How analytics can help navigate the great data divide

December 9, 2014

Now that the ACA has eliminated pre-existing conditions, payers have taken on many unknowns when evaluating the massive population of new members coming in from the state and federal exchanges.

When open enrollment closed for 2013, it was the first time both newly insured and previously-insured individuals seeking alternate health plan options were able to participate in the state or federal marketplaces since health insurance became mandatory for United States citizens. Health insurers have watched with great anticipation as more than 8 million people joined the marketplaces, taking advantage of accessible, affordable healthcare.

However, with healthcare reform, health plans are no longer permitted to ask newly insured patients about pre-existing conditions. As a result, much remains unknown about this patient population aside from basic demographic information, and health plans must wait for claims to be submitted before obtaining any indication of the health of their new members.

Without the patient data that health plans have traditionally relied on, they are finding themselves questioning how to effectively handle this new marketplace population, as well as what they need to manage patient demand while controlling premiums costs for patients.

The great unknown: how payers can overcome

Relative to underwriting methodologies used in the past, payers have taken on many unknowns in the past year when evaluating the massive population of new members coming in from the state and federal exchanges. This is the reality for many payers, and as such they need to prepare themselves for potential scenarios that may arise.

Without awareness of pre-existing conditions, it’s not possible to assess overall population health for a minimum of 3-6 months (or sometimes upwards of one year) as claims are adjudicated for every new patient. This lapse in knowledge can affect payers as well as patients. For example, take a new patient that had cancer who finished their treatment just before enrolling in a new health plan. The insurance company may not have record of this patient having cancer until they go for their annual checkup and the oncologist submits a claim for the office visit.

Compounding this challenge is a lack of trust between providers and health plans. Cooperation between all parties to patient care in this new era of health reform is necessary for productivity, and is also needed for pay-for-performance programs to be successful.

As the healthcare landscape continues to shift and new ways of controlling cost are presented, health plans, health systems and individual providers are being asked to change the way they provide care to align with the incentives of those new programs:

  • Providers are shifting to proactive, population-based care models with self-reported quality measures;

  • Health plans are paying providers based on the measured risk of their population and/or the quality of care they are rendering.

However, providers rightly don’t feel claims data can accurately reflect all the care they are delivering and health plans don’t trust easily manipulated, self-reported quality measures as they are burdensome to gather and prone to fraud. So, while the ultimate goal is to improve care while reducing costs, payers need to proactively equip themselves and their providers with an integration and analytics platform to help them streamline the exchange of claims and clinical data between medical facilities in a more accurate and timely fashion and to share the risk and reward with the provider.

NEXT: Real-time visibility into EHRs eliminated the "Wait and See" approach

 

Real-time visibility into EHRs eliminates the ‘wait and see’ approach

Sharing patient information through electronic health records (EHRs) has been a contested topic in healthcare since reform began. It’s a common assumption that health plans will likely raise rates if they're able to access sensitive information held inside providers’ patient records. However, the strong combination of clinical data in EHRs and claims information from health plans actually provide a longitudinal view of patient populations that can advance quality improvement initiatives and, in the long run, reduce rates for all.

A real-time view of patient information is a way for payers and providers to come together and achieve their shared goal. Having an integration and analytics solution in place will allow insurance companies to stay ahead of the curve in actuarial forecasting of premiums. It is critical that this integration pull information from the actual back end of the EHR, not just using a feed or Continuity of Care document as they rarely provide consistent enough data across platforms to be useful to a health plan.

Patient data can be analyzed in a meaningful way, tying together membership and utilization data from claims with the clinical and outcomes data found in EHRs. This comprehensive view will improve payers’ abilities in disease management and projections of medical expenditures, as well as strengthening collaboration with providers by incorporating programs with data that those providers trust.

As an example, if a patient was to enroll in a health plan through the federal marketplace and have their records shared in real time via an EHR, a problem list could reveal a cancer diagnosis that would allow health plans to manage needs in relation to costs, instead of finding out later that the patient could potentially need a greater level of care.

As payers look to work smarter rather than harder during this new era of healthcare, they should consider implementing integration and analytics technologies that can provide them with the ability to stop guessing and start acting on the overarching goals of reform. This will prove invaluable in examining the different exchange marketplace populations that will continue to rise and remain volatile for the next several years.

Greg Chittim is senior director for Arcadia Healthcare Solutions.