Finding the Missing Link: Public Health Advisories and Computable Decision Support for Frontline Health Care Personnel
Hyung Paek, Nitu Kashyap, Thomas S. Murray, Scott C. Roberts, Noelle Frye, Jamie Trumpler, Trini Mathew, , Richard A. MartinelloAbstract
Objective
Timely recognition and response to emerging infectious diseases are critical, yet frontline health care personnel often struggle with access to crucial information. This study assessed Centers for Disease Control and Prevention (CDC) Health Alert Network (HAN) advisories as potential computable data sources for clinical decision support (CDS) systems aimed at frontline health care personnel responding to emerging infectious diseases.
Methods
We analyzed 89 HAN advisories using a CDS prototype designed for emergency room triage nurses managing high-impact pathogens. Two reviewers systematically annotated advisories for key elements, with a third reviewer resolving discrepancies.
Results
Of 89 CDC HAN advisories, 70 addressed infectious pathogens, including 50 on 13 high-consequence organisms. Among these advisories, 47% included a start date, none had an end date, 53% mentioned symptoms, and 11% described isolation precautions, which varied significantly from 0% to 27%. Early COVID-19 advisories illustrated evolving guidance.
Conclusions
CDC HAN advisories are often incomplete, specifically lacking dynamic time-specific details and isolation precautions. Enhancing advisories with structured, computable data and a flexible CDS system will improve the timely dissemination of actionable information to frontline health care personnel. This will enable swift, informed decision-making and more optimized patient care.