Characterizing a Naturalistic Decision-Making Phenomenon: Loss of System Resilience Associated With Implementation of New Technology. (September 2016)

• Record Type: Journal Article
• Authors: Patterson, Emily S.; Militello, Laura G.; Su, George; Sarkar, Urmimala
• Other Names: Mosier Kathleen guest-editor.; Militello Laura G. guest-editor.
• Is Part Of: Journal of cognitive engineering and decision making. Volume 10:Number 3(2016:Sep.)
• Page Start: 229
• Page End: 243
• Publication Date: 2016-09
• Subjects: cognitive processes -- cognitive systems engineering -- macro-cognition -- naturalistic decision making -- problem detection -- resilience engineering; Human-computer interaction -- Periodicals; User-centered system design -- Periodicals; 004.019
• DOI: 10.1177/1555343416652524
• Languages: English
• ISSNs: 1555-3434

Abstract

We describe a phenomenon viewed through the conceptual lens of a naturalistic decision-making perspective: a loss of system resilience, due to increased difficulty in performing macrocognition functions, associated with the implementation of new information technology. Examples of the phenomenon collected in a targeted literature review are characterized by stakeholder groups, technology, typical changes in workflow before and after implementation, and potential impacts on macrocognition and patient outcomes for four clinical care environments. The loss of system resilience is due to increased difficulty in performing macrocognition functions: (a) sensemaking due to less effective cognitive warm-up and collaborative framing strategies, (b) detecting events due to missing trends in data and changes to orders, and (c) coordinating due to less clinical knowledge during scheduling and updating information and less effective cross-checks. Potential impacts to patient safety include an increase in unnecessary care, missed care, delays in diagnoses and treatment, redundant care, inaccurate diagnoses, medication errors, and adverse events. We recommended future conceptually driven research in other complex, sociotechnical settings in order to develop useful metrics and reduce the risk of incurring undesirable and unnecessary impacts on cognitive work associated with new technology.