Population Health Management最新文献

Type 2 diabetes mellitus (T2D) is a prevalent metabolic disorder with significant health and economic burdens worldwide. The relationship between inflammation-related indicators and the risk of developing new-onset T2D remains underexplored. This study aims to identify and validate an interpretable predictive model for incident T2D using inflammation-related indicators. We analyzed data from 220,937 participants free of diabetes at baseline in the UK Biobank. Six machine learning algorithms were employed to construct predictive models. Feature selection was performed using Least Absolute Shrinkage and Selection Operator regression. SHapley Additive exPlanations (SHAP) were used to interpret the best-performing model. A genetic risk score (GRS, an aggregate measure of genetic susceptibility to T2D) was constructed, and multivariate Cox regression assessed the combined effects of genetic and inflammatory factors on T2D incidence. The Extreme Gradient Boosting model demonstrated the best performance (training set AUC = 0.863, testing set AUC = 0.838). Key predictors included body mass index, cholesterol, age, alanine aminotransferase, high-density lipoprotein, and Prognostic Nutritional Index (a marker predictive of inflammation and nutritional outcomes). SHAP analysis revealed significant contributions from these features. C-reactive protein and white blood cell count showed strong associations with future T2D risk. Integrating the GRS significantly improved the model's predictive performance (ΔAUC = +0.025, P < 0.05 via DeLong's test). This study presents an interpretable machine learning model for new-onset T2D risk prediction, emphasizing the role of inflammation and genetic factors. The findings provide a valuable tool for early T2D prevention and intervention, offering insights into the complex interplay between inflammation and diabetes development.

Cancer is one of the leading causes of morbidity and mortality worldwide, disproportionately affecting low- and middle-income countries (LMICs) due to barriers to obtaining access to health care services and screening programs. The current study aimed to synthesize evidence on cost-effective strategies for cancer screening and early diagnosis in adults (≥18 years) in LMICs. The literature search was conducted in PubMed, the Cochrane Library, Embase, EconLit, CINAHL, LILACS, Global Health, and the Web of Science Core Collection databases. The review included cost-effectiveness studies compared with standard practices in LMICs. Two reviewers independently assessed eligibility, extracted data, and evaluated methodological quality using the Drummond and Jefferson guidelines. Twelve studies conducted in nine countries across four global regions were included. The results identified that the most cost-effective strategies for cervical cancer were human papillomavirus DNA testing, visual inspection with acetic acid, and combined tests. For breast and prostate cancer, digital breast tomosynthesis and the Prostate Health Index were promising options, repectively. However, limitations were noted in the studies, such as the lack of analysis on productivity changes and the justification of variables in sensitivity analyses. Population-based cancer screening strategies exist but must be adapted to the implementation context to maximize their cost-effectiveness in LMICs.

Health systems are integrating interventions to assist patients with food insecurity; however, people need varying levels of support. Rather than using a single intervention, adaptively providing interventions may be a more effective approach. The authors conducted a pilot, sequential, multiple-assignment randomized trial to determine the feasibility of an adaptive food insecurity intervention. Adults with uncontrolled hypertension who reported food insecurity were randomized to one of two interventions for 3 months in Stage 1: information about community resources or community health worker (CHW) support. Participants who did not have ≥10 mmHg improvement in systolic blood pressure at 3 months were re-randomized to CHW support or the delivery of medically tailored meals (MTM) in Stage 2 for an additional 3 months. We evaluated the proportion who enrolled, completed follow-up, and had an improvement in blood pressure. Sixty of 61 (98.3%) eligible patients enrolled. Four withdrew, 46 of 56 (82.1%) completed the 3-month follow-up, and 40 of 56 (71.4%) completed the 6-month follow-up. Of 27 randomized to resource information, 15 (55.6%) did not have ≥10 mmHg improvement and were re-randomized. Of 29 randomized to CHW support, 14 (48.3%) were re-randomized. The adaptive intervention that provided CHW support in Stage 1 and additional CHW support in Stage 2 resulted in 46.7% of participants with ≥10 mmHg improvement in systolic blood pressure at 6 months. The adaptive intervention that provided CHW support in Stage 1 and MTM in Stage 2 resulted in 66.7% of participants with ≥10 mmHg improvement. This study found that an adaptive food insecurity intervention was feasible to utilize.

