Impact of Mandated Public Reporting in California on 30-Day readmission following CABG surgery: A Health policy analysis

Monika Ray, Banafsheh Sadeghi, Dominique Ritley, Patrick S. Romano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The 30-day all-cause readmission rate following coronary artery bypass graft (CABG) surgery is considered an important outcome measure for patients because higher rates can be an indicator of low quality and unnecessary health care costs. Our research uses rigorous methods to explore the impact of mandatory public reporting of all-cause readmission rates following CABG surgery in California. We used a hierarchical logistic regression model on 173, 823 CABG patient records. This model standardised outcomes across 10 U.S. states that were not previously comparable due to different CABG definitions and metrics. Additionally, in order to account for the differences in medical practice across different states, we applied a differencein-difference method to estimate the impact of public reporting. Finally, a recycled prediction method was used to estimate the number of averted readmissions following public reporting initiation in California.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
EditorsChaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6205-6207
Number of pages3
ISBN (Electronic)9781728108582
DOIs
StatePublished - Dec 2019
Event2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States
Duration: Dec 9 2019Dec 12 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

Conference

Conference2019 IEEE International Conference on Big Data, Big Data 2019
CountryUnited States
CityLos Angeles
Period12/9/1912/12/19

Keywords

  • all-cause readmission rate
  • coronary artery bypass graft surgery
  • difference-in-difference model
  • hierarchical logistic regression
  • mandating public reporting
  • recycled predictions
  • risk-adjustment

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management

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