By Cindy Atoji

May 20, 2008 | Among the many flavors of Personal Health Records (PHR) trying to conquer the health care marketplace, few are backed up by clinical decision support. Or so says Frank Norman of ActiveHealth, a subsidiary of Aetna, which offers a Web-based “intelligent” PHR that can work with claims data as well as personal and clinical information, then use real-time technology to offer health and wellness feedback. The ActiveHealth PHR is part of Microsoft’s new consumer-centric health care platform, HealthVault, launched last year. Norman, who is executive vice president and CIO of New York-based ActiveHealth, says that the ActivePHR is available through payors and more recently, directly to consumers. He spoke with Digital HealthCare & Productivity about how clinical decision technology empowers the ActiveHealth PHR offering.

DHP: How do you define clinical decision support?

Norman: We define clinical decision support as identifying opportunities to improve care. Patient data is compiled from a variety of sources, either from claims or from members, and analyzed against up-to-date evidence-based standards. It is scanned and compared to a database of all of the new peer-reviewed medical literature, which is continuously monitored by a research team of physicians, nurses, and pharmacists; this is codified into updated rules and algorithms. Members and their clinicians can receive personalized email notifications that instruct them to log onto their PHR account and see such findings as potential adverse drug interactions, the absence of therapeutically beneficial drugs, and missing lab tests. They can also view reminders for preventative exams such as colonoscopies and mammograms. Each time a member visits physicians, fills prescriptions, or gets lab tests, that information is automatically added to their PHR, producing a longitudinal, evolving view of their health. We have measured and verified that this yields health care cost savings and outcomes improvements across our populations.

DHP: What are these cost savings and outcome improvements that people can expect to see?

Norman: A randomized study looked at the potential effect of a system that scans administrative claims information and clinical data to detect gaps in care and promote better health. The researchers looked at approximately 40,000 members of a Midwestern plan’s population and found that there was an 8.4 percent reduction in the number of hospital admissions, as well as that claims paid were $8 less per member.

DHP: How can clinical decision support help health plans and employers who already have Pharmacy Benefit Managers (PBM)s looking for drug-to-drug interactions or who already offer wellness and disease management programs?

Norman: The Active Health Clinical Decision Support Technology, which we call CareEngine, was built by doctors for doctors, and the physicians who built the CareEngine are keenly aware of the doctor’s interest in not being bombarded with non-specific clinical decision support orders. So as a result, the ActiveHealth rules are broader, deeper, and more specific than anything else we’ve seen out in the marketplace.

Related to health plans and employers who already have PBM programs with some level of clinical alerts, our view is that we know that those systems are not 100 percent effective in terms of what they point out, because we still see a high number of drug-to-drug interaction issues, and what that means is that many of those PBM alerts are either not being seen or being disregarded. Our rules look not only drug-to-drug interactions but drug condition and drug procedure interaction; it looks at the entire longitudinal health history of an individual across all of their caregivers.

DHP: What are some advances in the field of clinical decision support over the past year or two?

Norman: We have invested heavily in our clinical support platform to make it real-time and massively scalable. When Active Health was founded in 1998, we had an engine which was basically a batch-processing engine that read batch feeds of claimed-based health data submitted by health plans. We have completely re-architected that into a massively scaled grid-based architecture which works in real-time so that we can provide better service to health plans and large employers and we can also connect ourselves via Web services to RHIO-based platforms and Health Information Exchanges (HIE). Our PHR platform branches out into the provider-based clinical data streams. We’ve also developed one of the first platforms where our clinical decision support engine is connected with our personal health record platform, which is connected with our disease management wellness platform—all in real time.

DHP: What is different about working with RHIOS?

Norman: It’s a new clinical data stream, generally based either on the IHE (Integrating the Healthcare Enterprise) profile standards which are interpreted by HIMSS or the CCD standard which is being pushed by HITSP. It’s a new set of data types and it definitely needs to be dealt with in real time. What we’re also finding is that many of the RHIOS and HIEs are currently focused on gathering data and making that data available to the provider organizations in a region. There are very few people who are trying to apply clinical decision support in a HIE environment, and by actually looking at the data, analyzing it and finding opportunities to improve care, outcomes, and clinical performance measures, we are providing a value-added service back to the RHIO that they can actually use to develop a sustainable business model.

DHP: What role does clinical decision support play in HIE, RHIOs, etc.?

Norman: Starting this year we’re moving into the clinical data feed space, by building out clinical connections with RHIOs. We’re working with the CareSpark RHIO down in Tennessee and Virginia as our first RHIO connection. To certain extent, we also provide data validation and data quality services to the RHIO. We’re talking to some RHIOS in New York about our ability to provide them with consent architecture that can be applied in an HIE environment. And some of the consent technologies that we’ve built around our PHR can be used very broadly across the entire HIE environment.

DHP: Personal Health Records are taking off. What are some advances in this area?

Norman: Depending on your health plan relationships, we have the opportunity to auto-populate much of that Personal Health Record through available data supplies. We are also working to build support for PHR portability standards that are being developed. We think that will provide additional utility to consumers, to actually be able to maintain their PHR for life as they move among health plans and potentially now as they move among retail health sites as well.

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