Biomedical subjects
Publications and source records attributed to D Uyeno.
Faced with demands on maternity services exceeding design capacity, one British Columbia hospital commissioned forecasting studies to determine trends in demand and if accurate forecasts could be obtained. In addition to describing the forecasting method employed, the data used and the results, the authors look at what literature is available on obstetrics forecasting.
The only significant advances in blood-taking in 25 years have been the disposable needle and evacuated blood-drawing tube. With the exception of a few isolated barcode experiments, most sample-tracking is performed through handwritten or computer-printed labels. Attempts to reduce the hazards of centrifugation have resulted in air-tight lids or chambers, the use of which is time-consuming and cumbersome. Most commonly used clinical analyzers require serum or plasma, distributed into specialized containers, unique to that analyzer. Aliquots for different tests are prepared by handpouring or pipetting. Moderate to large clinical laboratories perform so many different tests that even multi-analyzers performing multiple analyses on a single sample may account for only a portion of all tests ordered for a patient. Thus several aliquots of each specimen are usually required. We have developed a proprietary serial centrifuge and blood-collection tube suitable for incorporation into an automated or robotic sample-handling system. The system we propose is (a) safe--avoids or prevents biological danger to the many "handlers" of blood; (b) small--minimizes the amount of sample taken and space required to adapt to the needs of satellite and mobile testing, and direct interfacing with analyzers; (c) serial--permits each sample to be treated according to its own "merits," optimizes throughput, and facilitates flexible automation; and (d) smart--ensures quality results through monitoring and intelligent control of patient identification, sample characteristics, and separation process.
This article presents a model for the annual transitions of clients through various home and facility placements in a long-term care program. The model, an application of Markov chain analysis, is developed, tested, and applied to over 9,000 clients (N = 9,483) in British Columbia's Long Term Care Program (LTC) over the period 1978-1983. Results show that the model gives accurate forecasts of the progress of groups of clients from state to state in the long-term care system from time of admission until eventual death. Statistical methods are used to test the modeling hypothesis that clients' year-over-year transitions occur in constant proportions from state to state within the long-term care system. Tests are carried out by examining actual year-over-year transitions of each year's new admission cohort (1978-1983). Various subsets of the available data are analyzed and, after accounting for clear differences among annual cohorts, the most acceptable model of the actual client transition data occurred when clients were separated into male and female groups, i.e., the transition behavior of each group is describable by a different Markov model. To validate the model, we develop model estimates for the numbers of existing clients in each state of the long-term care system for the period (1981-1983) for which actual data are available. When these estimates are compared with the actual data, total weighted absolute deviations do not exceed 10 percent of actuals. Finally, we use the properties of the Markov chain probability transition matrix and simulation methods to develop three-year forecasts with prediction intervals for the distribution of the existing total clients into each state of the system. The tests, forecasts, and Markov model supplemental information are contained in a mechanized procedure suitable for a microcomputer. The procedure provides a powerful, efficient tool for decision makers planning facilities and services in response to the needs of long-term care clients.
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.
This paper makes an assessment of the impact of toxic chemical regulation in Canada. Ranges of costs and benefits, supplemented by survey information, analogous American data, interviews and case studies have been used to demonstrate the general usefulness of a cost-benefit framework for public sector decision-making even where information availability is constrained and complete analysis is not feasible. It is concluded that, with few exceptions, the impact of environmental regulation on chemical producers in Canada is neither excessive nor unduly onerous.
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Explore the source record for details and available documents.