How to assess the impact of process improvement interventions with routinely collected longitudinal hospital data

Diego Martinez, Mehdi Jalalpour, David Efron, Scott Levin

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: To show how interrupted time series can be used to isolate and measure the impact of process improvement while accounting for confounders often present in complex hospital operations. Methods: Retrospective cohort study comparing the volume of operating room exit delays (OR holds) 52 weeks before and 62 weeks after implementation of a surgical patient throughput optimization program at a tertiary academic hospital. Time-stamped electronic medical records data were collected and analyzed using interrupted time-series design. Segmented regression and Box-Jenkins time series analysis were used to measure OR hold volume pre- and post-implementation, controlling for secular trends in surgical volume, downstream capacity, and the loss of high-volume surgeons. Results: A total of 8,983 surgical patients were discharged during the pre-intervention period and 9,855 during the post-intervention period. The median weekly discharge volume pre-intervention was 175 (interquartile range [IQR] 164–180), and the median bed occupancy was 86% (IQR 84.6–88.1%). The median weekly discharge volume post-intervention was 163 (IQR 150.5–169.8), and the median bed occupancy was 82.1% (IQR 78.9–84.7%). Post-intervention, there was an immediate 60% (95% confidence interval, 54–70%) reduction in the number of OR holds that was sustained over the 14-month post-intervention period.

Original languageEnglish (US)
Pages (from-to)371-375
Number of pages5
JournalIISE Transactions on Healthcare Systems Engineering
Volume9
Issue number4
DOIs
StatePublished - Oct 2 2019

Keywords

  • Care delivery process
  • healthcare management
  • length of stay
  • patient flow

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Safety Research
  • Public Health, Environmental and Occupational Health

Fingerprint Dive into the research topics of 'How to assess the impact of process improvement interventions with routinely collected longitudinal hospital data'. Together they form a unique fingerprint.

Cite this