title: How much do the physician review and InterVA model agree in determining causes of death? A comparative analysis of deaths in rural Ethiopia.
abstract: BACKGROUND
  Despite it is costly, slow and non-reproducible process, physician review (PR) is a commonly used method to interpret verbal autopsy data. However, there is a growing interest to adapt a new automated and internally consistent method called InterVA. This study evaluated the level of agreement in determining causes of death between PR and the InterVA model.
  
  
  METHODS
  Verbal autopsy data for 434 cases collected between September 2009 and November 2012, were interpreted using both PR and the InterVA model. Cohen's kappa statistic (κ) was used to compare the level of chance corrected case-by-case agreement in the diagnosis reached by the PR and InterVA model.
  
  
  RESULTS
  Both methods gave comparable cause specific mortality fractions of communicable diseases (36.6% by PR and 36.2% by the model), non-communicable diseases (31.1% by PR and 38.2% by the model) and accidents/injuries (12.9% by PR and 10.1% by the model). The level of case-by-case chance corrected concordance between the two methods was 0.33 (95% CI for κ = 0.29-0.34). The highest and lowest agreements were seen for accidents/injuries and non-communicable diseases; with κ = 0.75 and κ = 0.37, respectively.
  
  
  CONCLUSIONS
  If the InterVA were used in place of the existing PR process, the overall diagnosis would be fairly similar. The methods had better agreement in important public health diseases like; TB, perinatal causes, and pneumonia/sepsis; and lower in cardiovascular diseases and neoplasms. Therefore, both methods need to be validated against a gold-standard diagnosis of death.
authors.affiliation: Department of Public Health, Mekelle University, Mekelle, Ethiopia. berheph@gmail.com.|Centre of Cardiovascular Research and Education in Therapeutics, Department of Epidemiology and Preventive Medicine, Monash University, 99 Commercial Road, Melbourne, VIC, 3004, Australia. berheph@gmail.com.
authors.forename: Berhe
authors.initials: B
authors.lastname: Weldearegawi
authors.affiliation: Department of Public Health, Mekelle University, Mekelle, Ethiopia. adamayohannes@gmail.com.
authors.forename: Yohannes Adama
authors.initials: YA
authors.lastname: Melaku
authors.affiliation: CAPHRI, School for Public Health and Primary Care, Maastricht University, Maastricht, Netherlands. geertjan.dinant@maastrichtuniversity.nl.
authors.forename: Geert Jan
authors.initials: GJ
authors.lastname: Dinant
authors.affiliation: Department of Public Health, Mekelle University, Mekelle, Ethiopia. m.spigt@maastrichtuniversity.nl.|CAPHRI, School for Public Health and Primary Care, Maastricht University, Maastricht, Netherlands. m.spigt@maastrichtuniversity.nl.
authors.forename: Mark
authors.initials: M
authors.lastname: Spigt
mesh_terms: D000059:Accidents / Q000401:mortality; D001344:Autopsy / Q000379:methods*; D002423:Cause of Death; D002908:Chronic Disease / Q000401:mortality; D003141:Communicable Diseases / Q000401:mortality; D005002:Ethiopia / Q000453:epidemiology; D006301:Health Services Needs and Demand; D006801:Humans; D015233:Models, Statistical; D010820:Physicians; D011336:Probability; D011634:Public Health / Q000379:methods; D015203:Reproducibility of Results; D012107:Research Design; D012424:Rural Population; D014947:Wounds and Injuries / Q000401:mortality