Dataset Information

Using mobile health technology and community health workers to identify and refer caesarean-related surgical site infections in rural Rwanda: a randomised controlled trial protocol.

ABSTRACT: INTRODUCTION:Surgical site infections (SSIs) are a significant cause of morbidity and mortality in low-income and middle-income countries, where rates of SSIs can reach 30%. Due to limited access, there is minimal follow-up postoperatively. Community health workers (CHWs) have not yet been used for surgical patients in most settings. Advancements in telecommunication create an opportunity for mobile health (mHealth) tools to support CHWs. We aim to evaluate the use of mHealth technology to aid CHWs in identification of SSIs and promote referral of patients back to healthcare facilities. METHODS AND ANALYSIS:Prospective randomised controlled trial conducted at Kirehe District Hospital, Rwanda, from November 2017 to November 2018. Patients ?18 years who undergo caesarean section are eligible. Non-residents of Kirehe District or patients who remain in hospital >10 days postoperatively will be excluded. Patients will be randomised to one of three arms. For arm 1, a CHW will visit the patient's home on postoperative day 10 (±3 days) to administer an SSI screening protocol (fever, pain or purulent drainage) using an electronic tablet. For arm 2, the CHW will administer the screening protocol over the phone. For both arms 1 and 2, the CHW will refer patients who respond 'yes' to any of the questions to a health facility. For arm 3, patients will not receive follow-up care. Our primary outcome will be the impact of the mHealth-CHW intervention on the rate of return to care for patients with an SSI. ETHICS AND DISSEMINATION:The study has received ethical approval from the Rwandan National Ethics Committee and Partners Healthcare. Results will be disseminated to Kirehe District Hospital, Rwanda Ministry of Health, Rwanda Surgical Society, Partners In Health, through conferences and peer-reviewed publications. TRIAL REGISTRATION NUMBER:NCT03311399.

SUBMITTER: Sonderman KA

PROVIDER: S-EPMC5942430 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Using mobile health technology and community health workers to identify and refer caesarean-related surgical site infections in rural Rwanda: a randomised controlled trial protocol.

Sonderman Kristin A KA Nkurunziza Theoneste T Kateera Fredrick F Gruendl Magdalena M Koch Rachel R Gaju Erick E Habiyakare Caste C Matousek Alexi A Nahimana Evrard E Ntakiyiruta Georges G Riviello Robert R Hedt-Gauthier Bethany L BL

BMJ open 20180508 5

<h4>Introduction</h4>Surgical site infections (SSIs) are a significant cause of morbidity and mortality in low-income and middle-income countries, where rates of SSIs can reach 30%. Due to limited access, there is minimal follow-up postoperatively. Community health workers (CHWs) have not yet been used for surgical patients in most settings. Advancements in telecommunication create an opportunity for mobile health (mHealth) tools to support CHWs. We aim to evaluate the use of mHealth technology ...[more]

PMID: 29739786

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Project description:IntroductionIn low-resource settings, community health workers are frontline providers who shoulder the health service delivery burden. Increasingly, mobile technologies are developed, tested, and deployed with community health workers to facilitate tasks and improve outcomes. We reviewed the evidence for the use of mobile technology by community health workers to identify opportunities and challenges for strengthening health systems in resource-constrained settings.MethodsWe conducted a systematic review of peer-reviewed literature from health, medical, social science, and engineering databases, using PRISMA guidelines. We identified a total of 25 unique full-text research articles on community health workers and their use of mobile technology for the delivery of health services.ResultsCommunity health workers have used mobile tools to advance a broad range of health aims throughout the globe, particularly maternal and child health, HIV/AIDS, and sexual and reproductive health. Most commonly, community health workers use mobile technology to collect field-based health data, receive alerts and reminders, facilitate health education sessions, and conduct person-to-person communication. Programmatic efforts to strengthen health service delivery focus on improving adherence to standards and guidelines, community education and training, and programmatic leadership and management practices. Those studies that evaluated program outcomes provided some evidence that mobile tools help community health workers to improve the quality of care provided, efficiency of services, and capacity for program monitoring.DiscussionEvidence suggests mobile technology presents promising opportunities to improve the range and quality of services provided by community health workers. Small-scale efforts, pilot projects, and preliminary descriptive studies are increasing, and there is a trend toward using feasible and acceptable interventions that lead to positive program outcomes through operational improvements and rigorous study designs. Programmatic and scientific gaps will need to be addressed by global leaders as they advance the use and assessment of mobile technology tools for community health workers.

