title: Refining a probabilistic model for interpreting verbal autopsy data.
abstract: OBJECTIVE
  To build on the previously reported development of a Bayesian probabilistic model for interpreting verbal autopsy (VA) data, attempting to improve the model's performance in determining cause of death and to reassess it.
  
  
  METHODS
  An expert group of clinicians, coming from a wide range geographically and in terms of specialization, was convened. Over a four-day period the content of the previous probabilistic model was reviewed in detail and adjusted as necessary to reflect the group consensus. The revised model was tested with the same 189 VA cases from Vietnam, assessed by two local clinicians, that were used to test the preliminary model.
  
  
  RESULTS
  The revised model contained a total of 104 indicators that could be derived from VA data and 34 possible causes of death. When applied to the 189 Vietnamese cases, 142 (75.1%) achieved concordance between the model's output and the previous clinical consensus. The remaining 47 cases (24.9%) were presented to a further independent clinician for reassessment. As a result, consensus between clinical reassessment and the model's output was achieved in 28 cases (14.8%); clinical reassessment and the original clinical opinion agreed in 8 cases (4.2%), and in the remaining 11 cases (5.8%) clinical reassessment, the model, and the original clinical opinion all differed. Thus overall the model was considered to have performed well in 170 cases (89.9%).
  
  
  CONCLUSIONS
  This approach to interpreting VA data continues to show promise. The next steps will be to evaluate it against other sources of VA data. The expert group approach to determining the required probability base seems to have been a productive one in improving the performance of the model.
authors.affiliation: Umeå International School of Public Health, Umeå University, Umeå, Sweden. peterbyass@aol.com
authors.forename: Peter
authors.initials: P
authors.lastname: Byass
authors.forename: Edward
authors.initials: E
authors.lastname: Fottrell
authors.forename: Lan Huong
authors.initials: LH
authors.lastname: Dao
authors.forename: Yemane
authors.initials: Y
authors.lastname: Berhane
authors.forename: Tumani
authors.initials: T
authors.lastname: Corrah
authors.forename: Kathleen
authors.initials: K
authors.lastname: Kahn
authors.forename: Lulu
authors.initials: L
authors.lastname: Muhe
authors.forename: Duc Van
authors.initials: DV
authors.lastname: Do
mesh_terms: D001344:Autopsy / Q000379:methods; D001499:Bayes Theorem; D002423:Cause of Death; D003334:Coroners and Medical Examiners; D003625:Data Collection / Q000379:methods; D003627:Data Interpretation, Statistical; D003906:Developing Countries; D006801:Humans; D015233:Models, Statistical; D015203:Reproducibility of Results; D013060:Speech; D014744:Vietnam