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Examining Care Planning Efficiency and Clinical Decision Support Adoption in a System Tailoring to Nurses’ Graph Literacy: A National Web-Based RCT
Journal article   Open access   Peer reviewed

Examining Care Planning Efficiency and Clinical Decision Support Adoption in a System Tailoring to Nurses’ Graph Literacy: A National Web-Based RCT

Yingwei Yao, Karen Dunn Lopez, Ragnhildur I. Bjarnadottir, Tamara G R Macieira, Fabiana Cristina Dos Santos, Olatunde O. Madandola, Hwayoung Cho, Karen J B Priola, Jessica Wolf, Diana J. Wilkie, …
Journal of medical Internet research, Vol.25(1), e45043
2023
DOI: 10.2196/45043
PMCID: PMC10457701
PMID: 37566456
url
https://doi.org/10.2196/45043View
Published (Version of record) Open Access

Abstract

Background: The proliferation of health care data presented in electronic health records (EHRs) is fueling the need to consolidate and present the salient aspects in ways that reduce cognitive processing time and promote accurate use. The format in which data are presented can play a key role in achieving the desired patient outcomes while reducing burden to clinicians. Objective: To compare care planning time (CPT) and adoption of evidence-based clinical decision support (CDS) recommendations by registered nurses (RNs) randomly assigned to one of four CDS format groups; 1) text only (TO); 2) text+table (TT); 3) text+graph (TG); 4) tailored (based on RN’s graph literacy score). We hypothesize that the tailored CDS group will have faster CPT (primary) and higher adoption rates (secondary) than the three non-tailored CDS groups. Methods: Eligible RNs employed in an adult hospital unit within the past 2 years were recruited randomly from 10 state nursing licensure lists representing the five regions of the United States (NE, SE, MW, SW, W) to participate in a randomized controlled trial (RCT). RNs were randomly assigned to one of four CDS format groups; (1) text only; 2) text+table; 3) text+graph; 4) tailored (based on RN’s graph literacy score) and interacted with the intervention on their personal computers. Regression analysis was performed to estimate the effect of tailoring and the association between CDS format and RN characteristics. Results: The differences between the tailored (n=46) and the non-tailored (TO [n=55], TT [n=54], TG [n=48]) CDS groups were not significant for either the CPT or the CDS adoption rate. RNs with low graph literacy had longer CPT interacting with text+graph CDS format than text only CDS format (p=.01). CPT under text+graph CDS format was associated with age (p=.02), graph literacy (p=.02), and comfort with EHR (p<.05). Comfort with EHR was also associated with CPT under text+table CDS format (p<.001). Conclusions: We demonstrated the feasibility of an innovative approach for studying EHR CDS in a simulation environment that enables preliminary testing of EHR innovations with minimum unintended risk to patients. Our study findings provided further evidence of the effectiveness of CDS in supporting the adoption of evidence-based recommendations. Although our specific approach of tailoring the CDS format to a participant’s graph literacy did not lead to improvement in either care planning time or CDS adoption rate, we found a robust association between graph literacy and time needed to process graph based CDS. The study also revealed additional important factors to consider when tailoring CDS formats for nurse care planning (i.e., age, comfort with EHR).

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