Healthcare Finance in Singapore reports Bill Sizes to the Ministry of Health, who then publishes average bill sizes for DRGs across public hospitals in Singapore for patients to make more informed choices.
The need to drive costs down for hospital operations often arises from the administrative side of healthcare, rather than the medical side. Therefore the finance department’s role in reducing bill sizes is to understand anomalies and higher than average costs within DRGs to then understand why a higher cost may occur. The strength of the CUBOT’s data discovery features was really used in this scenario, where analysts were exploring bill size statistics within many categories, down to a reasonable level of depth.

Doctors fees were calculated based on the number of private and subsidised patients that the doctors consulted. Using the defined logic to calculate their fees, the process can be automated to save more time performing this routine activity.
Furthermore, the idea is that doctors should be rewarded for taking on greater workloads, and so the calculation of the rewards required fair amount of logical inputs that were not friendly to calculate in regular MS Excel or Access.

Understanding customers is just as important for revenue analysis as customer segments and patient characteristics become apparent. Demographic information, housing information were particularly noteworthy for Singapore public hospitals from a finance perspective.