Appl Clin Inform 2017; 08(03): 763-778
DOI: 10.4338/ACI-2017-02-RA-0033
Research Article
Schattauer GmbH

A Qualitative Exploration of Nurses’ Information-Gathering Behaviors Prior to Decision Support Tool Design

Alvin D. Jeffery
1  U.S. Department of Veterans Affairs, GRECC, Nashville, Tennessee, United States
Betsy Kennedy
2  Vanderbilt University School of Nursing, Nashville, Tennessee, United States
Mary S. Dietrich
2  Vanderbilt University School of Nursing, Nashville, Tennessee, United States
Lorraine C. Mion
3  Ohio State University College of Nursing, Columbus, Ohio, United States
Laurie L. Novak
4  Vanderbilt University Department of Biomedical Informatics, Nashville, Tennessee, United States
› Author Affiliations
Funding The publication was supported by CTSA award No. UL1TR000445 from the National Center for Advancing Translational Sciences as well as resources and the use of facilities at the VA Tennessee Valley Healthcare System. Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences, the National Institutes of Health, the Department of Veterans Affairs, or the United States Government.
Further Information

Publication History

received: 21 February 2017

accepted in revised form: 11 May 2017

Publication Date:
29 December 2017 (online)


Background: Large and readily-available clinical datasets combined with improved computational resources have permitted the exploration of many new research and clinical questions. Predictive analytics, especially for adverse events, has surfaced as one promising application of big data, and although statistical results can be highly accurate, little is known about how nurses perceive this new information and how they might act upon it. Objectives: Within the context of recognizing patients at risk for cardiopulmonary arrest, this study explored the possibility of incorporating predictive analytics into clinical workflows by identifying nurses’ current information gathering activities and perceptions of probability-related terms. Methods: We used a qualitative description approach for data collection and analysis in order to understand participants’ information gathering behaviors and term perceptions in their own words. We conducted one-on-one interviews and a focus group with a total of 10 direct care bedside nurses and 8 charge nurses. Results: Participants collected information from many sources that we categorized as: Patient, Other People, and Technology. The process by which they gathered information was conducted in an inconsistent order and differed by role. Major themes comprised: (a) attempts to find information from additional sources during uncertainty, (b) always being prepared for the worst-case scenario, and (c) the desire to review more detailed predictions. Use of the words probability, risk, and uncertainty were inconsistent. Conclusions: In an effort to successfully incorporate predictive analytics into clinical workflows, we have described nurses’ perceived work practices for gathering information related to clinical deterioration and nurses’ beliefs related to probability-based information. Findings from our study could guide design and implementation efforts of predictive analytics in the clinical arena.

Jeffery AD, Kennedy B, Dietrich MS, Mion LC, Novak LL. A Qualitative Exploration of Nurses’ Information-Gathering Behaviors Prior to Decision Support Tool Design. Appl Clin Inform 2017; 8: 763–778

Human and Animal Subjects Protections

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by Vanderbilt University Institutional Review Board. Animal subjects were not included in the project.