Population Health Management最新文献

Social determinants of health (SDOH) have a greater impact on health outcomes than clinical care. It is essential to address SDOH to improve population health outcomes and achieve success in value-based care models. Primary care delivery models have increased the focus on screening for SDOH to meet these needs. However, there are no publications regarding SDOH screening or addressing social needs in gastroenterology practice. Furthermore, there is no evidence regarding the impact of SDOH screening on the business of gastroenterology practice. This study surveyed community gastroenterologists to explore the potential benefits of addressing SDOH in gastrointestinal specialty care.

Providing value-based care (VBC) training to relevant stakeholders promotes broader adoption of VBC principles, which in turn can drive improvements in care coordination, patient outcomes, and cost efficiency across the health system. This study assessed the impact of VBC training on learners' self-reported knowledge and examined how learner characteristics influenced the implementation of VBC principles in professional practice post-training. A 12-week, open online VBC course with 6 modules was developed collaboratively by an academic institution and industry partners. Learners were invited to complete pre- and post-course surveys, and to self-report changes in their knowledge and implementation of VBC principles following course completion. Independent variables included age, geographic residence, education level, biological sex, race/ethnicity, student status, employment status, prior VBC experience, and health care work experience. A linear regression model was used to examine factors associated with increased self-reported knowledge, while logistic regression assessed the relationship between independent variables and the likelihood of learners implementing the course concepts learned in practice. The analytic sample included 715 pre- and post- survey responses. Self-reported knowledge and confidence in VBC concepts increased by 60% by course completion, with 63% of learners reporting early implementation of VBC concepts. Greater increases in self-reported were observed among learners with prior clinical experience and those without prior VBC experience. Learners with higher rates of self-reported VBC implementation were more likely to be female, in full-time employment (35+ hours a week), have prior VBC experience as providers, and undergraduate students. Online VBC education can improve self-reported knowledge and confidence in VBC concepts for a myriad of learners, which translates to increased implementation in health care environments.

Diabetes accounts for 1 in 4 health care dollars spent. Succeeding in value-based payment models depends on identifying those at risk for high costs and providing them with appropriate treatment. The objective was to determine factors associated with type 2 diabetes mellitus costs. In this cohort study, this study used longitudinal data from a national insurer between 2016 and 2020. The authors included individuals aged 65 and older with type 2 diabetes mellitus with at least 12 months of continuous enrollment in Medicare Advantage. Exclusions included those who died during the study period or had incomplete data. Factors included study year, demographics (age, sex, race/ethnicity, language, dual eligibility, rurality), and diabetes complications (Diabetes Complications Severity Index). The outcomes of interest were medical and prescription costs. The study included 49,843 individuals. Diabetes complications (coefficient = $3582.11, P < 0.001), year (coefficient = $1003.22, P < 0.001, 2020 vs. 2016), sex (coefficient = $238.35, P < 0.001, female vs. male), dual eligibility (coefficient = $618.61, P < 0.001, yes vs. no), and rurality (coefficient = $1242.38, P < 0.001, yes vs. no) were associated with higher medical costs. Age (coefficient = $-2851.67, P < 0.001), race/ethnicity (coefficient = $-1458.03, P < 0.001, Black vs. White; coefficient = $-1679.81, P < 0.001, Hispanic vs. White), and language (coefficient = $-2523.29, P < 0.001, Spanish vs. English) were associated with lower medical costs. Individuals who had complications, were female, were dually eligible, and lived in rural communities had higher medical costs. Black, Hispanic, and Spanish-speaking individuals had lower medical costs, mirroring well-known disparities. Policy makers and health care organizations can use these data to more efficiently deliver care to some while ensuring adequate access for others.

