The Effect and Feasibility of mHealth-Supported Surgical Site Infection Diagnosis by Community Health Workers After Cesarean Section in Rural Rwanda: Randomized Controlled Trial

BackgroundThe development of a surgical site infection (SSI) after cesarean section (c-section) is a significant cause of morbidity and mortality in low- and middle-income countries, including Rwanda. Rwanda relies on a robust community health worker (CHW)–led, home-based par...

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Main Authors: Fredrick Kateera, Robert Riviello, Andrea Goodman, Theoneste Nkurunziza, Teena Cherian, Laban Bikorimana, Jonathan Nkurunziza, Evrard Nahimana, Caste Habiyakare, Georges Ntakiyiruta, Alexi Matousek, Erick Gaju, Magdalena Gruendl, Brittany Powell, Kristin Sonderman, Rachel Koch, Bethany Hedt-Gauthier
Format: Article
Language:English
Published: JMIR Publications 2022-06-01
Series:JMIR mHealth and uHealth
Online Access:https://mhealth.jmir.org/2022/6/e35155
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author Fredrick Kateera
Robert Riviello
Andrea Goodman
Theoneste Nkurunziza
Teena Cherian
Laban Bikorimana
Jonathan Nkurunziza
Evrard Nahimana
Caste Habiyakare
Georges Ntakiyiruta
Alexi Matousek
Erick Gaju
Magdalena Gruendl
Brittany Powell
Kristin Sonderman
Rachel Koch
Bethany Hedt-Gauthier
author_facet Fredrick Kateera
Robert Riviello
Andrea Goodman
Theoneste Nkurunziza
Teena Cherian
Laban Bikorimana
Jonathan Nkurunziza
Evrard Nahimana
Caste Habiyakare
Georges Ntakiyiruta
Alexi Matousek
Erick Gaju
Magdalena Gruendl
Brittany Powell
Kristin Sonderman
Rachel Koch
Bethany Hedt-Gauthier
author_sort Fredrick Kateera
collection DOAJ
description BackgroundThe development of a surgical site infection (SSI) after cesarean section (c-section) is a significant cause of morbidity and mortality in low- and middle-income countries, including Rwanda. Rwanda relies on a robust community health worker (CHW)–led, home-based paradigm for delivering follow-up care for women after childbirth. However, this program does not currently include postoperative care for women after c-section, such as SSI screenings. ObjectiveThis trial assesses whether CHW’s use of a mobile health (mHealth)–facilitated checklist administered in person or via phone call improved rates of return to care among women who develop an SSI following c-section at a rural Rwandan district hospital. A secondary objective was to assess the feasibility of implementing the CHW-led mHealth intervention in this rural district. MethodsA total of 1025 women aged ≥18 years who underwent a c-section between November 2017 and September 2018 at Kirehe District Hospital were randomized into the three following postoperative care arms: (1) home visit intervention (n=335, 32.7%), (2) phone call intervention (n=334, 32.6%), and (3) standard of care (n=356, 34.7%). A CHW-led, mHealth-supported SSI diagnostic protocol was delivered in the two intervention arms, while patients in the standard of care arm were instructed to adhere to routine health center follow-up. We assessed intervention completion in each intervention arm and used logistic regression to assess the odds of returning to care. ResultsThe majority of women in Arm 1 (n=295, 88.1%) and Arm 2 (n=226, 67.7%) returned to care and were assessed for an SSI at their local health clinic. There were no significant differences in the rates of returning to clinic within 30 days (P=.21), with high rates found consistently across all three arms (Arm 1: 99.7%, Arm 2: 98.4%, and Arm 3: 99.7%, respectively). ConclusionsHome-based post–c-section follow-up is feasible in rural Africa when performed by mHealth-supported CHWs. In this study, we found no difference in return to care rates between the intervention arms and standard of care. However, given our previous study findings describing the significant patient-incurred financial burden posed by traveling to a health center, we believe this intervention has the potential to reduce this burden by limiting patient travel to the health center when an SSI is ruled out at home. Further studies are needed (1) to determine the acceptability of this intervention by CHWs and patients as a new standard of care after c-section and (2) to assess whether an app supplementing the mHealth screening checklist with image-based machine learning could improve CHW diagnostic accuracy. Trial RegistrationClinicalTrials.gov NCT03311399; https://clinicaltrials.gov/ct2/show/NCT03311399
