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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

State-Level Firearm Laws and Firearm Homicide in US Cities: Heterogenous Associations by City Characteristics

Kim, Byoungjun; Thorpe, Lorna E; Spoer, Ben R; Titus, Andrea R; Santaella-Tenorio, Julian; Cerdá, Magdalena; Gourevitch, Marc N; Matthay, Ellicott C
Despite well-studied associations of state firearm laws with lower state- and county-level firearm homicide, there is a shortage of studies investigating differences in the effects of distinct state firearm law categories on various cities within the same state using identical methods. We examined associations of 5 categories of state firearm laws-pertaining to buyers, dealers, domestic violence, gun type/trafficking, and possession-with city-level firearm homicide, and then tested differential associations by city characteristics. City-level panel data on firearm homicide cases of 78 major cities from 2010 to 2020 was assessed from the Centers for Disease Control and Prevention's National Vital Statistics System. We modeled log-transformed firearm homicide rates as a function of firearm law scores, city, state, and year fixed effects, along with time-varying city-level confounders. We considered effect measure modification by poverty, unemployment, vacant housing, and income inequality. A one z-score increase in state gun type/trafficking, possession, and dealer law scores was associated with 25% (95% confidence interval [CI]:-0.37,-0.1), 19% (95% CI:-0.29,-0.07), and 17% (95% CI:-0.28, -0.4) lower firearm homicide rates, respectively. Protective associations were less pronounced in cities with high unemployment and high housing vacancy, but more pronounced in cities with high income inequality. In large US cities, state-level gun type/trafficking, possession, and dealer laws were associated with lower firearm homicide rates, but buyers and domestic violence laws were not. State firearm laws may have differential effects on firearm homicides based on city characteristics, and city-wide policies to enhance socioeconomic drivers may add benefits of firearm laws.
PMID: 38536598
ISSN: 1468-2869
CID: 5644932

Associations between a Novel Measure of Census Tract-Level Credit Insecurity and Frequent Mental Distress in US Urban Areas, 2020

Titus, Andrea R; Li, Yuruo; Mills, Claire Kramer; Spoer, Benjamin; Lampe, Taylor; Kim, Byoungjun; Gourevitch, Marc N; Thorpe, Lorna E
Access to and utilization of consumer credit remains an understudied social determinant of health. We examined associations between a novel, small-area, multidimensional credit insecurity index (CII), and the prevalence of self-reported frequent mental distress across US cities in 2020. The census tract-level CII was developed by the Federal Reserve Bank of New York using Census population information and a nationally representative sample of anonymized Equifax credit report data. The CII was calculated for tracts in 766 cities displayed on the City Health Dashboard at the time of analysis, predominantly representing cities with over 50,000 residents. The CII combined data on tract-level participation in the formal credit economy with information on the percent of individuals without revolving credit, percent with high credit utilization, and percent with deep subprime credit scores. Tracts were classified as credit-assured, credit-likely, mid-tier, at-risk, or credit-insecure. We used linear regression to examine associations between the CII and a modeled tract-level measure of frequent mental distress, obtained from the CDC PLACES project. Regression models were adjusted for neighborhood economic and demographic characteristics. We examined effect modification by US region by including two-way interaction terms in regression models. In adjusted models, credit-insecure tracts had a modestly higher prevalence of frequent mental distress (prevalence difference = 0.38 percentage points; 95% CI = 0.32, 0.44), compared to credit-assured tracts. Associations were most pronounced in the Midwest. Local factors impacting credit access and utilization are often modifiable. The CII, a novel indicator of community financial well-being, may be an independent predictor of neighborhood health in US cities and could illuminate policy targets to improve access to desirable credit products and downstream health outcomes.
PMID: 38012504
ISSN: 1468-2869
CID: 5612662

Validation of a geospatial aggregation method for congressional districts and other US administrative geographies

Spoer, Ben R; Chen, Alexander S; Lampe, Taylor M; Nelson, Isabel S; Vierse, Anne; Zazanis, Noah V; Kim, Byoungjun; Thorpe, Lorna E; Subramanian, Subu V; Gourevitch, Marc N
Stakeholders need data on health and drivers of health parsed to the boundaries of essential policy-relevant geographies. US Congressional Districts are an example of a policy-relevant geography which generally lack health data. One strategy to generate Congressional District heath data metric estimates is to aggregate estimates from other geographies, for example, from counties or census tracts to Congressional Districts. Doing so requires several methodological decisions. We refine a method to aggregate health metric estimates from one geography to another, using a population weighted approach. The method's accuracy is evaluated by comparing three aggregated metric estimates to metric estimates from the US Census American Community Survey for the same years: Broadband Access, High School Completion, and Unemployment. We then conducted four sensitivity analyses testing: the effect of aggregating counts vs. percentages; impacts of component geography size and data missingness; and extent of population overlap between component and target geographies. Aggregated estimates were very similar to estimates for identical metrics drawn directly from the data source. Sensitivity analyses suggest the following best practices for Congressional district-based metrics: utilizing smaller, more plentiful geographies like census tracts as opposed to larger, less plentiful geographies like counties, despite potential for less stable estimates in smaller geographies; favoring geographies with higher percentage population overlap.
PMID: 37711359
ISSN: 2352-8273
CID: 5593552

