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The effect of an mHealth clinical decision-making support system on neonatal mortality in a low resource setting: A cluster-randomized controlled trial

BACKGROUND: MHealth interventions promise to bridge gaps in clinical care but documentation of their effectiveness is limited. We evaluated the utilization and effect of an mhealth clinical decision-making support intervention that aimed to improve neonatal mortality in Ghana by providing access to...

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Autores principales: Amoakoh, Hannah Brown, Klipstein-Grobusch, Kerstin, Agyepong, Irene Akua, Zuithoff, Nicolaas P.A., Amoakoh-Coleman, Mary, Kayode, Gbenga A., Sarpong, Charity, Reitsma, Johannes B., Grobbee, Diederick E., Ansah, Evelyn K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677648/
https://www.ncbi.nlm.nih.gov/pubmed/31388661
http://dx.doi.org/10.1016/j.eclinm.2019.05.010
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author Amoakoh, Hannah Brown
Klipstein-Grobusch, Kerstin
Agyepong, Irene Akua
Zuithoff, Nicolaas P.A.
Amoakoh-Coleman, Mary
Kayode, Gbenga A.
Sarpong, Charity
Reitsma, Johannes B.
Grobbee, Diederick E.
Ansah, Evelyn K.
author_facet Amoakoh, Hannah Brown
Klipstein-Grobusch, Kerstin
Agyepong, Irene Akua
Zuithoff, Nicolaas P.A.
Amoakoh-Coleman, Mary
Kayode, Gbenga A.
Sarpong, Charity
Reitsma, Johannes B.
Grobbee, Diederick E.
Ansah, Evelyn K.
author_sort Amoakoh, Hannah Brown
collection PubMed
description BACKGROUND: MHealth interventions promise to bridge gaps in clinical care but documentation of their effectiveness is limited. We evaluated the utilization and effect of an mhealth clinical decision-making support intervention that aimed to improve neonatal mortality in Ghana by providing access to emergency neonatal protocols for frontline health workers. METHODS: In the Eastern Region of Ghana, sixteen districts were randomized into two study arms (8 intervention and 8 control clusters) in a cluster-randomized controlled trial. Institutional neonatal mortality data were extracted from the District Health Information System-2 during an 18-month intervention period. We performed an intention-to-treat analysis and estimated the effect of the intervention on institutional neonatal mortality (primary outcome measure) using grouped binomial logistic regression with a random intercept per cluster. This trial is registered at ClinicalTrials.gov (NCT02468310) and Pan African Clinical Trials Registry (PACTR20151200109073). FINDINGS: There were 65,831 institutional deliveries and 348 institutional neonatal deaths during the study period. Overall, 47 ∙ 3% of deliveries and 56 ∙ 9% of neonatal deaths occurred in the intervention arm. During the intervention period, neonatal deaths increased from 4 ∙ 5 to 6 ∙ 4 deaths and, from 3 ∙ 9 to 4 ∙ 3 deaths per 1000 deliveries in the intervention arm and control arm respectively. The odds of neonatal death was 2⋅09 (95% CI (1 ∙ 00;4 ∙ 38); p = 0 ∙ 051) times higher in the intervention arm compared to the control arm (adjusted odds ratio). The correlation between the number of protocol requests and the number of deliveries per intervention cluster was 0 ∙ 71 (p = 0 ∙ 05). INTERPRETATION: The higher risk of institutional neonatal death observed in intervention clusters may be due to problems with birth and death registration, unmeasured and unadjusted confounding, and unintended use of the intervention. The findings underpin the need for careful and rigorous evaluation of mHealth intervention implementation and effects. FUNDING: Netherlands Foundation for Scientific Research - WOTRO, Science for Global Development; Utrecht University.
