Population Health Management: Saving Lives and Saving Money?

Improving uptake of population health management through scalable analysis of linked electronic health data

Population Health Management - often abbreviated to PHM - is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system's data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services.

Differential impact of hospital and community factors on breadth and depth of hospital population health partnerships

OBJECTIVE

The aim was to identify hospital and county characteristics associated with variation in breadth and depth of hospital partnerships with a broad range of organizations to improve population health.

DATA SOURCES

The American Hospital Association Annual Survey provided data on hospital partnerships to improve population health for the years 2017-2019.

DESIGN

The study adopts the dimensional publicness theory and social capital framework to examine hospital and county characteristics that facilitate hospital population health partnerships. The two dependent variables were number of local community organizations that hospitals partner with (breadth) and level of engagement with the partners (depth) to improve population health. The independent variables include three dimensions of publicness: Regulative, Normative and Cultural-cognitive measured by various hospital factors and presence of social capital present at county level. Covariates in the multivariate analysis included hospital factors such as bed-size and system membership.

METHODS

We used hierarchical linear regression models to assess various hospital and county factors associated with breadth and depth of hospital-community partnerships, adjusting for covariates.

PRINCIPAL FINDINGS

Nonprofit and public hospitals provided a greater breadth (coefficient, 1.61; SE, 0.11; p < 0.001 and coefficient, 0.95; SE, 0.14; p < 0.001) and depth (coefficient, 0.26, SE, 0.04; p < 0.001 & coefficient, 0.13; SE, 0.05; p < 0.05) of partnerships than their for-profit counterparts, partially supporting regulative dimension of publicness. At a county level, we found community social capital positively associated with breadth of partnerships (coefficient, 0.13; SE, 0.08; p < 0.001).

CONCLUSIONS

An environment that promotes collaboration between hospitals and organizations to improve population health may impact the health of the community by identifying health needs of the community, targeting social determinants of health, or by addressing patient social needs. However, findings suggest that publicness dimensions at an organizational level, which involves a culture of public value, maybe more important than county factors to achieve community building through partnerships.

Screening for Health-Related Social Needs and Collaboration With External Partners Among US Hospitals

Importance

In recent years, hospitals and health systems have reported increasing rates of screening for patients' individual and community social needs, but few studies have explored the national landscape of screening and interventions directed at addressing health-related social needs (HRSNs) and social determinants of health (SDOH).

Objective

To evaluate the associations of hospital characteristics and area-level socioeconomic indicators to quantify the presence and intensity of hospitals' screening practices, interventions, and collaborative external partnerships that seek to measure and ameliorate patients' HRSNs and SDOH.

Design, Setting, and Participants

This cross-sectional study used national data from the American Hospital Association Annual Survey Database for fiscal year 2020. General-service, acute-care, nonfederal hospitals were included in the study's final sample, representing nationally diverse hospital settings. Data were analyzed from July 2022 to February 2023.

Exposures

Organizational characteristics and area-level socioeconomic indicators.

Main Outcomes and Measures

The outcomes of interest were hospital-reported patient screening of and strategies to address 8 HRSNs and 14 external partnership types to address SDOH. Composite scores for screening practices and external partnership types were calculated, and ordinary least-square regression analyses tested associations of organizational characteristics with outcome measures.

Results

Of 2858 US hospital respondents (response rate, 67.0%), most hospitals (79.2%; 95% CI, 77.7%-80.7%) reported screening patients for at least 1 HRSN, with food insecurity or hunger needs (66.1%; 95% CI, 64.3%-67.8%) and interpersonal violence (66.4%; 95% CI, 64.7%-68.1%) being the most commonly screened social needs. Most hospitals (79.4%; 95% CI, 66.3%-69.7%) reported having strategies and programs to address patients' HRSNs; notably, most hospitals (52.8%; 95% CI, 51.0%-54.5%) had interventions for transportation barriers. Hospitals reported a mean of 4.03 (95% CI, 3.85-4.20) external partnership types to address SDOH and 5.69 (5.50-5.88) partnership types to address HRSNs, with local or state public health departments and health care practitioners outside of the health system being the most common. Hospitals with accountable care contracts (ACCs) and bundled payment programs (BPPs) reported higher screening practices (ACC: β = 1.03; SE = 0.13; BPP: β = 0.72; SE = 0.14), interventions (ACC: β = 1.45; SE = 0.12; BPP: β = 0.61; SE = 0.13), and external partnership types to address HRSNs (ACC: β = 2.07; SE = 0.23; BPP: β = 1.47; SE = 0.24) and SDOH (ACC: β = 2.64; SE = 0.20; BPP: β = 1.57; SE = 0.21). Compared with nonteaching, government-owned, and for-profit hospitals, teaching and nonprofit hospitals were also more likely to report more HRSN-directed activities. Patterns based on geographic and area-level socioeconomic indicators did not emerge.

