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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.
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
PMID: 23385269
ISSN: 0098-7484
CID: 249122

Building Public Health Surveillance 3.0: Emerging Timely Measures of Physical, Economic, and Social Environmental Conditions Affecting Health

Thorpe, Lorna E; Chunara, Rumi; Roberts, Tim; Pantaleo, Nicholas; Irvine, Caleb; Conderino, Sarah; Li, Yuruo; Hsieh, Pei Yang; Gourevitch, Marc N; Levine, Shoshanna; Ofrane, Rebecca; Spoer, Benjamin
In response to rapidly changing societal conditions stemming from the COVID-19 pandemic, we summarize data sources with potential to produce timely and spatially granular measures of physical, economic, and social conditions relevant to public health surveillance, and we briefly describe emerging analytic methods to improve small-area estimation. To inform this article, we reviewed published systematic review articles set in the United States from 2015 to 2020 and conducted unstructured interviews with senior content experts in public heath practice, academia, and industry. We identified a modest number of data sources with high potential for generating timely and spatially granular measures of physical, economic, and social determinants of health. We also summarized modeling and machine-learning techniques useful to support development of time-sensitive surveillance measures that may be critical for responding to future major events such as the COVID-19 pandemic. (Am J Public Health. Published online ahead of print August 4, 2022:e1-e10.
PMID: 35926162
ISSN: 1541-0048
CID: 5288242

Validation of a neighborhood-level COVID Local Risk Index in 47 large U.S. cities

Spoer, Ben R; McCulley, Edwin; Lampe, Taylor M; Hsieh, Pei Yang; Chen, Alexander; Ofrane, Rebecca; Rollins, Heather; Thorpe, Lorna E; Bilal, Usama; Gourevitch, Marc N
OBJECTIVES/OBJECTIVE:To present the COVID Local Risk Index (CLRI), a measure of city- and neighborhood-level risk for SARS COV-2 infection and poor outcomes, and validate it using sub-city SARS COV-2 outcome data from 47 large U.S. cities. METHODS:Cross-sectional validation analysis of CLRI against SARS COV-2 incidence, percent positivity, hospitalization, and mortality. CLRI scores were validated against ZCTA-level SARS COV-2 outcome data gathered in 2020-2021 from public databases or through data use agreements using a negative binomial model. RESULTS:CLRI was associated with each SARS COV-2 outcome in pooled analysis. In city-level models, CLRI was positively associated with positivity in 11/14 cities for which data were available, hospitalization in 6/6 cities, mortality in 13/14 cities, and incidence in 33/47 cities. CONCLUSIONS:CLRI is a valid tool for assessing sub-city risk of SARS COV-2 infection and illness severity. Stronger associations with positivity, hospitalization and mortality may reflect differential testing access, greater weight on components associated with poor outcomes than transmission, omitted variable bias, or other reasons. City stakeholders can use the CLRI, publicly available on the City Health Dashboard (, to guide SARS COV-2 resource allocation.
PMID: 35623163
ISSN: 1873-2054
CID: 5235802

Public Health and Public Safety: Converging Upstream [Editorial]

Gourevitch, Marc N; Kleiman, Neil; Falco, Katy Brodsky
PMID: 35324264
ISSN: 1541-0048
CID: 5200592

Data Dashboards for Advancing Health and Equity: Proving Their Promise? [Editorial]

Thorpe, Lorna E; Gourevitch, Marc N
PMID: 35446603
ISSN: 1541-0048
CID: 5218472

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.
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