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Population health and the academic medical center: the time is right

Gourevitch, Marc N
Optimizing the health of populations, whether defined as persons receiving care from a health care delivery system or more broadly as persons in a region, is emerging as a core focus in the era of health care reform. To achieve this goal requires an approach in which preventive care is valued and "nonmedical" determinants of patients' health are engaged. For large, multimission systems such as academic medical centers, navigating the evolution to a population-oriented paradigm across the domains of patient care, education, and research poses real challenges but also offers tremendous opportunities, as important objectives across each mission begin to align with external trends and incentives. In clinical care, opportunities exist to improve capacity for assuming risk, optimize community benefit, and make innovative use of advances in health information technology. Education must equip the next generation of leaders to understand and address population-level goals in addition to patient-level needs. And the prospects for research to define strategies for measuring and optimizing the health of populations have never been stronger. A remarkable convergence of trends has created compelling opportunities for academic medical centers to advance their core goals by endorsing and committing to advancing the health of populations.
PMCID:4024242
PMID: 24556766
ISSN: 1040-2446
CID: 864972

Opioid treatment at release from jail using extended-release naltrexone: a pilot proof-of-concept randomized effectiveness trial

Lee, Joshua D; McDonald, Ryan; Grossman, Ellie; McNeely, Jennifer; Laska, Eugene; Rotrosen, John; Gourevitch, Marc N
BACKGROUND AND AIMS: Relapse to addiction following incarceration is common. We estimated the feasibility and effectiveness of extended-release naltrexone (XR-NTX) as relapse prevention among opioid-dependent male adults leaving a large urban jail. DESIGN: Eight-week, proof-of-concept, open-label, non-blinded randomized effectiveness trial. SETTING: New York City jails and Bellevue Hospital Center Adult Primary Care clinics, USA. PARTICIPANTS: From January 2010 to July 2013, 34 opioid-dependent adult males with no stated interest in agonist treatments (methadone, buprenorphine) received a counseling and referral intervention and were randomized to XR-NTX (n = 17) versus no medication (n = 17) within one week prior to jail release. INTERVENTION: XR-NTX (Vivitrol((R)) ; Alkermes Inc.), a long-acting injectable mu opioid receptor antagonist. MEASURES: The primary intent-to-treat outcome was post-release opioid relapse at week 4, defined as >/=10 days of opioid misuse by self-report and urine toxicologies. Secondary outcomes were proportion of urine samples negative for opioids and rates of opioid abstinence, intravenous drug use (IVDU), cocaine use, community treatment participation, re-incarceration and overdose. FINDINGS: Acceptance of XR-NTX was high; 15 of 17 initiated treatment. Rates of the primary outcome of week 4 opioid relapse were lower among XR-NTX participants: 38 versus 88% [P<0.004; odds ratio (OR) = 0.08, 95% confidence interval (CI) = 0.01-0.48]; more XR-NTX urine samples were negative for opioids, 59 versus 29% (P<0.009; OR = 3.5, 95% CI = 1.4-8.5). There were no significant differences in the remaining secondary outcomes, including rates of IVDU, cocaine use, re-incarceration and overdose. CONCLUSION: Extended-release naltrexone is associated with significantly lower rates of opioid relapse among men in the United States following release from jail when compared with a no medication treatment-as-usual condition.
PMID: 25703440
ISSN: 1360-0443
CID: 1578432

Improving population health in US cities

Stine, Nicholas W; Chokshi, Dave A; Gourevitch, Marc N
PMCID:3618470
PMID: 23385269
ISSN: 0098-7484
CID: 249122

Social and Economic Differences in Neighborhood Walkability Across 500 U.S. Cities

Conderino, Sarah E; Feldman, Justin M; Spoer, Benjamin; Gourevitch, Marc N; Thorpe, Lorna E
INTRODUCTION/BACKGROUND:Neighborhood walkability has been established as a potentially important determinant of various health outcomes that are distributed inequitably by race/ethnicity and sociodemographic status. The objective of this study is to assess the differences in walkability across major urban centers in the U.S. METHODS:City- and census tract-level differences in walkability were assessed in 2020 using the 2019 Walk Score across 500 large cities in the U.S. RESULTS:At both geographic levels, high-income and majority White geographic units had the lowest walkability overall. Walkability was lower with increasing tertile of median income among majority White, Latinx, and Asian American and Native Hawaiian and Pacific Islander neighborhoods. However, this association was reversed within majority Black neighborhoods, where tracts in lower-income tertiles had the lowest walkability. Associations varied substantially by region, with the strongest differences observed for cities located in the South. CONCLUSIONS:Differences in neighborhood walkability across 500 U.S. cities provide evidence that both geographic unit and region meaningfully influence associations between sociodemographic factors and walkability. Structural interventions to the built environment may improve equity in urban environments, particularly in lower-income majority Black neighborhoods.
PMID: 34108111
ISSN: 1873-2607
CID: 4936682

