دانلود رایگان مقاله انگلیسی سیستم پشتیبانی تصمیم گیری برای مدیریت تریاژ: استدلال مبتنی بر قاعده و منطق فازی - الزویر 2018

ABSTRACT

Objectives: Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. Methods: A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist’s opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Results: Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Conclusions: Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes.

5. Conclusions

Nurses often encounter problems in triage-level decision making on diagnosis. The use of a CDSS is a well-recognized solution to increasing the quality and efficiency of care. The correspondence between CDSS design and guidelines and clinicians’ opinions is of utmost importance because this reduces over-triage and under-triage cases and improves safety. Conducting interviews with users and clinicians early in the development process informs the identification of design requirements and provides a context for how a CDSS will be most useful to providers. Insight into end-users’ cognitive processes can facilitate the design of CDSS systems with promising usability. Analyzing CDSSs before deploying these systems for real-world application potentially saves money, time, and effort during implementation. Tool developers are responsible for ensuring the safety, usability, and usefulness of such systems.

The essence of this study lies in its combination of FLC and RBR, which can improve the triage outcomes and will be useful in medical areas. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner. We expect the use of this method to minimize the design iterations of the developed CDSS, which combines two or more methodologies. The measurements obtained in this work are consistent with those reported in other related studies. The developed system proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines, and improved the quality measures for accuracy and documentation in the triage process. We designed and evaluated the CDSS on the basis of ESI triage guidelines and found that the designed system effectively determines the triage level required for patients. The methods put forward in this work can be applied to other clinical decision support systems and settings, and we hope that further exploration of the system will provide improved results.