Using Administrative Data for Monitoring and Improvement

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Using Administrative Data for Monitoring and
Improvement

• Irene Fraser, Ph.D.
• Director, Center for Delivery, Org. and Markets
• Presentation to
• AcademyHealth
• June 8, 2004

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Role of Data in Improvement

• Opportunity
• You cant improve what you cant measure
• Challenge
• Need national benchmarks
• But all improvement is local
• Improvement requires
• Rich data tools partnership strategy

3
Hospitals Are a Good Place to Start

• Are a third of total national health expenditures
• CMS, Office of the Actuary
• Represent more than half of increase in health
  care spending
• - Health Affairs, 2002
• Have documented patient safety and quality issues
• Show big variation by state, market, payer

4
Administrative vs. Clinical Data

• Administrative data
• Widely available
• Inexpensive
• Standardized codes
• Already used by org.
• BUT
• Lacks clinical detail
• Only as strong as the coding
• Can have data validity issues

• Clinical data
• Greater clinical detail
• BUT
• of extraction
• Access can be challenge
• Also hard to assure comparability

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Using Provider Data to Improve Quality Formula
for Data Value

• Use data thats already there
• Partner with those who have it and know it
• Develop measures and benchmarks
• Turn data into information quickly
• Put it into form audience can use
• Enable improvement at multiple levels
• Nation
• State
• Market or community
• Provider

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The Healthcare Cost and Utilization Project
(HCUP)

• Federal, state, industry partnership
• Has 90 of all inpatient discharges
• Growing to include ED, ambulatory surgery, other
• Includes charge, payer, clinical data
• Extensive use by researchers and policy-makers
• New methodology converts charges to cost
• Friedman, Journal of Health Care Finance, 2002
• Quality Indicators Usable with any discharge data

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AHRQ Quality Indicators (QIs)

• Provide indicators of quality, not necessarily
  definitive measures
• Developed through contract with UCSF-Stanford
  Evidence-based Practice Center
• Use existing hospital discharge data, based on
  readily available data elements
• Incorporate severity adjustment methods
  (APR-DRGs, comorbidity groupings)
• Current modules Prevention QIs, Inpatient QIs,
  and Patient Safety Indicators

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Overview of AHRQ QIs

• Prevention Quality
• Indicators
• Inpatient Quality Indicators
• Patient Safety Indicators

• Ambulatory care sensitive
• conditions
• Mortality following procedures
• Mortality for medical conditions
• Utilization of procedures
• Volume of procedures
• Post-operative complications
• Iatrogenic conditions

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National Uses National Healthcare Quality and
Disparities Reports

• Annual Reports mandated by Congress on quality of
  health care in the nation
• Goals
• Provide national benchmarks using standardized
  measures
• Monitor progress over time
• Identify areas for improvement
• Help act as a catalyst for action

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National Uses Measuring Cost of Medical
Injuries

• Postoperative blood stream infections
• Adds 11 days, 58,000 to each stay
• Increases risk of death 21.9 percent
• Causes 3,000 deaths a year
• Reopening of surgical incisions
• Adds 9.4 days, 40,000 to each stay
• Increases risk of death 9.6
• Causes 405 deaths a year
• Zhan, JAMA 2003

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National Uses Tracking Cost of Potentially
Preventable Admissions

• National Cost 29 billion
• Diabetes 2.5 billion
• Short-term complications
• Long-term complications
• Uncontrolled diabetes

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National Uses MedPAC Report to Congress on
Medicare Quality

• Findings from 1995-2002
• Hospital mortality associated w/ various
  diagnoses/procedures (e.g., pneumonia, CABG,
  stroke) decreased
• Rate of various adverse events increased
  including decubitis ulcer, accidental puncture,
  post-op respiratory failure and post-op sepsis
• Rate of potentially avoidable hospital admissions
  decreased for some conditions (e.g., adult
  asthma, uncontrolled diabetes), increased for
  others (e.g., hypertension, diabetes long-term
  complication)
• Source MedPAC testimony to Health Committee on
  Ways and Means, March 18, 2004 MedPAC Report to
  the Congress Medicare Payment Policy, March
  2004).

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State and Community Uses of PQIs for Quality
Improvement

• Look at potentially preventable admissions
• Variation by county/community in the state
• Changes over time
• Variations by population subgroups
• Compare to national figures on HCUPnet
• Do targeted interventions
• Track impact

15
AHRQ Prevention Quality Indicator Diabetes
Short-Term Complication Admission Rate (PQI 1)
Data Source Healthcare Cost and Utilization
Project (HCUP), Michigan State Inpatient Database
(SID), 2002
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Variation in Admission Rates in North Texas for
Prevention Quality Indicator
Diabetes - Long Term Complications
Admissions per 100,000 Population -- County of
Patient Residence
Texas
September 26, 2002 Draft Report
Dallas-Fort Worth Hospital Council -- Data
Initiative -- 2000 Hospital Discharge Data
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States With Inpatient Databases, 2002
VT
MT
ND
MN
NH
ID
SD
WY
RI
NE
NV
OH
IN
WV
KY
DC
NC
AR
OK
NM
AL
MS
TX
LA
AK
Key
HCUP partner
Data, not in HCUP
HI
No inpatient data
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States with MEDPAR Data
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Current Activities to Strengthen Quality
Indicators

• Provide national, state other benchmarks
• Provide customization and TA to users
• Do additional validation studies
• Provide guidance for new uses (reporting/ P4P)
• Expand indicators, e.g. for children
• Evaluate need for expanded datasets to include
• State-specific innovations (onset of diagnosis)
• Ability to link data across hospital stays,
  outpatient settings
• More clinical information

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For More Information on AHRQ QIs

• Quality Indicators Additional information and
  assistance
• E-mail support_at_qualityindicators.ahrq.gov
• Website http//qualityindicators.ahrq.gov/
• QI documentation and software is available on the
  website
• Support Phone [phone] (voice mail)
• Dr. Denise Remus, e-mail dremus_at_ahrq.gov, phone
  [phone]

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Home Pagehttp//www.AHRQ.gov

• Center for Delivery, Org. Markets
• http//www.AHRQ.gov/about/cods
• Irene Fraser ifraser_at_ahrq.gov