Curating maternal, neonatal and child health (MNCH) datasets from a hospital’s catchment area in Nigeria between 2014 and 2019

Abstract

In this Data Note, we present details regarding Maternal, Neonatal, and Child Health (MNCH) datasets sourced directly from patients' medical records. These datasets consist of 538 maternal, 720 neonatal, and 425 child records, all collected at St Luke’s General Hospital in Anua, Uyo, Nigeria, spanning from 2014 to 2019. Variables included in the datasets are:  Maternal {patient number, date of visit, gender, age, class of patient, address, LGA, diagnose, symptom, prescription, blood pressure (mm Hg), temperature (degree centigrade), weight (Kg), latitude, longitude, elevation, (MSL), date record, GPS Accuracy (m)}; Neonatal {patient number, date of visit, gender, age, class of patient, address, LGA, symptom, health status, height (cm), weight (Kg), latitude, longitude, elevation (MSL), date record, GPS Accuracy (m)}; and Child Health {patient number, date of visit, gender, age, class of patient, address, LGA, diagnose, health history, temperature (degree centigrade), weight (Kg), latitude, longitude, elevation (MSL), date record, GPS accuracy (m)}. The purpose of sharing these datasets is to provide a resource for researchers interested in their potential reuse, whether for analysis, research, quality assurance, policy formulation, decision-making, patient safety, or other purposes. The datasets also include location information obtained through GPS (Global Positioning System) data from the study area, facilitating spatiotemporal analysis. We outline the methods used for curating the datasets, including the protocol for selecting and processing variables. To protect patient privacy, certain personal details such as names were replaced with unique patient numbers generated using Microsoft Excel. Furthermore, specific patient information, including addresses/locations, date of visit, latitude, longitude, elevation, and GPS accuracy, has been restricted for privacy reasons. Readers interested in accessing restricted data can make a formal request to the corresponding author (see data restriction statement). The curated datasets are available at the Open Science Framework.