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spelling pubmed-66776482019-08-06 The effect of an mHealth clinical decision-making support system on neonatal mortality in a low resource setting: A cluster-randomized controlled trial Amoakoh, Hannah Brown Klipstein-Grobusch, Kerstin Agyepong, Irene Akua Zuithoff, Nicolaas P.A. Amoakoh-Coleman, Mary Kayode, Gbenga A. Sarpong, Charity Reitsma, Johannes B. Grobbee, Diederick E. Ansah, Evelyn K. EClinicalMedicine Research Paper BACKGROUND: MHealth interventions promise to bridge gaps in clinical care but documentation of their effectiveness is limited. We evaluated the utilization and effect of an mhealth clinical decision-making support intervention that aimed to improve neonatal mortality in Ghana by providing access to emergency neonatal protocols for frontline health workers. METHODS: In the Eastern Region of Ghana, sixteen districts were randomized into two study arms (8 intervention and 8 control clusters) in a cluster-randomized controlled trial. Institutional neonatal mortality data were extracted from the District Health Information System-2 during an 18-month intervention period. We performed an intention-to-treat analysis and estimated the effect of the intervention on institutional neonatal mortality (primary outcome measure) using grouped binomial logistic regression with a random intercept per cluster. This trial is registered at ClinicalTrials.gov (NCT02468310) and Pan African Clinical Trials Registry (PACTR20151200109073). FINDINGS: There were 65,831 institutional deliveries and 348 institutional neonatal deaths during the study period. Overall, 47 ∙ 3% of deliveries and 56 ∙ 9% of neonatal deaths occurred in the intervention arm. During the intervention period, neonatal deaths increased from 4 ∙ 5 to 6 ∙ 4 deaths and, from 3 ∙ 9 to 4 ∙ 3 deaths per 1000 deliveries in the intervention arm and control arm respectively. The odds of neonatal death was 2⋅09 (95% CI (1 ∙ 00;4 ∙ 38); p = 0 ∙ 051) times higher in the intervention arm compared to the control arm (adjusted odds ratio). The correlation between the number of protocol requests and the number of deliveries per intervention cluster was 0 ∙ 71 (p = 0 ∙ 05). INTERPRETATION: The higher risk of institutional neonatal death observed in intervention clusters may be due to problems with birth and death registration, unmeasured and unadjusted confounding, and unintended use of the intervention. The findings underpin the need for careful and rigorous evaluation of mHealth intervention implementation and effects. FUNDING: Netherlands Foundation for Scientific Research - WOTRO, Science for Global Development; Utrecht University. Elsevier 2019-07-04 /pmc/articles/PMC6677648/ /pubmed/31388661 http://dx.doi.org/10.1016/j.eclinm.2019.05.010 Text en © 2019 Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Paper
Amoakoh, Hannah Brown
Klipstein-Grobusch, Kerstin
Agyepong, Irene Akua
Zuithoff, Nicolaas P.A.
Amoakoh-Coleman, Mary
Kayode, Gbenga A.
Sarpong, Charity
Reitsma, Johannes B.
Grobbee, Diederick E.
Ansah, Evelyn K.
The effect of an mHealth clinical decision-making support system on neonatal mortality in a low resource setting: A cluster-randomized controlled trial
title The effect of an mHealth clinical decision-making support system on neonatal mortality in a low resource setting: A cluster-randomized controlled trial
title_full The effect of an mHealth clinical decision-making support system on neonatal mortality in a low resource setting: A cluster-randomized controlled trial
title_fullStr The effect of an mHealth clinical decision-making support system on neonatal mortality in a low resource setting: A cluster-randomized controlled trial
title_full_unstemmed The effect of an mHealth clinical decision-making support system on neonatal mortality in a low resource setting: A cluster-randomized controlled trial
title_short The effect of an mHealth clinical decision-making support system on neonatal mortality in a low resource setting: A cluster-randomized controlled trial
title_sort effect of an mhealth clinical decision-making support system on neonatal mortality in a low resource setting: a cluster-randomized controlled trial
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677648/
https://www.ncbi.nlm.nih.gov/pubmed/31388661
http://dx.doi.org/10.1016/j.eclinm.2019.05.010
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