Application of quantitative decision-making tools in planning for seasonal variations of fever cases reporting at the medical emergency of a tertiary care hospital in New Delhi

Background: The healthcare industry of today is defined by patient centricity, perishability, intangibility and heterogenicity. Healthcare managers are faced with a challenge to maximize results by utilizing minimum resources. Forecasting is one of the techniques that help them in planning services. However, the accuracy of the forecast depends on multiple factors such as time horizon, the technique that is applied and certain irregular variations, which may be beyond the control of managers. Methods A retrospective record analysis was done to analyze trends in the monthly footfall in the emergency. Forecasting techniques were applied to predict the number of fever cases that were expected during a particular time period, based on which, the quantum of supplies needed was calculated using linear programming model. The actual and predicted number of patients that visited the emergency for 4 years was tabulated. Results It was observed that the demand for different consumables increased by 33–200% during the peak season. The Mean Absolute Deviation (MAD) was calculated to be 3981.22, Mean Absolute Percentage Error (MAPE) was 30.17% and the Tracking Signal varied between − 1.78 and + 0.86 which indicates that the forecast method was fairly accurate. Conclusion The same method may be applied to forecast the number of patients and accordingly the quantum of resources required for their management.