Life Expectancy and Built Environments in the U.S.: A Multilevel Analysis

Kim, Byoungjun; Spoer, Ben R; Titus, Andrea R; Chen, Alexander; Thurston, George D; Gourevitch, Marc N; Thorpe, Lorna E
INTRODUCTION:The purpose of this study is to examine the associations between built environments and life expectancy across a gradient of urbanicity in the U.S. METHODS:Census tract‒level estimates of life expectancy between 2010 and 2015, except for Maine and Wisconsin, from the U.S. Small-Area Life Expectancy Estimates Project were analyzed in 2022. Tract-level measures of the built environment included: food, alcohol, and tobacco outlets; walkability; park and green space; housing characteristics; and air pollution. Multilevel linear models for each of the 4 urbanicity types were fitted to evaluate the associations, adjusting for population and social characteristics. RESULTS:Old housing (built before 1979) and air pollution were important built environment predictors of life expectancy disparities across all gradients of urbanicity. Convenience stores were negatively associated with life expectancy in all urbanicity types. Healthy food options were a positive predictor of life expectancy only in high-density urban areas. Park accessibility was associated with increased life expectancy in all areas, except rural areas. Green space in neighborhoods was positively associated with life expectancy in urban areas but showed an opposite association in rural areas. CONCLUSIONS:After adjusting for key social characteristics, several built environment characteristics were salient risk factors for decreased life expectancy in the U.S., with some measures showing differential effects by urbanicity. Planning and policy efforts should be tailored to local contexts.
PMID: 36935164
ISSN: 1873-2607
CID: 5449082

Racial/ethnic and income disparities in neighborhood-level broadband access in 905 US cities, 2017-2021

Li, Y; Spoer, B R; Lampe, T M; Hsieh, P Y; Nelson, I S; Vierse, A; Thorpe, L E; Gourevitch, M N
OBJECTIVES/OBJECTIVE:Broadband access is an essential social determinant of health, the importance of which was made apparent during the COVID-19 pandemic. We sought to understand disparities in broadband access within cities and identify potential solutions to increase urban access. STUDY DESIGN/METHODS:This was a descriptive secondary analysis using multi-year cross-sectional survey data. METHODS:Data were obtained from the City Health Dashboard and American Community Survey. We studied broadband access in 905 large US cities, stratifying neighborhood broadband access by neighborhood median household income and racial/ethnic composition. RESULTS:In 2017, 30% of urban households across 905 large US cities did not have access to high-speed broadband internet. After controlling for median household income, broadband access in majority Black and Hispanic neighborhoods was 10-15% lower than in majority White or Asian neighborhoods. Over time, lack of broadband access in urban households decreased from 30% in 2017 to 24% in 2021, but racial and income disparities persisted. CONCLUSIONS:As an emerging social determinant, broadband access impacts health across the life course, affecting students' ability to learn and adults' ability to find and retain jobs. Resolving lack of broadband access remains an urban priority. City policymakers can harness recent infrastructure funding opportunities to reduce broadband access disparities.
PMID: 36917875
ISSN: 1476-5616
CID: 5466972

Health and Equity Data to Teach the Next Generation of Public Health Leaders

Ofrane, Rebecca H; Breslin, Samantha; Levine, Shoshanna; Gourevitch, Marc N; Levy, Marian
The COVID-19 pandemic restructured university learning environments while also underscoring the need for granular local health data. We describe how the University of Memphis School of Public Health used the City Health Dashboard, an online resource providing data at the city and neighborhood level for more than 35 measures of health outcomes, health drivers, and health equity for all US cities with populations >50 000, to enrich students' learning of applying data to community health policy. By facilitating students' engagement with population needs, assets, and capacities that affect communities' health-key components of the master of public health accreditation process-the Dashboard supports in-person and virtual learning at undergraduate and graduate levels and is recommended as a novel and rigorous data source for public health trainees.
PMID: 36633364
ISSN: 1468-2877
CID: 5419062

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