Ji E Chang

Assistant Professor of Public Health Policy and Management

Professional overview

Ji Eun Chang, Ph.D., is an Assistant Professor in the Department of Public Health Policy and Management at the New York University School of Global Public Health, where she also serves as the public health policy and management concentration director for the Ph.D. program. Professor Chang uses mixed-methods research designs and draws from qualitative, quantitative, and geospatial data to demonstrate disparities and highlight barriers faced by safety net providers and underserved patients in accessing equitable care.

Professor Chang is the principal investigator of the AI4Healthy Cities Initiative in New York City, a multi-city collaboration between the Novartis Foundation, Microsoft AI4Health, and local health officials to reduce cardiovascular health inequities through big data analytics. Dr. Chang is also the co-principal investigator of an NIH NIDA-funded study to support implementing transitional opioid programs in safety net hospitals. Dr. Chang received a B.A. in Economics from the University of California at Berkeley, an M.S. in Public Policy and Management from Carnegie Mellon University, and a Ph.D. in Public Administration from New York University in 2016.

Education

BA, Economics, University of California at Berkeley, Berkeley, CA

MS, Public Policy and Management, Carnegie Mellon University, Pittsburgh, PA

PhD, Public Administration, New York University, New York, NY

Honors and awards

Governor’s Scholar (2007)

Regents and Chancellors’ Scholar (2005)

Areas of research and study

Cardiovascular Disease

Health Disparities

Health Equity

Public Health Management

Public Health Management

Safety Net Providers and Patients

Substance Use Disorders

Publications

Publications

A Year After Implementation of the Telehealth Waiver: Being Offered and Utilizing Video-Specific Telehealth Among Dual-Eligible Medicare Recipients During the COVID-19 Pandemic

An observational, sequential analysis of the relationship between local economic distress and inequities in health outcomes, clinical care, health behaviors, and social determinants of health

Weeks, W. B., Chang, J. E., Pagán, J. A., Aerts, A., Weinstein, J. N., & Ferres, J. L. (n.d.).

Publication year

2023

Journal title

International Journal for Equity in Health

Volume

22

Issue

1

10.1186/s12939-023-01984-6

Abstract

Abstract

Background: Socioeconomic status has long been associated with population health and health outcomes. While ameliorating social determinants of health may improve health, identifying and targeting areas where feasible interventions are most needed would help improve health equity. We sought to identify inequities in health and social determinants of health (SDOH) associated with local economic distress at the county-level. Methods: For 3,131 counties in the 50 US states and Washington, DC (wherein approximately 325,711,203 people lived in 2019), we conducted a retrospective analysis of county-level data collected from County Health Rankings in two periods (centering around 2015 and 2019). We used ANOVA to compare thirty-three measures across five health and SDOH domains (Health Outcomes, Clinical Care, Health Behaviors, Physical Environment, and Social and Economic Factors) that were available in both periods, changes in measures between periods, and ratios of measures for the least to most prosperous counties across county-level prosperity quintiles, based on the Economic Innovation Group’s 2015–2019 Distressed Community Index Scores. Results: With seven exceptions, in both periods, we found a worsening of values with each progression from more to less prosperous counties, with least prosperous counties having the worst values (ANOVA p < 0.001 for all measures). Between 2015 and 2019, all except six measures progressively worsened when comparing higher to lower prosperity quintiles, and gaps between the least and most prosperous counties generally widened. Conclusions: In the late 2010s, the least prosperous US counties overwhelmingly had worse values in measures of Health Outcomes, Clinical Care, Health Behaviors, the Physical Environment, and Social and Economic Factors than more prosperous counties. Between 2015 and 2019, for most measures, inequities between the least and most prosperous counties widened. Our findings suggest that local economic prosperity may serve as a proxy for health and SDOH status of the community. Policymakers and leaders in public and private sectors might use long-term, targeted economic stimuli in low prosperity counties to generate local, community health benefits for vulnerable populations. Doing so could sustainably improve health; not doing so will continue to generate poor health outcomes and ever-widening economic disparities.

Assessing Differences in Social Determinants of Health Screening Rates in a Large, Urban Safety-Net Health System

Association of Medicaid expansion and 1115 waivers for substance use disorders with hospital provision of opioid use disorder services: a cross sectional study

Chang, J. E., Cronin, C. E., Lindenfeld, Z., Pagán, J. A., & Franz, B. (n.d.).

