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6/21/2012
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U.S. Healthcare Needs Data Standards, Registries, Study Says

Several IT obstacles hold the nation back from establishing a value-based healthcare system, according to the Boston Consulting Group.

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25 CIOs Who Are Transforming Healthcare
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Due to the highly complex and fragmented nature of the U.S. healthcare system, developing a value-based healthcare model nationwide remains a daunting challenge, a new study from the Boston Consulting Group concludes.

The study, Progress Toward Value-Based Health Care, examined the progress toward implementing a value-based healthcare system in 12 developed countries: Australia, Austria, Canada, Germany, Hungary, Japan, the Netherlands, New Zealand, Singapore, Sweden, the U.K, and the U.S. The study assessed how these countries collect clinical data for the purpose of identifying best practices to improve the delivery of care while reducing costs.

As the U.S. moves from paper-based patient records to EHRs and looks to establish health information exchanges and accountable care organizations, Simon Kennedy, BCG's senior partner and managing director, says more could be done.

"There are several things the Obama administration and the ONC have not done that would make life a lot easier," Kennedy told InformationWeek Healthcare. Included in this wish list: strong patient identification, provider identification, and data exchange standards.

[ Is it time to re-engineer your Clinical Decision Support system? See 10 Innovative Clinical Decision Support Programs. ]

Kennedy also emphasized that the various terms used for a single medical event complicates matters. For example, myocardial infarction, MI, heart attack, and cardiac event are all terms used to describe a heart attack. "So many terms to describe the same medical event creates a lot of problems in the heterogeneity of the data," Kennedy said. "It would be nice if we could have a standardized medical nomenclature around the practice of medicine in the United States with much stronger data standard." He also lamented another roadblock interfering with a truly value-based healthcare system: "What we've got is a messy fee-for-service system with approximately 5,280 hospitals, 1,300 insurance companies, and 850,000 physicians, and a widely disaggregated system with lots of point-to-point connections. We need a more coherent more interoperable system," said Kennedy, who co-authored the report.

To conduct its research, BCG judged countries against 35 specific criteria--15 at the national level and 20 at the level of individual disease registries--all of which BCG says are essential requirements for developing an effective value-based healthcare system.

At the national level, the research group attempted to answer two questions: To what extent are a country's clinicians, government officials, and healthcare policymakers committed to creating and using a system of high-quality data? And to what degree is a national legal and IT infrastructure in place for collecting health outcome data and linking those data to issues of cost?

BCG researchers also identified four factors necessary for the successful implementation of a value-based healthcare system:

--Clinical engagement. Researchers' examination of 13 registries in five countries revealed that improvement in health outcomes are most effective when clinicians themselves are responsible for collecting and interpreting data and when clinicians lead the charge in clinical improvement.

--National infrastructure. A nationwide infrastructure must comprise common standards for tracking diagnoses, treatments, outcomes, and costs at the patient level as well as a limited number of shared IT platforms and a common legal framework within which to regulate the use of patient data.

--High-quality data. The most effective way to collect relevant data is through disease registries that track groups of patients' health outcomes who have the same diagnosis or who have undergone the same medical procedure. By analyzing the data, providers and payers can identify, codify, and promote more effective treatment protocols and enhance cost-effective care.

--Outcome-based incentives. The healthcare industry must use outcome data to drive incentives in the healthcare system. The data-driven incentive measures should spur changes in the way clinicians practice, payers reimburse, and suppliers of drugs and medical devices develop and deliver products and services.

Compared with other countries, the report found that while the U.S. has some excellent disease registries, including the Cystic Fibrosis Foundation Patient Registry, the Society for Thoracic Surgeons' STS National Database, and the American College of Cardiology's CathPCQ Registry, the nation falls short in other areas. For example, it does not have a national hip-replacement registry.

The report also heralds the efforts of Kaiser Permanente and Intermountain Healthcare, two organizations that have made significant progress in tracking outcomes in their own patient population and in developing incentives to encourage clinicians to use best practices identified through outcome research.

In its evaluation of how far countries have come in implementing value-based healthcare, the report concluded that Sweden is the most advanced country on the list, followed closely by Singapore. Germany and Hungary lagged behind other countries in the group. According to Kennedy, the research revealed the importance of incentives as a facilitator in building a value-based healthcare system.

"Germany has a similar budget to Sweden for registry data but very low uptake because it was done centrally and there was not any buy-in from the providers," Kennedy said. "To me, one of the primary findings was that you really need to get providers and payers and patients on the same page and aligned. Data and infrastructure and standards and tools are not by themselves sufficient."

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jsantangelo101
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jsantangelo101,
User Rank: Apprentice
11/6/2012 | 11:38:33 PM
re: U.S. Healthcare Needs Data Standards, Registries, Study Says
One key area is to have an automated and repeatable way to de-identify data for testing purposes.
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