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spelling doaj.art-c794b648f2a64c6287fda7c9f7ab73d32023-08-28T22:14:42ZengJMIR PublicationsJMIR mHealth and uHealth2291-52222022-06-01106e3515510.2196/35155The Effect and Feasibility of mHealth-Supported Surgical Site Infection Diagnosis by Community Health Workers After Cesarean Section in Rural Rwanda: Randomized Controlled TrialFredrick Kateerahttps://orcid.org/0000-0002-6363-5180Robert Riviellohttps://orcid.org/0000-0003-3783-153XAndrea Goodmanhttps://orcid.org/0000-0002-0948-8300Theoneste Nkurunzizahttps://orcid.org/0000-0002-5475-3396Teena Cherianhttps://orcid.org/0000-0002-7766-6076Laban Bikorimanahttps://orcid.org/0000-0001-6547-8310Jonathan Nkurunzizahttps://orcid.org/0000-0001-9952-9921Evrard Nahimanahttps://orcid.org/0000-0002-8437-3044Caste Habiyakarehttps://orcid.org/0000-0002-9347-6950Georges Ntakiyirutahttps://orcid.org/0000-0002-4549-9015Alexi Matousekhttps://orcid.org/0000-0001-9352-3393Erick Gajuhttps://orcid.org/0000-0001-8609-1588Magdalena Gruendlhttps://orcid.org/0000-0002-9402-5756Brittany Powellhttps://orcid.org/0000-0001-6297-0692Kristin Sondermanhttps://orcid.org/0000-0002-2623-1793Rachel Kochhttps://orcid.org/0000-0002-0536-5207Bethany Hedt-Gauthierhttps://orcid.org/0000-0002-9689-5413 BackgroundThe development of a surgical site infection (SSI) after cesarean section (c-section) is a significant cause of morbidity and mortality in low- and middle-income countries, including Rwanda. Rwanda relies on a robust community health worker (CHW)–led, home-based paradigm for delivering follow-up care for women after childbirth. However, this program does not currently include postoperative care for women after c-section, such as SSI screenings. ObjectiveThis trial assesses whether CHW’s use of a mobile health (mHealth)–facilitated checklist administered in person or via phone call improved rates of return to care among women who develop an SSI following c-section at a rural Rwandan district hospital. A secondary objective was to assess the feasibility of implementing the CHW-led mHealth intervention in this rural district. MethodsA total of 1025 women aged ≥18 years who underwent a c-section between November 2017 and September 2018 at Kirehe District Hospital were randomized into the three following postoperative care arms: (1) home visit intervention (n=335, 32.7%), (2) phone call intervention (n=334, 32.6%), and (3) standard of care (n=356, 34.7%). A CHW-led, mHealth-supported SSI diagnostic protocol was delivered in the two intervention arms, while patients in the standard of care arm were instructed to adhere to routine health center follow-up. We assessed intervention completion in each intervention arm and used logistic regression to assess the odds of returning to care. ResultsThe majority of women in Arm 1 (n=295, 88.1%) and Arm 2 (n=226, 67.7%) returned to care and were assessed for an SSI at their local health clinic. There were no significant differences in the rates of returning to clinic within 30 days (P=.21), with high rates found consistently across all three arms (Arm 1: 99.7%, Arm 2: 98.4%, and Arm 3: 99.7%, respectively). ConclusionsHome-based post–c-section follow-up is feasible in rural Africa when performed by mHealth-supported CHWs. In this study, we found no difference in return to care rates between the intervention arms and standard of care. However, given our previous study findings describing the significant patient-incurred financial burden posed by traveling to a health center, we believe this intervention has the potential to reduce this burden by limiting patient travel to the health center when an SSI is ruled out at home. Further studies are needed (1) to determine the acceptability of this intervention by CHWs and patients as a new standard of care after c-section and (2) to assess whether an app supplementing the mHealth screening checklist with image-based machine learning could improve CHW diagnostic accuracy. Trial RegistrationClinicalTrials.gov NCT03311399; https://clinicaltrials.gov/ct2/show/NCT03311399https://mhealth.jmir.org/2022/6/e35155
spellingShingle Fredrick Kateera
Robert Riviello
Andrea Goodman
Theoneste Nkurunziza
Teena Cherian
Laban Bikorimana
Jonathan Nkurunziza
Evrard Nahimana
Caste Habiyakare
Georges Ntakiyiruta
Alexi Matousek
Erick Gaju
Magdalena Gruendl
Brittany Powell
Kristin Sonderman
Rachel Koch
Bethany Hedt-Gauthier
The Effect and Feasibility of mHealth-Supported Surgical Site Infection Diagnosis by Community Health Workers After Cesarean Section in Rural Rwanda: Randomized Controlled Trial
JMIR mHealth and uHealth
title The Effect and Feasibility of mHealth-Supported Surgical Site Infection Diagnosis by Community Health Workers After Cesarean Section in Rural Rwanda: Randomized Controlled Trial
title_full The Effect and Feasibility of mHealth-Supported Surgical Site Infection Diagnosis by Community Health Workers After Cesarean Section in Rural Rwanda: Randomized Controlled Trial
title_fullStr The Effect and Feasibility of mHealth-Supported Surgical Site Infection Diagnosis by Community Health Workers After Cesarean Section in Rural Rwanda: Randomized Controlled Trial
title_full_unstemmed The Effect and Feasibility of mHealth-Supported Surgical Site Infection Diagnosis by Community Health Workers After Cesarean Section in Rural Rwanda: Randomized Controlled Trial
title_short The Effect and Feasibility of mHealth-Supported Surgical Site Infection Diagnosis by Community Health Workers After Cesarean Section in Rural Rwanda: Randomized Controlled Trial
title_sort effect and feasibility of mhealth supported surgical site infection diagnosis by community health workers after cesarean section in rural rwanda randomized controlled trial
url https://mhealth.jmir.org/2022/6/e35155
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