Analysis of Nursing Clinical Decision Support Requests and Strategic Plan in a Large Academic Health System

Comparison of nursing diagnostic accuracy when aided by Knowledge-Based Clinical Decision Support Systems with Clinical Diagnostic Validity and Bayesian Decision Models for psychiatric care plan formulation among nursing students: a quasi-experimental study

BACKGROUND

The most suitable and reliable inference engines for Clinical Decision Support Systems in nursing clinical practice have rarely been explored.

PURPOSE

This study examined the effect of Clinical Diagnostic Validity-based and Bayesian Decision-based Knowledge-Based Clinical Decision Support Systems on the diagnostic accuracy of nursing students during psychiatric or mental health nursing practicums.

METHODS

A single-blinded, non-equivalent control group pretest-posttest design was adopted. The participants were 607 nursing students. In the quasi-experimental design, two intervention groups used either a Knowledge-Based Clinical Decision Support System with the Clinical Diagnostic Validity or a Knowledge-Based Clinical Decision Support System with the Bayesian Decision inference engine to complete their practicum tasks. Additionally, a control group used the psychiatric care planning system without guidance indicators to support their decision-making. SPSS, version 20.0 (IBM, Armonk, NY, USA) was used for data analysis. chi-square (χ2) test and one-way analysis of variance (ANOVA) used for categorical and continuous variables, respectively. Analysis of covariance was done to examine the PPV and sensitivity in the three groups.

RESULTS

Results for the positive predictive value and sensitivity variables indicated that decision-making competency was highest in the Clinical Diagnostic Validity group, followed by the Bayesian and control groups. The Clinical Diagnostic Validity and Bayesian Decision groups significantly outperformed the control group in terms of scores on a 3Q model questionnaire and the modified Technology Acceptance Model 3. In terms of perceived usefulness and behavioral intention, the Clinical Diagnostic Validity group had significantly higher 3Q model and modified Technology Acceptance Model 3 scores than the Bayesian Decision group, which had significantly higher scores than the control group.

CONCLUSION

Knowledge-Based Clinical Decision Support Systems can be adopted to provide patient-oriented information and assist nursing student in the rapid management of patient information and formulation of patient-centered care plans.

Application and Feasibility Study of Integrated Nursing Information Construction in Nephrology Nursing

With the continuous deepening of medical reforms and the continuous attempts and explorations of various management models, the traditional health care model is undergoing tremendous changes, and patients' needs for medical institutions are becoming more and more comprehensive. Medical institutions are meeting the needs of providing medical services to patients at the same time. It is even more necessary to change our thinking and enhance the service concept. This article is based on case-based deep learning hospital nursing business process reengineering and the application and feasibility study of integrated nursing information construction in nephrology nursing. This article uses the literature analysis method, the social survey method, and other methods to discuss the construction of integrated nursing information. On the one hand, the content of this article uses the concept of process reengineering to analyze the current development status and existing problems of the hospital care industry and find countermeasures to solve problems. On the other hand, the main research content of this article is the construction of integrated nursing information and its analysis of the application and feasibility of nursing in the nephrology department. At the same time, under the background of the rapid development of the mobile Internet, we will carry out extended thinking on the continuous transformation of the construction of nursing information. According to the survey results, 87.5% of patients in the nephrology department are dissatisfied with the current hospital's work efficiency, and 85.7% of the nursing staff in the nephrology department are generally satisfied with the information management of the current department. After the implementation of the hospital information integration system, patient satisfaction is as high as 98.2%, and the satisfaction of medical staff reached 94.2%. The construction of integrated nursing information has played a great role in the application of nephrology nursing.

Implementation of a Nurse-Driven Asthma Pathway in the Pediatric Intensive Care Unit

Asthma is one of the most common conditions requiring admission to a pediatric intensive care unit. Dosing and weaning medications, particularly bronchodilators, are highly variable, and evidence-based weaning algorithms for clinicians are lacking in this setting.

METHODS

Patients admitted to a quaternary pediatric intensive care unit diagnosed with acute severe asthma were evaluated for time spent receiving continuous albuterol therapy, the length of stay in the intensive unit care unit, and the length of stay in the hospital. We developed an asthma pathway and continuous bronchodilator weaning algorithm to be used by bedside nurses. We then implemented two major Plan-Do-Study-Act cycles to facilitate the use of the pathway. They included implementing the algorithm and then integrating it as a clinical decision support tool in the electronic medical record. We used standard statistics and quality improvement methodology to analyze results.

