strategic health it advanced research projects (sharp) secondary use of ehr data principal...
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Strategic Health IT Advanced Research Projects (SHARP)Secondary Use of EHR Data
Principal Investigator: Christopher G. Chute, MD, DrPHProgram Manager: Lacey Hart, MBA, PMP
Mayo Clinic, Rochester, MN
ORGANIZATION COLLABORATORSAgilex Technologies, Inc.
Centerphase Solutions, Inc.
Clinical Data Interchange Standards Consortium (CDISC)
Deloitte
Group Health Research Institute
Harvard Childrens Hospital Boston
IBM T.J. Watson Research Center
Intermountain Healthcare
Mayo Clinic
Massachusetts Institute of Technology
Minnesota Health Information Exchange (MN HIE)
University at Albany - SUNY
University of Colorado
University of Pittsburgh
University of Utah
AREA 4 PROGRAMMayo Clinic, long a leader in the science of health care delivery, is proud to be a recipient of the Area 4 Strategic Health IT Advanced Research Project award. The SHARP Program – part of the Office of the National Coordinator for Health Information Technology, is focused on improving quality, safety and efficiency of health care through Information Technology.
Traditionally, a patient’s medical information, such as medical history, exam data, hospital visits and physician notes, are stored inconsistently and in multiple locations, both electronically and non-electronically. Mayo Clinic’s program will work towards creating a unified electronic healthcare record (EHR), allowing for the exchange of information among care providers, government agencies, and other stake holders.
Through six projects, Mayo Clinic’s program will:1. Standardize health data elements and ensure data integrityPatient 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 the project, called “Clinical Data Normalization”, will work towards transforming this non-standardized patient data into one unified set terminology. In this case, “diabetes mellitus,” “diabetic,” “249.00” and “DM” would all be re-named “diabetes.”
2. Merge and standardize patient data from non-electronic forms with the EHRSome important patient information, such as that from physician’s radiology and pathology notes, is stored in non-electronic, or “free text” form. This project will first work to merge the patient information in free texts with that in the electronic health care record. The next step, called “Natural Language Processing” (NLP), will work towards 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 the efficiency of patient care by reducing inconsistencies in patient data, giving physicians more accurate and uniform information in a centralized location.
3. Seek physically observable patient traits for further studyPhysically observable traits or phenotypes. 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 or groups of phenotypes.
4. Find processes to make clinical data normalization, NLP and high-throughput phenotyping more efficient using fewer resourcesThis 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 for those seeking patient information to receive it quickly, increasing the efficiency of patient care.
5. Detect and reconcile inconsistent dataMayo Clinic will utilize high-confidence services, or “data quality metrics,” to identify and optionally correct inconsistent or conflicting data.
6. Evaluate the progress and efficiency of Mayo Clinic’s projectThis program will use an “Evaluation Framework” using the Nationwide Health Information Network (NHIN). NHIN is a set of standards, services and policies that enable secure health information exchange over the internet.
COLLABORATION
Learn more about Mayo Clinic’s SHARP
Area 4 Program process at http://sharpn.org
Health IT Pilot Communities through Recovery Act Beacon Community Program
Principal Investigators: C. Michael Harper, Jr. M.D.; Christopher G. Chute, MD, DrPH; Douglas L. Wood, M.D. Program Manager: Lacey Hart, MBA, PMP
Mayo Clinic, Rochester, MN
PROGRAM ADVISORY COMMITTEESuzanne Bakken, RN DNSc, Columbia University
C. David Hardison, PhD, VP SAICBarbara A. Koenig, PhD, Bioethics, Mayo Clinic Issac Kohane, MD PhD, i2b2 Director, Harvard
Marty LaVenture, PhD MPH, Minnesota Department of Health Dan Masys, MD, Chair, Biomedical Informatics, Vanderbilt University Mark A. Musen, MD PhD, Division Head BMIR, Stanford University
Robert A. Rizza, MD, Executive Dean for Research, Mayo Clinic Nina Schwenk, MD, Vice Chair Board of Governors, Mayo Clinic
Kent A. Spackman, MD PhD, Chief Terminologist, IHTSDOTevfik Bedirhan Üstün, MD, Coordinator Classifications, WHO
SE MN POPULATION HEALTHSE MN community will embrace standards based HIE to improve
access, quality and efficiency of health care delivery
Childhood Asthma and DiabetesReduce Emergency room visits
Reduce unscheduled MD visits
Reduce hospitalization
Improve self-reported functioning
Improve compliance with the treatment of asthma
Improve school attendance
Reduce days out of work – self-reported for Diabetes
Improve compliance with Diabetes
Conceptual Infrastructure
BEACON COMMUNITIESCommunity Services Council of Tulsa, Tulsa, OK
Delta Health Alliance, Inc., Stoneville, MS
Eastern Maine Healthcare Systems, Brewer, ME
Geisinger Clinic, Danville, PA
HealthInsight, Salt Lake City, UT
Indiana Health Information Exchange, INC., Indianapolis, IN
Inland Northwest Health Services, Spokane, WA
Louisiana Public Health Institute, New Orleans, LA
Mayo Clinic Rochester, Rochester, MN
Rhode Island Quality Institute, Providence, RI
Rocky Mountain Health Maintenance Organization, Grand Junction, CO
Southern Piedmont Community Care Plan, Inc., Concord, NC
The Regents of the University of California at San Diego, San Diego, CA
University of Hawaii at Hilo, Hilo, HI
Western New York Clinical Information Exchange, Inc., Buffalo, NY
Learn more about Mayo Clinic’s Beacon Program at http://informatics.mayo.edu/beacon
Extend advanced health IT & exchange
infrastructure
Leverage data to inform specific
delivery system & payment strategies
Demonstrate a vision of the future where:
•Hospitals, clinicians, & patients are meaningful users of health IT
•Communities achieve measurable & sustainable improvements in health care quality, safety, efficiency, and population health
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Dodge countyDodge countyDodge countyDodge county
Freeborn countyFreeborn countyFreeborn countyFreeborn county
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Olmsted countyOlmsted countyOlmsted countyOlmsted county
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Steele countySteele countySteele countySteele county
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Home healthHome healthHome healthHome health
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Olmsted MedicalOlmsted MedicalOlmsted MedicalOlmsted Medical
Mayo Health SystemMayo Health SystemMayo Health SystemMayo Health System
Winona HealthWinona HealthWinona HealthWinona Health
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