Diagnostic accuracy of physician review, expert algorithms and data-derived algorithms in adult verbal autopsies.

Journal article

BACKGROUND: The verbal autopsy (VA) is used to collect information on cause-specific mortality from bereaved relatives. A cause of death may be assigned by physician review of the questionnaires, or by an algorithm. We compared the diagnostic accuracy of physician review, an expert algorithm, and data-derived algorithms. METHODS: Data were drawn from a multicentre validation study of 796 adult deaths that occurred in hospitals in Tanzania, Ethiopia, and Ghana. A 'gold standard' cause of death was assigned using hospital records and death certificates. The VA interviews were carried out by trained fieldworkers 1-21 months after the subject's death. A cause of death was assigned by physician review and an expert algorithm. Data-derived algorithms that most accurately estimated the cause-specific mortality fraction (CSMF) for each cause of death were identified using logistic regression. RESULTS: The most common causes of death were tuberculosis/AIDS (CSMF = 18.6%), malaria (CSMF = 10.7%), meningitis (CSMF = 8.3%), and cardiovascular disorders (CSMF = 8.2%). The CSMF obtained using physician review was within +/-20% of the gold standard value for 12 causes of death including the four common causes. The CSMF obtained using the expert algorithm was within +/-20% of the gold standard for eight causes of death, including tuberculosis/AIDS, malaria, and meningitis. The CSMF obtained using the data-derived algorithms was within +/-20% of the gold standard for seven causes of death, including tuberculosis/ AIDS, meningitis, and cardiovascular disorders. All three methods yielded a specificity of at least 80% for all causes of death, and a sensitivity of at least 80% for deaths due to injuries and rabies. CONCLUSIONS: For those settings where physician review is not feasible, expert and data-derived algorithms provide an alternative approach for assigning many causes of death. We recommend that the algorithms proposed herein are validated further.

Authors: Quigley, M; Chandramohan, D; Rodrigues, L

• Publication status: Published
• Journal: International journal of epidemiology
• Volume: 28
• Issue: 6
• Pages: 1081-1087
• Publication date: 1999-12-01
• DOI: 10.1093/ije/28.6.1081
• EISSN: 1464-3685
• ISSN: 0300-5771
• Language: English
• Keywords: Reproducibility of Results; Cause of Death; Meningitis; Algorithms; Middle Aged; Cardiovascular Diseases; Autopsy; Tanzania; Ethiopia; Wounds and Injuries; Ghana; Sensitivity and Specificity; Tuberculosis; Humans; Acquired Immunodeficiency Syndrome; Adult; Malaria