Developing Interoperable EHR: Maximizing Quality of Care

1
Developing Interoperable EHRMaximizing 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

• Veterans 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
EHRs and the Evidence Base

• 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

4
6
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-Sponsor
ed 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
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
Govt Policy
16

• THANK YOU
• Gregory Downing
• gregory.downing_at_hhs.gov