Can routinely collected primary healthcare data be used to assess Aboriginal children’s health and wellbeing longitudinally? A retrospective analysis of electronic medical records from an Aboriginal community-controlled health service in Central Australia - Lloyd-Johnsen, Catherine; Boffa, John; Baghbanian, Vahab; Walpole, Rachel; Guo, Shuaijun; Eades, Sandra; D'Aprano, Anita; Goldfeld, Sharon (International Journal of Population Data Science, 2025)
Introduction Electronic medical records (EMR) are an essential tool in modern healthcare, providing a centralised source of patient information. Longitudinal analysis of EMRs can identify opportunities for targeted interventions to improve health outcomes for children. However, the research value of EMRs is contingent on data quality and completeness. Methods This retrospective cohort study used deidentified EMRs from all Aboriginal children born in 2015 who attended an Aboriginal-controlled health service in Central Australia over a 5-year period. The purpose of this study was to demonstrate the utility of EMRs in longitudinal research via presentation of three case study example analyses, and to evaluate the quality of the extracted dataset. Results EMRs of 319 Aboriginal children (48.9% girls, 51.1% boys) were included in the analysis. These children visited the service an average of 19.9 times (min 2 - max 102). Attendance rates for routine well-child check-ups were highest at 0 to 8 weeks and 4 years of age (37.3% and 40.1% respectively). Among 12-month-olds with recorded haemoglobin levels, 43% were anaemic. Weight-for-age medians were comparable to World Health Organization (WHO) growth standards until 12 months age, thereafter Aboriginal girls tended to weigh more overtime. Data completeness varied: key variables (date of birth, sex and Aboriginal status) were 100% complete, while others like anthropometrics (up to 62.1%), birth weight (54.2%), gestational age (50.2%), and haemoglobin results (up to 34.1%) were less complete. Average accuracy (99.2%) and consistency of available data (100%) were high. However, crucial data on risk factors, maternal health, and family functioning were either not collected by the service, not provided to the service from external sources, or stored in inaccessible free-text fields. Conclusions Missing data were the greatest limiting factor for reporting on the health and development of these children. To reap the benefit of utilising EMRs for longitudinal research, the service should continue encouraging families to attend their child's routine health assessments in the first years of life. Setting key data variables as mandatory at each visit may also help increase data completeness over time.