Conclusions and Relevance

This cross-sectional study found that most US hospitals were screening patients for multiple HRSNs. Active participation in value-based care, teaching hospital status, and nonprofit status were the characteristics most consistently associated with greater overall screening activities and number of related partnership types. These results support previously posited associations about which types of hospitals were leading screening uptake and reinforce understanding of the role of hospital incentives in supporting health equity efforts.

Experiences of health management among people at high risk of stroke in China: A qualitative study

BACKGROUND

Effective health management of people at high risk of stroke in China is challenging.

AIM

To explore and identify the experiences of health management among people at high risk of stroke in order to provide a foundation for a targeted health management strategy for this special group.

DESIGN

A qualitative, descriptive study based on interviews.

METHODS

Semistructured interviews were conducted with 31 people at high risk of stroke. The interviews were collated and analysed using Colaizzi's seven-step method.

RESULTS

A total of 31 people at high risk of stroke were included, and the ages ranged from 40 to 86, with an average age of 60.71 (SD = 11.55). The experiences of health management were categorized into three themes. Theme 1: Facing many ongoing problems in health management, limited knowledge, lack of confidence and poor compliance. Theme 2: Accumulated some value experiences of coping with problems of health management, becoming active learners, promoting social interaction and enhancing self-health management. Theme 3: Sensitivity to multiple influencing factors, the severity of disease and complexity of disease management, family income and economic burden and the value of social support.

CONCLUSIONS

This study explored the experiences of health management among people at high risk of stroke, and these findings are of great significance in the primary prevention of stroke.

Community social capital or health needs: What is driving hospital-community partnerships to address social determinants of health?

Social determinants of health (SDOH) are strongly linked to individual and population health outcomes. Hospitals and health systems are in a unique position to initiate or partner on community-wide efforts address SDOH. However, such efforts typically require collaboration with other healthcare and local community organizations since SDOH affect more than just medical care. Despite studies that have identified specific organizational and environmental factors associated with hospital-community partnerships, the role of social capital and community health needs as drivers of such partnerships remains unexplored. This study examines whether hospital partnerships with community organizations in the United States are driven predominantly by community social capital or the prevailing health needs of the community, and whether these drivers are similar for overall partnerships as well as for partnerships with individual organizations. We use 2020 data from the American Hospital Association, US County Health Rankings, and Social Capital Project and employ ordinary least-squares (OLS) regression and logit models to assess the relationship between social capital, community health needs and hospital-community partnerships to address SDOH. Our results indicate that for community social capital was significantly and positively associated with total hospital partnerships (β = 0.05, p = 0.01). We also found that community social capital was significantly more likely to be associated with hospitals’ partnerships with local/state public health agencies, schools, law enforcement agencies, other healthcare providers, and organizations that assist with food insecurity. On the other hand, community health needs were not associated with total partnerships and had limited associations with hospital partnerships with individual organizations. Overall, this research suggests that social capital is a critical determinant of hospital partnerships with community organizations, and hospitals may seek partnerships with organizations that allow them to address community health issues outside of their own expertise since such partnerships and collaborative efforts can help address SDOH and manage population health.

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Addressing social determinants of health (SDOH) plays an important role in improving population health.

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Hospital multi sector partnerships with local organizations in the community play a key role in addressing SDOH.

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Role of community factors like social capital or health needs in driving hospital community partnerships is underexplored.

