title: Xpert®MTB/RIF for the Diagnosis of Tuberculosis in a Remote Arctic Setting: Impact on Cost and Time to Treatment Initiation.
abstract: BACKGROUND
  Tuberculosis (TB) remains a significant health problem in the Canadian Arctic. Substantial health system delays in TB diagnosis can occur, in part due to the lack of capacity for onsite microbiologic testing. A study recently evaluated the yield and impact of a rapid automated PCR test (Xpert®MTB/RIF) for the diagnosis of TB in Iqaluit (Nunavut). We conducted an economic analysis to evaluate the expected cost relative to the expected reduction in time to treatment initiation, with the addition of Xpert®MTB/RIF to the current diagnostic and treatment algorithms used in this setting.
  
  
  METHODS
  A decision analysis model compared current microbiologic testing to a scenario where Xpert®MTB/RIF was added to the current diagnostic algorithm for active TB, and incorporated costs and clinical endpoints from the Iqaluit study. Several sensitivity analyses that considered alternative use were also considered. We estimated days to TB diagnosis and treatment initiation, health system costs, and the incremental cost per treatment day gained for each individual evaluated for possible TB.
  
  
  RESULTS
  With the addition of Xpert®MTB/RIF, costs increased while days to TB treatment initiation were reduced. The incremental cost per treatment day gained (per individual investigated for TB) was $164 (95% uncertainty range $85, $452). In a sensitivity analysis that considered hospital discharge after a single negative Xpert®MTB/RIF, the Xpert®MTB/RIF scenario was cost saving.
  
  
  CONCLUSIONS
  Adding Xpert®MTB/RIF to the current diagnostic algorithm for TB in Nunavut appears to reduce time to diagnosis and treatment at reasonable cost. It may be especially well suited to overcome some of the other logistical barriers that are unique to this and other remote communities.
authors.affiliation: Respiratory Epidemiology and Clinical Research Unit, Department of Epidemiology, McGill University, Montreal, QC, Canada.|McGill International Tuberculosis Centre, McGill University, Montreal, QC, Canada.
authors.forename: Olivia
authors.initials: O
authors.lastname: Oxlade
authors.affiliation: Respiratory Epidemiology and Clinical Research Unit, Department of Epidemiology, McGill University, Montreal, QC, Canada.
authors.forename: Jordan
authors.initials: J
authors.lastname: Sugarman
authors.affiliation: Clinical Epidemiology, The Ottawa Hospital Research Institute, Ottawa, ON, Canada.|Division of Respirology, Department of Medicine, University of Ottawa, Ottawa, ON, Canada.
authors.forename: Gonzalo G
authors.initials: GG
authors.lastname: Alvarez
authors.affiliation: Respiratory Epidemiology and Clinical Research Unit, Department of Epidemiology, McGill University, Montreal, QC, Canada.|McGill International Tuberculosis Centre, McGill University, Montreal, QC, Canada.
authors.forename: Madhukar
authors.initials: M
authors.lastname: Pai
authors.affiliation: Respiratory Epidemiology and Clinical Research Unit, Department of Epidemiology, McGill University, Montreal, QC, Canada.|McGill International Tuberculosis Centre, McGill University, Montreal, QC, Canada.
authors.forename: Kevin
authors.initials: K
authors.lastname: Schwartzman
mesh_terms: D000995:Antitubercular Agents / Q000008:administration & dosage / Q000191:economics / Q000627:therapeutic use*; D001110:Arctic Regions; D017281:Cost of Illness; D006297:Health Services Accessibility; D006801:Humans; D020957:Nunavut; D011336:Probability; D012680:Sensitivity and Specificity; D014376:Tuberculosis / Q000175:diagnosis* / Q000188:drug therapy / Q000191:economics
chemical_list: D000995:Antitubercular Agents