the first tools designed both to systematize and document these activities.

Adjusting for Patient Economic/Access Issues in a Hypertension Quality Measure.

INTRODUCTION: The American Heart Association and American College of Cardiology have proposed adjusting hypertension-related care quality measures by excluding patients with economic/access issues from the denominator of rate calculations. No research to date has explored the methods to operationalize this recommendation or how to measure economic/access issues. This study applied and compared different approaches to populating these denominator exceptions. METHODS: Electronic health record data from 2019 were used in 2021 to calculate hypertension control rates in 84 community health centers. A total of 10 different indicators of patient economic/access barriers to care were used as denominator exclusions to calculate and then compare adjusted quality measure performance. Data came from a nonprofit health center‒controlled network that hosts a shared electronic health record for community health centers located in 22 states. RESULTS: A total of 5 of 10 measures yielded an increase in adjusted hypertension control rates in ≥50% of clinics (average rate increases of 0.7-3.71 percentage points). A total of 3 of 10 measures yielded a decrease in adjusted hypertension control rates in >50% of clinics (average rate decreases of 1.33-13.82 percentage points). A total of 5 measures resulted in excluding >50% of the clinic's patient population from quality measure assessments. CONCLUSIONS: Changes in clinic-level hypertension control rates after adjustment differed depending on the measure of economic/access issue. Regardless of the exclusion method, changes between baseline and adjusted rates were small. Removing community health center patients experiencing economic/access barriers from a hypertension control quality measure resulted in excluding a large proportion of patients, raising concerns about whether this calculation can be a meaningful measure of clinical performance.

Reduction of Long-Term Opioid Prescribing for Back Pain in Community Health Centers After a Medicaid Policy Change.

INTRODUCTION: Beginning around 2011, innumerable policies have aimed to improve pain treatment while minimizing harms from excessive use of opioids. It is not known whether changing insurance coverage for specific conditions is an effective strategy. We describe and assess the effect of an innovative Oregon Medicaid back/neck pain coverage policy on opioid prescribing patterns. METHODS: This retrospective cohort study uses electronic health record data from a network of community health centers (CHCs) in Oregon to analyze prescription opioid dose changes among patients on long-term opioid treatment (LOT) affected by the policy. RESULTS: Of the 1,789 patients on LOT at baseline, 41.6% had an average daily dose of <20 morphine milligram equivalents (MME), 32.3% had ≥20 to <50 MME, 14.5% had ≥50 to <90 MME, and 11.6% ≥90 MME. Around half of each group discontinued opioids within the 18-month policy period. Those who discontinued did so gradually (average of 11 months) regardless of starting dosage. Predictors of discontinuation included: diagnosis of opioid use disorder, older, non-Hispanic white, and less medical complexity. CONCLUSIONS: Regardless of starting opioid dose, nearly half of patients affected by the 2016 Oregon Medicaid back/neck pain treatment policy no longer received opioid prescriptions by the end of the 18-month study period; another 30% decreased their dose. Gradual dose reduction was typical. These outcomes suggest that the policy impacted opioid prescribing. Understanding patient experiences resulting from such policies could help clinicians and policy makers navigate the complex balance between potential harms and benefits of LOT.

Using Electronic Health Record-Based Clinical Decision Support to Provide Social Risk-Informed Care in Community Health Centers: Protocol for the Design and Assessment of a Clinical Decision Support Tool.

BACKGROUND: Consistent and compelling evidence demonstrates that social and economic adversity has an impact on health outcomes. In response, many health care professional organizations recommend screening patients for experiences of social and economic adversity or social risks-for example, food, housing, and transportation insecurity-in the context of care. Guidance on how health care providers can act on documented social risk data to improve health outcomes is nascent. A strategy recommended by the National Academy of Medicine involves using social risk data to adapt care plans in ways that accommodate patients' social risks. OBJECTIVE: This study's aims are to develop electronic health record (EHR)-based clinical decision support (CDS) tools that suggest social risk-informed care plan adaptations for patients with diabetes or hypertension, assess tool adoption and its impact on selected clinical quality measures in community health centers, and examine perceptions of tool usability and impact on care quality. METHODS: A systematic scoping review and several stakeholder activities will be conducted to inform development of the CDS tools. The tools will be pilot-tested to obtain user input, and their content and form will be revised based on this input. A randomized quasi-experimental design will then be used to assess the impact of the revised tools. Eligible clinics will be randomized to a control group or potential intervention group; clinics will be recruited from the potential intervention group in random order until 6 are enrolled in the study. Intervention clinics will have access to the CDS tools in their EHR, will receive minimal implementation support, and will be followed for 18 months to evaluate tool adoption and the impact of tool use on patient blood pressure and glucose control. RESULTS: This study was funded in January 2020 by the National Institute on Minority Health and Health Disparities of the National Institutes of Health. Formative activities will take place from April 2020 to July 2021, the CDS tools will be developed between May 2021 and November 2022, the pilot study will be conducted from August 2021 to July 2022, and the main trial will occur from December 2022 to May 2024. Study data will be analyzed, and the results will be disseminated in 2024. CONCLUSIONS: Patients' social risk information must be presented to care teams in a way that facilitates social risk-informed care. To our knowledge, this study is the first to develop and test EHR-embedded CDS tools designed to support the provision of social risk-informed care. The study results will add a needed understanding of how to use social risk data to improve health outcomes and reduce disparities. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/31733.