Publication year

2023

Journal title

BMC health services research

Volume

23

Issue

1

10.1186/s12913-023-09035-0

Abstract

Abstract

Introduction: Opioid-related hospitalizations have risen dramatically, placing hospitals at the frontlines of the opioid epidemic. Medicaid expansion and 1115 waivers for substance use disorders (SUDs) are two key policies aimed at expanding access to care, including opioid use disorder (OUD) services. Yet, little is known about the relationship between these policies and the availability of hospital based OUD programs. The aim of this study is to determine whether state Medicaid expansion and adoption of 1115 waivers for SUDs are associated with hospital provision of OUD programs. Methods: We conducted a cross-sectional study of a random sample of hospitals (n = 457) from the American Hospital Association’s 2015 American Hospital Directory, compiled with the most recent publicly available community health needs assessment (2015–2018). Results: Controlling for hospital characteristics, overdose burden, and socio-demographic characteristics, both Medicaid policies were associated with hospital adoption of several OUD programs. Hospitals in Medicaid expansion states had significantly higher odds of implementing any program related to SUDs (OR: 1.740; 95% CI: 1.032–2.934) as well as some specific activities such as programs for OUD treatment (OR: 1.955; 95% CI: 1.245–3.070) and efforts to address social determinants of health (OR: 6.787; 95% CI: 1.308–35.20). State 1115 waivers for SUDs were not significantly associated with any hospital-based SUD activities. Conclusions: Medicaid expansion was associated with several hospital programs for addressing OUD. The differential availability of hospital-based OUD programs may indicate an added layer of disadvantage for low-income patients with SUD living in non-expansion states.

Exploring Barriers and Facilitators to Integrating a Harm Reduction Approach to Substance Use in Three Medical Settings

Facilitation of team-based care to improve HTN management and outcomes: a protocol for a randomized stepped wedge trial

Factors associated with the adoption of evidence-based innovations by substance use disorder treatment organizations: A study of HIV testing

Hospital adoption of harm reduction and risk education strategies to address substance use disorders

Integrating Harm Reduction into Medical Care: Lessons from Three Models

Stakeholder Perspectives on Data-Driven Solutions to Address Cardiovascular Disease and Health Equity in New York City

Lindenfeld, Z., Pagán, J. A., Silver, D., McNeill, E., Mostafa, L., Zein, D., & Chang, J. E. (n.d.).

Publication year

2023

Journal title

AJPM Focus

Volume

2

Issue

3

10.1016/j.focus.2023.100093

Abstract

Abstract

Introduction: There is growing recognition of the importance of addressing the social determinants of health in efforts to improve health equity. In dense urban environments such as New York City, disparities in chronic health conditions (e.g., cardiovascular disease) closely mimic inequities in social factors such as income, education, and housing. Although there is a wealth of data on these social factors in New York City, little is known about how to rapidly use available data sources to address health disparities. Methods: Semistructured interviews were conducted with key stakeholders (N=11) from across the public health landscape in New York City (health departments, healthcare delivery systems, and community-based organizations) to assess perspectives on how social determinants of health data can be used to address cardiovascular disease and health equity, what data-driven tools would be useful, and challenges to using these data sources and developing tools. A matrix analysis approach was used to analyze the interview data. Results: Stakeholders were optimistic about using social determinants of health data to address health equity by delivering holistic care, connecting people with additional resources, and increasing investments in under-resourced communities. However, interviewees noted challenges related to the quality and timeliness of social determinants of health data, interoperability between data systems, and lack of consistent metrics related to cardiovascular disease and health equity. Conclusions: Future research on this topic should focus on mitigating the barriers to using social determinants of health data, which includes incorporating social determinants of health data from other sectors. There is also a need to assess how data-driven solutions can be implemented within and across communities and organizations.

Strategies to support substance use disorder care transitions from acute-care to community-based settings: a scoping review and typology

Substance Use Disorder Program Availability in Safety-Net and Non-Safety-Net Hospitals in the US

Chang, J. E., Franz, B., Pagán, J. A., Lindenfeld, Z., & Cronin, C. E. (n.d.).

