1. Modeling daily veterinary anesthetist patient care hours and probabilities of exceeding critical thresholds.
- Author
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Dexter, Franklin, Pinho, Renata H., and Pang, Daniel S. J.
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ANESTHESIOLOGISTS , *PATIENT care , *CONFIDENCE intervals , *PROBABILITY theory , *VETERINARY anesthesia , *COST estimates , *PEARSON correlation (Statistics) - Abstract
OBJECTIVE Use a referral dental clinic model to study how to calculate accurate 95% upper confidence limits for probabilities of workloads (total case duration, including turnover time) exceeding allocated times. ANIMALS Dogs and cats undergoing dental treatments. METHODS Managerial data (procedure date and duration) collected over 44 consecutive operative workdays were used to calculate the daily anesthetist workload. Workloads were compared with a normal distribution using the Shapiro-Wilk test, serial correlation was examined by runs test, and comparisons among weekdays were made using the KruskalWallis test. The 95% confidence limits for normally distributed workloads exceeding allocated times were estimated with a generalized pivotal quantity. The impact of a number of procedures was assessed with scatterplots, Pearson linear correlation coefficients, and multivariable linear regression. RESULTS Mean anesthetist’s workload was normally distributed (Shapiro-Wilk P = .25), without serial correlation (P = .45), and without significant differences among weekdays (P = .52). Daily workload, mean 9.39 hours and SD 3.06 hours, had 95% upper confidence limit of 4.47% for the probability that exceeding 16 hours (ie, 8 hours per each of 2 tables). There was a strong positive correlation between daily workload and the end of the workday (r = .85), significantly larger than the correlation between the end of the workday and the number of procedures (r = .64, P < .0001). CLINICAL RELEVANCE There are multiple managerial applications in veterinary anesthesia wherein the problem is to estimate risks of exceeding thresholds of workload, including the costs of hiring a locum, scheduling unplanned add-on cases, planning for late discharge of surgical patients to owners, and coordinating anesthetist breaks. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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