| Primary Author: | Michael J. Yuan, PhD |
| Co-Principal Investigators/Collaborators: | Mike Finley, Ju Long, Christy Mills, Kim Johnson |
| Organization: | Ringful Health |
Abstract
Background
Failure to rescue (FTR) is a leading hospital quality indicator (1,2). Research has indicated that FTR can be reduced or prevented if the nurse can recognize, evaluate, and escalate early warning signs when the patient suffers a critical change before coding (3,4). However, nurses are not trained to evaluate symptoms for diagnoses, and communication barriers in hospitals prevent effective escalation of problems (5). Furthermore, diagnostic decisions are prone to cognitive errors such as premature closure (6).
Purpose
To develop a bedside clinical decision support system (CDSS) device that provides diagnostic aid for nurses at the point of care when critical change occurs, guides nurses through the escalation process without interrupting workflow, and facilitates communication between nurses, Rapid Response Team (RRT) and physicians.
Materials & Methods
The CDSS UI is an iPad featuring an innovative dynamic probabilistic checklist (7). It is supported by a Bayesian decision engine and evidence-based decision rules, as well as standard order / procedure sets for escalation. The rules and contents are managed by a central web based Content Management System (CMS). Research and evaluation methods to validate the CDSS include heuristic evaluation by experts, end user performance evaluation, task load index evaluation, RRT chart analysis, clinician panels for content development and validation, and simulated end user tests.
Results
The CDSS proves to be easy to use for nurses, and integrates well into their existing teamwork workflow. The decision rules and contents, including medical descriptions, findings, Bayesian probabilities and standard order sets, are validated by both physicians and nurses.
Conclusion
We have validated a novel approach to build technology-enabled CDSS for nurses with potentials to reduce FTRs and associated diagnostic errors. The project is currently under clinical trial, which will yield new evidence on the validity of rules and user adoption.
Bibliography
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- Tait D. Nursing recognition and response to signs of clinical deterioration. Nurs Manag (Harrow). 2010 Oct;17(6):31-5.
- Hodgetts TJ, Kenward G, Vlachonikolis IG, Payne S, Castle N. The identification of risk factors for cardiac arrest and formulation of activation criteria to alert a medical emergency team. Resuscitation. 2002 Aug; 54(2):125-31.
- Mackintosh N, Sandall J. Overcoming gendered and professional hierarchies in order to facilitate escalation of care in emergency situations: the role of standardised communication protocols. Soc Sci Med. 2010 Nov; 71(9):1683-6.
- Graber, ML. Diagnostic error in internal medicine. Arch Intern Med. 2005 Jul 11;165(13):1493-9.
- Winters BD, Gurses AP, Lehmann H, Sexton JB, Rampersad CJ, Pronovost PJ, “Clinical review: checklists – translating evidence into practice,” Crit Care. 2009;13(6):210.
© Improvement Science Research Network, 2011