Patient Diversion Across Primary Health Centers Using Real Time Delay Predictors

TL;DR

This study develops and tests real-time delay predictors for patient diversion in primary health centers, demonstrating that more accurate predictors improve resource distribution and operational outcomes in Indian healthcare settings.

Contribution

The paper introduces a new delay predictor that combines system state and service time distribution, enhancing patient diversion decisions in primary health centers.

Findings

More accurate delay predictors lead to equitable resource distribution.

Simulation results show improved operational outcomes with better delay predictions.

Incorporating system state information enhances delay prediction accuracy.

Abstract

In the current work, we consider diversion of childbirth patients who arrive seeking emergency admission to public primary health centers (PHCs). PHCs are the first point of contact for an Indian patient with formal medical care, and offer medical care on an outpatient basis, and limited inpatient and childbirth care. In this context, real-time prediction of the wait time of the arriving patient becomes important in order to determine whether the patient must be diverted to another PHC or not. We study this problem using a discrete event simulation that we develop of medical care operations in two PHCs in India. We approximate the labour room service at each PHC as an M/G/1 queueing system and show how the accuracy of real-time delay predictors impacts the extent of the change in operational outcomes at each PHC. We simulate patient diversion using actual delays as well as the delay estimates generated by various delay predictors based on the state of the system such as queue-length, elapsed service time, and observed delay histories. The simulation of the diversion process also incorporates travel time between the PHCs. We also propose a new delay predictor that incorporates information regarding the system state as well as the service time distribution. We compare the operational outcomes at both PHCs without diversion and with diversion using the above delay predictors. We show numerically that more accurate delay predictors lead to more equitable distribution of resources involved in provision of childbirth care across both PHCs.