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Harnessing the power of enhanced dat... [J Healthc Manag. 2012 Nov-Dec] - PubMed - NCBI

Hybrid Data Sets Can Improve Hospital Quality Reporting

The Minnesota Hospital Association piloted a project funded by the Agency for Healthcare Research and Quality in 13 Minnesota hospitals to see if using a hybrid data set that combined clinical laboratory data with administrative claims data could improve measurement of risk-adjusted hospital performance. Project investigators found that using a hybrid data set was not only feasible, but also improved the ability to compare risk-adjusted mortality and risk-adjusted complications across multiple hospitals. The report, “Harnessing the Power of Enhanced Data for Healthcare Quality Improvement: Lessons from a Minnesota Hospital Association Pilot Project,” outlines the challenges and lesson learned during the study and provides recommendations for others wishing to collect hybrid data sets. It was published in the November/December issue of the Journal of Healthcare Management. To access the abstract, select: http://www.ncbi.nlm.nih.gov/pubmed/23297607.

J Healthc Manag. 2012 Nov-Dec;57(6):406-18; discussion 419-20.

Harnessing the power of enhanced data for healthcare quality improvement: lessons from a Minnesota Hospital Association Pilot Project.

Pine M, Sonneborn M, Schindler J, Stanek M, Maeda JL, Hanlon C.

Source

USA.

Abstract

The imperative to achieve quality improvement and cost-containment goals is driving healthcare organizations to make better use of existing health information. One strategy, the construction of hybrid data sets combining clinical and administrative data, has strong potential to improve the cost-effectiveness of hospital quality reporting processes, improve the accuracy of quality measures and rankings, and strengthen data systems. Through a two-year contract with the Agency for Healthcare Research and Quality, the Minnesota Hospital Association launched a pilot project in 2007 to link hospital clinical information to administrative data. Despite some initial challenges, this project was successful. Results showed that the use of hybrid data allowed for more accurate comparisons of risk-adjusted mortality and risk-adjusted complications across Minnesota hospitals. These increases in accuracy represent an important step toward targeting quality improvement efforts in Minnesota and provide important lessons that are being leveraged through ongoing projects to construct additional enhanced data sets. We explore the implementation challenges experienced during the Minnesota Pilot Project and their implications for hospitals pursuing similar data-enhancement projects. We also highlight the key lessons learned from the pilot project's success.