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Electronic Health Records Facilitating Clinical Research

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Presentation on theme: "Electronic Health Records Facilitating Clinical Research"— Presentation transcript:

1 Electronic Health Records Facilitating Clinical Research
Clinical Research Management Workshop Tuesday, June 22, 2010 Anil Jain, MD, FACP Senior IT Executive, Information Technology, Cleveland Clinic Managing Director, eResearch, eCleveland Clinic Co-Director, Biomedical Informatics, CTSC, Case Western Reserve University 1 1

2 Objectives Provide an overview of eResearch at the Cleveland Clinic
Review our experience with simulation of clinical trial protocols using EHR data Demonstrate our ability to enhance clinical trial recruitment with EHRs Show how we have leveraged EHR data for comparative effectiveness research

3 The Cleveland Clinic

4 The Cleveland Clinic The Cleveland Clinic Founded in 1921
Not-for-profit group practice 2096 Professional Staff and scientists Innovations include: First coronary angiography Development and refinement of coronary bypass surgery First minimally invasive aortic heart valve surgery First successful larynx transplant Discovery of first gene linked to coronary artery disease CCHS Statistics (2009): Operating Revenue: ~ 5.6 Billion Clinical visits: Nearly 4 Million Admissions: 155,000 U.S.News & World Report rankings: 4th among nation’s 6,000 hospitals Nation’s #1 heart program 16 specialties ranked The Cleveland Clinic The Cleveland Clinic

5 Cleveland Clinic and Research (2009)
Funding & Scope $272 M Total Research Funding $91 M in Federal NIH Awards Over 2,200 active projects 434 Active Registries with avg. 4 – 6 cohorts per registry Generalizability of Patient Population 75% of patients came from Cleveland’s seven adjacent counties 1.5 M visits in the regional medical practice sites (community-based clinics) “Centers of Excellence” for numerous diseases areas

6 Cleveland Clinic EHR implementation Path
1999 2000 2002 2004 2006 2008 2010 HIE OR IS Billing & Reimbursement Inpt Notes ADT Inpatient CPOE Document Scanning Tethered Patient Portal Enterprise Master Patient Index Electronic Prescriptions Clinical Decision Support and Quality Reporting Ambulatory EMR CPOE + Documentation Integrated Lab/Radiology Results Reporting Scheduling & Registration 6 6

7 EHR data is routinely used at our Institution…
Health Wellness and Prevention Immunizations, Osteoporosis, Diabetes and Cancer screening Disease-based Reporting Diabetes, Hypertension, Heart Failure, Asthma Patient Safety Adverse Drug Events and sentinel events FDA Public Health Advisories (e.g., Vioxx® and Ortho-Evra®) Local Consensus (e.g., Avandia ® notification) Public Reporting Pediatric Immunizations (SIRS), Communicable Diseases, process measures and quality indicators (JCAHO, HEDIS, CMS, etc.) EHR Data Reports

8 Clinical Care Domain Clinical Research Domain
The Silos… Clinical Care Domain EMR w/multiple interfaces Aggregates ALL avail. data Organized around Patients HIPAA Policy HL7 a common Messaging standard Non-Structured & Structured Clinical Research Domain Independent Data Organized around a Study Well Behaved Data Biostatisticians Manage Drug Trials 21 CFR Part 11 Involves Sponsor and FDA +/- CDISC Standards 8

9 Our investigators want the EHR to help them!
Identify current research subjects in the EHR Develop tools to help recruit potential research subjects Appropriately bill activity occurring in EHR-managed visits to the sponsor for research activity versus usual payor for standard of care. Develop Single Source capability with extraction to eCRF Capture rich structured data from the EHR (phenotypic) and combine with bio-informatics data (genotypic) Easily move valid data from EMR into research registries Facilitate secure EMR access for research monitors 9

10 Provides EMR-centric Resources for other groups
Quality & Patient Safety Institute Quantitative Health Sciences eAnalytics and Research: Research Standardization Center for Clinical Trials & Clinical Operations Clinical & Translational Science Consortium

11 Leveraging the EHR to capture critical data for researchers
Electronic Health Record Personal Health Record Clinical Events Adverse Reactions Patient Outcomes Clarity ??? Dialysis Center Local “EMR”s Registries Genomics Imaging Registries eResearch Db 11

12 Clinical Research Cycle
Subject Recruitment Clinical Data eCRF Data Collection Trial Management Site Selection Regulated Databases eResearch Services Protocol Assessment Research Billing Protocol Development Data Analysis Research Hypothesis Knowledge Dissemination 12

13 Multidisciplinary eResearch Team

14 Guidance… 14

15 A Research Study Scenario (These parameters and numbers are purely fictional and intended only to demonstrate the scenario) Inclusion Diabetes Type 2 Age 18 to 65 at screening Treatment Naïve or Oral mono-therapy Exclusion Uncontrolled Hypertension Triglycerides >= 1000 mg/dl Lipid-lowering therapy not stable for 1 year History of myocardial infarction or unstable angina History of coronary artery bypass graft surgery or angioplasty History of insulin use (other than gestational diabetes) History of substance abuse or unlikely to finish study

