However, organizations can step ahead of the oncoming disruption by following the common-sense steps noted in the article, “How to Avoid Insuretech Disruption”. The first important component of this effort is accurate data. Data should be viewed as a significant organizational asset that is respected, valued, and protected at its collection points and throughout its useful life.
Inaccurate and incomplete data from providers ranges from deliberate fraud to simple negligence. Data integrity is the basis for accurate provider performance evaluation and selection, essential to quality care and accurate claims adjudication. Source networks should require accuracy from their provider members or correct the data at their point of data progression. Payers, the purchasers of networks and bill review services, can use their leverage to encourage data correction at these points, as well.
Keep in mind manually entered data, is the least reliable method of data collection. Misspelled and abbreviated names and addresses create duplicate entities in the data, thereby skewing downstream analysis. Because the data entry source is not arms-length for payers, they will need to correct the data themselves.
Claim data entry is an internal manual data entry process for payers. Years ago, typists were tested and scored for how fast they could type a paragraph without errors. Accurate typing performance determined hiring or dismissal. Today’s data entry personnel should be similarly evaluated for accuracy, regardless of their level in the organization. Make accuracy a performance measurement for everyone.
Manually correcting the data is a challenging prospect, but the benefits to downstream analysis are enormous. Programmatic systems are available to merge duplicate records, for instance, and they are accurate to a point. Also, systems can be created to highlight data needing manual attention to facilitate data corrections.
Inform and train employees regarding the corporate value of data integrity. Design systems that highlight errors and omissions for work in progress. They can also be used as accountability tools. A simple audit trail will identify the error perpetrators going forward. Moreover, objective feedback is the best way to improvement.
For the last thirty years, the big push in the insurance industry has been collecting data while little emphasis was placed on accuracy. Now the focus has shifted. Predictive analytics relies on historic data to inform so be sure the data is as robust as possible.