Patient dependency in the Oncology Emergency Room. Reliability and validity of the Jones Dependency Tool.

BACKGROUND: Patients' dependency has significant nursing implications. Nurse skill mix and staffing levels may be addressed more successfully when dependency can be measured. In the oncology emergency room, a valid and reliable tool that measures patients' dependency on nursing care is necessary. AIM: This study aimed to evaluate the psychometric properties of the Jones Dependency Tool in Adult Oncology Emergency Setting at a Cancer Center in Jordan. METHODS: A prospective cross-sectional design was used to test the Reliability and Validity of the Jones Dependency Tool among patients with cancer visiting the ED. A sample of 79 patients were assessed using the JDT and Conner's tool. RESULTS: Jones Dependency Tool showed a high level of validity and reliability. In terms of reliability, which was tested by test-re-test, Intra-class correlation (ICC) = 0.902 which indicates good to excellent. The tool demonstrates a high validity evidenced by its correlation with a criterion (p < 0.001). CONCLUSION: The study demonstrated that the JDT tool is a valid and reliable tool that can be used to quantify a patient's dependency level and the level of nursing care they need, assisting in the selection of the ideal staffing level in terms of quantity and skill mix.

Analyzing the queuing theory at the emergency department at King Hussein cancer center.

OBJECTIVES: This study was conducted in 2022 at King Hussein Cancer Center (KHCC) to analyze the queuing theory approach at the Emergency Department (ED) to estimate patients' wait times and predict the accuracy of the queuing theory approach. METHODS: According to the statistics, the peak months were July and August, with peak hours from 10 a.m. until 6 p.m. The study sample was a week in July 2022, during the peak days and hours. This study measured patients' wait times at these three stations: the health informatics desk, triage room, and emergency bed area. RESULTS: The average number of patients in line at the health informatics desk was not more than 3, and the waiting time was between 1 and 4 min. Since patients were receiving the service immediately in the triage room, there was no waiting time or line because the nurse's role ended after taking the vital signs and rating the patient's disease acuity. Using equations of queuing theory and other relativistic equations in the emergency bed area gave different results. The queuing theory approach showed that the average residence time in the system was between 4 and 10 min. CONCLUSIONS: Conversely, relativistic equations (ratios of served patients and departed patients and other related variables) demonstrated that the average residence time was between 21 and 36 min.