Health insurance companies are obligated to review hospital bills for accuracy in order to protect the community of need from unjustified claims. The identification and selection of cases to be audited is becoming increasingly important, particularly due to the reform of the Health Insurance Medical Service (MDK) and the resulting limitation on the number of potential audits.
InGef supports health insurance companies in hospital billing audits through the use of machine learning. This involves examining extensive datasets with the help of statistical models and automatically evaluating the respective invoices in terms of their relevance for billing audits.
To support our clients according to their individual requirements, we have developed various models and scoring values. These can be used to evaluate billing cases regarding their suitability for audit, expected success and anticipated savings in the event of an audit by the medical service.
Our processes are tailored to the requirements of statutory health insurance companies. This enables us to integrate new clients from the SHI sector into our scoring pipeline quickly and effortlessly, and to provide the generated results in an automated and standardized manner upon request. The models used are subject to a continuous validation and optimization process. Furthermore, a special focus lies on the integration of our score values into our clients’ existing workflows. If desired, a direct integration into billing software can also be implemented.