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Computer-based technologies have been widely used in nursing education, although the best educational modality to improve documentation and nursing diagnostic accuracy using electronic health records is still under investigation. It is important to address this gap and seek an effective way to address increased accuracy around nursing diagnoses identification. Nursing diagnoses are judgments that represent a synthesis of data collected by the nurse and used to guide interventions and to achieve desirable patients' outcomes. This current investigation is aimed at comparing the nursing diagnostic accuracy, satisfaction, and usability of a computerized system versus a traditional paper-based approach. A total of 66 nursing students solved three validated clinical scenarios using the NANDA-International terminologies traditional paper-based approach and then the computer-based Clinical Decision Support System. Study findings indicated a significantly higher nursing diagnostic accuracy (P To explore the impact of 12 American Nurses Association recognized standardized nursing terminologies (SNTs) on patient and organizational outcomes.
Previous studies reported an effect of SNTs on outcomes, but no previous frameworks nor meta-analyses were found.
Systematic review and meta-analyses.
PubMed, Scopus, CINAHL, and OpenGrey databases were last consulted in July 2021. All abstracts and full texts were screened independently by two researchers. The review included primary quantitative studies that reported an association between recognized SNTs and outcomes. Two reviewers independently assessed the risk of bias and certainty of evidence for each meta-analyzed outcome using the “Grading of Recommendations, Assessment, Development and Evaluation” (GRADE) approach.
Fifty-three reports were included. NANDA-NIC-NOC and Omaha System were the most frequently reported SNTs used in the studies. Risk of bias in randomized controlled trials and not-randomized controlled trials ranged from high to unclear, this risk was low in cross-sectional studies. The number of nursing diagnoses NANDA-I moderately correlated with the intensive care unit length of stay (r = 0.38; 95% CI = 0.31–0.44). Using the Omaha System nurse-led transitional care program showed a large increase in both knowledge (d = 1.21; 95% CI = 0.97–1.44) and self-efficacy (d = 1.23; 95% CI = 0.97–1.48), while a reduction on the readmission rate (OR = 0.46; 95% CI = 0.09–0.83). Nursing diagnoses were found to be useful predictors for organizational (length of stay) and patients' outcomes (mortality, quality of life). The GRADE indicated that the certainty of evidence was rated from very low to low.
Studies using SNTs demonstrated significant improvement and prediction power in several patients' and organizational outcomes. Further high-quality research is required to increase the certainty of evidence of these relationships.
SNTs should be considered by healthcare policymakers to improve nursing care and as essential reporting data about patient's nursing complexity to guide reimbursement criteria.
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