An Easily Accessed Clinical Research Database from your Epic EMR

Transcription

1 Loyola University Chicago Health Sciences Division Stritch School of Medicine (SSOM) An Easily Accessed Clinical Research Database from your Epic EMR February 13, 2014

2 Speakers: Richard H. Kennedy, Ph.D. Vice Provost for Research Loyola University Chicago Health Sciences Division & Senior Associate Dean for Research Loyola University Chicago Stritch School of Medicine Maywood, Illinois Ron Price Associate Vice President, Informatics and Systems Development Loyola University Chicago Health Sciences Division & Associate Dean Information Systems Loyola University Chicago Stritch School of Medicine Maywood, Illinois

3 Ever get these types of research requests? I need : to know how many anemia patients we saw in the past year all creatine and tacrolimus lab results, 30 days post tx, for every bone marrow transplant patient first and last A1c lab result for any patient with a diagnosis of diabetes in the past 12 months to know all inpatient hepatology service encounters that had a patient with a platelet count < 50,000 during their admission and also had a thrombotic event (ICD-9 codes 453.X, 415.1X, 452.X or 444.X)

4 SSOM s Clinical Data Analysts One dedicated FTE for clinical research data extracts 0.5 FTE support as available Faculty, residents, students and other business units as data customers Preparatory for research requests (10-15+/week) IRB approved requests ( /year) Effort for requests varies from 1-2 hours -- all the way to a couple of weeks for very complex extracts with multiple temporal aspects

5 Need for Clinical Analytic Infrastructure Need computing infrastructure that can: aggregate and analyze large amounts of clinical data and related information support creation of rich data structures traditional relational structures too numerous, too difficult to use and to understand operate on structured and unstructured data leverage open source tools and technologies

6 Need for Clinical Analytic Infrastructure Need computing infrastructure that can: incorporate advanced analysis technologies (e.g., NLP, image analysis, machine learning, etc.) be flexible, scalable and affordable provide data and services to a wide range of audiences (e.g., faculty, knowledge workers, analysts and other systems)

7 The Clinical Research Database (CRDB)

8 CRDB Development Timeline December 2012 Back of the envelope discussion at AAMC SDRE meeting in DC January 2013 Skunk-works Hadoop/www prototype February- March 2013 Approval and implementation of production environments and web site May June 2013 Development of CRDB version 1.0 July 2013 Broad roll-out of CRDB site December 2013 release of CRDB version 1.1

9 What is the Clinical Research Database (CRDB)? Large-scale, de-identified clinical data warehouse structured to support a wide range of clinical analytics Operates on advanced Hadoop technology stack CRDB data are accessible via a web-based front-end for casual users (e.g., faculty, housestaff and students) and via a wide range of tools for advanced users (e.g., analysts, bioinformatics staff, etc.) Data loads for the CRDB are from Epic (1/1/2007-9/30/2013)

10 Hadoop and Open Source Software SSOM s Hadoop environments Development ($0K re-purposed equipment) 6 data nodes, 2 name nodes, 1 MySQL server 12TBs of HDFS storage Production (approximately $60K) 9 data node, 2 name nodes, 1 MySQL server 178TBs of HDFS storage Open source software: Linux (Centos), Hadoop, Hive, MySQL, OpenBlueDragon, Python, and Perl

11 Why use Hadoop? Hadoop s strengths are its ability to scale and to efficiently handle unstructured data (e.g., text reports, images, BLOBs, etc.) Of the 1.2 billion clinical documents produced in the United States each year, approximately 60 percent contain valuable information trapped in unstructured documents that are unavailable for clinical use, quality measurement and data mining. * Some estimates put this number closer to 80% * Health Management Technology June 2012

12 CRDB Version 1.1 (Dec 2013) Current data De-identified with keys held in Epic Clarity data warehouse Data source of Epic Clarity (updated nightly) Data period of 1/1/2007 through 09/30/2013 Updated quarterly (next update mid-march 2014) Data tables Demographics Encounters (Inpatient, Outpatient, ED, Obs and home health) Procedures and clinical lab values Flowsheet measures (vitals, physical findings, etc.) Medications Payor information at encounter level CRDB application is widely available on the portal

13 Demonstration of the CRDB

14 CRDB Version 1.0 Future Efforts Capture of additional data (current calendar year) Microbiology results and other report text blobs Socioeconomic data Large-scale analysis Continuous comorbidity analysis Institutional cohort definitions 27 chronic disease states PCORI CRDN activity End-user Query Tool Additional query parameters and analysis modules CPTs (March 2014) Labs (June 2014) Flowsheet measures (August 2014) Service Units (October 2014)

15 Current Usage (July 2013 Jan 2013) Unique CRDB Users 399 Query Tool CRDB Cohort identifications 589 Defined Disease Groupings - 69 Notable Large-Scale CRDB data extracts 5 extracts for a recent PCORI grant 150+K patients 3 extracts for Chicago Health Atlas project

16 Questions and Answers