Exploring the role narrative free-text plays in discrepancies between physician coding and the InterVA regarding determination of malaria as cause of death, in a malaria holo-endemic region

• Verfasst von: Rankin, Johanna C. [VerfasserIn]
• Verfasst von: Lorenz, Eva [VerfasserIn]
• Verfasst von: Neuhann, Florian [VerfasserIn]
• Verfasst von: Yé, Maurice [VerfasserIn]
• Verfasst von: Sié, Ali [VerfasserIn]
• Verfasst von: Becher, Heiko [VerfasserIn]
• Verfasst von: Ramroth, Heribert [VerfasserIn]
• Titel: Exploring the role narrative free-text plays in discrepancies between physician coding and the InterVA regarding determination of malaria as cause of death, in a malaria holo-endemic region
• Verf.angabe: Johanna C. Rankin, Eva Lorenz, Florian Neuhann, Maurice Yé, Ali Sié, Heiko Becher and Heribert Ramroth
• E-Jahr: 2012
• Jahr: [21 February 2012]
• Umfang: 9 S.
• Fussnoten: Gesehen am 14.11.2018
• Titel Quelle: Enthalten in: Malaria journal
• Ort Quelle: London : BioMed Central, 2002
• Jahr Quelle: 2012
• Band/Heft Quelle: 11(2012), Artikel-ID 51
• ISSN Quelle: 1475-2875
• DOI: doi:10.1186/1475-2875-11-51
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1583720219

Abstract

In countries where tracking mortality and clinical cause of death are not routinely undertaken, gathering verbal autopsies (VA) is the principal method of estimating cause of death. The most common method for determining probable cause of death from the VA interview is Physician-Certified Verbal Autopsy (PCVA). A recent alternative method to interpret Verbal Autopsy (InterVA) is a computer model using a Bayesian approach to derive posterior probabilities for causes of death, given an a priori distribution at population level and a set of interview-based indicators. The model uses the same input information as PCVA, with the exception of narrative text information, which physicians can consult but which were not inputted into the model. Comparing the results of physician coding with the model, large differences could be due to difficulties in diagnosing malaria, especially in holo-endemic regions. Thus, the aim of the study was to explore whether physicians' access to electronically unavailable narrative text helps to explain the large discrepancy in malaria cause-specific mortality fractions (CSMFs) in physician coding versus the model.