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Clinical Algorithms at Work: Shifting from Surveillance to Improving Clinical Outcomes

Andrew Cardon (Health Catalyst), John Shepard (Stanford University)
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Learn how Stanford Hospitals and Clinics used a clinical effectiveness model and late-binding™(1) data warehouse to help reduce central line associated bloodstream infections (CLABSI) and catheter-associated urinary tract infections (CA-UTI). A multidisciplinary team of clinicians, preventionists, clinical informaticists and IT specialists created data visualization, analytic algorithms, and automated data reporting systems to increase the efficiency of CLABSI and CA-UTI surveillance. The algorithm provided inclusion and exclusion criteria, utilizing National Healthcare Safety Network (NHSN) definitions, for patients with a possible CLABSI or CA-UTI as well as an algorithm for calculating central line days.

(1) Trademark of Health Catalyst


Utilizing the hospital’s electronic health record (EHR) system, the interdisciplinary team successfully developed prototype CLABSI and CA-UTI surveillance systems. For six months, the results from the surveillance system were validated by trained infection preventionists by comparing the electronic results to results gathered through complete chart review over the time period. There was an average of 90% reduction in surveillance requirements by utilizing the algorithms. The result? Clinicians can focus on interventions instead of chart abstraction. In addition, the system produced a near real time reporting dashboard which eliminated the need for the staff to produce surveillance reports along with compliance results related to the department’s interventions.

Lesson Learned

Key success factors include executive sponsorship and interdisciplinary team buy-in, late-binding™ data architecture and algorithm implementation design.

Andrew Cardon

Health Catalyst

Mr. Cardon is the Health Catalyst technical lead for Stanford Hospitals and Clinics. Health Catalyst organizes healthcare data into a single source of truth to improve quality of care and reduce cost in a number of months, not years. Mr. Cardon drove the Stanford development efforts for the Late-binding™ Health Catalyst data warehouse platform. He and his team led the design for implementation of the infectious disease clinical algorithms.

Prior to joining Health Catalyst, Mr. Cardon worked for Accenture and Fast Enterprises in program management and consultant roles. He holds a Masters in Business Administration from the University of Notre Dame and a Bachelor in Business from Brigham Young University.

Photo of John Shepard

John Shepard

Stanford University

John Shepard received his BA in Math and MBA from Humboldt State University in Arcata, CA. He then moved to Baltimore to work as the Biostatistician for Hospital Epidemiology, Infection Control, and Antimicrobial Stewardship at The Johns Hopkins Hospital under Trish Perl and Sara Cosgrove. John transitioned to a role as the clinical analyst for Hospital Epidemiology and Infection Control for The Johns Hopkins Health System where he developed processes to integrate and report data from the five hospitals in the Johns Hopkins Health System.

While in Baltimore, John received his Masters in Health Administration and Certificate in Public Informatics from the Johns Hopkins Bloomberg School of Public Health. Upon graduation, he moved to Stanford Hospital and Clinics where he worked as the Quality Analyst for Infection Prevention and Control Department under Sasha Madison. John now acts as a Data Architect for Clinical Business Analytics in the fields of infection control, critical care, chronic disease management, and public health. John’s research focus is in clinical algorithm development and financial modeling of quality improvement initiatives.

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