A Balanced Investment Portfolio For Equitable Health And Well-Being Is An Imperative, And Within Reach

The Role of Place in Person- and Family-Oriented Long-Term Services and Supports

Policy Points Little attention to date has been directed at examining how the long-term services and supports (LTSS) environmental context affects the health and well-being of older adults with disabilities. We develop a conceptual framework identifying environmental domains that contribute to LTSS use, care quality, and care experiences. We find the LTSS environment is highly associated with person-reported care experiences, but the direction of the relationship varies by domain; increased neighborhood social and economic deprivation are highly associated with experiencing adverse consequences due to unmet need, whereas availability and generosity of the health care and social services delivery environment are inversely associated with participation restrictions in valued activities. Policies targeting local and state-level LTSS-relevant environmental characteristics stand to improve the health and well-being of older adults with disabilities, particularly as it relates to adverse consequences due to unmet need and participation restrictions.

CONTEXT

Long-term services and supports (LTSS) in the United States are characterized by their patchwork and unequal nature. The lack of generalizable person-reported information on LTSS care experiences connected to place of community residence has obscured our understanding of inequities and factors that may attenuate them.

METHODS

We advance a conceptual framework of LTSS-relevant environmental domains, drawing on newly available data linkages from the 2015 National Health and Aging Trends Study to connect person-reported care experiences with public use spatial data. We assess relationships between LTSS-relevant environmental characteristic domains and person-reported care adverse consequences due to unmet need, participation restrictions, and subjective well-being for 2,411 older adults with disabilities and for key population subgroups by race, dementia, and Medicaid enrollment status.

FINDINGS

We find the LTSS environment is highly associated with person-reported care experiences, but the direction of the relationship varies by domain. Measures of neighborhood social and economic deprivation (e.g., poverty, public assistance, social cohesion) are highly associated with experiencing adverse consequences due to unmet care needs. Measures of the health care and social services delivery environment (e.g., Medicaid Home and Community-Based Service Generosity, managed LTSS [MLTSS] presence, average direct care worker wage, availability of paid family leave) are inversely associated with experiencing participation restrictions in valued activities. Select measures of the built and natural environment (e.g., housing affordability) are associated with participation restrictions and lower subjective well-being. Observed relationships between measures of LTSS-relevant environmental characteristics and care experiences were generally held in directionality but were attenuated for key subpopulations.

CONCLUSIONS

We present a framework and analyses describing the variable relationships between LTSS-relevant environmental factors and person-reported care experiences. LTSS-relevant environmental characteristics are differentially relevant to the care experiences of older adults with disabilities. Greater attention should be devoted to strengthening state- and community-based policies and practices that support aging in place.

NYS Nonprofit Hospital Assessment and Response to Environmental Pollution as Community Health Need: Prevalence in Community Benefit Practices

CONTEXT

Given the impact of environmental pollution on health and health inequity, there may be substantial value in integrating assessment and response to pollution into nonprofit hospital community benefit processes. Such hospital engagement has not yet been studied.

OBJECTIVES

We take a preliminary step of inquiry in investigating if nonprofit hospitals in New York State (NYS) assess, identify, or respond to environmental pollution as part of community benefit processes.

DESIGN

This study is of retrospective, observational design. Data were abstracted from community health needs reports (2015-2017), associated implementation plans, and related IRS (Internal Revenue Service) filings from a randomly geographically stratified selection of NYS nonprofit hospitals.

PARTICIPANTS

The sample includes 53 hospitals from 23 counties. The sampling frame consists of NYS nonspecialty private nonprofit hospitals.

MAIN OUTCOME MEASURES

Dichotomous findings for the following: (1) engagement of environmental pollution in the process of assessment of community health needs; (2) environmental pollution concern identified as a priority community health need; (3) strategic planning present to address pollution identified as community health need; and (4) action taken on same.

RESULTS

We found that 60.5% (95% confidence interval [CI], 0.46-0.74) of hospitals evidenced some form of assessment of environmental pollution and 18.9% (95% CI, 0.09-0.32) identified pollution as a priority community health need. However, no hospital went on to take independent or collaborative planning or action to address pollution. In additional analysis, we found that social justice in hospital mission was a positive predictor of assessment of environmental pollution.

CONCLUSIONS

For NYS hospitals, we found a substantial presence of assessment and identification of pollution as a community health concern. Our finding of the absence of response to environmental pollution represents a gap in community benefit implementation. This indicates a yet untaken opportunity to address racial and economic environmental health injustices and to improve population health.

Population health management in Belgium: a call-to-action and case study

BACKGROUND

Although there are already success stories, population health management in Belgium is still in its infancy. A health system transformation approach such as population health management may be suited to address the public health issue of atherosclerotic cardiovascular disease, as this is one of the main causes of mortality in Belgium. This article aims to raise awareness about population health management in Belgium by: (a) eliciting barriers and recommendations for its implementation as perceived by local stakeholders; (b) developing a population health management approach to secondary prevention of atherosclerotic cardiovascular disease; and (c) providing a roadmap to introduce population health management in Belgium.