Devastating mortality, morbidity, economic, and quality of life impacts have resulted from disasters in the United States. This study aimed to validate a preexisting machine learning (ML) model of household disaster preparedness. Data from 2021 to 23 Federal Emergency Management Agency's National Household Surveys (n = 21,294) were harmonized. Importance features from the preexisting random forest ML model were transferred and tested in multiple linear and logistic regression models with updated datasets. Multiple regression models explained 42%-53% of the variance in household disaster preparedness. Features that improved the odds of overall disaster preparedness included detailed evacuation plans (odds ratios [OR] = 3.5-5.5), detailed shelter plans (OR = 4.3-11.0), having flood insurance (OR = 1.5-2.0), and higher educational attainment (OR = 1.1). Having no specified source of disaster information lowered preparedness odds (OR = 0.11-0.53). When stratified further by older adults with Black racial identities (n = 350), television as a main source of disaster-related information demonstrated associations with increased preparedness odds (OR = 2.2). These results validate the importance of detailed evacuation and shelter planning and the need to consider flood insurance subsidies in population health management to prepare for disasters. Tailored preparedness education for older adults with low educational attainment and targeted television media for subpopulation disaster-related information are indicated. By demonstrating a feasible use case to import ML model findings for regression testing in new datasets, this process promises to enhance population management health equity for those in sites that do not yet utilize local ML.

Physician workload is known to impact provider well-being and individual patient encounters, but less is understood about how provider availability affects broader community health outcomes. Primary care physicians (PCPs) often serve as de facto mental health providers, particularly in underserved communities. This study evaluated whether PCP and mental health provider workload, measured by provider-to-resident ratios, predict population-level physical and mental health outcomes. County-level data from the 2024 Robert Wood Johnson Foundation County Health Rankings dataset (N = 3142 counties) were analyzed using two path analysis models; such models are used to estimate both direct and indirect relationships among multiple predictors and outcomes simultaneously. Predictor variables included provider ratios, percent uninsured (mediator), and self-reported physically and mentally unhealthy days (outcomes). Higher PCP workload was significantly associated with greater numbers of poor physical and mental health days. Mental health provider ratios were not directly associated with either outcome. Indirect effects through the percent uninsured were also significant, particularly for physical health outcomes. These findings suggest that PCPs play a disproportionate role in shaping both mental and physical health at the community level. The analysis supports the conclusion that addressing provider shortages and improving insurance coverage can enhance health outcomes, particularly when efforts are integrated into collaborative care models that distribute workload across providers and align treatment approaches with the diverse psychosocial and medical needs of the populations they serve.

The increasing demand for skilled professionals in population health management (PHM) has highlighted the need for a clear understanding of workforce requirements and competencies. This scoping review aims to address this gap by identifying key roles, responsibilities, and competencies necessary for effective PHM implementation. The review was conducted using PubMed and Google Scholar. Articles focusing on PHM workforce requirements, job titles, roles, responsibilities, and competencies were included. Data were extracted and synthesized to address the research questions. A total of 30 records were reviewed, revealing a diverse range of PHM leadership roles, the importance of interdisciplinary teams, and the need for strategic workforce planning. Five core competency domains were identified: Population Health Knowledge and Expertise, Leadership, Data Literacy and Analytics, Business and Operations, and InterpersonalCommunication Skills. Effective PHM implementation requires a diverse, skilled workforce with clearly defined roles and competencies. These findings provide a framework for workforce development and highlight the need for standardized competency-based training in PHM.

Personal health factors and direct and indirect costs of obesity affect employers and employees. This research aimed to understand perceptions of obesity management and anti-obesity medications (AOMs) among employers and employees. In 2022, people with obesity and employers completed cross-sectional surveys about perceptions of obesity and its management, including AOMs. Data were analyzed with descriptive statistics. Data from 461 employed people with obesity (EwO) and 51 employer representatives (ER) were analyzed. Both EwO and ER acknowledged the impact of obesity on future health problems (88.3%; 100.0%) and perceived obesity as a disease (60.5%; 80.4%) to varied degrees. Both groups perceived an incremental value in combining self-directed lifestyle changes and AOMs (57.5%; 66.7%) and perceived healthcare provider-guided lifestyle change alongside AOMs as the most effective approach for maintaining long-term weight reduction (56.4%; 66.6%). More than two-thirds (68.6%) of ER expressed willingness to revisit their AOM coverage decisions, though cost of medication coverage (72.5%) and affordability of medications for employees (68.7%) were identified as barriers. ER believed that data showing reductions in premiums and claims at their organizations (78.4%) would be helpful in supporting the coverage of AOMs. While EwO and ER were receptive toward AOMs, organization-level barriers existed with AOM coverage. Evidence demonstrating the benefits of evidence-based obesity care, direct/indirect cost reductions, and the impact of obesity may address barriers to AOM coverage and improve obesity care and outcomes of their workforces.