Efficiency Improvement Achieved through Adoption of New Healthcare Data-Mining Technology

Siemens Healthcare (Erlangen, Germany) presented the general availability of its healthcare data-mining tool, Soarian Quality Measures powered by the patented REMIND (Reliable Extraction and Meaningful Inference from Non-structured Data) Platform, at the Healthcare Information and Management Systems Society (HIMSS) 2008 annual conference and Exhibition in Orlando, FL, USA, in February 2008. Soarian Quality Measures replaces time-consuming manual chart reviews with highly accurate and automated chart abstraction of quality measures, as defined by the Centers for Medicare and Medicaid Services (CMS; Baltimore, MD, USA) and The Joint Commission (Oakbrook Terrace, IL, USA).

The system analyzes and draws conclusions from all available electronic patient data from both Siemens and non-Siemens information technology (IT) systems, including structured data, such as demographics and financial information, and unstructured free text found in clinical notes and transcribed reports. The results of the analysis are presented in a simple, intuitive interface allowing the abstractor to quickly review and validate the results.

"This innovative solution serves as a key product in our growing portfolio of knowledge-driven technologies to help improve the quality and efficiency of healthcare delivery,” stated Ajit Singh, Ph.D., CEO, Image and Knowledge Management business unit, Siemens Healthcare. "Soarian Quality Measures provides unprecedented intelligence to healthcare providers, allowing them to focus more on helping their patients rather than collecting data.”

The Reading Hospital and Medical Center, an 800-bed not-for-profit healthcare center (West Reading, PA, USA), joined the growing list of medical facilities using advanced decision support technology to create efficiencies and orchestrate clinical best practices when it signed up to serve as one of Siemens customer beta sites for Soarian Quality Measures in 2007. Prior to implementing the system, Reading Hospital manually abstracted patient records to extract core measure information. After implementation of Soarian Quality Measures, the time required to review and extract core measures was reduced dramatically. After just one month of use, the average time required to review heart failure patients went from over 22 minutes per chart to just under seven minutes (332% improvement), and acute myocardial infarction record reviews went from over 33 minutes per chart to just over 10 minutes a chart (331% improvement).

"Soarian Quality Measures further reduces the dependency on manual chart abstraction, while improving the accuracy and speed of abstraction,” said Jay Raman, chief information officer, Reading Hospital. "The automated solution is extremely beneficial in accurately capturing the acuity of care.”

Reading Hospital initially volunteered to participate in the Soarian Quality Measures customer beta program due to its own organizational quality measures improvement goals and its successful, long-standing relationship with Siemens.


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