Using verbal autopsy to ascertain perinatal cause of death: are trained non-physicians adequate?
- PMID: 19799757
- PMCID: PMC3959775
- DOI: 10.1111/j.1365-3156.2009.02395.x
Using verbal autopsy to ascertain perinatal cause of death: are trained non-physicians adequate?
Abstract
Objectives: To develop a standardized verbal autopsy (VA) training program and evaluate whether its implementation resulted in comparable knowledge required to classify perinatal cause of death (COD) by physicians and non-physicians.
Methods: Training materials, case studies, and written and mock scenarios for this VA program were developed using conventional VA and ICD-10 guidelines. This program was used to instruct physicians and non-physicians in VA methodology using a train-the-trainer model. Written tests of cognitive and applied knowledge required to classify perinatal COD were administered before and after training to evaluate the effect of the VA training program.
Results: Fifty-three physicians and non-physicians (nurse-midwives/nurses and Community Health Workers [CHW]) from Pakistan, Zambia, the Democratic Republic of Congo, and Guatemala were trained. Cognitive and applied knowledge mean scores among all trainees improved significantly (12.8 and 28.8% respectively, P < 0.001). Cognitive and applied knowledge post-training test scores of nurse-midwives/nurses were comparable to those of physicians. CHW (high-school graduates with 15 months or less formal health/nursing training) had the largest improvements in post-training applied knowledge with scores comparable to those of physicians and nurse-midwives/nurses. However, CHW cognitive knowledge post-training scores were significantly lower than those of physicians and nurses.
Conclusions: With appropriate training in VA, cognitive and applied knowledge required to determine perinatal COD is similar for physicians and nurses-midwives/nurses. This suggests that midwives and nurses may play a useful role in determining COD at the community level, which may be a practical way to improve the accuracy of COD data in rural, remote, geographic areas.
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