Research Reports from the Department of Operations
Document Type
Report
Publication Date
10-1-1973
Abstract
As a result of the study of the length of service of 360 resigned and 360 currently employed registered nurses in a single general hospital in Cleveland, a Markov chain model is developed which predicts on the average the proportion of employees who leave and the proportion of employees who stay over any number of monthly time periods. While the Markov chain is a discrete time Markov process, the model has a time dependent feature. The transition probability matrix can be updated and accuracy will improve. This approach can be easily operationalized given the historical data regarding the total number of employees and the number of resignations for each month past. Current results are based on 4 years of historical data. Preliminary tests indicate that the model predicts numbers of resignations which are a good fit to the actual numbers who leave. The predictions are proposed as an aid to planning in registered nurse labor turnover.
Keywords
Operations research, Nurses--Employment--United States, Manpower planning, Labor turnover--Mathematical models, Markov processes, Personnel management--United States, Hospitals--Ohio--Cleveland, Nurses--Supply and demand--United States, Forecasting--Mathematical models
Publication Title
Technical Memorandums from the Department of Operations, School of Management, Case Western Reserve University
Issue
Technical memorandum no. 308
Rights
This work is in the public domain and may be freely downloaded for personal or academic use
Recommended Citation
Kiley, Marylou and Subba Rao, S., "Predicting Registered Nurse Labor Turnover" (1973). Research Reports from the Department of Operations. 421.
https://commons.case.edu/wsom-ops-reports/421