Secondary Use of EHR Data
Mayo Clinic’s Strategic Healthcare IT Advanced Research Project (SHARP) will enhance patient safety and improve patient medical outcomes through the use of an EHR. Traditionally, a patient’s medical information, such as medical history, exam data, hospital visits and physician notes, are inconsistently stored in multiple locations, both electronically and non-electronically. With a vision of solving this issue, the project aims to efficiently leverage EHR data to improve care, generate new knowledge, and address population needs through the secondary use of EHR data.
Mayo Clinic’s project will work toward creating a unified EHR through the secondary use of EHR data, which will allow for the exchange of patient information among care providers, government agencies, insurers and other stakeholders. By creating tools, services and software for large-scale health record data sharing, Mayo Clinic’s project will ultimately advance the quality and efficiency of patient care through the use of an EHR.
Standardize health data elements and ensure data integrity - Patient information can be stored using several different abbreviations and representations for the same piece of data. For example, “diabetes mellitus” (more commonly referred to as “diabetes”), can be referred to in a patient’s medical record alternately as “diabetic,” “249.00” and “DM.” The first phase of Mayo Clinic’s project, called “Clinical Data Normalization,” will work toward transforming this non-standardized patient data into one unified set of terminology. In this case, “diabetes mellitus,” “diabetic,” “249.00” and “DM” would all be re-named “diabetes.” Watch a video of Dr. Huff discussing data normalization
Merge and standardize patient data from non-electronic forms with the EHR - Some important information, such as that from a physician’s radiology and pathology notes, is stored in “free text” form. Mayo Clinic’s project will first work to merge the patient information in free texts with that in the EHR. The next step of this project, called “Natural Language Processing” (NLP), will work toward classifying certain tags, such as “diabetic,” “DM” and “57 year old male” under specific categories, such as “disease” or “demographics.” NLP, in addition to clinical data normalization, will help improve patient care by reducing inconsistencies in patient data, providing physicians with more accurate and uniform information in a centralized location.
Watch a video of Dr. Savova discussing the steps to natural language processing or information extraction of clinical narrative
Seek physically observable patient traits for further study - Physically observable traits, or phenotypes, can include growth and development, absorption and processing of nutrients, and the functioning of different tissues and organs. These traits result from interactions between a patient’s genes and environmental conditions. Mayo Clinic will use a process called “High-Throughput Phenotyping”, which uses clinical data normalization and NLP to identify and group a particular phenotype, such as Type 2 diabetes. This process will enhance a physician’s ability to identify and study individual phenotypes or groups of phenotypes. Watch a video of Dr. Chute discussing phenotype characteristics for identifying patient cohorts
Find processes to make clinical data normalization, NLP and high-throughput phenotyping more efficient using fewer resources - This part of the process will focus on building adequate computing resources and infrastructures to accomplish the previous steps. Called “Performance Optimization,” this system will allow those seeking patient information to receive it quickly, increasing the efficiency of patient care while using fewer resources. Learn more about the IBM Research: Unstructured Information Management Architecture (UIMA) in the SHARPn program
Detect and reconcile inconsistent data - Mayo Clinic will utilize high-confidence services, or “data quality metrics,” to identify and optionally correct inconsistent or conflicting data.
Evaluate the progress and efficiency of Mayo Clinic’s project - Mayo Clinic will use an “Evaluation Framework” using the Nationwide Health Information Network, an Office of the National Coordinator for Health Information Technology program. Nationwide Health Information Network Exchange is a set of standards, services, and policies that enable secure health information exchange over the internet. Learn about the "tracer-shot" pilot conducted in the SHARPn program.
Dr. Christopher Chute, The Mayo Clinic of Medicine
For More Information:
Please refer questions and comments regarding SHARPn to SHARP.Secondary@hhs.gov.