Health systems worldwide are challenged by the need to prioritize and fund rapidly evolving health technologies. The methodology of health technology assessment (HTA) incorporates benefits, costs, and social implications, supporting prioritization of public coverage regarding national health policy. The aim of this study is to identify, analyze, and compare key considerations in the adoption of medical technologies reflecting the national health policies in Israel and England. All Israeli pharmaceuticals approved for public funding during 2020-2022 (287) were analyzed and compared with England recommendations concerned clinical effectiveness, economic considerations, and social values. Both health systems demonstrated 49% agreement regarding approval of funding recommendations policy, while in oncology, diabetes, and hematology, this reached 60%-65%. In both health systems, adoption was determined by clinical impact considering the disease burden and regarding the added value of the innovative technology compared with existing treatments, followed by social considerations. Budget considerations prevail in England. This relatively high resemblance in adoption decisions between England and Israel may emerge from similar principles of accountability for public coverage of medical care. In addition, it may also be driven by the forefront of innovative technological research worldwide and global interest. Nevertheless, economic considerations differ between the 2 health systems, introducing policy discrepancies or tactical diversity.

Differences in preference-weighted health-related quality of life (HRQOL) scores by race/ethnicity may be due to social factors. Here, Short-Form Six-Dimension (SF-6D) scores are analyzed among men in a prostate cancer prevention trial to explore such differences. Selenium and vitamin E cancer prevention trial participants who completed the SF-6D at baseline, and in at least 1 of follow-up years 1, 3, and 5 were included. This study compared mean SF-6D scores across race/ethnicity at each point using a linear mixed model controlling for demographic and clinical characteristics. At baseline, 9691 men were eligible for analysis, of whom 7556 (78%) were non-Hispanic White, 1592 (16.4%) were non-Hispanic Black, and 543 (5.6%) were Hispanic. Hispanic and White participants had higher unadjusted mean SF-6D scores than Black participants at every time point (P < 0.05), while white participants had lower mean scores than Hispanic participants at every time point after baseline (P < 0.05). After adjusting for covariates, statistically significant differences in HRQOL among the 3 groups persisted. Hispanic participants had higher preference scores than White participants by 0.073 (P < 0.001), 0.075 (P < 0.001), and 0.040 (P < 0.001) in follow-up years 1, 3, and 5, respectively. Black participants had lower scores than White participants by 0.009 (P = 0.004) and 0.008 (P = 0.02) in follow-up years 1 and 3, respectively. The results suggest there is a preference-weighted HRQOL difference by race/ethnicity that cannot be explained by social and clinical variables alone. Understanding how individuals belonging to different racial/ethnic categories view their own HRQOL is necessary for culturally competent care and cost-effectiveness analyses.

Recombinant zoster vaccine (RZV) was recommended in 2020 in the US for adults aged ≥50 years. This retrospective study used cross-sectional data from 2020 National Health Interview Survey respondents aged ≥50 years. Sample weights were applied to allow results to be representative of the non-institutionalized US population. Associations between respondent characteristics and coverage were explored using logistic regression. An estimated 14.1% of US adults aged ≥50 years had received ≥1 dose of RZV by 2020. Coverage varied by race and ethnicity (6.3% Hispanic, 6.9% Black/African American, 13.7% Asian, 16.6% White), education (6.9% for grade 1-11 to 24.1% with master's degrees), household income (8.8% for <$35,000 to 18.8% for ≥$100,000), age (7.3%, 14.6%, 19.9%, and 18.1% for ages 50-59, 60-64, 65-74, and ≥75 years, respectively), health insurance (2.2% without, 14.8% with), recency of last health visit (1.8% if >3 years prior to 15.1% if <1 year), and receipt of influenza vaccine in the past year (3.9% without, 21.1% with) (all P < 0.001). In multivariable analysis, factors associated with lower RZV coverage included Black/African American race, Hispanic ethnicity, age 50-59 years, lower household income, less recent last health visit, and no influenza vaccination. In conclusion, only 1-in-7 non-institutionalized Americans aged ≥50 years reported RZV coverage by 2020, with significant disparities among subgroups defined by race and ethnicity, age, and levels of educational attainment, income, and insurance. These results highlight an opportunity to improve herpes zoster protection through increased vaccination, pursued in a more equitable manner. [Figure: see text].

