title: Challenges and benefits of adding laboratory data to a mortality risk adjustment method.
abstract: BACKGROUND
  There is increased interest in improving the clinical acceptance and statistical performance of hospital mortality rate comparisons. This study assessed the feasibility of linking separate electronic feeds of laboratory data and claims-based information and, if successful, to identify laboratory data elements that significantly improved mortality rate predictions for All-Patient Refined Diagnosis Related Groups (APRDRGs), a risk of mortality (ROM) classification tool in regular use for public reporting purposes.
  
  
  METHODS
  The Florida Agency for Health Care Administration recruited 15 hospitals to supply computerized administrative and laboratory information that could be linked at the patient level. The hospitals, standardized computer code terminology, which was then merged with administrative data. We evaluated the ability of the merged data to improve APRDRG ROM predictions.
  
  
  RESULTS
  We describe the procedures that the laboratory information systems used to link the electronic laboratory data with standard claims data. The addition of 11 clinical laboratory test results increased the C statistic by 0.574% and R2 by 4.53%.
  
  
  CONCLUSIONS
  This study supports the feasibility of linking laboratory data elements with claims-based administrative data to enhance ROM assessments. This linkage resulted in modest statistical improvement in a commonly used ROM model.
authors.affiliation: 3M Health Information Systems, Inc, Wallingford, Connecticut 06492, USA.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: McCullough
authors.forename: Christopher
authors.initials: C
authors.lastname: Sullivan
authors.forename: Pamela
authors.initials: P
authors.lastname: Banning
authors.forename: Norbert
authors.initials: N
authors.lastname: Goldfield
authors.forename: John
authors.initials: J
authors.lastname: Hughes
mesh_terms: D002984:Clinical Laboratory Information Systems / Q000458:organization & administration; D003953:Diagnosis-Related Groups / Q000458:organization & administration; D005431:Florida; D017052:Hospital Mortality; D006801:Humans; D007256:Information Systems / Q000458:organization & administration*; D007345:Insurance Claim Review / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D012307:Risk Factors