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Hospitals tackle broad range of applications with data warehouses

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In its second survey of data warehouse use in healthcare organizations, the HIMSS Data Warehouse and Data Mining Special Interest Group reports that hospitals are branching out in the ways they use data repositories to improve their business operations.

In its second survey of data warehouse use in healthcare organizations, the HIMSS Data Warehouse and Data Mining Special Interest Group reports that hospitals are branching out in the ways they use data repositories to improve their business operations.

Based on its 2004 survey, the group reports that data warehouses are no longer the exclusive province of either the clinical or financial components of a healthcare organization. They are now more generally used in all areas of the hospital, according to Larry Wolf, senior consulting architect at Kindred Healthcare in Louisville, KY.

Wolf presented the survey results during an electronic session at the 2005 HIMSS meeting in Dallas. The findings represent the answers of 29 respondents, including chief medical officers, physicians, CIOs, and technologists.

In addition to financial analysis, budgeting, and clinical research - the areas that had been addressed in the group's first study, released in 2001 - respondents reported using data warehouse technology to address several new areas:

  • managed-care analysis

  • clinical benchmarking

  • performance management

  • clinical effectiveness

  • labor/productivity analysis

As a result of the wide variety of applications, facilities rely on a mixture of data warehouse architectures. According to Wolfe, many respondents said they have more than one type of data warehouse architecture in use, including:

  • query transaction system (80%)

  • internal analytic database with shared data (73%)

  • internal analytic database without shared data (73%)

  • integrated warehouse (33%)

  • turnkey analytic application - healthcare (67%)

  • turnkey analytic application - nonhealthcare (40%)

  • outsourced (13%)

The variety of architectures used, often at the same institution, contradicts most data warehouse theories, which argue for a tightly integrated data-sharing model, Wolf said.

The question, he said, is whether organizations will move toward reducing architecture complexity to meet the integrated warehouse gold standard, or whether the architectures will stay fragmented to cope with the increasing complexity and wide array of tasks being addressed.

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