Forecasting demand for long-term care services.
This article analyzes three methods used to forecast the transition of long-term care clients through a variety of possible home and facility placements and levels of care. The test population (N = 1,653) is derived from the larger population of clients admitted in 1978 to British Columbia's newly established Long-Term Care program. The investigators have accumulated 5 years of service-generated data on moves, discharges, and deaths of these clients. Results show that the first-order Markov chain with stationary transition probabilities yields a superior forecast to state-by-state moving average growth and state-by-state regression analyses. The results of these analyses indicate that the Markov method should receive serious consideration as a tool for resource planning and allocation in long-term care.
D000368:Aged; D001955:British Columbia; D003365:Costs and Cost Analysis; D005260:Female; D005544:Forecasting; D006301:Health Services Needs and Demand; D006302:Health Services Research; D006699:Home Care Services; D006801:Humans; D007380:Intermediate Care Facilities; D008134:Long-Term Care / Q000639:trends*; D008297:Male; D012866:Skilled Nursing Facilities; D013223:Statistics as Topic