Evaluation of the Maternal Death Surveillance System in the Maritime Region, Togo, 2018.

  • Maternal and child health
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Background:
Globally, maternal mortality rates have declined since 1990, but still, 830 women die every day from pregnancy or childbirth related causes that are often preventable. Additionally, 99% of these deaths occur in low and middle in- come countries. However, the mortality measurement remains a critical challenge. For instance, In Togo, maternal deaths are underreported, because of the lack of consistent vital statistics due to limited resources. In 2013, the Maritime region implemented the Maternal Death Surveillance and Response (MDSR) system. The purpose of our study is to assess the MDSR system in the Maritime region.
Methods:
We conducted a cross-sectional study from January to June 2018 for the first evaluation of the MDSR and administered a structured questionnaire to involved public health workers. We reviewed death reporting forms for data quality assessment, entered data using MS Excel and analyzed them with Epi Info 7. In accordance with the 2001 CDC guidelines for evaluating surveillance systems, we assessed the following attributes: data quality, acceptability, simplicity, stability, representativeness, usefulness and Positive Predictive Value (PPV).
Results:
Of 229 public health workers, a total of 156 (68%) participated in the survey. Approximately 65% of respondents agreed on the usefulness of MDSR and 55% on the simplicity. The representativeness of data providers (3 districts out of 7) was low. For 49% of respondents, the system is binding, 8% did not comment on this aspect, while 43% believed it is not binding; this finding indicates a low acceptability. Data completeness varies from 41.6% to 68% per form; important variables were more concerned with missing answers. In 2017, 37 maternal deaths were reported a high positive predictive (100%) compared to the records of the hospitals.
Conclusion
This study reveals several weaknesses in the MDSR system in the Maritime region: data quality, representativeness and acceptability are not good. Decision-makers must put the necessary resources in place to provide training for health workers, monitoring and supervision. Furthermore, setting up a motivation system would be beneficial for the system.

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