Population Health Management最新文献

Screening for social determinants of health (SDOH) has been mandated by health systems nationwide. However, a gap exists in closed-loop referral for care coordination between health care and social services. This article presents the framework of a technology-based project to facilitate closed-loop referral between health care and social service agencies in Greater Houston by leveraging and connecting the existing care coordination technology infrastructure. Ten health care and social service organizations in Greater Houston participated in the demonstration project initiated in January 2023. The authors leveraged and linked regional health information exchange (HIE) technology with a master patient index of >18 million, and sector-specific care coordination platforms to build closed-loop referral capacity between HIE-participating health care organizations and social service organizations to meet patient SDOH needs. Evaluation efforts will assess the reach, adoption, implementation, and the effectiveness of the closed-loop framework in improving social and health outcomes. The framework comprised the following 4 components: (1) establishment of collaborative governance for shared decision-making processes, fostering trust, alignment, and transparency among organizations; (2) development of technology linkages between existing platforms to facilitate seamless referrals between organizations and ensure visibility of referral outcomes; (3) integration of regional resource directories into technology infrastructure to ensure resource accessibility/quality; and (4) evaluation of the system's impact on health equity, efficiency, and cost reduction. This project aimed to close the loop for care coordination between health care and social service agencies, enable data evaluation to determine care coordination effectiveness, and lay the foundation for SDOH-related research/practice equitably.

Cardiovascular disease (CVD) remains a major national health challenge with significant disparities linked to socioeconomic status, race, ethnicity, sex, and geography, prompting federal efforts to build statewide primary care quality improvement (QI) cooperatives to improve heart health. To be effective, cooperatives require high levels of member engagement and leaders need ways to assess engagement. The objective of this study was to develop and validate a novel Cooperative Member Survey to assess cooperative member engagement and assess the value of the cooperative to members across three statewide heart health QI cooperatives. The 14-item survey included fixed-response and open-ended questions and was developed through multiple iterative rounds across the three cooperatives to gain consensus on the wording of final items using a Delphi process. The survey then was administered to the key stakeholders in the three cooperatives. Findings from both the quantitative and qualitative items were analyzed and reported based on frequencies and emerging themes. The survey was then analyzed to determine factor structure and validity. Analysis revealed a two-factor structure which the research team identified as: (1) Cooperative Engagement, consisting of 11 items that measured how well the cooperative functioned overall, and (2) Cooperative Value, consisting of two items that assessed the perceived value of mutual learning and respect within the cooperative. This two-factor structure indicated that the Cooperative Member Survey successfully captured both the practical aspects of how the cooperative operates and the members' perceived benefits of their involvement. Successful QI cooperatives not only require efficient operations but also a sense of shared value among members. These findings suggest that cooperatives designed to improve public health outcomes may benefit from focusing not only on practical aspects of engagement but also on cultivating mutual respect and collective learning.

Social risks refer to individuals' social and economic conditions shaped by underlying social determinants of health. Health care delivery organizations increasingly screen patients for social risks given their potential impact on health outcomes. However, it can be challenging to meaningfully address patients' needs. Existing frameworks do not comprehensively describe and classify ways in which health care delivery organizations can address social risks after screening. Addressing this gap, the authors developed the Social Risk ACTIONS framework (Actionability Characteristics To Inform Organizations' Next steps after Screening) describing 4 dimensions of actionability: Level of action, Actor, Purpose of action, and Action. First, social risk actions can occur at 3 organizational levels (ie, patient encounter, clinical practice/institution, community). Second, social risk actions are initiated by different staff members, referred to as "actors" (ie, clinical care professionals with direct patient contact, clinical/institutional leaders, and researchers). Third, social risk actions can serve one or more purposes: strengthening relationships with patients, tailoring care, modifying the social risk itself, or facilitating population health, research, or advocacy. Finally, specific actions on social risks vary by level, actor, and purpose. This article presents the Social Risk ACTIONS framework, applies its concepts to 2 social risks (food insecurity and homelessness), and discusses its broader applications and implications. The framework offers an approach for leaders of health care delivery organizations to assess current efforts and identify additional opportunities to address social risks. Future work should validate this framework with patients, clinicians, and health care leaders, and incorporate implementation challenges to social risk action.

Centers for Medicare & Medicaid Services provides reimbursement through Hierarchical Condition Category (HCC) coding. Medical systems strive toward risk adjustment optimization, often implementing costly chart review processes. Previously, our organization implementing countermeasures through workflows was complex and performed in silos. Our goal was to put in place HCC-Risk Adjustment Factor (RAF) improvement tools to optimize HCC-RAF management in Population Health using rapid process improvement methods. In this quality improvement analysis (IRB#806198), we used Lean methodology to develop tools and implement streamlined processes for providers to manage, document, and code high-risk HCC conditions. Rather than applying costly countermeasures, Transformational Healthcare conducted a Rapid Process Improvement Workshop (RPIW), with workgroups implementing proposed changes, to improve processes. Each of these tools was embedded in standard work, for teams to use in practice. Tools included the development of RPIW-inspired work groups, a Provider Education website, tip sheets, clinical champions, trainings, audits, practice alerts, smart phrases, schedule view tools, severity scores, reports, dashboards, on-screen decision-support tools, coding expertise, and HCC standard work. Quantitatively, Year 1 showed enterprise HCC-RAF scores improved by 4.1%. We were able to develop tools for providers and team members to allow for more optimized pathways. Although quantitatively we realized an improvement in enterprise HCC-RAF score, our overall aim was to improve process flow and limit waste. Leveraging Lean improvement methods for the collective design of tools has supported culture change. In the end, we found that providers are indeed willing to adopt these newly built tools. These tools have optimized operations, allowing providers to work smarter, not harder.

