Fully automated TDABC

Ms Anne Graulund Dal


Model that shows a detailed overview of the operational costs for each patient flow and resource, to improve hospital organization, patient flow, resource efficiency and quality control.


Today’s costing model in danish healthcare is a top-down transactional model. It distributes expenses onto departments registered procedures code and provides an annual price for each procedure. However, this is a price statement only. The data from this model cannot be used to plan and optimize patient flows and resource utilization.

Other industries rely on ERP system to provide data for these objectives. But hospitals do not have ERP systems. This initiative produced ERP like data from current hospital IT systems. It developed an automatic TDABC model, that can be used to predict, plan, and optimize patient flows and resource utilization.

The initiative found that the hospitals booking system and HR database could be used to produce an event log. The columns of the log were: [patient id, activity, start time, end time, resource, diagnosis, cost]. All information except ‘Cost’, come from the booking system. The cost for an individual activity is determined by calculating each resource hourly cost rate (annual hours for each resource in the event log divided by the annual expenses of the resource) and multiplying it with the activity time.

The booking systems was not implemented for this type of purpose, and departments were told to use it as they see fit. All departments used the system differently and start/end times of activities did not mimic reality. Resource id’s in the booking system did not match the Id’s in the HR database. And there was no database related to non-human resources (location, purchase date and cost).

In conclusion the model could show the movement and cost of patients across the entire hospital, but the data was not reliable. Therefore, the initiative collaborated with the endocrinology department to develop registration practices and methodologies to produce the missing data.

The endocrinology department is an out-patient clinic for chronic patients over the age of 18. A patient flow was defined as all activity within a year – hence the cost of a patient flow is the annual cost. After one year with new registration practices and collection of necessary data, the initiative could display the cost of individual patients, activities, diagnosis, and resource utilization.

Supplementing the cost data, the initiative also produced a health outcome score for patients with type I and II diabetes. The score is produced by scoring a selection of indicators from 1-5. Placing them in relevant medical groups and adding a % of importance. Thereafter, the indicator scores are aggregated to medical group scores. These groups are given different % of importance and aggregated to a single health outcome score.

A single outcome score made it easier for the department to get an overview of their patient population and navigate their efforts. As an example, the department is now able to look up patients with low scores and track their cost data or vice versa.

The efforts of this initiative created a data infrastructure that can be scaled to all departments in the hospital and contribute to integrated planning, costing and quality management.