Shu Yin Hoi1, Norafida Ismail, Li Chern Ong, Jasmine Kang. 1. Department of Nursing Services, Tan Tock Seng Hospital Pte Ltd., 11 Jalan Tan Tock Seng, Singapore City, Singapore. Shu_Yin_Hoi@ttsh.com.sg
Abstract
OBJECTIVE: To develop a prototype nursing workload intensity measurement system (WIMS). BACKGROUND: Current nurse staffing was determined based on a development. The predetermined nurse-to-patient ratio of a measurement system in the present work environment was deemed essential. METHODS: The study was conducted in a 1500-bed acute care hospital in Singapore. A questionnaire was designed to identify critical indicators for workload measurement. Nineteen wards were observed over a period of 1 week on day shifts. The WIMS was developed using regression modelling. RESULTS: Nursing time required for a low-acuity ward increased from 90.5 to 177.1 hours per day. The WIMS was developed using nursing diagnoses as critical indicators of workload. The model (WIMS) yield R(2) values ranging from 0.615 to 0.736 across the six key disciplines, rendering it a model with relatively good predictive ability of nursing time required. CONCLUSION: In such a rapidly changing work environment, workload measurement systems should be reviewed periodically. The WIMS was developed as a potential methodology for measuring staffing needs. IMPLICATION FOR NURSING MANAGEMENT: Workload predictions should de-link patient dependency with acuity status as both do not correlate, as evidenced by this study.
OBJECTIVE: To develop a prototype nursing workload intensity measurement system (WIMS). BACKGROUND: Current nurse staffing was determined based on a development. The predetermined nurse-to-patient ratio of a measurement system in the present work environment was deemed essential. METHODS: The study was conducted in a 1500-bed acute care hospital in Singapore. A questionnaire was designed to identify critical indicators for workload measurement. Nineteen wards were observed over a period of 1 week on day shifts. The WIMS was developed using regression modelling. RESULTS: Nursing time required for a low-acuity ward increased from 90.5 to 177.1 hours per day. The WIMS was developed using nursing diagnoses as critical indicators of workload. The model (WIMS) yield R(2) values ranging from 0.615 to 0.736 across the six key disciplines, rendering it a model with relatively good predictive ability of nursing time required. CONCLUSION: In such a rapidly changing work environment, workload measurement systems should be reviewed periodically. The WIMS was developed as a potential methodology for measuring staffing needs. IMPLICATION FOR NURSING MANAGEMENT: Workload predictions should de-link patient dependency with acuity status as both do not correlate, as evidenced by this study.
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