Modelling NHS 111 demand for primary care services: a discrete event simulation

Abstract Background Almost half of the 16,650,745 calls to NHS 111 each year are triaged to a primary care disposition. However, there is evidence that contact with a primary care service occurs in less than 50% of cases and triage time frames are frequently not met. This can result in increased utilisation of other healthcare services.This feasibility study aimed to modelin-silicothe current healthcare system for patients triaged to a primary care disposition and determine the effect of reconfiguring the system to ensure a timely primary care service contact.Methods Data from the Connected Yorkshire research database were used to develop a model and Discrete Event Simulation in Python, using the SimPy package. This included all 111 calls made in 2021 by callers registered with a Bradford GP who were triaged to a primary care disposition, and their subsequent healthcare system access during the following 72 hours.We simulated 100 runs of one year of 111 calls and calculated the mean difference and 95% confidence intervals in primary care contacts, emergency ambulance (999) calls and avoidable ED attendances.Results The simulation of the current system estimated that there would be 39,283 (95%CI 39,237–39,328) primary care contacts, 2,042 (95%CI 2,032–2,051) 999 calls and 1,120 (95%CI 1,114–1,127) avoidable ED attendances. Modifying the model to ensure a timely primary care response resulted in a mean increase in primary care contacts of 37,748 (95%CI 37,667–37,829), a mean reduction in 999 calls of -449 (95%CI -461– -436) and a mean reduction in avoidable ED attendance of -26 (95%CI -35– -17).Conclusion In this simulated study, ensuring timely contact with a primary care service would lead to a significant reduction in 999 and 111 calls, and ED attendances (although not avoidable ED attendance). However, this is likely to be impractical given the need to almost double current primary care service provision. Further economic and qualitative research is needed to determine whether this intervention would be cost effective and acceptable to both patients and primary care clinicians..

Medienart:	Preprint

Erscheinungsjahr:	2023
Erschienen:	2023

Enthalten in:	bioRxiv.org - (2023) vom: 25. Mai Zur Gesamtaufnahme - year:2023

Sprache:	Englisch

Beteiligte Personen:	Pilbery, Richard [VerfasserIn] Smith, Madeleine [VerfasserIn] Green, Jonathan [VerfasserIn] Chalk, Daniel [VerfasserIn] O’Keeffe, Colin [VerfasserIn]

Links:	Volltext [kostenfrei]

Themen:	570 Biology

doi:	10.1101/2023.05.22.23290330

funding:
Förderinstitution / Projekttitel:

PPN (Katalog-ID):	XBI039676692