Population Health Management最新文献

{"title":"Evaluation of the Electronic Health Record-Support Social Support Score in Breast Cancer: Comparison of Count and Item Response Theory Scores.","authors":"Salene M W Jones, Rhonda-Lee F Aoki, Stacey E Alexeeff, David Carrell, David Cronkite, Lawrence H Kushi, David Mosen, Shaila Strayhorn, Leah Tuzzio, Jessica Mogk, Lauren Mammini, Candyce H Kroenke","doi":"10.1177/19427891251383539","DOIUrl":"https://doi.org/10.1177/19427891251383539","url":null,"abstract":"<p><p>In breast cancer, clinicians add data on social support to patient electronic health records (EHRs) often in free text notes, but those data may be challenging to use for population health initiatives or research purposes. We evaluated the EHR-Support score designed to summarize need for social support using data from the EHR. This study included 996 women from the Pathways study, a Kaiser Permanente Northern California cohort of women diagnosed in 2005-2013 with breast cancer. This unique data resource included both EHR data and questionnaire data on patient-reported social support. Using unstructured EHR data and natural language processing, we developed 11 concept groups (items) characterizing social support. We also used structured data to create two additional concept groups. EHR-Support scores reflecting the lack of social support were generated three ways: counting the number of negative concept groups (count score), using item response theory (IRT), and converting counts to the IRT metric (converted count scores). The count scores were only associated with two of six patient-reported measures (r's: -0.004 to -0.073). The IRT score (r's: -0.038 to -0.179) and converted count score (r's: -0.032 to -0.195) were associated with five of six patient-reported measures, indicating more need for support was associated with less patient-reported social support. The EHR-Support score is a valid and feasible measure of social support that can be used for health services research and managing population health. The converted count score may provide the best balance of validity, precision from IRT and feasibility.</p>","PeriodicalId":20396,"journal":{"name":"Population Health Management","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145239451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Scoping Review of RCT Studies on Community Health Worker Effectiveness.","authors":"Gilbert Gimm, Carolyn Hoffman, Leila Elahi, Len M Nichols","doi":"10.1177/19427891251384659","DOIUrl":"https://doi.org/10.1177/19427891251384659","url":null,"abstract":"<p><p>Community health workers (CHW) play a unique role as trusted frontline public health workers who connect underserved populations with health and social services. In addition, CHWs have local insights on underserved patients and families, which can help to reduce information gaps and enhance the capacity of health care systems to understand health-related social needs. However, prior reviews have included studies of varying quality, which makes it difficult to assess rigorous evidence from randomized control trial (RCT) studies. Also, many CHW intervention studies do not clearly specify in which organizational setting a CHW is employed. This scoping review of US studies published in the peer-reviewed literature from 2000 to 2023 focuses on RCT studies of CHW interventions by type of organization. A total of 39 studies met all inclusion criteria. Most RCT studies were conducted in health care systems and among safety-net providers, including community health centers. However, only a handful of rigorous RCT studies of CHW interventions were conducted in public health agencies or payer settings (managed care organizations). Overall, most RCT studies of CHW interventions found consistent evidence of improved outcomes. Health care organizations can enhance their efforts to address resource gaps by hiring CHWs or partnering with organizations that employ CHWs. Finally, future RCT studies on CHWs employed by health plans (payers) or public health agencies are needed to bolster the growing body of rigorous evidence that CHWs are highly effective in improving patient outcomes across multiple organizational settings.