UT SHIS Researchers Receive Nearly $2 Million in NIH Challenge Grants

Researchers at The University of Texas School of Health Information Sciences at Houston (SHIS) were awarded nearly $2 million as part of the government’s economic stimulus package. The money comes from the American Recovery and Reinvestment Act of 2009 (ARRA) that provided $8.2 billion to the National Institutes of Health (NIH) to help stimulate the U.S economy through support and advancement of scientific research.

SHIS faculty Elmer Bernstam, MD, MSE, and Kim Dunn, MD, PhD, received ARRA-supported awards called Challenge Grants that were designed to spur new areas of research. These awards were made available by the National Center for Research Resources, part of the NIH.

The Challenge Grant selection process was highly competitive with NIH officials receiving about 20,000 applications and awarding 750, according to an NIH representative.

“The awards that Drs. Bernstam and Dunn received are a testament to the role biomedical informatics plays in the future of healthcare,” said Jack Smith, MD, PhD, Dean of the School of Health Information Sciences.

Dunn received a $960,000 NIH Challenge Grant to demonstrate the value of the medical home as a model for improving quality of care incorporating telemedicine and as a strategic stepping stone to a sustainable health information exchange model. A medical home is not an actual place, but rather an avenue to providing comprehensive primary care. To reduce what she sees as fragmentation in the healthcare system, Dunn would like to see the medical home as the co-manager of information by both the patient and his or her primary care physician.

“People expect their primary care physician to be their point of access to healthcare and to assure that the care they receive within the system is evidence-based, cost-effective, coordinated, and safe,” said Dunn, “Unfortunately, primary care providers do not have the systems in place and are not paid to coordinate care. This results in many people turning to emergency rooms, the most costly sites for care, for primary care.”

There has not been a significant business model to support the necessary services and technology-supported processes to assure a patient has an accountable healthcare delivery system, according to Dunn. To address these issues, Dunn proposed a pilot Medical Home project in a community-based setting. The Medical Home model is based on an electronic data infrastructure, that Dunn and her colleagues have built, that allows physicians to coordinate care, evaluate the quality of the care provided, incorporate telemedicine (email, live interactive videos and health information exchange) and participate in quality improvement initiatives. In addition, this data infrastructure provides the opportunity for community-based comparative effectiveness research (CER) to be carried out and to have an impact. CER compares treatments and strategies to improve health.

“Our aim is to evaluate a rapid implementation of a medical home model including telemedicine on costs, patient acceptance, doctor acceptance and impact on quality of care indicators,” she said.

Bernstam was awarded $950,000 to make clinical data more accessible to medical researchers. His project titled “Concept-Level Methods for Comparative Effectiveness Research,” will unlock the potential of a Clinical Data Warehouse to perform CER.

Clinical Data Warehouses archive data from electronic medical records (EMRs) and support queries across patients. For example, they can help determine the percentage of patients taking a certain drug who will develop a specific condition versus those who don’t. Therefore, they are important enablers of comparative effectiveness research. However, simply transferring healthcare data from EMRs to a CDW is not sufficient. To answer questions such as these, researchers must be able to quickly process and visualize large datasets without compromising data quality or patient privacy.

“Healthcare data, unlike clinical trial data, are not collected with a research question in mind. Thus, they may be poorly structured and contain protected health information or identifying phrases such as 'senator with lymphoma.' Our unifying hypothesis is that concept level approaches can be applied to Clinical Data Warehouses to bring meaning to vast amounts of healthcare data while protecting subject privacy," Bernstam said.

The potential impact of this project is therefore faster and more efficient biomedical discovery using clinical datasets that are already being collected at multiple institutions. In other words, researchers will be able to learn from routine clinical care, complementing traditional research methods such as clinical trials. This research will enable discovery of safer, more economical medications, and previously unseen correlations between diseases, medications, and procedures.

by Rachel Christianson, School of Health Information Sciences