The HIT of ACOs, Part I: Analytic Data (July/August 2011)

By Dr. John Loonsk
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From the July/August issue of Government Health IT.

The Accountable Care Organization (ACO) draft rule is out, and the political, clinical and technical trek is on to establish these lynchpins of the Affordable Care Act and health reform. Community physicians and hospitals are jockeying for potential shares of the incentives that will be distributed via the ACO program. Health information technology has been so frequently cited as being a critical part of making ACOs successful that it is now de rigueur.

But if ACO information technology is assumed, it's still not completely defined, and certainly not completely available or implemented. 

ACOs will need new analytic, clinical workflow, administrative and communication functions if they are to actually reduce costs and improve care. They'll have to aggressively pursue prevention, decision support, error reduction, revenue cycle optimization and disease management to be successful. But not all of these functions or activities are currently performed by existing electronic health records, health information exchange or traditional hospital IT systems. Where the functions do exist, they aren't carried out at the required scale in an integrated fashion across multiple care organizations.

With this article we will begin an exploration of the HIT needs of ACOs. While provider organizations are hashing out the financial distribution, we will start with the second most important influencer – the data. Data for an ACO can be considered as being used for at least three purposes: 1) to analyze and report on trends in clinical and claims data, 2) to support traditional clinical care and administrative recording processes, and, in a new category; 3) to manage shared information across multiple providers such as in ACO-wide managed problem lists, medication lists, care plans or directories of identity and privacy settings.
Here we focus on use the first: data analysis and reporting.
   
Identifying the Analytic Data

As HIT goes through its awkward teenage years and heads toward young adulthood, it's clear that a mix of well and poorly structured and maintained clinical data will persist. The first stage of meaningful use didn't specify health data transactions, but it began to specify a few important terminologies for recording problem, drug and lab data. These and other standards will be important when they slowly find their way into clinical systems as, at least, mappings for local codes and terms. Comparable high-quality, coded clinical data is important because, in conjunction with coded but clinically flawed claims data, it will be the basis for forming comparable lists, charts and statistical analyses of costs and care.

The ACO draft regulation describes how ACOs can get identifiable Medicare claims data from the Centers for Medicare and Medicaid Services. It's assumed that this will lead to the availability of Medicaid and even all-claims data at the ACO level as well. With both coded clinical and claims data in hand, ACOs will be better able to report on and, more importantly, advance IT and non-IT programs to manage costs and quality internally. ACOs need to work on where high healthcare costs align with actionable programs for prevention, clinical efficiencies and comparable, but more economical, treatments.

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While not easily talked about, the ability of ACOs to aggregate patient-identifiable hospital, community and payment data in one place will be central to this work. The data needs to be identifiable to track and manage patients across care settings. Analysis will also be much easier when the data is in one place. Some ACOs, particularly those made up of community physicians, may outsource data analysis. In general, though, hospitals and health systems will be best equipped to implement the kind of data warehouse and analytic infrastructure necessary for supporting broad community data stores. An issue is whether the ACO savings-sharing discussions can overcome community provider distrust of local hospitals enough to allow them to fully access community provider data. At the same time, it will be critical for hospitals to be allowed to actually benefit from prevented admissions. Regardless of these political questions, ACOs that aggregate the most and best-structured clinical and claims data will be best positioned to analyze and benefit.

That ACO Sweet Spot

Analytics are usually done in non-transactional data stores, sometimes as data marts built off of the transactional store (like an EHR) and sometimes as stand-alone data warehouses. ACOs will have to merge large amounts of clinical care, process and claims data and be able to perform canned and dynamic queries. Some ACOs will likely build up existing hospital data warehouses and business intelligence software packages they may have already deployed. Generally speaking, health data in these systems are loaded, as they are available with only a limited degree of work done to clean them. A substantial effort is then involved in developing customized queries for that organization.

There are, however, a number of newer tools angling for the ACO sweet spot that focus on using structured data inputs like the HL7 Continuity of Care Document standard and lab messages and use proprietary storage schema that allow for more pre-developed query and data analytic capabilities. As a result, some of these products can also support outgoing services for alerting and reporting back into EHRs. At times this would mean supporting somewhat redundant transactional, data warehouse and dedicated analytic stores. But with data storage costs continuing to drop and with the challenges of working with large data sets on multi-use systems, this redundancy may be expedient and not extravagant.
   
Others may try to arrive at an ACO analytic sweet spot via health information exchange or even EHR software. While one can't rule out either of these approaches, for an ACO of any significant size that has multiple EHR software systems and other claims and process data needs, a separate infrastructure will probably make the most sense.

In our next issue, part 2: The HIT of ACOs – Data to Improve Quality Management.

John Loonsk, MD, FACMI, is chief medical officer for CGI Federal. From 2006-09, he was director of interoperability and standards in the Office of the National Coordinator for Health Information Technology.