Building the Electronic Data Infrastructure: Lessons from Indiana PROSPECT Paul Dexter, MD Chief...
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Transcript of Building the Electronic Data Infrastructure: Lessons from Indiana PROSPECT Paul Dexter, MD Chief...
Building the Electronic Data Infrastructure: Lessons from Indiana PROSPECT
Paul Dexter, MD
Chief Medical Information Officer, Wishard Health Services
Regenstrief Institute Scientist
Supported by AHRQ Grant R01 HS19818-01
Dr Dexter has no conflict of interest.
Enhancing health care IT infrastructure
• A learning health system• Coordinated clinical, research, and quality
improvement efforts• Outcomes important to patients• CER, PCOR• Leveraging EHRs and other data sources• Rapid, comprehensive, hypothesis-generating
results
Local opportunities and challenges
• A large health information exchange• Creation of new software• Study enrollment challenges, PBRN• Investigator access to preliminary data• Integration of clinical and genetic research• Capture of patient reported outcomes• Improved support of standards
Specific aimsEnhance existing information technology infrastructure:
• Support providers, caregivers, and researchers by providing new tools for communication and co-management
• Provide de-identified access to the INPC database for CER work
• Capture and store health care outcomes important to patients and their caregivers
Comparative effectiveness clinical trial of medication treatment for behavioral symptoms of Alzheimer’s disease
INPC Data
» 80 hospitals signed up» 46 hospitals “live”• 1,400 interfaces• 12 million individuals• 4 billion structured results
• Also includes:• Laboratories• Radiology centers• Public health• 5 large payors
Record Countas denominator
Realtime
Automated study recruitment
Informatics decision support research
Record Countas denominator
Realtime
Study design tool
Record Countas denominator
Realtime
Study design tool
Integration and enhancements to eMR-ABC
Automated biospecimen tracking
Lab Technician
caTrack
PDA with Scanner
Web Service
Phlebotomist caTissue Application
BioSpecimen Database
caTrack Business
Logic
Scan patient barcode
Scan blood tube
barcode
Scan centrifuge
barcode
Scan blood tube
barcode
Scan box
barcode
Scan aliquot
barcode
De-identified I2b2 queries
I2B2Database
Global IDGlobal ID
De-identification
Staging Server
INPCBiospecimen
Tissue Tracking
myTrackMolecular
Data
INPCBiospecimen
Tissue Tracking
“Vending machine” concepts
Diabetes mellitus
Coronary artery disease
Myocardial infarction
Heart failure
COPD
Asthma
Hypertension
Breast cancer
Prostate cancer
Lung cancer
Colorectal cancer
Ovarian cancer
Esophageal cancer
Stroke
Chronic kidney disease
GI bleeding
HIV/AIDS
Schizophrenia
Hyperlipidemia
Osteoarthritis
Rheumatoid arthritis
Falls
ADHD
Etc….
UIMA/cTAKES open source NLP
Real-time NLP
Integration of LOINC survey instruments
Striving for sustainability
Thank you