The uses of patient health care data are diverse. The context of data creation is the treatments involved in caring for the patient. The care, in turn, generates payment processing and insurance claims; operations and quality management within organizations such as hospitals, clinics and related business units; health care research using randomized clinical trials; comparative analyses of medical as well as financial results across multiple enterprises; and the performance of health care providers.

The performance of providers across a variety of health care and financial metrics is receiving intense attention. Why? With health care services hitting nearly 15 percent of the gross domestic product of the U.S. and costs to payers, employers and consumers rising at double digit rates, one of the financial mechanisms that promises to provide tools needed to bring costs under control is “pay-for-performance.” However, benchmarking medical group practice performance faces obstacles such as the absence of consistent, unified and conformed patient outcome results. Standards are useful, but there are so many of them. Each data source has its own set of standards and formats, resulting in a formidable array of clinical and operational data (see Figure 1).

To measure performance against peer organizations, a longitudinal view of patient records plus patient financial data is needed. That has been hard to find - until now. A race is on in the market to build health care data warehouses and the related infrastructure that meet the requirements of both health care providers and payers for objective, independent, HIPAA-compliant information. Health insurance companies, large pharmaceutical firms and nonaligned, independent research networks are engaging the challenge. One of the early entrants in the race is Convergence CT (CCT).

Data warehousing is an essential component, but by itself it is not enough. The idea is to build a global health care research network that converges properly anonymized patient data with current life sciences data in the context of secure analytic services via a high-performance platform able to sustain custom analytics by medical groups, payers and industry clients. The result is a collaborative data warehouse comprised of rich clinical data along with analytic services that will advance patient care, clinical research and operational decision-making in the health care and life sciences domains (see Figure 2 at the end of the article).

In addition to the data warehouse technology and clinically relevant data model, CCT has access to patient data through trusted intermediaries. For example, it is working with the American Medical Group Association subsidiary, Anceta. Phase I promises to deliver a clinical data warehouse with 7 million patients and almost 5,000 physicians, facilities and hospitals.

This raises the bar on data and application integration. Instead of an application integration technology, CCT’s Clinical Data Warehouse secures, optimizes, anonymizes and literally converges - meaningfully merges — clinical and financial data for process optimization. The CCT Clinical Data Warehouse provides a patent-pending algorithm to reidentify patients from the anonymized version of data if permission is given to identify and use them in clinical trials. Thus, one of the innovations enabling pay-for-performance is the merging of properly anonymized clinical and financial data.

For those medical practice groups whose data complexity and readiness for analytics is behind the curve, whether due to legacy systems or legacy practices, CCT will refer the group to suitable professional services (including some from IBM’s Global Business Services) for process optimization, data rationalization and application integration. For those whose data is ready, CCT provides the road to medical code rationalization, data mapping and the automated creation of longitudinal deidentified patient records using both local medical vocabulary and the standardized version with encryption of sensitive patient identifiers and audit logs. The number of source systems for which metadata is available to facilitate the process is extensive.

IBM’s role in enabling a practical approach to pay-for-performance is to help CCT connect the dots between the underlying data warehousing technology and the mission of bringing breakthrough pay-for-performance results to practice groups and health care providers. IBM’s Linux Balanced Warehouse (formerly Balanced Configuration Unit) provides a powerful open source hardware platform that leverages the economic advantages of the open source revolution in IT, while providing the scalability, performance and ease of administration needed to deliver low-latency transformations and queries against the data warehouse. While a single silver bullet to slay the dragon of rising health care costs is unlikely, CCT’s collaborative clinical data warehouse is a promising method of taking significant steam out of the beast and paving the way to improved financial performance along with best practices in clinical outcomes and research.

As a result of years of research and innovation, according to Rob Albertson, CCT’s vice president, Global Marketing, “CCT’s HIPAA-compliant, secure Clinical Data Warehouse provides such a view, opening up the way to operational efficiencies, collaborative benchmarking against peers and improved clinical best practices.” One group providing leadership is Anceta LLC. Its National Collaborative Data Warehouse that CCT is building will use a 20 Core Linux Balanced Warehouse. With IBM’s DB2 Warehouse (V9), the Balanced Warehouse is data warehousing made simple - front end, middle and back end - due to a scalable, flexible, high-performing architecture that produces results without friction. According to Albertson, “Our decision was driven by our determination that, in supporting Clinical Data Warehouse, the infrastructure provided by IBM will persist and deliver the analytics for the Anceta National Collaborative Data Warehouse in a way making the underlying technology invisible. ‘Invisible’ means highly useable yet requiring minimal effort to the health care professionals accessing it. It’s so advanced, it’s simple.”

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