Using HIT to Help Measure Quality

1
Using HIT to (Help) Measure Quality

• James M. Walker, MD, FACP
• CMIO
• Geisinger Health System

2
Agenda

• Geisinger Overview
• Challenges
• Processes used to select metrics
• Lessons Learned

3
Geisinger Overview

• 40 counties (mostly poor, elderly, and
  under-served)
• 4 hospitals 30,000 discharges
• 41 clinic sites, 1.5 M visits
• 2.4 million patients in EHR
• HMO

4
Clinical Information Systems

• Outpatient EHR all docs, all activities
• Inpatient EHR complete 2007
• Patient EHR 87,000 users
• Outreach EHR 250,000 encounters/year
• RHIE 4 M patients, record locator, results
  transmission
• Research EHR benefits, information-optimized
  care processes

5
Challenges

• A welter of (evolving) requirements
• Defining quality internally at least as much as
  externally
• Achieving the minimum number of data elements
  (and definitions) required to
• manage quality internally and
• report to various recipients.

6
Challenges

• A welter of (evolving) requirements
• Un-organized recipients
• Lack of standards

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Lack of Standards

• Lead time
• Topics
• Data elements (with definitions)
• Communications standards
• Operating systems and applications

8
Challenges

• A welter of (evolving) requirements
• Disorganized recipients
• Lack of standards
• Organizational silos
• Fragmented data repositories
• Data capture
• Clinician acceptance

9
Metric-Selection Processes

• Legacy metrics
• Clinical-process optimization

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Clinical-Process Optimization

• Chronic and Acute Care
• Create internal consensus on performance
  standards and metrics.
• Re-design processes to capture structured data
  for metrics.
• Create internal consensus on reports (internal
  and external).

11
Metric-Selection Processes

• Legacy metrics
• Clinical-process optimization
• Literature Review (inpatient)
• Data Standards and Applications Committee

12
Data Standards and Applications Committee

• Define unified reporting needs (internal and
  external).
• Commission necessary database (and
  data-warehouse) changes.
• Coordinate development of information-capture
  prompts and tools.
• Feed needs forward to policymakers.

13
Lessons Learned (internal)

• Prioritize internal and external needs.
• Focus organizational attention
• Multiple voices over time
• The tipping point on the business case
• One organizational set of quality metrics
• Integrate the report, the databases, and the
  capture tools.

14
Lessons Learned (external)

• One national set of quality metrics
• One place to send the one data set
• EHRs designed to prompt for and report the right
  data

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• jmwalker_at_geisinger.edu