When it comes to IT, health plans face a quality problem. In fact, it’s less that they face one problem and more that virtually their entire business model generates challenges for the strategy, governance and operation of high-quality IT infrastructures. Getting it right requires expertise and effort that few other industries demand.
These problems grow both out of the nature of the healthcare industry as a whole and the specific challenges health insurers face. In addition to fundamental industry-wide challenges such as privacy, security and interoperability, health plans also face unique challenges of data quality, external limitations on resources and unique business process needs.
All the stakeholders in the broader healthcare industry recognize and must deal with the complexity of the multi-provider, multi-payer, multi-regulator model on which most of the industry operates. When it comes to designing and implementing IT solutions, these challenges come to the forefront and can appear in issues of interoperability, security and privacy, data quality, timeliness and more.
To address these challenges, the healthcare industry has invested in data governance, master data management (MDM) processes, EDI systems, data warehouses and other tools that attempt to forge connections, reduce redundancies, solidify dependencies and minimize operational gaps.
Health insurers certainly take on these initiatives as well. But when it comes to their core business processes, the demands for quality IT solutions go even deeper. With margins limited by the “80/20 Rule” and other regulations, capabilities such as coordination of benefits (COB) and fraud, waste and abuse (FWA) become critical components of health plans’ ability to meet their bottom lines.
That’s why health plans have been among the most ardent adopters of Data Harmonization, a broad and function-focused approach that takes data from multiple internal and external sources and systems and aligns it strategically with the health plan’s organizational functions. This goes beyond traditional data integration and is of special value given the myriad sources of data that insurers deal with on a minute-by-minute basis.
Health plans are also turning to data analytics, AI and machine learning to identify situations where problems either in their own processes or in information received from others – providers, vendors or even customers – create opportunity for cost reduction or recoveries through COB or broader FWA initiatives.
The good news is that the size and variety of challenges health plans face mean that coming up with comprehensive and strategic solutions for them can make a meaningful difference in a health insurer’s bottom line.
If you’re interested in learning what that might look like for your organization, contact us to find out more.