Saving Lives With Algorithm-Enabled Process Innovation for Sepsis Care

37 Pages Posted: 27 Sep 2019

See all articles by Idris Adjerid

Idris Adjerid

Pamplin College of Business

Mehmet Ayvaci

University of Texas at Dallas - Department of Information Systems & Operations Management

Özalp Özer

Jindal School of Management - The University of Texas at Dallas

Date Written: September 19, 2019

Abstract

Predictive algorithms have an increasingly important role in supporting the day-to-day operations of healthcare organizations. Yet, fully realizing the value of algorithms lies critically in the opportunity to re-engineer the related processes and redefine roles in ways that make organizations more effective. We study whether and how algorithm-enabled process innovation (AEPI) creates value in the context of early diagnosis of sepsis|a costly condition that is the leading cause of death for hospitalized patients. Specifically, we collaborated with a large U.S. based hospital system and examined how AEPI developed for sepsis care impact patient mortality and related process outcomes (e.g., timely diagnosis and treatment). Our empirical analysis shows that sepsis AEPI reduces the likelihood of death from sepsis (42% relative reduction in mortality risk due to sepsis). This reduction occurs in parallel with improvements in timeliness of diagnostic (53% relative increase in the likelihood of timely lactate measurement) and clinical interventions (28% relative increase in the likelihood of timely antibiotics administration) for sepsis patients. We identify partial lapses in process outcomes in parallel to a partial lapse in AEPI's propensity to reduce sepsis-related mortality in the early phase of implementation. This lapse mostly recovers when the entire hospital implements sepsis AEPI. Our findings suggest that streamlining sepsis care processes through a predictive algorithm holds significant promise in reducing the loss of life from sepsis. We show that such value, however, requires adherence to process changes even after the algorithm becomes a routine part of the day-to-day operations of the hospital.

Suggested Citation

Adjerid, Idris and Ayvaci, Mehmet and Özer, Özalp, Saving Lives With Algorithm-Enabled Process Innovation for Sepsis Care (September 19, 2019). Available at SSRN: https://ssrn.com/abstract=3456870 or http://dx.doi.org/10.2139/ssrn.3456870

Idris Adjerid

Pamplin College of Business ( email )

2058 Pamplin College of Business
Blacksburg, VA 20461
United States

Mehmet Ayvaci

University of Texas at Dallas - Department of Information Systems & Operations Management ( email )

P.O. Box 830688
Richardson, TX 75083-0688
United States

Özalp Özer (Contact Author)

Jindal School of Management - The University of Texas at Dallas ( email )

Jindal School of Management
800 W. Campbell Road
Richardson, TX 75080
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
28
Abstract Views
175
PlumX Metrics