The National Healthcare Safety Network’s digital quality measures: CDC’s automated measures for surveillance of patient safety
Nadine Shehab, Liora Alschuler, Sean McILvenna, Zabrina Gonzaga, Andrew C. Laing, David deRoode, Raymund Dantes, Kristina Betz, Shuai Zheng, Sheila Abner, Elizabeth S. Stutler, Rick Geimer, Andrea L. Benin
Abstract
OBJECTIVE: This article presents the National Healthcare Safety Network (NHSN)'s approach to automation for public health surveillance using digital quality measures (dQMs) via an open-source tool (NHSNLink) and piloting of this approach using real-world data in a newly established collaborative program (NHSNCoLab). The approach leverages Health Level Seven Fast Healthcare Interoperability Resources (FHIR) application programming interfaces to improve data collection and reporting for public health and patient safety beginning with common, clinically significant, and preventable patient harms, such as medication-related hypoglycemia, healthcare facility-onset Clostridioides difficile infection, and healthcare-associated venous thromboembolism. CONCLUSIONS: The NHSN's FHIR dQMs hold the promise of minimizing the burden of reporting, improving accuracy, quality, and validity of data collected by NHSN, and increasing speed and efficiency of public health surveillance.