Ji E Chang
Assistant Professor of Public Health Policy and Management
Dr Ji. Chang is an equity-focused health services researcher who studies the role of organization, management, and policies in facilitating equitable access to evidence-based care. The primary goal of her research has been to build a greater understanding and awareness of how changes in health care policy, organization, and delivery may differentially affect disadvantaged populations and safety net providers. She uses mixed-methods research designs to demonstrate disparities in the availability of care and highlight barriers faced by safety net providers and underserved patients in accessing evidence-based care. In addition to research, Dr. Chang is enthusiastic about developing new courses in the Public Health Policy and Management program and training students to face the workforce with skills that are both desired and needed in public health organizations.
Dr. Chang received a B.A. in Economics from the University of California at Berkeley as a Regents and Chancellor’s Scholar in 2005, a M.S. in Public Policy and Management from Carnegie Mellon University with distinction in 2007, and a PhD in Public Administration from New York University in 2016.
BA, Economics, University of California at Berkeley, Berkeley, CAMS, Public Policy and Management, Carnegie Mellon University, Pittsburgh, PAPhD, Public Administration, New York University, New York, NY
Governor’s Scholar (2007)Regents and Chancellors’ Scholar (2005)
Continuity of CareInter-organizational NetworksPublic Health ManagementPublic Health Policy
Racial/ethnic disparities in the availability of hospital based opioid use disorder treatmentChang, J. E., Franz, B., Cronin, C. E., Lindenfeld, Z., Lai, A. Y., & Pagán, J. A.
Journal titleJournal of Substance Abuse TreatmentAbstractIntroduction: 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 EraChang, J. E., Lai, A. Y., Gupta, A., Nguyen, A. M., Berry, C. A., & Shelley, D. R.
Journal titleMilbank Quarterly
Page(s)340-368AbstractPolicy 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
Coordination across ambulatory care a comparison of referrals and health information exchange across convenient and traditional settingsChang, J., Chokshi, D., & Ladapo, J.
Journal titleJournal of Ambulatory Care Management
Page(s)128-137AbstractUrgent care centers have been identified as one means of shifting care from high-cost emergency departments while increasing after-hours access to care. However, the episodic nature of urgent care also has the potential to fragment care. In this study, we examine the adoption of 2 coordination activities—referrals and the electronic exchange of health information—at urgent care centers and other ambulatory providers across the United States. We find that setting is significantly associated with both health information exchange and referrals. Several organization-level variables and environment-level variables are also related to the propensity to coordinate care.
Hospital Readmission Risk for Patients with Self-Reported Hearing Loss and Communication TroubleChang, J. E., Weinstein, B., Chodosh, J., & Blustein, J. In Journal of the American Geriatrics Society.
Health reform and the changing safety net in the United States
Convenient ambulatory care-promise, pitfalls, and policy
Community health worker integration into the health care team accomplishes the triple aim in a patient centered medical homeFindley, S., Matos, S., Hicks, A., Chang, J., & Reich, D.
Journal titleJournal of Ambulatory Care Management
Preventing early readmissionsChokshi, D. A., & Chang, J. E.
Journal titleJAMA - Journal of the American Medical Association
Page(s)1344-1345AbstractResults In 42 trials, the tested interventions prevented early readmissions (pooled random-effects relative risk, 0.82 [95%CI, 0.73-0.91]; P < .001; I2 = 31%), a finding thatwas consistent across patient subgroups. Trials published before 2002 reported interventions thatwere 1.6 times more effective than those tested later (interaction P = .01). In exploratory subgroup analyses, interventions with many components (interaction P = .001), involving more individuals in care delivery (interaction P = .05), and supporting patient capacity for self-care (interaction P = .04)were 1.4, 1.3, and 1.3 times more effective than other interventions, respectively. A post hoc regression model showed incremental value in providing comprehensive, postdischarge support to patients and caregivers.Conclusions and Relevance Tested interventions are effective at reducing readmissions, but more effective interventions are complex and support patient capacity for self-care. Interventions tested more recently are less effective.Jamainternal Medicine Preventing 30-Day Hospital Readmissions: A Systematic Reviewand Meta-analysis of Randomized Trials Aaron L. Leppin, MD; Michael R. Gionfriddo, PharmD; Maya Kessler, MD; Juan Pablo Brito, MBBS; Frances S. Mair, MD; Katie Gallacher, MBChB; ZhenWang, PhD; Patricia J. Erwin, MLS; Tanya Sylvester, BS; Kasey Boehmer, BA; Henry H. Ting, MD, MBA; M. Hassan Murad, MD; Nathan D. Shippee, PhD; Victor M. Montori, MD.Importance Reducing early (<30 days) hospital readmissions is a policy priority aimed at improving health care quality. The cumulative complexity model conceptualizes patient context. It predicts that highly supportive discharge interventions will enhance patient capacity to enact burdensome self-care and avoid readmissions.Objective To synthesize the evidence of the efficacy of interventions to reduce early hospital readmissions and identify intervention features-including their impact on treatment burden and on patients' capacity to enact postdischarge self-care-that might explain their varying effects. DATA SOURCESWe searched PubMed, Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL, and Scopus (1990 until April 1, 2013), contacted experts, and reviewed bibliographies.Study Selection Randomized trials that assessed the effect of interventions on all-cause or unplanned readmissions within 30 days of discharge in adult patients hospitalized for a medical or surgical cause for more than 24 hours and discharged to home.Data Extraction and Synthesis Reviewer pairs extracted trial characteristics and used an activity-based coding strategy to characterize the interventions; fidelity was confirmed with authors. Blinded to trial outcomes, reviewers noted the extent to which interventions placed additional work on patients after discharge or supported their capacity for self-care in accordance with the cumulative complexity model.Main Outcomes and Measures Relative risk of all-cause or unplanned readmission with or without out-of-hospital deaths at 30 days postdischarge.