The University of Southampton
University of Southampton Institutional Repository

Programmatic implications of implementing the relational algebraic capacitated location (RACL) algorithm outcomes on the allocation of laboratory sites, test volumes, platform distribution and space requirements.

Programmatic implications of implementing the relational algebraic capacitated location (RACL) algorithm outcomes on the allocation of laboratory sites, test volumes, platform distribution and space requirements.
Programmatic implications of implementing the relational algebraic capacitated location (RACL) algorithm outcomes on the allocation of laboratory sites, test volumes, platform distribution and space requirements.
Introduction: The National Health Laboratory Service (NHLS) of South Africa provides national coordination of laboratory services. CD4 testing is based on an integrated tiered service delivery model (ITSDM) that matches testing demand with capacity. Currently, the NHLS has predominantly implemented laboratory based CD4 testing (tiers 4 and 5). An objective methodology was required to identify coverage gaps, over/under capacitation and optimal placement of point of care (POC) testing sites.

Objectives: To assess the impact of a relational algebraic capacitated location (RACL) algorithm outcome on the allocation of laboratory sites, test volumes, platform distribution and space requirements.

Methods: The RACL algorithm was developed to efficiently allocate laboratories and POC sites to ensure coverage using a set coverage approach for a defined travel time (T). The algorithm was repeated for three scenarios (A: T=4, B: T=3 and C: T=2 hours). Drive times for a representative sample of health facility clusters were used to approximate T. The algorithm outcomes included the allocation of testing sites, Euclidian distances and test volumes. The analysis included the allocation of laboratory and POC sites, test volumes, platform distribution and space requirements. Each scenario was reported as a fusion table map.

Results: Scenario A would offer a fully centralised approach with 15 CD4 laboratories (closure of CD4 testing at 44 laboratories) without any POC testing. A significant increase in volumes would result in a 4-fold increase at busier laboratories. CD4 laboratories would be increased to 41 and 61 in scenarios B and C respectively. POC testing would be offered at 2 and 20 sites respectively. Scenario B and C laboratory test volumes would be similar to current volumes with significant decentralisation in rural areas.

Conclusion: The RACL algorithm provides an objective methodology to address coverage gaps through the allocation of CD4 laboratories and POC sites for a given T. The algorithm outcome needs to be assessed in the context of local conditions to address coverage gaps in a sustainable manner. Additionally, a tier 3 pilot highlights the ability of rural laboratories to improve coverage cost effectively.
CD4; Coverage; Modelling
2225-2002
Cassim, Naseem
d55ab05f-1b62-499a-975e-a27485a9ea4d
Smith, Honora
1eaef6a6-4b9c-4997-9163-137b956c06b5
Coetzee, Lindi
97e0af82-8475-4233-9132-78b42fe08762
Glencross, Debbie
ad612f32-cf5d-482a-8759-20e7233d0014
Cassim, Naseem
d55ab05f-1b62-499a-975e-a27485a9ea4d
Smith, Honora
1eaef6a6-4b9c-4997-9163-137b956c06b5
Coetzee, Lindi
97e0af82-8475-4233-9132-78b42fe08762
Glencross, Debbie
ad612f32-cf5d-482a-8759-20e7233d0014

Cassim, Naseem, Smith, Honora, Coetzee, Lindi and Glencross, Debbie (2017) Programmatic implications of implementing the relational algebraic capacitated location (RACL) algorithm outcomes on the allocation of laboratory sites, test volumes, platform distribution and space requirements. African Journal of Laboratory Medicine, 6 (1). (doi:10.4102/ajlm.v6i1.545).

Record type: Article

Abstract

Introduction: The National Health Laboratory Service (NHLS) of South Africa provides national coordination of laboratory services. CD4 testing is based on an integrated tiered service delivery model (ITSDM) that matches testing demand with capacity. Currently, the NHLS has predominantly implemented laboratory based CD4 testing (tiers 4 and 5). An objective methodology was required to identify coverage gaps, over/under capacitation and optimal placement of point of care (POC) testing sites.

Objectives: To assess the impact of a relational algebraic capacitated location (RACL) algorithm outcome on the allocation of laboratory sites, test volumes, platform distribution and space requirements.

Methods: The RACL algorithm was developed to efficiently allocate laboratories and POC sites to ensure coverage using a set coverage approach for a defined travel time (T). The algorithm was repeated for three scenarios (A: T=4, B: T=3 and C: T=2 hours). Drive times for a representative sample of health facility clusters were used to approximate T. The algorithm outcomes included the allocation of testing sites, Euclidian distances and test volumes. The analysis included the allocation of laboratory and POC sites, test volumes, platform distribution and space requirements. Each scenario was reported as a fusion table map.

Results: Scenario A would offer a fully centralised approach with 15 CD4 laboratories (closure of CD4 testing at 44 laboratories) without any POC testing. A significant increase in volumes would result in a 4-fold increase at busier laboratories. CD4 laboratories would be increased to 41 and 61 in scenarios B and C respectively. POC testing would be offered at 2 and 20 sites respectively. Scenario B and C laboratory test volumes would be similar to current volumes with significant decentralisation in rural areas.

Conclusion: The RACL algorithm provides an objective methodology to address coverage gaps through the allocation of CD4 laboratories and POC sites for a given T. The algorithm outcome needs to be assessed in the context of local conditions to address coverage gaps in a sustainable manner. Additionally, a tier 3 pilot highlights the ability of rural laboratories to improve coverage cost effectively.

Other
545_R1-Manuscript-CLEAN.DOCX - Accepted Manuscript
Available under License Creative Commons Attribution.
Download (3MB)

More information

Accepted/In Press date: 16 September 2016
e-pub ahead of print date: 28 February 2017
Keywords: CD4; Coverage; Modelling
Organisations: Operational Research

Identifiers

Local EPrints ID: 403606
URI: https://eprints.soton.ac.uk/id/eprint/403606
ISSN: 2225-2002
PURE UUID: d489c27f-3875-4807-9c66-7781bbb571b2
ORCID for Honora Smith: ORCID iD orcid.org/0000-0002-4974-3011

Catalogue record

Date deposited: 07 Dec 2016 11:44
Last modified: 05 Oct 2018 00:33

Export record

Altmetrics

Contributors

Author: Naseem Cassim
Author: Honora Smith ORCID iD
Author: Lindi Coetzee
Author: Debbie Glencross

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×