Population Health Management最新文献

The authors describe a rapid implementation of medication treatment for substance use disorders in a value-based organization, delivered in the community-based, interdisciplinary primary care of Medicaid and dual-eligible members. The determinants of increased need are reviewed, as well as the growing opportunity to improve access to treatments, and a template for implementation is shared.

This cross-sectional study assessed hepatitis C virus (HCV) antibody and RNA test results performed from 2016 to 2021 at a large US clinical reference laboratory. When individual patient factors (ie, income, education, and race/ethnicity) were not available, estimates from the US Census were linked to the residential zip code. The final analytic cohort comprised 19,543,908 individuals with 23,233,827 HCV antibody and RNA test results. An analysis of progressively increasing poverty quintiles demonstrated an increasing trend in both HCV antibody positivity (from 2.6% in the lowest quintile to 6.9% in the highest, P < 0.001 for trend) and HCV RNA positivity (from 1.0% to 3.6%, P < 0.001 for trend). Increasing levels of education were associated with a decreasing trend in both HCV antibody positivity (from 8.4% in the least educated quintile to 3.0% in the most, P < 0.001 for trend) and HCV RNA positivity (from 4.7% to 1.2%, P < 0.001 for trend). Persistent differences in positivity rates by these social determinants were observed over time. HCV antibody and RNA positivity rates were nearly identical in predominantly Black non-Hispanic, Hispanic, and White non-Hispanic zip codes. However, after adjustment for all other factors in the study, residents of predominantly Black non-Hispanic and Hispanic zip codes were significantly less likely to test positive for HCV RNA (adjusted odds ratios [AOR]: 0.51, 95% confidence interval [CI]: 0.51-0.52; AOR: 0.46, 95% CI: 0.46-0.46, respectively). These findings may benefit targeted intervention initiatives by public health agencies.

Advanced Care at Home is a Mayo Clinic hospital-at-home (HaH) program that provides hospital-level care for patients. The study examines patient- and community-level factors that influence health outcomes. The authors performed a retrospective study using patient data from July 2020 to December 2022. The study includes 3 Mayo Clinic centers and community-level data from the Agency for Healthcare Research and Quality. The authors conducted binary logistic regression analyses to examine the relationship among the independent variables (patient- and community-level characteristics) and dependent variables (30-day readmission, mortality, and escalation of care back to the brick-and-mortar hospital). The study examined 1433 patients; 53% were men, 90.58% were White, and 68.2% were married. The mortality rate was 2.8%, 30-day readmission was 11.4%, and escalation back to brick-and-mortar hospitals was 8.7%. At the patient level, older age and male gender were significant predictors of 30-day mortality (P-value <0.05), older age was a significant predictor of 30-day readmission (P-value <0.05), and severity of illness was a significant predictor for readmission, mortality, and escalation back to the brick-and-mortar hospital (P-value <0.01). Patients with COVID-19 were less likely to experience readmission, mortality, or escalations (P-value <0.05). At the community level, the Gini Index and internet access were significant predictors of mortality (P-value <0.05). Race and ethnicity did not significantly predict adverse outcomes (P-value >0.05). This study showed promise in equitable treatment of diverse patient populations. The authors discuss and address health equity issues to approximate the vision of inclusive HaH delivery.

The health care industry is experiencing a transformative shift from traditional fee-for-service models to value-based care (VBC), emphasizing improved patient outcomes, enhanced quality, and reduced costs. While Centers for Medicare & Medicaid Services Innovation Center models focus on financial and quality outcomes, a critical opportunity for reform lies in organizational culture. VBC signifies a cultural and systemic evolution aligned with the quintuple aim of enhancing equitable patient outcomes, improving quality, reducing costs, and prioritizing provider well-being. Cultural impacts play a pivotal role in this transformation.