Neighborhood-level Asian American Populations, Social Determinants of Health, and Health Outcomes in 500 US Cities

Spoer, Ben R; Juul, Filippa; Hsieh, Pei Yang; Thorpe, Lorna E; Gourevitch, Marc N; Yi, Stella
Introduction/UNASSIGNED:The US Asian American (AA) population is projected to double by 2050, reaching ~43 million, and currently resides primarily in urban areas. Despite this, the geographic distribution of AA subgroup populations in US cities is not well-characterized, and social determinants of health (SDH) and health measures in places with significant AA/AA subgroup populations have not been described. Our research aimed to: 1) map the geographic distribution of AAs and AA subgroups at the city- and neighborhood- (census tract) level in 500 large US cities (population ≥66,000); 2) characterize SDH and health outcomes in places with significant AA or AA subgroup populations; and 3) compare SDH and health outcomes in places with significant AA or AA subgroup populations to SDH and health outcomes in places with significant non-Hispanic White (NHW) populations. Methods/UNASSIGNED:Maps were generated using 2019 Census 5-year estimates. SDH and health outcome data were obtained from the City Health Dashboard, a free online data platform providing more than 35 measures of health and health drivers at the city and neighborhood level. T-tests compared SDH (unemployment, high-school completion, childhood poverty, income inequality, racial/ethnic segregation, racial/ethnic diversity, percent uninsured) and health outcomes (obesity, frequent mental distress, cardiovascular disease mortality, life expectancy) in cities/neighborhoods with significant AA/AA subgroup populations to SDH and health outcomes in cities/neighborhoods with significant NHW populations (significant was defined as top population proportion quintile). We analyzed AA subgroups including Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, and Other AA. Results/UNASSIGNED:The count and proportion of AA/AA subgroup populations varied substantially across and within cities. When comparing cities with significant AA/AA subgroup populations vs NHW populations, there were few meaningful differences in SDH and health outcomes. However, when comparing neighborhoods within cities, areas with significant AA/AA subgroup vs NHW populations had less favorable SDH and health outcomes. Conclusion/UNASSIGNED:When comparing places with significant AA vs NHW populations, city-level data obscured substantial variation in neighborhood-level SDH and health outcome measures. Our findings emphasize the dual importance of granular spatial and AA subgroup data in assessing the influence of SDH in AA populations.
PMCID:8288474
PMID: 34295131
ISSN: 1945-0826
CID: 5003942

Health and Health Determinant Metrics for Cities: A Comparison of County and City-Level Data

Spoer, Ben R; Feldman, Justin M; Gofine, Miriam L; Levine, Shoshanna E; Wilson, Allegra R; Breslin, Samantha B; Thorpe, Lorna E; Gourevitch, Marc N
We evaluated whether using county-level data to characterize public health measures in cities biases the characterization of city populations. We compared 4 public health and sociodemographic measures in 447 US cities (percent of children living in poverty, percent of non-Hispanic Black population, age-adjusted cardiovascular disease mortality, life expectancy at birth) to the same measures calculated for counties that contain those cities. We found substantial and highly variable city-county differences within and across metrics, which suggests that use of county data to proxy city measures could hamper accurate allocation of public health resources and appreciation of the urgency of public health needs in specific locales.
PMID: 33155973
ISSN: 1545-1151
CID: 4668752

Community Health Worker Intervention in Subsidized Housing: New York City, 2016-2017

Freeman, Amy L; Li, Tianying; Kaplan, Sue A; Ellen, Ingrid Gould; Gourevitch, Marc N; Young, Ashley; Doran, Kelly M
From April 2016 to June 2017, the Health + Housing Project employed four community health workers who engaged residents of two subsidized housing buildings in New York City to address individuals' broadly defined health needs, including social and economic risk factors. Following the intervention, we observed significant improvements in residents' food security, ability to pay rent, and connection to primary care. No immediate change was seen in acute health care use or more narrowly defined health outcomes. (Am J Public Health. Published online ahead of print March 19, 2020: e1-e4. doi:10.2105/AJPH.2019.305544).
PMID: 32191526
ISSN: 1541-0048
CID: 4353682

