CC BY 4.0 · ACI Open 2019; 03(01): e18-e25
DOI: 10.1055/s-0039-1684001
Original Article
Georg Thieme Verlag KG Stuttgart · New York

Optimization of Data Collection during Public Health Emergencies—Experience with APACHE II Score

Elizabeth B. White
1  Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States
,
Sarah Collins Rossetti
2  Department of Biomedical Informatics, Columbia University, New York, New York, United States
3  School of Nursing, Columbia University, New York, New York, United States
,
Neelima Karipineni
4  Brigham and Women's Hospital, Boston, Massachusetts, United States
5  Harvard Medical School, Boston, Massachusetts, United States
,
Saverio Maviglia
4  Brigham and Women's Hospital, Boston, Massachusetts, United States
5  Harvard Medical School, Boston, Massachusetts, United States
,
Raquel Bartz
6  Duke University Medical Center, Durham, North Carolina, United States
,
Satish Bhagwanjee
7  University of Washington, Seattle, Washington, United States
,
J. Perren Cobb
8  University of Southern California, Los Angeles, California, United States
,
Roberto A. Rocha
4  Brigham and Women's Hospital, Boston, Massachusetts, United States
5  Harvard Medical School, Boston, Massachusetts, United States
,
Beatriz H. Rocha
4  Brigham and Women's Hospital, Boston, Massachusetts, United States
5  Harvard Medical School, Boston, Massachusetts, United States
› Author Affiliations
Funding This work was partially funded by a contract from the US Food and Drug Administration.
Further Information

Publication History

16 January 2018

16 January 2019

Publication Date:
10 April 2019 (online)

Abstract

Background Capturing accurate clinical data in real time is a challenge during public health emergencies. The United States Critical Illness and Injury Trials Group-Program for Emergency Preparedness is committed to improving these preparedness efforts.

Objectives We aimed to create an electronic Acute Physiology and Chronic Health Evaluation (APACHE) II data collection instrument that (1) leverages Research Electronic Data Capture (REDCap) automated calculations and logic, (2) may be shared across sites, (3) overcomes limitations in existing APACHE II instruments in the REDCap library, and (4) suggests changes to be made to data collection instruments during emergencies.

Methods The APACHE II instrument was implemented using REDCap. Data fields were divided into four sections: age, Acute Physiology, Glasgow Coma Scale, and chronic health status. Usability testing was followed by two preliminary evaluations: a comparison to existing APACHE II instruments and a simulated emergency exercise.

Results The final instrument consisted of 34 data fields. It produced an accurate APACHE II score and was faster to complete than two previous implementations (average of 97.5 seconds vs. 323.5 and 183.5 seconds). During the simulated emergency exercise, the instrument was used at 10 sites to create 34 patient records; median time to complete the instrument was 150.5 seconds.

Conclusion This project demonstrated feasibility of improving the accuracy and efficiency of a data collection instrument. Future efforts should focus on expanding these methods to develop other scoring tools for use during emergencies and additional testing to ensure it is ready for use during a real emergency.

Protection of Human and Animal Subjects

This study did not involve any human/animal subjects.