Examining Care Planning Efficiency and Clinical Decision Support Adoption in a System Tailoring to Nurses' Graph Literacy: National, Web-Based Randomized Controlled Trial.

Autor:	Yao Y; University of Florida College of Nursing, Gainesville, FL, United States., Dunn Lopez K; University of Iowa College of Nursing, Iowa City, IA, United States., Bjarnadottir RI; University of Florida College of Nursing, Gainesville, FL, United States., Macieira TGR; University of Florida College of Nursing, Gainesville, FL, United States., Dos Santos FC; University of Florida College of Nursing, Gainesville, FL, United States., Madandola OO; University of Florida College of Nursing, Gainesville, FL, United States., Cho H; University of Florida College of Nursing, Gainesville, FL, United States., Priola KJB; University of Florida College of Nursing, Gainesville, FL, United States., Wolf J; University of Iowa College of Nursing, Iowa City, IA, United States., Wilkie DJ; University of Florida College of Nursing, Gainesville, FL, United States., Keenan G; University of Florida College of Nursing, Gainesville, FL, United States.
Jazyk:	angličtina
Zdroj:	Journal of medical Internet research [J Med Internet Res] 2023 Aug 11; Vol. 25, pp. e45043. Date of Electronic Publication: 2023 Aug 11.
DOI:	10.2196/45043
Abstrakt:	Background: The proliferation of health care data in electronic health records (EHRs) is fueling the need for clinical decision support (CDS) that ensures accuracy and reduces cognitive processing and documentation burden. The CDS format can play a key role in achieving the desired outcomes. Building on our laboratory-based pilot study with 60 registered nurses (RNs) from 1 Midwest US metropolitan area indicating the importance of graph literacy (GL), we conducted a fully powered, innovative, national, and web-based randomized controlled trial with 203 RNs. Objective: This study aimed to compare care planning time (CPT) and the adoption of evidence-based CDS recommendations by RNs randomly assigned to 1 of 4 CDS format groups: text only (TO), text+table (TT), text+graph (TG), and tailored (based on the RN's GL score). We hypothesized that the tailored CDS group will have faster CPT (primary) and higher adoption rates (secondary) than the 3 nontailored CDS groups. Methods: Eligible RNs employed in an adult hospital unit within the past 2 years were recruited randomly from 10 State Board of Nursing lists representing the 5 regions of the United States (Northeast, Southeast, Midwest, Southwest, and West) to participate in a randomized controlled trial. RNs were randomly assigned to 1 of 4 CDS format groups-TO, TT, TG, and tailored (based on the RN's GL score)-and interacted with the intervention on their PCs. Regression analysis was performed to estimate the effect of tailoring and the association between CPT and RN characteristics. Results: The differences between the tailored (n=46) and nontailored (TO, n=55; TT, n=54; and TG, n=48) CDS groups were not significant for either the CPT or the CDS adoption rate. RNs with low GL had longer CPT interacting with the TG CDS format than the TO CDS format (P=.01). The CPT in the TG CDS format was associated with age (P=.02), GL (P=.02), and comfort with EHRs (P=.047). Comfort with EHRs was also associated with CPT in the TT CDS format (P<.001). Conclusions: Although tailoring based on GL did not improve CPT or adoption, the study reinforced previous pilot findings that low GL is associated with longer CPT when graphs were included in care planning CDS. Higher GL, younger age, and comfort with EHRs were associated with shorter CPT. These findings are robust based on our new innovative testing strategy in which a diverse national sample of RN participants (randomly derived from 10 State Board of Nursing lists) interacted on the web with the intervention on their PCs. Future studies applying our innovative methodology are recommended to cost-effectively enhance the understanding of how the RN's GL, combined with additional factors, can inform the development of efficient CDS for care planning and other EHR components before use in practice. (©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, Gail Keenan. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.08.2023.)
Databáze:	MEDLINE
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