JMIR Publications

ABSTRACT

Background:

Crisis intervention services have been found excessively in demand, particularly in the midst of social unrest and pandemic crisis. Responding to callers efficiently is one of the major managerial challenges of such service platforms.

Objective:

This paper presents a discrete event simulation (DES) model to assess the queuing performance of a 24-hour text-based crisis online counseling platform, formulated to evaluate worker combinations needed to meet with demand. It is able to account for unbalanced and overlapped shifts, custom worker types having unequal simultaneous serving capacities, time-dependent user arrivals, and service durations influenced by user characteristics.

Methods:

Usage and queue statistics were tabulated from past counseling platform database records and incorporated into a discrete event simulation model to determine the supply and demand equilibrium and identify potential service bottlenecks. An unobserved components time series model was fitted to make 30-day forecasts of the arrival rate. Those results were piped back to the DES model to estimate the number of workers needed to staff each work shift and the number of repeated service users encountered by a service operation.

Results:

The model estimates an 85% chance that counseling service is no more than 10 minutes away. It also estimates half the user traffic is generated by repeated users.

Conclusions:

Using DES, crisis chatline operators can adopte strategies to manage service bottlenecks and increase uptakes for a not-for-profit entity with limited resources.