Complex care curricula (or "interprofessional student hotspotting") are experiential, longitudinal programs based on complex care practice models where health professions students engage patients with complex health and social needs through personalized, hands-on interventions. Prior studies report mixed impacts of complex care curricula and practice models on hospital readmissions and health care costs, but evaluation of patient-driven goals and outcomes has been sparse. The objective of this study was to characterize the goals of individuals with complex health and social needs that engage with complex care curricula and the associated interventions and barriers reported by interprofessional student teams. Capstone projects of 30 student teams spanning a 5-year period (2015-2020) were analyzed via directed content analysis to identify patient goals, team interventions, and barriers. Thematic analysis revealed that the most common patient goals and team interventions focused on enhancing self-efficacy in managing health (72% and 59%, respectively) and health care system navigation (50% and 69%). Identified barriers fell into 3 major categories: barriers encountered with the health system (28%), related to the individual (66%), and arising in teamwork (50%). Over the course of each curricular cycle, students graduated with an appreciation of the importance of collaborative care for complex patients. The longitudinal impact of this analysis emphasizes patients as key stakeholders in the development of complex care curricula. By deepening our understanding of patient goals, intervention trends, and barriers-we allow for enhanced programming that prepares health professionals for practice, optimizes collaboration on interprofessional health teams, and ensures better outcomes for patients.

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.

Patients with co-occurring medical and psychiatric conditions often face fragmented care and prolonged hospitalizations in traditional medical units (MUs). Integrated medical-psychiatry units (MPUs) offer a model of concurrent care that may better meet the needs of these patients, but limited data exist on which patient populations benefit most. This study retrospectively compared outcomes for patients with psychiatric conditions discharged from an MPU versus traditional MUs within a single academic medical center between 2019 and 2023. Subgroups included patients presenting with suicidal ideation (SI) or toxic overdose (OD). Primary outcomes were length of stay (LOS) and discharge to the community. MPU patients were younger, more likely to be on Medicaid, and had significantly higher rates of psychotic, mood, substance use, and cognitive disorders (all P < 0.001). Despite this higher psychiatric complexity, MPU patients had shorter LOS and higher rates of discharge to home than their counterparts on general MUs, even after adjusting for demographic and clinical differences. Among patients with SI, those on the MPU had an average LOS of 5.5 days compared to 6.7 days in traditional units (P = 0.006). These findings highlight the effectiveness of MPUs in managing complex, high-need patients and support the broader implementation of integrated, interdisciplinary care models to improve hospital outcomes and care transitions for vulnerable populations.

Bulk messaging is an important population health tool used to engage patients in preventive care and chronic disease management, yet little is known about optimal formatting of the communication. One factor to consider is whether the signatory of the patient-facing communication is the patient's own Primary Care Provider (PCP) or a generic care team signature. In this quasi-randomized, non-blinded study we compared identical generic bulk outreach messages directed toward patients with an upcoming appointment and invited them to self-schedule a Medicare Annual wellness visit prior to their scheduled PCP appointment. Twenty-eight PCPs (1582 patients) were assigned to the PCP signature group, and 22 PCPs (1289 patients) to the care team signature group. The primary outcome was patient engagement, defined as a reply to the outreach message. Demographic, utilization, and rates of reading the bulk outreach message were similar between groups. Reply rates were significantly higher in the PCP signature group compared with the care team signature group (39.2% vs. 25.2%; odds ratio 1.86; P < 0.001). These findings suggest that using a patient's own PCP signature in bulk outreach can meaningfully increase engagement, likely leveraging the trust inherent in established PCP-patient relationships. These results may inform health system leaders and population health teams seeking to optimize digital outreach strategies.