title: The costs and benefits of automatic estimated glomerular filtration rate reporting.
abstract: OBJECTIVE
  The prevalence of chronic kidney disease (CKD) has increased over the past two decades. The sensitivity of serum creatinine (sCr) to identify CKD is low. As a result, many healthcare centers report estimated GFR (eGFR) with routine blood work. The aim of this study was to determine the cost-effectiveness of automatic eGFR reporting compared with reporting sCr alone.
  
  
  METHODS
  A Markov model was designed to evaluate the cost-effectiveness of reporting eGFR compared with reporting sCr alone in a hypothetical cohort of 60-yr-old individuals undergoing annual blood chemistry testing over 18 yr. Paths and path probabilities were identical between the two arms, except for the sensitivity and specificity of eGFR and sCr to detect CKD.
  
  
  RESULTS
  eGFR reporting was dominant with a cost/effectiveness ratio of $16,751/quality-adjusted life year (QALY) versus $16,779/QALY for sCr reporting. Monte Carlo microsimulations in a hypothetical cohort of 10,000 patients demonstrated that over 18 yr, an average of 13 fewer deaths, 29 fewer ESRD events, and 11,348 more false positive CKD (FP-CKD) cases occurred with eGFR reporting. A sensitivity analysis revealed that decreasing the FP-CKD quality of life by > 2% rendered sCr reporting more cost-effective than eGFR reporting. If FP-CKD reduced quality of life by 5%, the incremental cost-effectiveness ratio for sCr reporting versus eGFR reporting would be $4367/QALY.
  
  
  CONCLUSIONS
  A decision analysis suggests that reporting eGFR may be beneficial, but this limited benefit was reversed with virtually any reduction in quality of life caused by incorrect diagnosis of CKD.
authors.affiliation: Internal Medicine, University of Virginia Health System, Charlottesville, Virginia, USA.
authors.forename: Julia R
authors.initials: JR
authors.lastname: den Hartog
authors.forename: Peter P
authors.initials: PP
authors.lastname: Reese
authors.forename: Borut
authors.initials: B
authors.lastname: Cizman
authors.forename: Harold I
authors.initials: HI
authors.lastname: Feldman
mesh_terms: D002908:Chronic Disease; D003198:Computer Simulation; D003362:Cost-Benefit Analysis; D003404:Creatinine / Q000097:blood*; D003661:Decision Support Techniques; D018450:Disease Progression; D005189:False Positive Reactions; D005919:Glomerular Filtration Rate; D006801:Humans; D007674:Kidney Diseases / Q000150:complications / Q000175:diagnosis* / Q000191:economics / Q000401:mortality; D007676:Kidney Failure, Chronic / Q000191:economics / Q000209:etiology* / Q000401:mortality; D007677:Kidney Function Tests / Q000191:economics*; D037141:Mandatory Programs / Q000191:economics*; D019221:Mandatory Reporting; D008390:Markov Chains; D008875:Middle Aged; D018803:Models, Economic; D009010:Monte Carlo Method; D011237:Predictive Value of Tests; D015397:Program Evaluation; D019057:Quality-Adjusted Life Years; D012680:Sensitivity and Specificity
chemical_list: D003404:Creatinine