UBC Theses and Dissertations
Predicting short term disability benefit days for the Workers’ Compensation Board of British Columbia Fukui Innes, Junko
The objective of this study was to predict Short Term Disability (STD) benefits paid by the Workers' Compensation Board of British Columbia. An STD benefit is defined as the total number of wage days that a worker is unable to work because of an injury incurred at the workplace. Factors which may explain variability in STD days paid at the claim level were studied with regression analysis and ranked according to the level of importance. This analysis indicated that injury related factors have more of an effect on STD days than other factors such as age and occupation. Regression analysis was used to study total STD days paid within the truncation periods and to predict the total STD days in the coming 6, 12, and 18 months at the area office and WCB levels. The model developed to total STD days paid within the truncation periods showed the relative difference of STD days within each factor. For example, this model showed that the older the claimant is, the more STD days they are likely to receive. The model to predict the total STD days in the coming 6, 12, and 18 months at the area office and WCB level yielded accurate results as measured by a comparison of the estimated STD days and the actual STD days paid in the past. Survival analysis was used to estimate additional and total STD days given that a claim has already received more than a certain number of STD days. The model showed that the more STD days a claimant has received so far, the more additional and total STD days the claimant will receive. Knowing the influential factors on STD days will help WCB seek possible methods to reduce STD days. The predictive models for the coming 6, 12, and 18 months will help the process of budgeting. Finally, based on the predictive model of the additional and total STD days, WCB can anticipate how many STD days will be paid on a particular type of claim given that a claim has already received more than a certain number of days of payment.
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