</p>","PeriodicalId":20396,"journal":{"name":"Population Health Management","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145186445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Honoring the Past While Shaping the Future: Reflections From the Incoming Editor-in-Chief.","authors":"Bettina M Beech","doi":"10.1177/19427891251379361","DOIUrl":"https://doi.org/10.1177/19427891251379361","url":null,"abstract":"","PeriodicalId":20396,"journal":{"name":"Population Health Management","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145065270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of Social Determinants of Health in Gastroenterology Care.","authors":"Costas H Kefalas, Mitchell A Kaminski","doi":"10.1177/19427891251369769","DOIUrl":"https://doi.org/10.1177/19427891251369769","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":20396,"journal":{"name":"Population Health Management","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145016064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Influencing Learners' Knowledge and Implementation of Value-Based Care Concepts Postcourse Certification.","authors":"Omolola E Adepoju, Tonghui Xu, Andy Rollins, Susie Gronseth, Maycie ElChoufi, Faith Obanua, Sara McNeil","doi":"10.1177/19427891251365940","DOIUrl":"https://doi.org/10.1177/19427891251365940","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":20396,"journal":{"name":"Population Health Management","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144966118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transforming Population Health in Saudi Arabia: Aligning Strategies with Vision 2030 for a Healthier Future.","authors":"Assim M AlAbdulKader, Mohammed Jabr","doi":"10.1089/pop.2025.0047","DOIUrl":"10.1089/pop.2025.0047","url":null,"abstract":"","PeriodicalId":20396,"journal":{"name":"Population Health Management","volume":" ","pages":"224-227"},"PeriodicalIF":2.1,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143994828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors Associated with Health Care Costs in Older Adults with Type 2 Diabetes: Insights for Value-Based Payment Models.","authors":"Winston Liaw, Omolola E Adepoju, Jiangtao Luo, Bill Glasheen, Ben King, Ioannis Kakadiaris, Todd Prewitt, Pete Womack, Jess Dobbins, Mohammad Madani, Rajit Shah, Carlos G Fuentes, LeChauncy Woodard","doi":"10.1089/pop.2025.0054","DOIUrl":"10.1089/pop.2025.0054","url":null,"abstract":"<p><p>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, <i>P</i> < 0.001), year (coefficient = $1003.22, <i>P</i> < 0.001, 2020 vs. 2016), sex (coefficient = $238.35, <i>P</i> < 0.001, female vs. male), dual eligibility (coefficient = $618.61, <i>P</i> < 0.001, yes vs. no), and rurality (coefficient = $1242.38, <i>P</i> < 0.001, yes vs. no) were associated with higher medical costs. Age (coefficient = $-2851.67, <i>P</i> < 0.001), race/ethnicity (coefficient = $-1458.03, <i>P</i> < 0.001, Black vs. White; coefficient = $-1679.81, <i>P</i> < 0.001, Hispanic vs. White), and language (coefficient = $-2523.29, <i>P</i> < 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.</p>","PeriodicalId":20396,"journal":{"name":"Population Health Management","volume":" ","pages":"191-197"},"PeriodicalIF":2.1,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144120331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Machine Learning Explainability of Disaster Preparedness Models from the FEMA National Household Survey to Inform Tailored Population Health Interventions.","authors":"Taryn Amberson, Wenhui Zhang, Samuel E Sondheim, Wanda Spurlock, Jessica Castner","doi":"10.1089/pop.2024.0243","DOIUrl":"10.1089/pop.2024.0243","url":null,"abstract":"<p><p>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 (<i>n</i> = 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 (<i>n</i> = 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.</p>","PeriodicalId":20396,"journal":{"name":"Population Health Management","volume":" ","pages":"204-213"},"PeriodicalIF":2.1,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12419149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143796215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leading with Love: An Evidence-Informed Framework for Leading Health System Transformation.","authors":"Patrick Runnels, Peter Pronovost","doi":"10.1089/pop.2025.0055","DOIUrl":"10.1089/pop.2025.0055","url":null,"abstract":"","PeriodicalId":20396,"journal":{"name":"Population Health Management","volume":" ","pages":"228-230"},"PeriodicalIF":2.1,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144181208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physician Workload Attenuates the Impact of Mental Health Care Workload on Community Health Outcomes: Implications for Distributing Provider Workload.","authors":"Gregory J Privitera, James J Gillespie, Arpitha Pamula, Brooke J Piper","doi":"10.1089/pop.2025.0080","DOIUrl":"10.1089/pop.2025.0080","url":null,"abstract":"<p><p>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 <i>de facto</i> 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 (<i>N</i> = 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.</p>","PeriodicalId":20396,"journal":{"name":"Population Health Management","volume":" ","pages":"198-203"},"PeriodicalIF":2.1,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144275799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}