RESULTS

One-hundred twenty-six patients met inclusion criteria during the study period, with 32 during baseline collection, 60 after weaning algorithm development and implementation, and 34 after clinical decision support implementation. Using quality improvement methodology, hours spent receiving continuous albuterol decreased from a mean of 43.6 to 28.6 hours after clinical decision support development. There were no differences in length of stay using standard statistics and QI methodology.

CONCLUSION

Protocolized asthma management in the intensive care unit setting utilizing a multidisciplinary approach and clinical decision support tools for bedside nursing can reduce time spent receiving continuous albuterol and may lead to improved patient outcomes.

System Level Informatics to Improve Triage Practices for Sickle Cell Disease Vaso-Occlusive Crisis: A Cluster Randomized Controlled Trial

BACKGROUND

National Heart Lung and Blood Institute guidelines for the treatment of vaso-occlusive crisis among people with sickle cell disease in the emergency department recommend assigning an emergency severity index of 2 at triage. However, patients with sickle cell disease often do not receive guideline-concordant care at triage. To address this gap, a decision support tool was developed, in the form of a text banner on the triage page in the electronic health record system, visible to triage nurses.

METHODS

A prospective quality improvement initiative was designed where the emergency severity index clinical decision support tool was deployed to a stratified random sample of emergency department triage nurses to receive the banner (n = 24) or not to receive the banner (n = 27), reminding them to assign the patient to emergency severity index category 2. The acceptability of the emergency severity index clinical decision support tool was evaluated with the Ottawa Acceptability of Decision Rules Instrument. Descriptive and bivariate (chi-square test) statistics were used to characterize the study's primary outcome, proportion of visits assigned an emergency severity index of 2 or higher. A generalized linear mixed model with clustering at the level of the triage nurse was performed to test the association between the banner intervention and triage practices.

RESULTS

A total of 384 ED visits were included for analysis. Before study initiation, the percentage of sickle cell disease patients' visits with the proper emergency severity index assignment at triage was 37.04%. After initiation, the proportion of sickle cell disease patients' visits with an emergency severity index of 2 or higher triaged by nurses in the intervention group was markedly higher in the intervention group than in the control group (64.95% vs 35.05%; χ² = 8.79, P ≤ .003). Accounting for clustering by nurse, the odds ratio for proper triage emergency severity index assignment was 3.22 (95% confidence interval 1.17-8.85; P ≤ .02) for the intervention versus control. Surveyed triage nurses reported the emergency severity index clinical decision support tool to be moderately acceptable (nurses' mean Ottawa Acceptability of Decision Rules Instrument scores ranged from 4.13 to 4.90 on the 6-point scale; n = 11). There were no differences in ED experience outcomes including time to first analgesic or length of stay between the control and intervention groups.

CONCLUSION

Substantial improvements in triage guideline concordance were achieved and sustained without direct nursing education.

Design and evaluation of a knowledge-based clinical decision support system for the psychiatric nursing process

BACKGROUND AND OBJECTIVES

The nursing assessment in the psychiatric department differ from those used in other departments considerably. We developed a psychiatric knowledge-based clinical decision support system (Psy-KBCDSS), which may aid nurses in solving patients' problems in the psychiatric department. In addition, we compared the sensitivity and specificity for the nursing diagnoses between the psychiatric nursing process system (Psy-NPS) and Psy-KBCDSS to determine that the Psy-KBCDSS can assist nurses in performing the nursing assessment and diagnosis.

METHODS

Visual Studio 2019 was adopted as the primary software development tool, and C# as the main development language. The concept of the nursing process was applied to develop the Psy-KBCDSS user interface. We developed a clinical diagnostic validity inference engine to calculate the frequencies of the nursing assessment items and nursing diagnoses in clinical tasks in the Psy-NPS for generating a knowledge-based database of the Psy-KBCDSS. The sensitivity and specificity for nursing diagnoses formulated by senior and junior nurses were used to determining the effectiveness of adopting Psy-NPS and Psy-KBCDSS.

RESULTS

This study include 22 nursing diagnoses commonly encountered in psychiatric wards. The top eight most common diagnoses in the Psy-NPS and Psy-KBCDSS were altered thought processes, ineffective coping, sensory and perceptual alterations, insomnia, risk for other-directed violence, anxiety, impaired social interaction, and risk for suicide. Compared with the Psy-NPS, the Psy-KBCDSS had significantly higher sensitivity for sensory and perceptual alterations, ineffective coping, and insomnia and significantly higher specificity for ineffective coping.

CONCLUSIONS

Considering its high sensitivity and specificity for various nursing diagnoses, the Psy-KBCDSS, as an empirical patient-oriented nursing clinical decision-making support system, can assist nurses in clinical nursing tasks including nursing process-based patient assessment and nursing diagnosis.