Publication year

2023

Journal title

JAMA network open

Volume

6

Issue

8

Page(s)

e2331243

10.1001/jamanetworkopen.2023.31243

Abstract

Abstract

Importance: Safety-net hospitals (SNHs) are ideal sites to deliver addiction treatment to patients with substance use disorders (SUDs), but the availability of these services within SNHs nationwide remains unknown. Objective: To examine differences in the delivery of different SUD programs in SNHs vs non-SNHs across the US and to determine whether these differences are increased in certain types of SNHs depending on ownership. Design, Setting, and Participants: This cross-sectional analysis used data from the 2021 American Hospital Association Annual Survey of Hospitals to examine the associations of safety-net status and ownership with the availability of SUD services at acute care hospitals in the US. Data analysis was performed from January to March 2022. Main Outcomes and Measures: This study used 2 survey questions from the American Hospital Association survey to determine the delivery of 5 hospital-based SUD services: screening, consultation, inpatient treatment services, outpatient treatment services, and medications for opioid use disorder (MOUD). Results: A total of 2846 hospitals were included: 409 were SNHs and 2437 were non-SNHs. The lowest proportion of hospitals reported offering inpatient treatment services (791 hospitals [27%]), followed by MOUD (1055 hospitals [37%]), and outpatient treatment services (1087 hospitals [38%]). The majority of hospitals reported offering consultation (1704 hospitals [60%]) and screening (2240 hospitals [79%]). In multivariable models, SNHs were significantly less likely to offer SUD services across all 5 categories of services (screening odds ratio [OR], 0.62 [95% CI, 0.48-0.76]; consultation OR, 0.62 [95% CI, 0.47-0.83]; inpatient services OR, 0.73 [95% CI, 0.55-0.97]; outpatient services OR, 0.76 [95% CI, 0.59-0.99]; MOUD OR, 0.6 [95% CI, 0.46-0.78]). With the exception of MOUD, public or for-profit SNHs did not differ significantly from their non-SNH counterparts. However, nonprofit SNHs were significantly less likely to offer all 5 SUD services compared with their non-SNH counterparts (screening OR, 0.52 [95% CI, 0.41-0.66]; consultation OR, 0.56 [95% CI, 0.44-0.73]; inpatient services OR, 0.45 [95% CI, 0.33-0.61]; outpatient services OR, 0.58 [95% CI, 0.44-0.76]; MOUD OR, 0.61 [95% CI, 0.46-0.79]). Conclusions and Relevance: In this cross-sectional study of SNHs and non-SNHs, SNHs had significantly lower odds of offering the full range of SUD services. These findings add to a growing body of research suggesting that SNHs may face additional barriers to offering SUD programs. Further research is needed to understand these barriers and to identify strategies that support the adoption of evidence-based SUD programs in SNH settings.

Synchronous Home-Based Telemedicine for Primary Care: A Review

Trends in the Prioritization and Implementation of Substance Use Programs by Nonprofit Hospitals: 2015-2021

Chang, J. E., Cronin, C. E., Pagán, J. A., Simon, J., Lindenfeld, Z., & Franz, B. (n.d.).

Publication year

2023

Journal title

Journal of Addiction Medicine

Volume

17

Issue

4

Page(s)

E217-E223

10.1097/ADM.0000000000001128

Abstract

Abstract

Objectives Hospitalizations are an important opportunity to address substance use through inpatient services, outpatient care, and community partnerships, yet the extent to which nonprofit hospitals prioritize such services across time remains unknown. The objective of this study is to examine trends in nonprofit hospitals' prioritization and implementation of substance use disorder (SUD) programs. Methods We assessed trends in hospital prioritization of substance use as a top five community need and hospital implementation of SUD programing at nonprofit hospitals between 2015 and 2021 using two waves (wave 1: 2015-2018; wave 2: 2019-2021) by examining hospital community benefit reports. We utilized t or χ2 tests to understand whether there were significant differences in the prioritization and implementation of SUD programs across waves. We used multilevel logistic regression to evaluate the relation between prioritization and implementation of SUD programs, hospital and community characteristics, and wave. Results Hospitals were less likely to have prioritized SUD but more likely to have implemented SUD programs in the most recent 3 years compared, even after adjusting for the local overdose rate and hospital-and community-level variables. Although most hospitals consistently prioritized and implemented SUD programs during the 2015-2021 period, a 11% removed and 15% never adopted SUD programs at all, despite an overall increase in overdose rates. Conclusions Our study identified gaps in hospital SUD infrastructure during a time of elevated need. Failing to address this gap reflects missed opportunities to engage vulnerable populations, provide linkages to treatment, and prevent complications of substance use.

