Obesity is a significant burden in hospitals, yet comprehensive data on its prevalence and impact on healthcare utilisation remain limited. The use of Electronic Medical Records (EMRs) for obesity surveillance is restricted by data completeness and accuracy. This study aimed to determine obesity prevalence across hospital specialties, examine the relationships between body mass index (BMI) and length of stay (LOS), identify patterns of missing anthropometric data, and explore the implications for clinical resource allocation.
A retrospective analysis was conducted on 2,221 patients admitted to Blacktown and Mt Druitt Hospitals in Sydney, NSW, with 1,298 patients meeting the inclusion criteria. Data on patient demographics, BMI, specialty, and LOS were extracted from the EMR. Descriptive statistics and correlation analyses assessed associations between BMI, LOS, and data completeness.
The mean BMI was 29.4 kg/m², with 37.0% of patients classified as obese (Classes I–III). Patients with Class III obesity had the longest average LOS at 15.1 days compared to an overall average of 9.3 days, while underweight patients had an average LOS of 10.5 days. Notably, BMI data were missing in 19.5% of patients, with the highest missing rate (37.0%) in the 17–39 age group.
Although the overall obesity prevalence in the inpatient population reflects community levels, both Class III obesity and underweight statuses are disproportionately represented and linked to prolonged hospital stays. The substantial proportion of missing data underscores significant deficiencies in current documentation practices. Implementation of automated EMR prompts, standardised measurement protocols, and AI-driven risk stratification tools could convert static anthropometric data into dynamic, actionable clinical insights. Such advancements have the potential to improve resource allocation and patient outcomes. These findings emphasise that early, targeted interventions for patients with high-risk BMI categories may optimise hospital resource utilisation and enhance the quality-of-care delivery.