Building the Electronic Data Infrastructure: Lessons from Indiana PROSPECT Paul Dexter, MD Chief Medical Information Officer, Wishard Health Services Regenstrief.

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