16 Analysis of Protocol Criteria
Inclusion and Exclusion Study Criteria Data Source Demo Vitals Dx/Proc Rx Lab Chart Diabetes Type 2 X Age 18 to 65 Rx Naïve or mono-therapy No Uncontrolled Hypertension No Triglycerides >=1000 If being treated, stable dose of lipid-lowering agent No Hx of MI/USA, CABG/PTCA No Insulin use (except gest DM) No history of substance abuse Likely to complete study

17 Ontology & Vocabulary Information Standard Vocabulary Diagnoses
ICD9 Codes IMO Terms SNOMED Mapping (limited, via IMO) Medications First Data Bank / NDDF+ National Drug Code RxNorm (limited, thru eResearch cross-walk) Laboratory Local Codes LOINC Mapping (limited, thru eResearch cross-walk via RELMA tool) Allergies Local Family History Procedures CPT™, ICD9 Procedure Codes

18 High-level Summary of the Impact of Each Criterion

19 Assess Each Criteria for Ethnic/Gender Diversity

20 e Trial Support eResearch Tools Traditional Recruitment Strategies
Clinical Data Repository Electronic Health Record eResearch Tools Traditional Recruitment Strategies Research Coordinator 20 20

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23 Physician attitudes… Embi PJ, Jain AK, Harris CM. Physicians' perceptions of an electronic health record-based clinical trial alert approach to subject recruitment: A survey. BMC Med Inform Decis Mak Apr 2;8:13.

24 What are the characteristics of the alert?
False Positives Many referrals made for each enrollee – excessive false positives… EHR may not capture key criteria. Chart review may not validate “computable” criteria Patients may not necessarily be good candidates or willing to consent False Negatives Documentation gap Time lag between presentation and documentation Only patients who have come in for a visit ??

25 Integrating study criteria with scheduling…
Site Admin Provider Clinical Trial Alert Study Filter (patient & provider) Study Criteria AUTOMATED PROCESS DURING THE NIGHT DURING THE OFFICE VISIT Patient Schedules (sites) Secure EHR order enrolls Pt into Study Patient Tracked via EHR 25

26 EHR-data based recruitment lists work!
Cleveland Clinic involved in multi-site clinical trial for safety of NIH - H1N1 vaccine among children with severe asthma. Comparison of the eResearch services to the Severe Asthma Research Program (SARP) network registry. eResearch led to higher enrollment, 93/540 (17.2%) eResearch vs. 24/109 (22%) for SARP. Performance was similar to the volunteer registry without significant increase in costly screen failures Diversity in terms of race/ethnicity of the subjects was increased using EHR-based identification Parikh P, Jain A, et al. Recruitment and Enrollment of Asthmatics in a Phase II Clinical Trial, ATS Meeting, May 17, 2010.

27 Increasing participation and diversity… (U Pitt)
Over a 22-month period, EMR-prompts for recruitment: PCPs referred 794 patients via EMR-prompts and 176 (22%) met study inclusion criteria and enrolled, 8,095 patients were approached by wait room-based recruiters of whom 193 (2.4%) enrolled. Subjects enrolled by EMR-prompted PCPs were more likely to be non-white (23% vs 5%; P < 0.001), male (28% vs 18%; P = 0.03) Rollman BL et al. Comparison of electronic physician prompts versus waitroom case-finding on clinical trial enrollment. J Gen Intern Med Apr;23(4): 27

28 Three recent outcomes and CER projects…
Modeling cardiovascular outcomes in patients on oral hypoglycemic agents Modeling cardiovascular complication rates in patients admitted to the hospital with acute coronary syndrome Identifying determinants of progression of kidney disease in patients with chronic kidney disease Why was the EHR used? Size and scope of required electronic data was mostly already in the EHR Competitive advantage for obtaining sponsors

29 Strategies to Overcome EHR Data Reliability Issues
RELIABILITY CHALLENGES Death is not always reliably captured in an EHR derived data set. Documentation of certain exclusions and adverse events are generally not captured as structured data Prescription medication dispensed and taken including OTC Patients may have fragmented care with some clinical data outside institutional EHR. POTENTIAL SOLUTIONS EHR data can be linked to SSDI assuming appropriate permissions Text mining/analysis of progress notes, discharge summaries, operative reports can identify some events/adverse events Widespread adoption of Medication-Reconciliation Leveraging Health Information Exchanges or inclusion of payer data can mitigate the problems with fragmented care

30 eResearch Facilitated Studies…

31 Explorys Population Explorer
Cleveland Clinic spin-off - Software-as-a-Service offering… Explore: Search, browse, and define cohorts based on clinically normalized dataset from multiple providers. Compare: Analyze temporal measures between cohorts. Collaborate: Safely connect and share with trust peers and sponsors. Engage: Analyze in-depth HIPAA compliant datasets or recruit across internal or distributed trusted networks.

32 The Explorys Unified Platform
Healthcare Cloud Secure high-speed VPN OLAP Comp Matrix Search Engine Alert Population Exploration Comparative Effectiveness Business Intelligence Pharma- covigilance Open Module Questions:

33 “Not everything that can be counted counts, and not everything that counts can be counted.”
Sign hanging on Albert Einstein’s Princeton University Office Questions? Anil Jain, MD, FACP Cleveland Clinic

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