Background: Complete and timely health information is essential to inform public health decision-making for maternal and child health, but is often lacking in resource-constrained settings. Electronic medical record (EMR) systems are increasingly being adopted to support the delivery of health care, and are particularly amenable to maternal and child health services. An EMR system could enable the mother and child to be tracked and monitored throughout maternity shared care, improve quality and completeness of data collected and enhance sharing of health information between outpatient clinic and the hospital, and between clinical and public health services to inform decision-making.
Methods: This study implemented a novel cloud-based electronic medical record system in a maternal and child health outpatient setting in Western Kenya between April and June 2013 and evaluated its impact on improving completeness of data collected by clinical and public health services. The impact of the system was assessed using a two-sample test of proportions pre- and post-implementation of EMR-based data verification.
Results: Significant improvements in completeness of the antenatal record were recorded through implementation of EMR-based data verification. A difference of 42.9% in missing data (including screening for hypertension, tuberculosis, malaria, HIV status or ART status of HIV positive women) was recorded pre- and post-implementation. Despite significant impact of EMR-based data verification on data completeness, overall screening rates in antenatal care were low.
Conclusion: This study has shown that EMR-based data verification can improve the completeness of data collected in the patient record for maternal and child health. A number of issues, including data management and patient confidentiality, must be considered but significant improvements in data quality are recorded through implementation of this EMR model.
Keywords: Data verification; Electronic medical record; Maternal and child health; Medical informatics; Resource-constrained settings.
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