METHODS

Two virtual focus group discussions were organized with 11 high-level decision makers in medicine, policy and science between October and December 2021. A semi-structured guide based on a literature review was used to anchor discussions. These qualitative data were studied by means of an inductive thematic analysis.

RESULTS

Seven inter-related barriers and recommendations towards the development of population health management in Belgium were identified. These related to responsibilities of different layers of government, shared responsibility for the health of the population, a learning health system, payment models, data and knowledge infrastructure, collaborative relationships and community involvement. The introduction of a population health management approach to secondary prevention of atherosclerotic cardiovascular disease may act as a proof-of-concept with a view to roll out population health management in Belgium.

CONCLUSIONS

There is a need to instill a sense of urgency among all stakeholders to develop a joint population-oriented vision in Belgium. This call-to-action requires the support and active involvement of all Belgian stakeholders, both at the national and regional level.

Health Measurement Model-Bringing a Life Course Perspective to Health Measurement: The PRISM Model

Health is a multidimensional concept that is challenging to measure, and in the rapidly evolving developmental changes that occur during the first 21 years of human life, requires a dynamic approach to accurately capture the transitions, and overall arc of a complex process of internal and external interactions. We propose an approach that integrates a lifecourse framework with a layered series of assessments, each layer using a many to many mapping, to converge on four fundamental dimensions of health measurement-Potential, Adaptability, Performance, and Experience. The four dimensions can conceptually be mapped onto a plane with each edge of the resulting quadrilateral corresponding to one dimension and each dimensions assessment calibrated against a theoretical ideal. As the plane evolves over time, the sequential measurements will form a volume. We term such a model the Prism Model, and describe conceptually how single domain assessments can be built up to generate the holistic description through the vehicle of a layer of Exemplar Cases. The model is theoretical but future work can use the framework and principles to generate scalable and adaptable applications that can unify and improve the precision of serial measurements that integrate environmental and physiologic influences to improve the science of child health measurement.

A Health Opportunity Cost Threshold for Cost-Effectiveness Analysis in the United States

BACKGROUND

Cost-effectiveness analysis is an important tool for informing treatment coverage and pricing decisions, yet no consensus exists about what threshold for the incremental cost-effectiveness ratio (ICER) in dollars per quality-adjusted life-year (QALY) gained indicates whether treatments are likely to be cost-effective in the United States.

OBJECTIVE

To estimate a U.S. cost-effectiveness threshold based on health opportunity costs.

DESIGN

Simulation of short-term mortality and morbidity attributable to persons dropping health insurance due to increased health care expenditures passed though as premium increases. Model inputs came from demographic data and the literature; 95% uncertainty intervals (UIs) were constructed.

SETTING

Population-based.

PARTICIPANTS

Simulated cohort of 100 000 individuals from the U.S. population with direct-purchase private health insurance.

MEASUREMENTS

Number of persons dropping insurance coverage, number of additional deaths, and QALYs lost from increased mortality and morbidity, all per increase of $10 000 000 (2019 U.S. dollars) in population treatment cost.

RESULTS

Per $10 000 000 increase in health care expenditures, 1860 persons (95% UI, 1080 to 2840 persons) were simulated to become uninsured, causing 5 deaths (UI, 3 to 11 deaths), 81 QALYs (UI, 40 to 170 QALYs) lost due to death, and 15 QALYs (UI, 6 to 32 QALYs) lost due to illness; this implies a cost-effectiveness threshold of $104 000 per QALY (UI, $51 000 to $209 000 per QALY) in 2019 U.S. dollars. Given available evidence, there is about 14% probability that the threshold exceeds $150 000 per QALY and about 48% probability that it lies below $100 000 per QALY.

LIMITATIONS

Estimates were sensitive to inputs, most notably the effects of losing insurance on mortality and of premium increases on becoming uninsured. Health opportunity costs may vary by population. Nonhealth opportunity costs were excluded.

CONCLUSION

Given current evidence, treatments with ICERs above the range $100 000 to $150 000 per QALY are unlikely to be cost-effective in the United States.

PRIMARY FUNDING SOURCE

None.

Which Priorities for Health and Well-Being Stand Out After Accounting for Tangled Threats and Costs? Simulating Potential Intervention Portfolios in Large Urban Counties

Policy Points Interventions in a regional system with intertwined threats and costs should address those threats that have the strongest, quickest, and most pervasive cross-impacts. Instead of focusing on an individual county's apparent shortcomings, a regional intervention portfolio can yield greater results when it is designed to counter those systemic threats, especially poverty and inadequate social support, that most undermine health and well-being virtually everywhere. Likewise, efforts to reduce smoking, addiction, and violent crime and to improve routine care, health insurance, and youth education are important for most counties to unlock both short- and long-term potential.

