Population Health Management最新文献

Lower-extremity peripheral artery disease (PAD), the accumulation of atherosclerotic plaque in the arteries of the legs, causes substantial morbidity and mortality. Frequent under- and delayed diagnosis result in poor outcomes, disproportionately affecting individuals from racial and ethnic minority groups. To understand barriers to early detection and treatment and factors contributing to disparities, American Medical Group Association (AMGA) conducted roundtable discussions and semistructured interviews in 2021. Eighteen participants discussed PAD evaluation, diagnosis, early medical management, and disparities in care. A qualitative case study approach and data reduction methods were used to generate themes, draw conclusions, and make actionable recommendations. Identified themes included lack of (1) prioritization of PAD for population health; (2) engagement of primary care providers in early evaluation and referral; (3) "ownership" of lower-extremity PAD within health systems; and (4) focus on disparities in care. Participant solutions included (1) financial impact of early PAD management, in the context of value-based payment; (2) embedding an advanced practice provider into a vascular surgery practice to facilitate evaluation and provide medical therapy; and (3) leveraging care coordination, multidisciplinary clinics, and telehealth technology to provide comprehensive care for patients with PAD and address disparities. A deliberate focused effort is necessary to close gaps and the accompanying disparities in early evaluation, diagnosis, and treatment for people with lower-extremity PAD. The authors describe 3 models that can be emulated to improve care for this high-risk population. With improved reimbursement and better medical therapies, now is the time to focus on early diagnosis and management of PAD.

The relative distribution of proportions of cardiovascular health (CVH) categories within racial groups has been examined. However, little scientific evidence exists on the gap trend in racial/ethnic disparities in mean CVH score among non-Hispanic (NH) Whites and Blacks. This study examined the trend(s) in the gap(s) in predicted CVH scores between NH Whites and Blacks over 10 years. In a cross-sectional analytical study, 10 years of Medical Expenditure Panel Survey data from 2008 to 2018 were pooled, utilizing multivariate Poisson's regression of CVH metrics on race, while controlling for relevant covariates. The interactions of acute coronary syndrome (ACS) with CVH metrics, and other key variables such as trends and grouped Charlson Comorbidity Index allowed for variations in the effect of these variables on the subgroups. The mean gap in CVH scores was on average 0.15 [95% confidence interval (CI) 0.137 to 0.170], with Blacks consistently having reduced odds of having ideal CVH until 2014. The overall impact of having an ACS decreased acquired CVH scores by 24.1% [95% CI -0.275 to 0.207], and was equal for both racial subgroups (P < 0.05). The Affordable Care Act (ACA)-trend was positive, increasing the likelihood of improved CVH in the sample (P < 0.05), deflecting a downward trend in acquired CVH scores for both races, as the gap narrowed into more recent years. The CVH gap was stabilized by the ACA, but never really converged, suggesting that efforts to reduce existing disparities between Blacks and NH Whites in the United States would require government policies to look beyond mere "access" and/or "affordability" to health care.

The rise in health care costs, caused by older and more complex patient populations, requires Population Health Management approaches including risk stratification. With risk stratification, patients are assigned individual risk scores based on medical records. These patient stratifications focus on future high costs and expensive care utilization such as hospitalization, for which different models exist. With this study, the research team validated the accuracy of risk prediction scores for future hospitalization and high health care costs, calculated by the Adjusted Clinical Group (ACG)'s risk stratification models, using Dutch primary health care data registries. In addition, they aimed to adjust the US-based predictive models for Dutch primary care. The statistical validity of the existing models was assessed. In addition, the underlying prediction models were trained on 95,262 patients' data from de Zoetermeer region and externally validated on data of 48,780 patients from Zeist, Nijkerk, and Urk. Information on age, sex, number of general practitioner visits, International Classification of Primary Care coded information on the diagnosis and Anatomical Therapeutic Chemical Classification coded information on the prescribed medications, were incorporated in the model. C-statistics were used to validate the discriminatory ability of the models. Calibrating ability was assessed by visual inspection of calibration plots. Adjustment of the hospitalization model based on Dutch data improved C-statistics from 0.69 to 0.75, whereas adjustment of the high-cost model improved C-statistics from 0.78 to 0.85, indicating good discrimination of the models. The models also showed good calibration. In conclusion, the local adjustments of the ACG prediction models show great potential for use in Dutch primary care.

Abstract Social needs, such as social isolation and food insecurity, are important individual-level social determinants of health, especially for adults ages 65 years and older. These needs may be associated with future health care utilization, but this research area has not been studied extensively. The objective of this study was to examine the independent association of 5 individual social needs with future (1) emergency department (ED) visits and (2) hospital admissions. This observational study included 9649 Kaiser Permanente Northwest (KPNW) Medicare members who completed the Medicare Total Health Assessment (MTHA) quality improvement survey between August 17, 2020 and January 31, 2022. The 5 social needs assessed by the MTHA, defined as binary measures (yes/no), included (1) financial strain, (2) food insecurity, (3) housing instability, (4) social isolation, and (5) transportation needs. ED utilization (yes/no) and hospitalization (yes/no), the current study outcome measures, were measured in the 12 months after MTHA assessment. In multivariable analyses, 3 of the 5 social needs were significantly associated with higher ED utilization: financial strain (odds ratio [OR] = 1.40, 95% confidence interval [CI] = 1.11-1.76, P < 0.05), housing instability (OR = 1.43, 95% CI = 1.02-1.99, P < 0.05), and social isolation (OR = 1.19, 95% CI = 1.05-1.34, P < 0.05), and 1, financial strain, was significantly associated with hospital admissions (OR = 1.66, 95% CI = 1.23-2.23, P < 0.05). The study results identified which social needs are most strongly associated with future ED utilization and hospital admissions. Further research is needed to better understand whether addressing social needs is associated with improved patient-level health outcomes over time.

As health care systems invest significant resources to address social needs associated with poor health such as food, financial, and housing insecurity, many eligible patients are still not obtaining the resources they need. The recently initiated PURPLE Project (Promoting Understanding in Social Needs Research Projects by Listening and Engaging) engages stakeholder advisors to help address 2 challenges: (1) many patients do not accept offered assistance, and (2) of patients who accept assistance, less than half have their needs addressed. This article presents the team's engagement with local advisors, garnering real-life insights from patients with social needs, staff and leadership in public health, health care, and community service organizations. The team shares these organizations' priorities and recommendations and how these can be applied to these major challenges. This article can assist others in the social care arena who seeks to involve local partners as advisors to improve practices and policies in addressing social needs.

Individuals with complex, chronic diseases represent 5% of the population but consume 50% of the costs of care. These patients have complex lives, characterized by multiple chronic physical health conditions paired with a combination of behavioral health issues and/or unmet social needs. Unlike for most health problems, the problems faced by individuals with complex lives cannot be broken down into simpler parts to be solved independent from 1 another. In this article, the authors describe a 2-phase framework for improving outcomes in patients with complex lives, outline how the model works in more detail, and discuss lessons learned in this journey. In phase 1, a case manager carefully and deliberately focuses on building a relationship with the patient to first gain trust, and then identify, in partnership with the patient, how to best approach assisting the patient in improving their health. That pathway is often unknowable without a deep investment of time, a radical acceptance of the patient, faults and all, and an unwavering commitment to stay by their side, even when things are tough. Once the case manager and patient have established a trusting relationship, they enter phase 2-building a path toward wellness, including further emphasis on the relationship, solving prioritized issues, changing the health system approach, and engaging the patient in self-reflection and behavior change activities.