Developing Interoperable EHR: Maximizing Quality of Care

1. Developing Interoperable EHR:Maximizing Quality of Care Gregory J Downing, DO, PhD Office of the Secretary Department of Health and Human Services July 13th, 2009

2. What Does an Interoperable EHR Provide? • Information Sharing • Continuity of Care • Privacy • Evidence Base • Clinical Decision Support (CDS) Platform • Effectiveness Assessment • Quality Measures • Regional vs. Nation-wide • Public Health • FDA Sentinel • Adverse event reporting and safety alerts • CDC • Biosurveillance and safety alerts A Learning Health Care System Etheredge LM. A Rapid-Learning Health SystemHealth Affairs, 2007

3. Model EHR Deployment for Information Management • Veteran’s Affairs and Indian Health Service • VistA (Veterans Health Information System and Technology Architecture) • Private sector healthcare systems • Kaiser Permanente • Geisinger • Harvard Partners • National Health Information Network (NHIN) • Regional Health Information Organization (RHIO) • Health Information Exchange (HIE) • Distributed Ambulatory Research in Therapeutics Network (DARTNet) • AHRQ and American Academy of Family Physicians • SOA Platforms (e.g. MS HealthVault, GoogleHealth, Dossia) 2

4. Can Information Management Improve Quality of Care? • Current ability to measure and compare health care quality • How much medical practice is actually evidence-based? • Numbers vary greatly on geography and specialty • Range from 10-80% • Policies about evidence development • The Medicare Evidence Development & Coverage Advisory Committee (MEDCAC) was established to provide independent guidance and expert advice to CMS on specific clinical topics. 3

5. EHR data can be used for research to develop evidence-based guidelines Guidelines can be supplied to the clinician at the appropriate time through clinical decision support (CDS) Quality of care can be measured through improved health outcomes EHRs and the Evidence Base 4

6. EHR-Provided Data EHR Data for Evidence-Based Medicine • US Preventive Services Task Force: • Level I: Evidence obtained from at least one properly designed randomized controlled trial. • Level II-1: Evidence obtained from well-designed controlled trials without randomization. • Level II-2: Evidence obtained from well-designed cohort or case-control analytic studies, preferably from more than one center or research group. • Level II-3: Evidence obtained from multiple time series with or without the intervention. Dramatic results in uncontrolled trials might also be regarded as this type of evidence. • Level III: Opinions of respected authorities, based on clinical experience, descriptive studies, or reports of expert committees.

7. Developing and Evidence-Base with EHR Data Basic Clinical Research Investigator-Sponsored Data Acquisition, Analysis Insurance Claims Shared Information Publications Healthcare Delivery Patient Information Guideline Development Academia, Government Biopharmaceutical -Sponsored Data Acquisition, Analysis Protocol-driven Clinical Trials Regulatory Reviews With permission: Kush, R; CDISC; 2009

8. EHR Clinical Research Value/Use Case • ANSI convened an EHR Clinical Research Value Case Workgroup for prioritization of clinical research use cases. • Core Research Data Element Exchange • Identify core research data elements • Identify processes for transacting these data appropriately • EHR Ability to Provide Data for Guideline Development and Quality Measurement • Establishes standards for interoperability • Enables information exchange

9. Comparative Effectiveness • Accelerate the development and dissemination of research assessing the comparative effectiveness of health care treatments and strategies, through efforts that: • conduct, support, or synthesize research that compares the clinical outcomes, effectiveness, and appropriateness of items, services, and procedures that are used to prevent, diagnose, or treat diseases, disorders, and other health conditions; and • encourage the development and use of clinical registries, clinical data networks, and other forms of electronic health data that can be used to generate or obtain outcomes data • AHRQ - $700M • NIH OD - $400M • HHS - $400M • EHRs support comparative effectiveness research as a source of aggregated data on interventions and outcomes 8

10. CDS Roadmap Osheroff et al., 2006 JAMIA Clinical Decision Support • EHRs provide a platform for clinical decision support to promote adherence to evolving evidence-based guidelines. • Clinical Decision Support (CDS) • computerized alerts and reminders • clinical guidelines • order sets • patient data reports and dashboards • documentation templates • diagnostic support • clinical workflow tools • Three pillars of CDS • Best knowledge available when needed • High adoption and effective use • Continuous improvement of knowledge and CDS methods • CCHIT certification for CDS 9

11. Translation of Guidelines into Executable Actions www.intracarecorporation.com

12. IHS Resource and Patient Management System http://www.ihs.gov/CIO/EHR/

13. IHS RPMS – Patient Record

14. IHS RPMS iCARE – Population Management Tool

15. Challenges of Planning in Times of Uncertainty • Technology – massive deployment across diffuse networks and systems in widely diverse platforms and states of readiness • Diverse users with widely variable skill sets and workflows • clinicians, nurses, PA • primary care, specialty care • Variability of evidence base, multiple guidelines • conversion of machine and human readable information into executable actions • Moving target of reimbursement models for patient care • Incentives for physician and health system EHR adoption • Performance-based practice measures • Application of EHRs in measures of quality performance IT Human Factors Gov’t Policy

16. THANK YOU Gregory Downing gregory.downing@hhs.gov