Gathering and confirming insurance information is a much more strenuous process than expected. Mistakes in the information collection process can contribute to billions of dollars’ worth of rejected claims every year because of mistakes. The techniques that are frequently used today, such as manual input with a pen and paper, digital input, and optical character recognition (OCR) input, can lead to mistakes.
In order to reduce the error rate in the information collection process, there needs to be a complete revamp of insurance benefit verification automation methods. The most advanced option is developing an AI-enabled system, but companies have to decide whether to build or buy their solution. Building internally gives you complete customization, but it also has significant initial costs (between $1 and $5 million) and requires a high level of technical expertise from engineers. The length of the development period can be extremely long as well, which could postpone the realization of benefits.
As an alternative, there is the option to buy an already designed solution from a third-party, which can cut down on the number of days or weeks needed for implementation. There is also no need to have all the technical expertise in-house; the software engineers from the other company perform installation, maintenance, and repairs.
Source: Orbit Healthcare