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Menghan Shen

Harvard Kennedy School, Research fellow

Email: menghanshen@hks.harvard.edu

Menghan Shen is currently a research fellow at the Harvard Kennedy School. She is an associate professor at the School of Government at Sun Yat-sen University, Guangzhou, China. She worked at Waseda University as an assistant professor between 2016 to 2018.

She received her doctoral degree from the economics and education program, Teachers College, Columbia University. She received a B.A. in economics and mathematics from Bryn Mawr College and Master in International Education Policy from Harvard University.

Her dissertation focused on school desegregation in the U.S. and the paper was published in Economics of Education Review. She currently conducts research on health policy in China and has published paper in Social Science and Medicine.

She teaches methods of social science to undergraduate students and public economics to MPA students.

You can reach her at shenmenghan at gmail.com or menghanshen@hks.harvard.edu

EDUCATION

  • 2016 Ph.D., Economics and Education Columbia University, USA
  • 2011 Master, International Education Policy Harvard University, USA
  • 2010 B.A., Economics; Mathematics Bryn Mawr College, USA

Research Field

  • Health Economics
  • Economics of Education
  • Development Economics

ACADEMIC APPOINTMENTS

  • 2023 – Research Fellow, Harvard Kennedy School
  • 2019 – Associate Professor, School of Government, Sun Yat-sen University, China
  • 2016 – 2018 Assistant Professor, Institute for Advanced Study, Waseda University, Japan

WORKING PAPER 

  • Migrant children’s take-up of social health insurance: experimental evidence from China
  • Hospitals’ response to changes in the prospective payment system: evidence from China
  • Is There A Return to Data Analysis Skills: evidence from an audit study
  • Impact of a targeted nurse-led care coordination intervention for the elderly using predictive algorithm: a regression discontinuity analysis

ABSTRACT

  • OBJECTIVE: This study used a regression discontinuity design to assess if a nurse-led care coordination intervention targeting post-discharge elderly patients with elevated risk of emergency medical admission is associated with 30-day readmission and mortality outcomes.
    DESIGN: Observational study.
  • SETTING: All public hospitals in Hong Kong.
  • PARTICIPANTS: 641,492 eligible index admissions corresponding to 194,091 unique patients aged 60 or above from April 2009 to December 2011. Of these patients, 222,982 (34.76%) were considered to be at elevated risk and were assigned to receive the intervention after discharge.
    INTERVENTIONS: Patients were automatically enrolled in the Hospital Admission Risk Reduction Program for the Elderly program if their predicted risk of 28-day emergency medical admission was greater than 17%, as determined by an automated predictive model based on electronic health record data. For this group of elderly patients, the program employed a specialized team of nurses trained to provide a structured telephone-based care coordination intervention.
  • MAIN OUTCOME MEASURES: Emergency department visits, unplanned and planned hospital readmissions, and in-hospital mortality outcomes within 30 days after hospital discharge.
  • RESULTS: Regression discontinuity estimates indicated that the intervention was significantly associated with a reduction in emergency department visits (absolute risk reduction -2.2%, 3.4% to 0.9%), a reduction in emergency readmission rates (absolute risk reduction -1.3%, 2.3% to 3%), an increase in planned readmission rates (absolute risk reduction 6.5%, 4.9% to 8.3%), an increase in total readmission rates (absolute risk reduction 6.5%, 4.9% to 8.3%), and a reduction in in-hospital mortality (absolute risk reduction 0.6%, 0.1% to 0.3%). Similar effects were found for 60-day, 90-day, and 180-day readmission and mortality outcomes. The associations varied across subgroups, with no statistically significant effect on patients aged 80 or above.
  • CONCLUSIONS: The use of an automated predictive model to identify patients with elevated risk of emergency medical admission for a care coordination program was associated with lower rate of 30-day emergency department visits, lower rate of unplanned readmissions, higher rate of planned readmissions and total readmissions, and lower rate of in-hospital mortality among the targeted elderly population. Similar effects were found for 60-day, 90-day, and 180-day outcomes. However, no effects of the intervention were found on patients aged 80 or above. The study provides evidence suggesting the effectiveness of the intervention at a city-wide scale in a fragmented healthcare setting, but more research is needed to understand how to further improve the care coordination program to reduce total readmissions.

PUBLICATIONS