Routine records from hospitals and other health facilities could help fill a persistent gap in measuring maternal mortality, according to researchers from Karolinska Institutet and Tanzania. But the records cannot simply be treated as a ready-made replacement for existing estimates: their completeness and quality must first be assessed and improved.
The work, published in the Bulletin of the World Health Organization, proposes four ways to examine the quality of facility data before it is used as an additional source for maternal mortality estimates. The researchers tested the approach with data from Tanzania and found problems with completeness and quality across all four measures and across the data sources available to them.
Why routine records matter
Maternal mortality covers deaths during pregnancy, childbirth, or the six weeks after pregnancy. Reliable figures are essential for tracking progress in maternal health, yet such estimates remain difficult in many low- and middle-income countries where civil registration and death-recording systems are incomplete or unavailable.
Health facilities represent a potentially valuable source of information. More than 80% of births take place in facilities in about two-thirds of low- and middle-income countries, the researchers note. Hospitals and other facilities already collect information in the course of providing care, creating a large body of routine data that could complement other sources used to estimate maternal deaths.
That potential comes with a major qualification: a death that is not recorded cannot improve an estimate. Underreporting of maternal deaths is a central concern, as are errors and inconsistencies that can distort apparent differences between districts, age groups, or causes of death.
“Health facility data could provide additional information for estimates of maternal mortality, but we first need to understand and improve the completeness and quality of the reporting,” Claudia Hanson, a professor of global health systems research at Karolinska Institutet, said in the source report.
Four checks rather than one score
The proposed framework looks for patterns that may indicate whether a data set is plausible and sufficiently complete for its intended use. It examines reported maternal mortality levels and geographical patterns; the relationship between reported stillbirths and maternal deaths; the distribution of recorded causes of death; and the age distribution of women who died.
These measures are designed to be considered together. A single unusual result may have several explanations, and an apparently reasonable measure in isolation does not establish that the records are complete. The authors caution that the framework is not a universal standard because expected patterns can vary by country and context.
The first measure considers whether reported mortality levels and their geographic distribution look plausible. Large differences can reflect real disparities in access to care or underlying health risks, but they can also point to differences in reporting. The second measure compares stillbirths and maternal deaths, two outcomes that may reveal signs of incomplete recording when their relationship is unexpectedly inconsistent.
The remaining measures focus on the information recorded for deaths. A cause-of-death profile that is implausible or unusually concentrated can signal a data-quality problem. Similarly, the age distribution of women reported to have died can be examined for patterns that warrant closer review.
Tanzania test finds reporting gaps
When the researchers applied the four measures to Tanzanian data, they found concerns in every area assessed. Some districts reported maternal mortality at levels the researchers considered implausibly low. Other patterns suggested that maternal deaths or stillbirths had not always been reported.
The finding does not mean routine health-facility data should be discarded. Instead, it underscores the distinction between data that are available and data that are ready to support national or subnational mortality estimates. Routine records can be an important supplement, but their limitations need to be visible to the people using them.
A practical implication is that data-quality assessment should be part of the measurement process rather than an afterthought. Health ministries, facilities, and researchers may be able to use the proposed measures to identify where reporting needs investigation, training, or system improvements before results are incorporated into wider estimates.
A route to stronger measurement
The study’s contribution is methodological: it offers a structured way to interrogate a source of information that is already collected at scale. In settings where vital registration is incomplete, improving the usefulness of facility records could provide a more timely view of maternal deaths and help reveal where records are weakest.
The authors’ caution is as important as their proposal. The four measures should not be treated as a simple pass-fail test or applied without regard for national circumstances. They are indicators for interpretation alongside one another and alongside knowledge of local health systems.
For maternal health monitoring, the objective is not merely to generate another number. It is to make estimates credible enough to guide action. Routine facility data may become a meaningful part of that effort, the researchers argue, if reporting systems are strengthened and the quality of their records is tested openly.
This article is based on reporting by Medical Xpress. Read the original article.
Originally published on medicalxpress.com
