Laboratory Data Timeliness and Completeness Improves Following Implementation of an Electronic Laboratory Information System in Côte d'Ivoire: Quasi-Experimental Study on 21 Clinical Laboratories From 2014 to 2020.

HIV adoption clinical laboratory data quality effectiveness electronic laboratory information system evaluation impact evaluation implementation information system information systems lab laboratory labs sexually transmitted sexually transmitted disease sexually transmitted infection time series

Journal

JMIR public health and surveillance
ISSN: 2369-2960
Titre abrégé: JMIR Public Health Surveill
Pays: Canada
ID NLM: 101669345

Informations de publication

Date de publication:
20 Mar 2024
Historique:
received: 29 06 2023
accepted: 23 01 2024
revised: 04 01 2024
medline: 20 3 2024
pubmed: 20 3 2024
entrez: 20 3 2024
Statut: epublish

Résumé

The Ministry of Health in Côte d'Ivoire and the International Training and Education Center for Health at the University of Washington, funded by the United States President's Emergency Plan for AIDS Relief, have been collaborating to develop and implement the Open-Source Enterprise-Level Laboratory Information System (OpenELIS). The system is designed to improve HIV-related laboratory data management and strengthen quality management and capacity at clinical laboratories across the nation. This evaluation aimed to quantify the effects of implementing OpenELIS on data quality for laboratory tests related to HIV care and treatment. This evaluation used a quasi-experimental design to perform an interrupted time-series analysis to estimate the changes in the level and slope of 3 data quality indicators (timeliness, completeness, and validity) after OpenELIS implementation. We collected paper and electronic records on clusters of differentiation 4 (CD4) testing for 48 weeks before OpenELIS adoption until 72 weeks after. Data collection took place at 21 laboratories in 13 health regions that started using OpenELIS between 2014 and 2020. We analyzed the data at the laboratory level. We estimated odds ratios (ORs) by comparing the observed outcomes with modeled counterfactual ones when the laboratories did not adopt OpenELIS. There was an immediate 5-fold increase in timeliness (OR 5.27, 95% CI 4.33-6.41; P<.001) and an immediate 3.6-fold increase in completeness (OR 3.59, 95% CI 2.40-5.37; P<.001). These immediate improvements were observed starting after OpenELIS installation and then maintained until 72 weeks after OpenELIS adoption. The weekly improvement in the postimplementation trend of completeness was significant (OR 1.03, 95% CI 1.02-1.05; P<.001). The improvement in validity was not statistically significant (OR 1.34, 95% CI 0.69-2.60; P=.38), but validity did not fall below pre-OpenELIS levels. These results demonstrate the value of electronic laboratory information systems in improving laboratory data quality and supporting evidence-based decision-making in health care. These findings highlight the importance of OpenELIS in Côte d'Ivoire and the potential for adoption in other low- and middle-income countries with similar health systems.

Sections du résumé

BACKGROUND BACKGROUND
The Ministry of Health in Côte d'Ivoire and the International Training and Education Center for Health at the University of Washington, funded by the United States President's Emergency Plan for AIDS Relief, have been collaborating to develop and implement the Open-Source Enterprise-Level Laboratory Information System (OpenELIS). The system is designed to improve HIV-related laboratory data management and strengthen quality management and capacity at clinical laboratories across the nation.
OBJECTIVE OBJECTIVE
This evaluation aimed to quantify the effects of implementing OpenELIS on data quality for laboratory tests related to HIV care and treatment.
METHODS METHODS
This evaluation used a quasi-experimental design to perform an interrupted time-series analysis to estimate the changes in the level and slope of 3 data quality indicators (timeliness, completeness, and validity) after OpenELIS implementation. We collected paper and electronic records on clusters of differentiation 4 (CD4) testing for 48 weeks before OpenELIS adoption until 72 weeks after. Data collection took place at 21 laboratories in 13 health regions that started using OpenELIS between 2014 and 2020. We analyzed the data at the laboratory level. We estimated odds ratios (ORs) by comparing the observed outcomes with modeled counterfactual ones when the laboratories did not adopt OpenELIS.
RESULTS RESULTS
There was an immediate 5-fold increase in timeliness (OR 5.27, 95% CI 4.33-6.41; P<.001) and an immediate 3.6-fold increase in completeness (OR 3.59, 95% CI 2.40-5.37; P<.001). These immediate improvements were observed starting after OpenELIS installation and then maintained until 72 weeks after OpenELIS adoption. The weekly improvement in the postimplementation trend of completeness was significant (OR 1.03, 95% CI 1.02-1.05; P<.001). The improvement in validity was not statistically significant (OR 1.34, 95% CI 0.69-2.60; P=.38), but validity did not fall below pre-OpenELIS levels.
CONCLUSIONS CONCLUSIONS
These results demonstrate the value of electronic laboratory information systems in improving laboratory data quality and supporting evidence-based decision-making in health care. These findings highlight the importance of OpenELIS in Côte d'Ivoire and the potential for adoption in other low- and middle-income countries with similar health systems.

