Improving Administrative Data for Public Reporting

1
Improving Administrative Data for Public
Reporting

• Anne Elixhauser
• Joe Parker
• Michael Pine
• Roxanne Andrews
• September 9, 2008

2
Outline

• Background and rationale
• Summary of two prior studies
• Potential safety events present on admission?
• Adding clinical information to administrative
  data
• Problems in POA coding California example
• Screens for detecting these problems
• Supporting the enhancement of administrative
  claims data through state pilots

3
Administrative, or Billing Data

• Patient demographics (age, sex)
• Diagnoses procedures
• (ICD-9-CM, DRG)
• Expected payer
• Length of stay
• Patient disposition
• Admission source type
• Admission month
• Charges

UB-92 (UB-04) Billing Form
4
12 States Use AHRQ QIs for Hospital Reporting to
the Public
Oregon
Wisconsin (part of state)
Vermont
New York
Massachusetts
Iowa
Ohio
Utah
Colorado
Kentucky
Texas
Florida
5
Limitations of Administrative Data

• Lack clinically important information
• Limited to ICD-9-CM diagnosis codes
• Do not distinguish between diagnoses present on
  admission (POA) and those that originate during
  the hospital stay
• Questions regarding use of only administrative
  data for hospital-specific reporting
• Inadequate risk adjustment additional data
  needed to predict individual patients risk of
  mortality
• Concern about penalizing providers with the
  sickest patients

6
Tension Between Value of Data and Cost of
Obtaining the Data

• New York and California provide POA coding for
  diagnoses now required for Medicare patients
  and many states will collect for all
• Pennsylvania hospitals provided chart-abstracted
  clinical detail
• Hospital concern about costs of medical record
  abstraction
• Electronic medical records not yet poised to
  provide data efficiently
• Exception Lab data

7
How Often are Potential Patient Safety Events
Present on Admission?

• Study aimed at using POA information to determine
  what effect it will have on AHRQ Patient Safety
  Indicators
• Examined face validity of POA coding in two
  states California (CA) and New York (NY)
• Study reported in
• Houchens R, Elixhauser A, Romano P. How often are
  potential patient safety events present on
  admission? Joint Commission Journal on Quality
  and Patient Safety. March 2008.

8
Percent of patient safety events remaining after
POA diagnoses were removed
Based on California data.
9
Impact of Adding Clinical Data to Administrative
Data

• Assess impact of incrementally adding
• POA codes for diagnoses
• Lab values on admission
• Increased number of diagnosis fields
• Improved documentation (ICD-9-CM codes)
• Vital signs
• More difficult to obtain clinical data

10
Study Reported in

• Pine M, Jordan HS, Elixhauser A, et al.
  Enhancement of claims data to improve risk
  adjustment of hospital mortality. JAMA 2007
  267(1)71-76.
• Jordan HS, Pine M, Elixhauser A, et al.
  Cost-effective enhancement of claims data to
  improve comparisons of patient safety. Journal
  of Patient Safety 2007 3(2) 82-90.
• Fry DR, Pine M, Jordan HS, et al. Combining
  administrative and clinical data to stratify
  surgical risk. Annals of Surgery 2007 246(5)
  875-885.
• Pine M, Jordan HS, Elixhauser A, et al. Modifying
  claims data to improve risk-adjustment of
  inpatient mortality rates. Medical Decision
  Making (forthcoming)

11
Indicators Studied

• Mortality
• Indicators
• AAA repair
• CABG surgery
• Craniotomy
• AMI
• CHF
• Cerebrovascular accident
• GI hemorrhage
• Pneumonia

• Post-operative patient
• safety events
• Pulmonary embolism/deep vein thrombosis
• Physiologic/metabolic abnormalities
• Respiratory failure
• Sepsis

12
Data Used in Incrementally More Complex Models
13
C-Statistics for Mortality Models
14
Numerical Lab Data

• Results of 22 lab tests entered at least one
  model
• Results of 14 of these tests entered four or
  more models

• pH (11)
• PTT (10)
• Na (9)
• WBC (9)
• BUN (8)
• pO2 (8)
• K (7)

• SGOT (7)
• Platelets (7)
• Albumin (5)
• pCO2 (4)
• Glucose (4)
• Creatinine (4)
• CPK-MB (4)

15
Vital Signs and Other Clinical Data

• All vital signs entered four or more models
• Pulse (8)
• Temp (6)
• Blood pressure (6)
• Respirations (5)
• Ejection fraction and culture results entered two
  models
• Composite scores entered four or more models
• ASA classification (6)
• Glasgow Coma Score (4)

16
Abstracted Key Clinical Findings

• 35 clinical findings entered at least one model
• Only three findings entered more than two models
• Coma (6)
• Severe malnutrition (4)
• Immunosuppressed (4)
• 14 of these clinical findings have corresponding
  ICD-9-CM codes (e.g., coma, malnutrition)

17
Summary of Analyses

• For some measures, POA coding has a significant
  impact on whether conditions are considered
  patient safety events
• Administrative data can be improved at relatively
  low cost by
• Adding POA modifiers
• Adding numerical lab data on admission
• Improved ICD coding

18
Other Enhancements

• Link to vital statistics
• Link across settings
• Readmissions
• Episodes of care
• Todays focus POA and lab data