Hospital Bed : Case of perishable inventory
Hospital Bed inventory is perishable in nature. Therefore the more efficiently a bed is vacated, the faster is the bed turnaround. Further the duration from the preparation of bill to actual vacation of the bed by patient to fumigation of the bed till finally occupation by the next patient is a non-revenue generating phase for a bed. Hence a key endeavor to increase profitability per bed is to reduce this non-revenue generating phase. The proposed analytics platform using myCOL proprietary data dissects this phase into milestones, calculates the opportunity cost per milestone and provide the key insights to reduce the opportunity cost. Incidentally this cost varies at a departmental level, patient mode of payment (insurance/cash/CGHS/Corporate), TPA level (for an insurance patient) etc. By providing this level of information the hospital can accurately map out its costs, benchmark department/doctor performance, calculate differential cost of serving patient viz their mode of
payment and insurer/TPA and incentivize them accordingly.
The platform will perform analytics on the occupancy of the hospital using combination of Hospital MIS and myCOL data to tease out information about say OT utilization to identify patterns in the utilization after controlling for noise introduced through patient level as well as external
environmental idiosyncrasies. By creating patterns out of the utilization the platform will enable the hospitals to extract and identify any departmental/ doctor level behavior that introduces variability into the OT utilization and the qualitative impact on the outcome due the variability. Equipped with the analytical tool to benchmark, identify and measure deviations from the ideal pattern, the hospital will be for the first time able to better utilize its capacity and dynamically allocate resources across departments.
For illustration:- below is the representative sample of a hospital
Such variability after controlling for patient and external idiosyncrasies leads to approximate under-
utilization to the extent of 30 procedures in a week. Based on this controlled pattern in the
department and across departments the hospital is able to better plan its OT capacity and thereby