Despite focusing on drivers of health, or social determinants of health, for more than a decade, health care organizations have made minimal progress in improving these factors and associated health outcomes. This data- and theory-driven analysis looks at (1) why that is the case and (2) how organizational leaders and operators can go about correcting it. The authors' research finds that lack of progress is often due to ill-fit, entrenched business models that were optimized for a fee-for-service environment and cannot easily pivot to focus on drivers of health. Additionally, leaders are often unclear about what to change and overwhelmed by how to do it. The authors propose a 5-step strategy and execution process to address these challenges, laying out an end-to-end road map that enables health care leaders to meaningfully improve drivers of health and associated health outcomes for their patients and communities.

Composite health indicators are valuable tools to assess population health over time and identify areas for intervention. This scoping review (ScR) aimed to map the literature describing comprehensive health-related metrics used to assess community health. The Arksey and O'Malley framework was used to conduct the ScR, using the following steps: identifying the research question, identifying relevant studies, charting the data, collating and reporting results. United States-based studies that developed/utilized a composite health index using geographic information system (GIS) mapping capabilities to assess community health at the county level or more granular were identified through literature searches conducted in PubMed and EMBASE databases. Literature searches identified 5112 articles; of these, 8 studies describing composite health indices were included. The number of indicators used in each index ranged from 4 to 75 (median: 22). Health outcomes, health behaviors, education, and economics were incorporated into most indices. High school graduation rate (n = 6 indices), health insurance status (n = 5), commute time, median household income, unemployment, and obesity rates (n = 4 each) were the most common indicators across indices. All indicators were derived from publicly available data sources, such as the American Community Survey and US Census Bureau. Although a limited number of community health indices were identified in the ScR, the indices included a broad range of indicators covering both health outcomes and factors contributing to health vulnerabilities. The public data sources and GIS integration of the indices provide potential for broad, insightful applications to various contexts across the United States.

There is a global mental health crisis: mental illness is underrecognized, underdiagnosed, and undertreated with adverse effects on mental, physical, and social health. In the United States, there is an insufficient number of traditional psychiatric and psychological resources to provide the mental health care needed to solve this crisis. Community-based interventions could be an important adjunct to traditional mental health care. An evaluation of peer-reviewed articles was performed describing community-based interventions and identified 3 approaches with some evidence of effectiveness: (1) interventions that enhance community mental health literacy to improve recognition of early signs of mental illness for early engagement and provide community, family, and peer support; (2) community clinics providing social, medical, and mental health care and support to transition-age youth (15-25 years); and (3) social networking activities to enhance interactions among elders suffering from social isolation and loneliness. Multisector, multidisciplinary, and multicomponent interventions involving health care providers and community-based organizations had the best evidence of effectiveness and should target transition-age youth and elders.

Cardiovascular disease (CVD) is a leading cause of premature mortality among patients with severe mental illness (SMI). Effective care delivery models are needed to address this mortality gap. This study examines the impact of an enhanced primary care (PC) program that specializes in the treatment of patients with SMI, called Medicine in Psychiatry Service-Primary Care (MIPS-PC). Using multipayer claims data in Western New York from January 1, 2016 to December 31, 2021, patients with SMI and CVD were identified using International Classification of Diseases, Tenth Revision codes. National Provider Identification numbers of MIPS-PC providers were then used to identify those patients who were treated by MIPS-PC during the period. These MIPS-PC-treated patients were compared against a cohort of one-to-one propensity score matched contemporaneous comparison group (ie, patients receiving PC from providers unaffiliated with MIPS-PC). A difference-in-difference approach was used to identify the treatment effects of MIPS-PC on all-cause emergency department (ED) visits and hospitalization rates. The MIPS-PC group was associated with a downtrend in the acute care utilization rates over a 3-year period following the index date (ie, date of first MIPS-PC or other PC provider encounter), specifically a lower hospitalization rate in the first year since the index date (25%; P < 0.001). ED visit rate reduction was significant in the third-year period (18%; P = 0.021). In summary, MIPS-PC treatment is associated with a decreasing trend in acute care utilization. Prospective studies are needed to validate this effect of enhanced PC in patients with SMI and CVD.

The objective was to examine Medical Advantage (MA) organizations' commitment toward addressing social determinants of health (SDOH) through their health-related social benefit offerings, and the perceived impact of providing supplemental benefits associated with SDOH in their plans. Public reporting documents were reviewed from six of the largest MA firms: Humana, UnitedHealthcare, Cigna, Elevance Health, CVS Health, and Centene. Public reports were obtained from each company's website (eg, from the "Investor Relations" page). Quarterly reports for Q1 2023, annual reports for 2022, and proxy statements for 2023 for all companies were examined. Content analysis of the public reports was conducted under three constructs: (1) Growth of MA in the company, (2) SDOH-related activities in the company, and (3) SDOH-related activities in the MA plans of the company. Each of the three constructs was further analyzed for recurring themes and elements. The findings from content analysis suggests that plans are providing tailored benefits that may address the social needs of vulnerable and underserved populations. Companies that offered supplemental benefits and value-based arrangements that addressed social needs reported beneficiary clinical outcomes resulting in cost savings and increased revenue. Health insurance companies identify MA as a significant growth opportunity and a strategically important market for overall membership and revenue growth. Moreover, companies providing innovative social benefits through their MA plans reported witnessing increased value propositions by underserved and vulnerable populations, leading to increased revenue and cost containment.