Quality data is so important for claims processing. Clean, quality data ensures claims are processed in an efficient manner, resulting in reduced stress for employees, and increased customer satisfaction.
1. Less Claim Refusals
Ensuring all necessary data had been collected within deadlines ensures that each claim gets a fair assessment from an administrator. Approving claims first time ensures they are processed within a shorter time frame, improving customer satisfaction.
Only claims that are rejected for genuine reasons will take up administrator’s time and efforts, reducing the resources necessary to process claims efficiently.
2. Improved fraud Detection
With an increase in the use of analytical capabilities by insurers, improved data will provide more accurate predictions and results. The more inaccurate the inputted information, the less accurate the results, hence good quality data will provide good insights for administrators to use when processing and reviewing claims.
Historical data can be used to determine factors that may indicate fraudulent claims. When a factor is triggered, the claim will be flagged as high risk, indicating it is in need of further investigation by an administrator. The better the data, the better able an automated system can predict fraudulent claims.
3. Efficient Reporting Capabilities
Reports that contain quality data provide valuable outputs for insurance administrators. As claim information is updated, real-time reports are continually up to date providing valuable insights and business overviews.
To ensure you have a database containing quality information remember to:
- Use technology to your advantage. Use electronic files, payments and medical records compiled in a centralized database to improve efficiency
- Make sure all data fields are in the correct format and are correct, particularly medical codes
- Avoid duplicate claims
- Use deadlines to ensure all data is collected, and claims are processed in a timely manner
With the influx of analytical and reporting capabilities being discussed in the insurance industry lately, it is becoming increasingly important to ensure data is clean and accurate to ensure outputs provide accurate accounts of the business.