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Health Management

Diagnosis "Incorrect billing"

Incorrect invoices, abuse and fraud in the healthcare sector impose a substantial burden on both insurers and insured. But checking invoices manually involves high costs. Munich Re's health business has developed a service that automatically and instantly identifies invoices that are incorrect.

05.06.2012

A large proportion of the worldwide costs incurred in the healthcare sector are simply not justified. They are the result of invoicing errors, deliberate or unintentional overpayments, fraud or abuse. As a component of health expenditure, which according to OECD Health Statistics 2011 accounts for 10% of global GDP on average, this is costing the insurance industry and its customers or insureds an enormous amount of money.

Checking invoices manually is a costly business

Millions of invoices would need to be checked manually in order to weed out all the unjustified claims. This requires time and expertise and costs a lot of money. In addition, manual checking doesn’t always discover all the errors in invoices, and decisions can be erratic. Expert systems now make it possible to automatically check the medical accuracy of invoices: for example the MH Rule Engine, a service provided by Munich Re's health business.

Automatic invoice checking in real time

The MH Rule Engine is integrated into the workflow of the claims management system, and automatically recognises inconsistencies in an invoice. Details in the invoice such as age and gender of the patient, diagnosis, treatment, and prescribed medication are compared against the information on file, thus verifying the logical consistency of all the relevant medical information. The MH Rule Engine can thus determine whether the invoice is reasonable and appropriate from a medical viewpoint, and whether the invoice is correct.

Incorrect invoices, abuse and fraud in the healthcare sector impose a substantial burden on both insurers and insured. But checking invoices manually involves high costs. Munich Health has developed a service that automatically and instantly identifies invoices that are incorrect. © Munich Re
Medical treatments that are unnecessary are identified by the MH Rule Engine and either displayed in graphical form to the claims handler for manual processing or, in the case of fully automated processing, reported directly to the administration system.

Among other things, the MH Rule Engine recognises contradictions between the diagnosis made and the medical services provided, or the medication prescribed. For example, if magnetic resonance imaging instead of computer tomography is billed for the diagnosis of a kidney stone, the MH Rule Engine rejects the invoice that has been submitted. In addition, data from claims that have already been settled are used to cross-check the medical circumstances. For example, if a tooth extraction was performed on a patient at an earlier date, any benefit application to insert a filling in the same tooth results in the application being automatically rejected by the system.

Configurable expert system

The MH Rule Engine is a configurable expert system that can be integrated into the insurer's IT landscape and work flow. When implemented, the system is modified to meet specific market features and individual customer requirements. The knowledge base comes from the pool of Munich Re's health business global network of physicians and is further supplemented with current guidelines. Among other things, the system can access the details of international treatment guidelines.

Higher clear-up rate within a shorter period

Based on our experience up to now, with over 50,000 automatic invoice verifications per day, incorrect invoices can be identified within a much shorter period. This results in faster and more straightforward claims assessment and processing, reduced costs through being able to identify more incorrect invoices, and much lower operating costs: both the insurance industry and its customers can only benefit from the decision to implement an automated claims processing system.

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