As the costs of claim expenses and indemnity pay outs increase, many companies are becoming more sophisticated in their data analysis.

Here are nine tips for capturing and using data for predictive analysis:

  • Claims systems capture large amounts of data. They include the names of providers, dollars spent, indemnity costs, types of injuries, body parts, comorbidities, lost time, geographic location, prescription drug use, costs associated with outside counsel, independent adjusters, case managers and various vendors.
  • Age, comorbidities and medications can be analyzed for predictive modeling. Example: Age, obesity and diabetes all, either singularly or collectively, increase medical care costs and the time off work required for recovery and rehab. By using this information in various ways, insurance companies and payer sources can create in-depth risk analytics and claim trends.
  • Through data collection, patterns in payments, providers, employers, injuries and more can be found. This can lead to more successful risk models and predictive analysis.
  • Information can be analyzed to help identify emerging trends that can impact the carrier at various points along the claims continuum. This information also can be used to create other risk or claims products to assist the payer source or employer; address safety or return to work issues; or implement different claims or underwriting practices.  
  • Analysis of providers and hospital data can identify treatment trends, patient outcomes, length of treatment and care, dollar expenditure and other issues.  This information can be obtained through claims paying or bill audit software.
  • Outside sources, including review companies and nurses, also can obtain helpful data for analysis.
  • Trends in hospital charges and the use of services by patients or claimants can be captured and analyzed. Comparison of hospital information in a geographic location can be invaluable to a payer source.
  • Much of this data is used to analyze risk and claims trends, which, in turn, gives a more accurate risk profile. By providing hard data, underwriting should be improved. This information is then shared with the insured, which can help explain or justify underwriting decisions.
  • Possible trends that can be captured to help identify various types of fraud.

Need Help?

At MKC Medical Management, we help claims adjusters and attorneys understand complex medical records and information.