Leveraging Population Health Expertise to Enhance Community Benefit

Kaplan, Sue A; Gourevitch, Marc N
As the Internal Revenue Service strengthens the public health focus of community benefit regulations, and many states do the same with their tax codes, hospitals are being asked to look beyond patients in their delivery system to understand and address the needs of geographic areas. With the opportunities this affords come challenges to be addressed. The regulations' focus on population health is not limited to a defined clinical population-and the resulting emphasis on upstream determinants of health and community engagement is unfamiliar territory for many healthcare systems. At the same time, for many community residents and community-based organizations, large medical institutions can feel complicated to engage with or unwelcoming. And for neighborhoods that have experienced chronic underinvestment in upstream determinants of health-such as social services, housing and education-funds made available by hospitals through their community health improvement activities may seem insufficient and unreliable. Despite these regulatory requirements, many hospitals, focused as they are on managing patients in their delivery system, have not yet invested significantly in community health improvement. Moreover, although there are important exceptions, community health improvement projects have often lacked a strong evidence base, and true health system-community collaborations are relatively uncommon. This article describes how a large academic medical center tapped into the expertise of its population health research faculty to partner with local community-based organizations to oversee the community health needs assessment and to design, implement and evaluate a set of geographically based community-engaged health improvement projects. The resulting program offers a paradigm for health system investment in area-wide population health improvement.
PMCID:7136395
PMID: 32296672
ISSN: 2296-2565
CID: 4401742

Census tract-level association between racial composition and life expectancy among 492 large cities in the United States [Meeting Abstract]

Spoer, B; Thorpe, L; Gourevitch, M; Levine, S; Feldman, J
Purpose: Non-Hispanic black communities in the US experience below-average life expectancy (LE). However, little is known about how the magnitude of these inequities vary between major US cities. We sought to understand variability in the relationship between percent of census tract residents who were non-Hispanic black and tract-level LE.
Method(s): We obtained census tract-level estimates of LE in 492 large US cities from the US Small Area Life Expectancy Estimates Project and combined them with socio-demographic data from the American Community Survey. We fit a multilevel linear null model to partition the variance in LE between the tract, city, and state levels. We estimated a random slope model to quantify the degree to which the association between percent non-Hispanic black and LE in census tracts varied between cities.
Result(s): In a null model, 10% of LE variation was at the state level, 21% at the city level, and 69% was within cities at the tract level. Detroit and Flint, Michigan, both majority-black cities, had the lowest city-level average LE estimates (>5 years below average), and Chicago had the widest range for tract LEs (30.1 years). Nationally, a 10-point increase in tract percent non-Hispanic black was associated with 1.1 years shorter LE (95% CI: 1.0, 1.1). However, there was considerable variation in this association (standard deviation for random slope = 0.29).
Conclusion(s): The magnitude of inequalities in LE by tract racial composition varied considerably between cities. Further research to understand this variability can inform efforts to address urban health inequities.
Copyright
EMBASE:2004182611
ISSN: 1873-2585
CID: 4244742

Measuring Population Health in a Large Integrated Health System to Guide Goal Setting and Resource Allocation: A Proof of Concept

Stevens, Elizabeth R; Zhou, Qinlian; Nucifora, Kimberly A; Taksler, Glen B; Gourevitch, Marc N; Stiefel, Matthew C; Kipnis, Patricia; Braithwaite, R Scott
In integrated health care systems, techniques that identify successes and opportunities for targeted improvement are needed. The authors propose a new method for estimating population health that provides a more accurate and dynamic assessment of performance and priority setting. Member data from a large integrated health system (n = 96,246, 73.8% female, mean age = 44 ± 0.01 years) were used to develop a mechanistic mathematical simulation, representing the top causes of US mortality in 2014 and their associated risk factors. An age- and sex-matched US cohort served as comparator group. The simulation was recalibrated and retested for validity employing the outcome measure of 5-year mortality. The authors sought to estimate potential population health that could be gained by improving health risk factors in the study population. Potential gains were assessed using both average life years (LY) gained and average quality-adjusted life years (QALYs) gained. The simulation validated well compared to integrated health system data, producing an AUC (area under the curve) of 0.88 for 5-year mortality. Current population health was estimated as a life expectancy of 84.7 years or 69.2 QALYs. Comparing potential health gain in the US cohort to the Kaiser Permanente cohort, eliminating physical inactivity, unhealthy diet, smoking, and uncontrolled diabetes resulted in an increase of 1.5 vs. 1.3 LY, 1.1 vs. 0.8 LY, 0.5 vs. 0.2 LY, and 0.5 vs. 0.5 LY on average per person, respectively. Using mathematical simulations may inform efforts by integrated health systems to target resources most effectively, and may facilitate goal setting.
PMID: 30513070
ISSN: 1942-7905
CID: 3520632