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Higher community social capital is associated with hospital community partnerships.

Associations of Intensive Lifestyle Intervention in Type 2 Diabetes With Health Care Use, Spending, and Disability: An Ancillary Study of the Look AHEAD Study

IMPORTANCE

Intensive lifestyle interventions focused on diet and exercise can reduce weight and improve diabetes management. However, the long-term effects on health care use and spending are unclear, especially for public payers.

OBJECTIVE

To estimate the association of effective intensive lifestyle intervention for weight loss with long-term health care use and Medicare spending.

DESIGN, SETTING, AND PARTICIPANTS

This ancillary study used data from the Look AHEAD randomized clinical trial, which randomized participants with type 2 diabetes to an intensive lifestyle intervention or control group (ie, diabetes support and education), provided ongoing intervention from 2001 to 2012, and demonstrated improved diabetes management and reduced health care costs during the intervention. This study compared Medicare data between study arms from 2012 to 2015 to determine whether the intervention was associated with persistent reductions in health care spending.

EXPOSURE

Starting in 2001, Look AHEAD's intervention group participated in sessions with lifestyle counselors, dieticians, exercise specialists, and behavioral therapists with the goal of reducing weight 7% in the first year. Sessions occurred weekly in the first 6 months of the intervention and decreased over the intervention period. The controls participated in periodic group education sessions that occurred 3 times per year in the first year and decreased to 1 time per year later in the trial.

MAIN OUTCOMES AND MEASURES

Outcomes included total Medicare spending, Part D prescription drug costs, Part A and Part B Medicare spending, hospital admissions, emergency department visits, and disability-related Medicare eligibility.

RESULTS

This study matched Medicare administrative records for 2796 Look AHEAD study participants (54% of 5145 participants initially randomized and 86% of 3246 participants consenting to linkages). Linked intervention and control participants were of a similar age (mean [SD] age, 59.6 [5.4] years vs 59.6 [5.5] years at randomization) and sex (818 [58.1%] women vs 822 [59.3%] women). There was no statistically significant difference in total Medicare spending between groups (difference, -$133 [95% CI, -$1946 to $1681]; P = .89). In the intervention group, compared with the control group, there was statistically significantly higher Part B spending (difference, $513 [95% CI, $70 to $955]; P = .02) but lower prescription drug costs (difference, -$803 [95% CI, -$1522 to -$83]; P = .03).

CONCLUSIONS AND RELEVANCE

This ancillary study of a randomized clinical trial found that reductions in health care use and spending associated with an intensive lifestyle intervention for type 2 diabetes diminished as participants aged. Intensive lifestyle interventions may need to be sustained to reduce long-term health care spending.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03952728.

Proactive and Integrated Management and Empowerment in Parkinson's Disease: Designing a New Model of Care

Parkinson's disease is the second most common neurodegenerative condition after Alzheimer's disease. The number of patients will rise dramatically due to ageing of the population and possibly also due to environmental issues. It is widely recognised that the current models of care for people with Parkinson's disease or a form of atypical parkinsonism lack continuity, are reactive to problems rather than proactive, and do not adequately support individuals to self-manage. Integrated models of care have been developed for other chronic conditions, with a range of positive effects. A multidisciplinary team of professionals in the United Kingdom and the Netherlands, all with a long history of caring for patients with movement disorders, used knowledge of deficiencies with the current model of care, an understanding of integrated care in chronic disease and the process of logic modelling, to develop a novel approach to the care of patients with Parkinson's disease. We propose a new model, termed PRIME Parkinson (Proactive and Integrated Management and Empowerment in Parkinson's Disease), which is designed to manage problems proactively, deliver integrated, multidisciplinary care, and empower patients and their carers. It has five main components: (1) personalised care management, (2) education and empowerment of patients and carers, (3) empowerment of healthcare professionals, (4) a population health approach, and (5) support of the previous four components by patient- and professional-friendly technology. Having mapped the processes required for the success of this initiative, there is now a requirement to assess its effect on health-related and quality of life outcomes as well as determining its cost-effectiveness. In the next phase of the project, we will implement PRIME Parkinson in selected areas of the United Kingdom and the Netherlands.