Obesity-related comorbidities (ORCs) cause significant economic and clinical burdens for people with obesity and the US health care system. A reduction in weight at the population level may reduce incident ORC diagnoses and associated costs of treatment. The aim of this work is to describe obesity burden in the United States through the prevalence and direct treatment costs of ORCs, as well as the clinical and economic value of 15% weight loss in a population of adults with obesity. The IQVIA Ambulatory US electronic medical record database was used to create a cohort (7,667,023 individuals 20-69 years of age, body mass index of 30-50 kg/m²), utilized to characterize the prevalence of 10 ORCs. Direct treatment costs were collected from literature reports. A risk model was leveraged to estimate the number and cost of additional ORC diagnoses over 5 years from baseline through two scenarios: stable weight and 15% lower body weight at baseline for all members of the population. Prevalence, incidence, and cost data were scaled down to a representative subset of 100,000 individuals. In 2022, the annual treatment costs for all 10 ORCs exceeded $918 million for the representative cohort. In a stable-weight scenario, these costs were estimated to increase to ≈$1.4 billion by 2027. With 15% lower body weight at baseline, $221 million in cumulative savings was estimated, corresponding to $2205 in savings/patient over 5 years. Consequently, weight loss in this population may correspond to significantly reduced numbers of incident ORC complications translating to substantial cost savings.

For-profit companies addressing disparities in social determinants of health (SDOH), also known as SDOH Industry companies, often lack member-level claims data to evaluate their organizational interventions. Health-related quality of life (HRQOL) measures, such as the Centers for Disease Control and Prevention's Healthy Days Measure, offer a unique proxy metric to evaluate impact. This retrospective study sought to explore the association between self-reported physically and mentally unhealthy days with health care costs among a Medicare Advantage (MA) population. A cross-sectional study of MA members receptive to a companion care program, and thus likely to have unmet social needs, was conducted. The analysis included members with recorded baseline unhealthy days and complete claims data (n = 2,354). Least squares regression analyses were performed to determine the relationship between baseline medical costs, physically unhealthy days, and mentally unhealthy days. A review of Major Diagnostic Categories (MDCs) was also included to elucidate the strength of the Healthy Days Measure as an indicator of the burden of health conditions. Each additional unhealthy day reported was associated with an increase in 30-day medical costs of $60 and $34 for physically and mentally unhealthy days, respectively. Unhealthy days and costs increased with an increasing number of MDCs. Compared with previous studies linking unhealthy days and health care expenditure, these data reveal the potential for even higher savings by reducing the number of unhealthy days in a high-risk population. This evidence supports using unhealthy days as a HRQOL measure and as an important tool for cost estimations.

Chronic kidney disease (CKD) is common, costly, and life-limiting, requiring dialysis and transplantation in advanced stages. Although effective guideline-based therapy exists, the asymptomatic nature of CKD together with low health literacy, adverse social determinants of health, unmet behavioral health needs, and primary care providers' (PCP) limited understanding of CKD result in defects in screening and diagnosis. Care is fragmented between PCPs and specialty nephrologists, with limited time, expertise, and resources to address systemic gaps. In this article, the authors define how they classified defects in care and report the current numbers of patients exposed to these defects, both nationally and in their health system Accountable Care Organization. They describe use of the health system's three-pillar leadership model (believing, belonging, and building) to empower providers to transform CKD care. Believing entailed engaging individuals to believe defects in CKD care could be eliminated and were a collective responsibility. Belonging fostered the creation of learning communities that broke down silos and encouraged open communication and collaboration between PCPs and nephrologists. Building involved constructing a fractal management infrastructure with transparent reporting and shared accountability, which would enable success in innovation and transformation. The result is proactive and relational CKD care organized around the patient's needs in University Hospitals Systems of Excellence. Systems of excellence combine multiple domains of expertise to promote best practice guidelines and integrate care throughout the system. The authors further describe a preliminary pilot of the CKD System of Excellence in primary care.

Screening for social needs has gained traction as an approach to addressing social determinants of health, but it faces challenges regarding standardization, resource allocation, and follow-up care. The year-long study, conducted by the Association of American Medical Colleges, integrated data from conferences, surveys, and key informant interviews to examine the integration of social needs screening into health care services within Academic Health Systems (AHS). The authors' analysis unveiled eight key themes, showcasing AHS's active involvement in targeted social needs screening alongside persistent resource allocation obstacles. AHS are dedicated to efficiently identifying high-risk populations, fostering partnerships with community-based organizations, and embracing technology for closed-loop referrals. However, concerns endure about the utilization of reimbursement codes for social needs and regulatory compliance. AHS confront staffing issues, resource allocation intricacies, and the imperative for seamless integration across clinical and nonclinical departments. Notably, opportunities arise in standardized training, alignment of AHS priorities, exploration of social investment models, and engagement with state-level health information exchanges. Aligning clinical care, research pursuits, and community engagement endeavors holds promise for AHS in effectively addressing social needs.