Uses of Social Determinants of Health Data to Address Cardiovascular Disease and Health Equity: A Scoping Review

McNeill, E., Lindenfeld, Z., Mostafa, L., Zein, D., Silver, D., Pagán, J., Weeks, W. B., Aerts, A., Rosiers, S. D., Boch, J., & Chang, J. E. (n.d.).

Publication year

2023

Journal title

Journal of the American Heart Association

Volume

12

Issue

21

10.1161/JAHA.123.030571

Abstract

Abstract

BACKGROUND: Cardiovascular disease is the leading cause of morbidity and mortality worldwide. Prior research suggests that social determinants of health have a compounding effect on health and are associated with cardiovascular disease. This scoping review explores what and how social determinants of health data are being used to address cardiovascular disease and improve health equity. METHODS AND RESULTS: After removing duplicate citations, the initial search yielded 4110 articles for screening, and 50 studies were identified for data extraction. Most studies relied on similar data sources for social determinants of health, including geo-coded electronic health record data, national survey responses, and census data, and largely focused on health care access and quality, and the neighborhood and built environment. Most focused on developing interventions to improve health care access and quality or characterizing neighborhood risk and individual risk. CONCLUSIONS: Given that few interventions addressed economic stability, education access and quality, or community context and social risk, the potential for harnessing social determinants of health data to reduce the burden of cardiovascular disease remains unrealized.

Utilizing Publicly Available Community Data to Address Social Determinants of Health: A Compendium of Data Sources

Lindenfeld, Z., Pagán, J. A., & Chang, J. (n.d.).

Publication year

2023

Journal title

Inquiry (United States)

Volume

60

10.1177/00469580231152318

Abstract

Abstract

To compile a compendium of data sources representing different areas of social determinants of health (SDOH) in New York City. We conducted a PubMed search of the peer-reviewed and gray literature using the terms “social determinants of health” and “New York City,” with the Boolean operator “AND.” We then conducted a search of the “gray literature,” defined as sources outside of standard bibliographic databases, using similar terms. We extracted publicly available data sources containing NYC-based data. In defining SDOH, we used the framework outlined by the CDC’s Healthy People 2030, which uses a place-based framework to categorize 5 domains of SDOH: (1) healthcare access and quality; (2) education access and quality; (3) social and community context; (4) economic stability; and (5) neighborhood and built environment. We identified 29 datasets from the PubMed search, and 34 datasets from the gray literature, resulting in 63 datasets related to SDOH in NYC. Of these, 20 were available at the zip code level, 18 at the census tract-level, 12 at the community-district level, and 13 at the census block or specific address level. Community-level SDOH data are readily attainable from many public sources and can be linked with health data on local geographic-levels to assess the effect of social and community factors on individual health outcomes.

Variance of US Hospital Characteristics by Safety-Net Definition

Obesity and Patient Activation: Confidence, Communication, and Information Seeking Behavior

Patient Characteristics Associated with Phone Versus Video Telemedicine Visits for Substance Use Treatment during COVID-19

Patients’ Perspectives on the Shift to Telemedicine in Primary and Behavioral Health Care during the COVID-19 Pandemic

Racial/ethnic disparities in the availability of hospital based opioid use disorder treatment

Chang, J. E., Franz, B., Cronin, C. E., Lindenfeld, Z., Lai, A. Y., & Pagán, J. A. (n.d.).

