Ji E Chang
Ji E Chang
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Assistant Professor of Public Health Policy and Management
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Professional overview
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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
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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
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Honors and awards
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Governor’s Scholar (2007)Regents and Chancellors’ Scholar (2005)
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Areas of research and study
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Cardiovascular DiseaseHealth DisparitiesHealth EquityPublic Health ManagementPublic Health ManagementSafety Net Providers and PatientsSubstance Use Disorders
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Publications
Publications
Coordination across ambulatory care a comparison of referrals and health information exchange across convenient and traditional settings
AbstractChang, J., Chokshi, D., & Ladapo, J. (n.d.).Publication year
2018Journal title
Journal of Ambulatory Care ManagementVolume
41Issue
2Page(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 Trouble
Chang, J. E., Weinstein, B., Chodosh, J., & Blustein, J. (n.d.). In Journal of the American Geriatrics Society (1–).Publication year
2018Volume
66Issue
11Page(s)
2227-2228Health reform and the changing safety net in the United States
Chokshi, D. A., Chang, J. E., & Wilson, R. M. (n.d.).Publication year
2016Journal title
New England Journal of MedicineVolume
375Issue
18Page(s)
1790-1796Convenient ambulatory care-promise, pitfalls, and policy
Chang, J. E., Brundage, S. C., & Chokshi, D. A. (n.d.).Publication year
2015Journal title
New England Journal of MedicineVolume
373Issue
4Page(s)
382-388Community health worker integration into the health care team accomplishes the triple aim in a patient centered medical home
Findley, S., Matos, S., Hicks, A., Chang, J., & Reich, D. (n.d.).Publication year
2014Journal title
Journal of Ambulatory Care ManagementVolume
37Issue
1Page(s)
82Preventing early readmissions
AbstractChokshi, D. A., & Chang, J. E. (n.d.).Publication year
2014Journal title
JAMA - Journal of the American Medical AssociationVolume
312Issue
13Page(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.