CONTEXT

Counties across the United States must contend with multiple, intertwined threats and costs that defy simple solutions. Decision makers face the necessary but difficult task of prioritizing those interventions with the greatest potential to produce equitable health and well-being.

METHODS

Using County Health Rankings data for a predefined peer group of 39 urban US counties, we performed statistical regressions to identify 37 cross-impacts among 15 threats to health and well-being. Adding appropriate time delays, we then developed a dynamic model of these cross-impacts and simulated each of the counties over 20 years to assess the likely impact of 12 potential interventions-individually and in a combined portfolio-for three outcomes: (1) years of potential life lost, (2) fraction of adults in fair or poor health, and (3) total spending on urgent services.

FINDINGS

The combined portfolio yielded improvements by year 20 that are considerably greater than those at year 5, indicating that the time delays have a major effect. Despite the wide variation in threat levels across counties, the list of top-ranked interventions is strikingly similar. Poverty reduction and social support were the most highly ranked interventions, even in the shorter term, for all outcomes in all counties. Interventions affecting smoking, addiction, routine care, health insurance, violent crime, and youth education also were important contributors to some outcomes.

CONCLUSIONS

To safeguard health and well-being in a system dominated by tangled threats and costs, the most important priorities for a county cannot be simply inferred from a profile of its relative strengths and weaknesses. Two interventions stood out as the top priorities for almost all the counties in this study, and six others also were important contributors. Interventions directed toward these priority areas are likely to yield the greatest impact, irrespective of the county's specifics. A significant concentration of resources in a regional portfolio therefore ought to go to these strongest contributors for equitable health and well-being.

Government Health and Social Services Spending Show Evidence of Single-Sector Rather Than Multi-Sector Pursuit of Population Health

Population health improvements can be achieved through work made possible by government spending on health care, public health, and social services. The extent to which spending allocations across these sectors is synergistic with or trade-off against one another is unknown. Achieving a balanced portfolio with multi-sector contributions is key to improving health outcomes. This study tested competing hypotheses regarding achievement of balanced multi-sector resources for health. County-level U.S. Census Bureau data on all local governmental spending measured each county’s average per capita local government spending for public hospitals, public health, social services, and education. American Hospital Association (AHA) Annual Survey data on hospital community health service provision were used to calculate an index of hospital community service provision aggregated to county level by year. County Health Rankings data measured each county’s health outcomes and health factors. Longitudinal mixed-effects regression models (n = 1877 counties) predicted changes in spending for each government spending category based on two sets of predictors (government spending vs community health services and needs) from current and prior year. Models account for average spending in each category and county-, state-, and time-trends. Models showed that spending increases in each of the four spending categories examined (public hospitals, public health, social services, and education) were not associated with changes in spending across other categories in current or prior years. For all categories, an increase from baseline spending levels in Year 1 was always significantly associated with an increase from baseline spending level in that same category in Year 2 (ie, spending stayed above baseline in Year 2). Multi-sector initiatives to health outcomes require funding across sectors, yet there was little evidence to suggest that communities that invest in public hospitals, public health, or other social services see commensurate increases in other areas. Underlying funding decisions may reflect strategic decisions within a community to scale up single sectors, constrained resources for multi-sector scale up, or a host of additional factors not measured here.

Using Neighborhood-Level Census Data to Predict Diabetes Progression in Patients with Laboratory-Defined Prediabetes

CONTEXT

Research on predictors of clinical outcomes usually focuses on the impact of individual patient factors, despite known relationships between neighborhood environment and health.

OBJECTIVE

To determine whether US census information on where a patient resides is associated with diabetes development among patients with prediabetes.

DESIGN

Retrospective cohort study of all 157,752 patients aged 18 years or older from Kaiser Permanente Northern California with laboratory-defined prediabetes (fasting plasma glucose, 100 mg/dL-125 mg/dL, and/or glycated hemoglobin, 5.7%-6.4%). We assessed whether census data on education, income, and percentage of households receiving benefits through the US Department of Agriculture's Supplemental Nutrition Assistance Program (SNAP) was associated with diabetes development using logistic regression controlling for age, sex, race/ethnicity, blood glucose levels, and body mass index.

MAIN OUTCOME MEASURE

Progression to diabetes within 36 months.

RESULTS

Patients were more likely to progress to diabetes if they lived in an area where less than 16% of adults had obtained a bachelor's degree or higher (odds ratio [OR] =1.22, 95% confidence interval [CI] = 1.09-1.36), where median annual income was below $79,999 (OR = 1.16 95% CI = 1.03-1.31), or where SNAP benefits were received by 10% or more of households (OR = 1.24, 95% CI = 1.1-1.4).

CONCLUSION

Area-level socioeconomic and food assistance data predict the development of diabetes, even after adjusting for traditional individual demographic and clinical factors. Clinical interventions should take these factors into account, and health care systems should consider addressing social needs and community resources as a path to improving health outcomes.