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Background Clinical decision support (CDS) tools—with easily understood and actionable information, at the point of care—are needed to help registered nurses (RNs) make evidence-based decisions. Not clear are the optimal formats of CDS tools. Thorough, preclinical testing is desirable to avoid costly errors associated with premature implementation in electronic health records. Objective The aims of this study were to determine feasibility of the protocol designed to compare multiple CDS formats and evaluate effects of numeracy and graph literacy on RN adoption of best practices and care planning time in a simulated environment. Methods In this pilot study, 60 RNs were randomly assigned to one of four CDS conditions (control, text, text + graph, and text + table) and asked to adjust the plan of care for two patient scenarios over three shifts. Fourteen best practices were identified for the two patients and sent as suggestions with evidence to the three CDS groups. Best practice adoption rates, care planning time, and their relationship to the RN's numeracy and graph literacy scores were assessed. Results CDS groups had a higher adoption rate of best practices ( p < .001) across all shifts and decreased care planning time in shifts 2 ( p = .01) and 3 ( p = .02) compared with the control group. Higher numeracy and graph literacy were associated with shorter care planning times under text + table ( p = .05) and text + graph ( p = .01) conditions. No significant differences were found between the three CDS groups on adoption rate and care planning time. Discussion This pilot study shows the feasibility of our protocol. Findings show preliminary evidence that CDS improves the efficiency and effectiveness of care planning decisions and that the optimal format may depend on individual RN characteristics. We recommend a study with sufficient power to compare different CDS formats and assess the impact of potential covariates on adoption rates and care planning time.

We present findings of a comparative study of numeracy and graph literacy in a representative group of 60 practicing nurses. This article focuses on a fundamental concern related to the effectiveness of numeric information displayed in various features in the electronic health record during clinical workflow. Our findings suggest the need to consider numeracy and graph literacy when presenting numerical information as well as the potential for tailoring numeric display types to an individual's cognitive strengths.

PURPOSE To determine the acceptability, usefulness, and ease of use for four nursing clinical decision support interface prototypes. METHODS In a simulated hospital environment, 60 registered nurses (48 female; mean age = 33.7 ± 10.8; mean years of experience = 8.1 ± 9.7) participated in a randomized study with four study groups. Measures included acceptability, usefulness, and ease of use scales. FINDINGS Mean scores were high for acceptability, usefulness, and the ease of use for all four groups. Inexperienced participants (

Our long-term goal was to ensure nurse clinical decision support works as intended before full deployment in clinical practice. As part of a broader effort, this pilot project explored factors influencing acceptance/nonacceptance of eight clinical decision support suggestions displayed in an electronic health record-based nursing plan of care software prototype. A diverse sample of 21 nurses participated in this high-fidelity clinical simulation experience and completed a questionnaire to assess reasons for accepting/not accepting the clinical decision support suggestions. Of 168 total suggestions displayed during the experiment (eight for each of the 21 nurses), 123 (73.2%) were accepted, and 45 (26.8%) were not accepted. The mode number of acceptances by nurses was seven of eight, with only two of 21 nurses accepting all. The main reason for clinical decision support acceptance was the nurse's belief that the suggestions were good for the patient (100%), with other features providing secondary reinforcement. Reasons for nonacceptance were less clear, with fewer than half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high-quality simulation and targeted questionnaires about specific clinical decision support selections offer a cost-effective means for testing before full deployment in clinical practice.