The GAP-DRG Model: Simulation of Outpatient Care for Comparison of Different Reimbursement Schemes


In healthcare the reimbursement of medical providers is an important topic and can influence the overall outcome. We present the agent-based healthcare model, which allows a comparison of reimbursement schemes in outpatient care. It models patients and medical providers as agents. In the simulation of healthcare system, patients develop medical problems (i.e., diseases) and a need for medical services. This leads to utilization of medical providers. The reimbursement system receives information on the patients’ visits via its generic interface, which facilitates an easy replacement. We describe the assumptions of the model in detail and show how it makes extensive use of available Austrian routine care data for its parameterization. The model design is optimized for utilizing as much of these data as possible. However, many assumptions have to be simplifications. Further work and detailed comparisons with healthcare data will provide insight on which assumptions are valid descriptions of the real process.

Heathcare routine big data and simulation

We present an agent-based simulation model of healthcare system of Austria that aims at the comparison of different reimbursement schemes. It utilizes pseudonymous routine data from practically all insured persons of the Austrian public health insurances. “Pseudonymous” means that, in order to guarantee protection of privacy, the data are linked to individual patients by an artificially generated patient identification number (the pseudonym) and not by the original social security number. The data include the time span of two years (2006 and 2007) and contain medical services in the outpatient sector, drug data, sick-leaves and hospital stays. The model construction was part of the “General Approach for Patient-oriented Ambulant Diagnosis Related Groups” (GAP-DRG) project.

The general idea of the model is that reimbursement is the result of patients consuming medical services from medical providers because of their medical problems (i.e., diseases). It roughly follows the proposed structure of Krol and Reich (1999), which is object-oriented and also contains the classes medical provider and patient. Figure 1 shows the general idea of the model diagrammatically and emphasizes that different reimbursement systems could be the basis for reimbursement. The general idea translates to two types of agents, the patients and the medical providers. The behavior in the model splits into five modules:

  1. epidemiology
  2. service need
  3. provider utilization
  4. service provision
  5. reimbursement

Healthcare routine big data and simulation