Identifiants

pubmed: 38506899
pii: v10i1e50407
doi: 10.2196/50407
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e50407

Informations de copyright

©Yao He, Yves-Rolland Kouabenan, Paul Henri Assoa, Nancy Puttkammer, Bradley H Wagenaar, Hong Xiao, Stephen Gloyd, Noah G Hoffman, Pascal Komena, N'zi Pierre Fourier Kamelan, Casey Iiams-Hauser, Adama Sanogo Pongathie, Alain Kouakou, Jan Flowers, Nadine Abiola, Natacha Kohemun, Jean-Bernard Amani, Christiane Adje-Toure, Lucy A Perrone. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 20.03.2024.

Auteurs

Yao He (Y)

Digital Initiatives Group at International Training and Education Center for Health, Department of Global Health, Schools of Public Health and Medicine, University of Washington, Seattle, WA, United States.

Yves-Rolland Kouabenan (YR)

International Training and Education Center for Health - Côte d'Ivoire, Abidjan, Cote D'Ivoire.

Paul Henri Assoa (PH)

International Training and Education Center for Health - Côte d'Ivoire, Abidjan, Cote D'Ivoire.

Nancy Puttkammer (N)

Digital Initiatives Group at International Training and Education Center for Health, Department of Global Health, Schools of Public Health and Medicine, University of Washington, Seattle, WA, United States.

Bradley H Wagenaar (BH)

Department of Global Health, Schools of Public Health and Medicine, University of Washington, Seattle, WA, United States.
Department of Epidemiology, Schools of Public Health and Medicine, University of Washington, Seattle, WA, United States.

Hong Xiao (H)

Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, United States.

Stephen Gloyd (S)

Department of Global Health, Schools of Public Health and Medicine, University of Washington, Seattle, WA, United States.

Noah G Hoffman (NG)

Department of Pathology and Laboratory Medicine, University of Washington, Seattle, WA, United States.

Pascal Komena (P)

International Training and Education Center for Health - Côte d'Ivoire, Abidjan, Cote D'Ivoire.

N'zi Pierre Fourier Kamelan (NPF)

International Training and Education Center for Health - Côte d'Ivoire, Abidjan, Cote D'Ivoire.

Casey Iiams-Hauser (C)

Digital Initiatives Group at International Training and Education Center for Health, Department of Global Health, Schools of Public Health and Medicine, University of Washington, Seattle, WA, United States.

Adama Sanogo Pongathie (AS)

Direction de l'Informatique et de l'Information Sanitaire, Ministry of Health, Public Hygiene and Universal Health Coverage, Abidjan, Cote D'Ivoire.

Alain Kouakou (A)

Direction de l'Informatique et de l'Information Sanitaire, Ministry of Health, Public Hygiene and Universal Health Coverage, Abidjan, Cote D'Ivoire.

Jan Flowers (J)

Digital Initiatives Group at International Training and Education Center for Health, Department of Global Health, Schools of Public Health and Medicine, University of Washington, Seattle, WA, United States.

Nadine Abiola (N)

International Training and Education Center for Health - Côte d'Ivoire, Abidjan, Cote D'Ivoire.

Natacha Kohemun (N)

Laboratory Branch, United States Centers for Disease Control and Prevention, Abidjan, Cote D'Ivoire.

Jean-Bernard Amani (JB)

Laboratory Branch, United States Centers for Disease Control and Prevention, Abidjan, Cote D'Ivoire.

Christiane Adje-Toure (C)

Retro-CI Laboratory, United States Centers for Disease Control and Prevention, Abidjan, Cote D'Ivoire.

Lucy A Perrone (LA)

Department of Global Health, Schools of Public Health and Medicine, University of Washington, Seattle, WA, United States.
Department of Pathology and Laboratory Medicine, University of British Columbia (UBC), Vancouver, BC, Canada.

Classifications MeSH