Publication year

2022

Journal title

Journal of Substance Abuse Treatment

Volume

138

10.1016/j.jsat.2022.108719

Abstract

Abstract

Introduction: While racial/ethnic disparities in the use of opioid use disorder (OUD) treatment in outpatient settings are well documented in the literature, little is known about racial/ethnic disparities in access to hospital-based OUD services. This study examines the relationship between hospital-based or initiated OUD services and the racial/ethnic composition of the surrounding community. Methods: We constructed a dataset marking the implementation of eight OUD strategies for a 20% random sample of nonprofit hospitals in the United States based on 2015–2018 community health needs assessments. We tested the significance of the relationship between each OUD strategy and the racial/ethnic composition of the surrounding county using two-level mixed effects logistic regression models that considered the hierarchical structure of the data of hospitals within states while controlling for hospital-level county-level, and state-level covariates. Results: In both unadjusted and adjusted models, we found that hospital adoption of several OUD services significantly varied based on the percentage of Black or Hispanic residents in their communities. Even after controlling for hospital size, the overdose burden in the community, community socioeconomic characteristics, and state funding, hospitals in communities with high percentage of Black or Hispanic residents had significantly lower odds of offering the most common hospital-based programs to address OUD – including programs that increase access to formal treatment services, prescriber guidelines, targeted risk education and harm reduction, and community coalitions to address opioid use. Conclusions: Hospital adoption of many OUD services varies based on the percentage of Black or Hispanic residents in their communities. More attention should be paid to the role, ability, and strategies that hospitals can assume to address disparities among OUD treatment and access needs, especially those that serve communities with a high concentration of Black and Hispanic residents.

Rapid Transition to Telehealth and the Digital Divide: Implications for Primary Care Access and Equity in a Post-COVID Era

Chang, J. E., Lai, A. Y., Gupta, A., Nguyen, A. M., Berry, C. A., & Shelley, D. R. (n.d.).

Publication year

2021

Journal title

Milbank Quarterly

Volume

99

Issue

2

Page(s)

340-368

10.1111/1468-0009.12509

Abstract

Abstract

Policy Points Telehealth has many potential advantages during an infectious disease outbreak such as the COVID-19 pandemic, and the COVID-19 pandemic has accelerated the shift to telehealth as a prominent care delivery mode. Not all health care providers and patients are equally ready to take part in the telehealth revolution, which raises concerns for health equity during and after the COVID-19 pandemic. Without proactive efforts to address both patient- and provider-related digital barriers associated with socioeconomic status, the wide-scale implementation of telehealth amid COVID-19 may reinforce disparities in health access in already marginalized and underserved communities. To ensure greater telehealth equity, policy changes should address barriers faced overwhelmingly by marginalized patient populations and those who serve them. Context: The COVID-19 pandemic has catalyzed fundamental shifts across the US health care delivery system, including a rapid transition to telehealth. Telehealth has many potential advantages, including maintaining critical access to care while keeping both patients and providers safe from unnecessary exposure to the coronavirus. However, not all health care providers and patients are equally ready to take part in this digital revolution, which raises concerns for health equity during and after the COVID-19 pandemic. Methods: The study analyzed data about small primary care practices’ telehealth use and barriers to telehealth use collected from rapid-response surveys administered by the New York City Department of Health and Mental Hygiene's Bureau of Equitable Health Systems and New York University from mid-April through mid-June 2020 as part of the city's efforts to understand how primary care practices were responding to the COVID-19 pandemic following New York State's stay-at-home order on March 22. We focused on small primary care practices because they represent 40% of primary care providers and are disproportionately located in low-income, minority or immigrant areas that were more severely impacted by COVID-19. To examine whether telehealth use and barriers differed based on the socioeconomic characteristics of the communities served by these practices, we used the Centers for Disease Control and Prevention Social Vulnerability Index (SVI) to stratify respondents as being in high-SVI or low-SVI areas. We then characterized respondents’ telehealth use and barriers to adoption by using means and proportions with 95% confidence intervals. In addition to a primary analysis using pooled data across the five waves of the survey, we performed sensitivity analyses using data from respondents who only took one survey, first wave only, and the last two waves only. Findings: While all providers rapidly shifted to telehealth, there were differences based on community characteristics in both the primary mode of telehealth used and the types of barriers experienced by providers. Providers in high-SVI areas were almost twice as likely as providers in low-SVI areas to use telephones as their primary telehealth modality (41.7% vs 23.8%; P <.001). The opposite was true for video, which was used as the primary telehealth modality by 18.7% of providers in high-SVI areas and 33.7% of providers in low-SVI areas (P <0.001). Providers in high-SVI areas also faced more patient-related barriers and fewer provider-related barriers than those in low-SVI areas. Conclusions: Between April and June 2020, telehealth became a prominent mode of primary care delivery in New York City. However, the transition to telehealth did not unfold in the same manner across communities. To ensure greater telehealth equity, policy changes should address barriers faced overwhelmingly by marginalized patient populations and those who serve them.

Telephone vs. video visits during COVID-19: Safety-net provider perspectives

Difficulty Hearing Is Associated With Low Levels of Patient Activation

Hearing loss is associated with low patient activation