title: Three cost-utility analyses of screening for intracranial hemorrhage in neonates with hemophilia.
abstract: BACKGROUND
  Intracranial hemorrhage (ICH) in the newborn period is a potential cause of serious morbidity and mortality in individuals with hemophilia. The incidence of ICH is estimated to be 2% to 4%; however, depending on the mode of delivery, it may be considerably higher. Considering the varying sensitivities and costs of various imaging modalities, there remains controversy surrounding universal cranial imaging. Cost-utility analysis is the ideal tool to display the consequences of a decision made.
  
  
  METHODS
  We constructed a decision tree to evaluate the direct and indirect costs, possible outcomes, and probabilities of ICH in neonates with hemophilia. We created 3 decision analysis models to evaluate the cost-utility of different screening modalities for ICH: ultrasound, computed tomography, and magnetic resonance imaging. Within each model, 3 different strategies were compared: screen all neonates; screen only neonates born by instrumented delivery; and not screen any neonates. A societal perspective was used for all models. The base case models were later reanalyzed in sensitivity analysis to account for uncertainties.
  
  
  RESULTS
  Total costs for screening all neonates, screening only neonates born by instrumented delivery, and not screening any neonates were $9501, $9297, and $9347, respectively, for US, and $9761, $9351, and $9353, respectively, for CT. Screening instrumented deliveries using MRI had an incremental cost-effectiveness ratio of $12,440.
  
  
  CONCLUSIONS
  Screening newborns born by an instrumented delivery appears to be the most cost-effective strategy irrespective of the imaging modality. Subsequent studies will require a longer time frame to factor in possible late effects of radiation, anesthesia, and the high cost of factor replacement and hospital admission.
authors: *Department of Pediatrics, Division of Hematology/Oncology, Children's Hospital of Pittsburgh of UPMC ‡Section of Decision Sciences and Clinical Decisions Modeling, Department of Medicine, University of Pittsburgh, Pittsburgh, PA †Department of Pediatrics, Division of Hematology/Oncology, Vanderbilt University Medical Center, Nashville, TN.
authors: Lynn M
authors: LM
authors: Malec
authors: Robert F
authors: RF
authors: Sidonio
authors: Kenneth J
authors: KJ
authors: Smith
authors: James D
authors: JD
authors: Cooper
mesh_terms: D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D003663:Decision Trees; D005102:Health Expenditures; D006467:Hemophilia A / Q000175:diagnosis* / Q000191:economics* / Q000453:epidemiology; D006801:Humans; D007231:Infant, Newborn; D020300:Intracranial Hemorrhages / Q000175:diagnosis* / Q000191:economics* / Q000453:epidemiology; D008279:Magnetic Resonance Imaging / Q000191:economics / Q000706:statistics & numerical data; D015997:Neonatal Screening / Q000191:economics* / Q000706:statistics & numerical data*; D015995:Prevalence; D011788:Quality of Life; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000191:economics / Q000706:statistics & numerical data; D014463:Ultrasonography / Q000191:economics / Q000706:statistics & numerical data; D035501:Uncertainty