Project description:BackgroundCommunity health workers (CHWs) play an important role in improving access to services in areas with limited health infrastructure or workforce. Supervision of CHWs by qualified health professionals is the main link between this lay workforce and the formal health system. The quality of services provided by lay health workers is dependent on adequate supportive supervision. It is however one of the weakest links in CHW programs due to logistical and resource constraints, especially in large scale programs. Interventions such as point of care testing using malaria rapid diagnostic tests (RDTs) require real time monitoring to ensure diagnostic accuracy. In this study, we evaluated the utility of a mobile health technology platform to remotely monitor malaria RDT (mRDT) testing by CHWs for quality improvement.MethodsAs part of a large implementation trial involving mRDT testing by CHWs, we introduced the Fionet system composed of a mobile device (Deki Reader, DR) to assist in processing and automated interpretation of mRDTs, which connects to a cloud-based database which captures reports from the field in real time, displaying results in a custom dashboard of key performance indicators. A random sample of 100 CHWs were trained and provided with the Deki Readers and instructed to use it on 10 successive patients. The CHWs interpretation was compared with the Deki Reader's automatic interpretation, with the errors in processing and interpreting the RDTs recorded. After the CHW entered their interpretation on the DR, the DR provided immediate, automated feedback and interpretation based on its reading of the same cassette. The study team monitored the CHW performance remotely and provided additional support.ResultsA total of 1251 primary and 113 repeat tests were performed by the 97 CHWs who used the DR. 91.6% of the tests had agreement between the DR and the CHWs. There were 61 (4.9%) processing and 52 (4.2%) interpretation errors among the primary tests. There was a tendency towards lower odds of errors with increasing number and frequency of tests, though not statistically significant. Of the 62 tests that were repeated due to errors, 79% achieved concordance between the CHW and the DR. Satisfaction with the use of the DR by the CHWs was high.ConclusionsUse of innovative mHealth strategies for monitoring and quality control can ensure quality within a large scale implementation of community level testing by lay health workers.

Project description:BackgroundA shortage of community health workers to triage sick neonates and poor recognition of neonatal illness by mothers contribute significantly toward neonatal deaths in low- and middle-income countries. Providing low-resource communities with the tools and knowledge to recognize signs of neonatal distress can lead to early care-seeking behavior. To empower and educate mothers to recognize signs of neonatal illness, we developed a neonatal health assessment device consisting of a smartphone app and a wearable sensor (the NeMo system).ObjectiveThe aim of this study was to determine if mothers in rural Uganda were willing and able to use the NeMo system during the first week of their infant's life. We also assessed mothers' responses to the device's recommendation to seek care.MethodsA total of 20 mothers were enrolled in the study after giving birth in the Iganga District Hospital. Each mother was trained to use the NeMo system to assess her infant for signs of illness before leaving the hospital and was given the NeMo system to use at home for 1 week. Throughout the week, the smartphone tracked the mothers' usage of NeMo, and the study team visited twice to observe mothers' ability to use NeMo. Each mother was interviewed at the end of 1 week to gather qualitative feedback on her experience with the NeMo system.ResultsIn total, 18 mothers completed the study; 2 mothers were withdrawn during the week because of extenuating health circumstances. Moreover, 1 day after enrollment and training, 75% (15/20) of mothers used NeMo properly with no mistakes. Three days after enrollment and training, only 1 mother placed the wearable sensor improperly on her infant. On the final study day, only 1 mother connected the device improperly. Mothers used NeMo an average of 11.67 (SD 5.70) times on their own at home during the 5 full study days. Although the frequency of use per day decreased from day 1 to day 5 of the study (P=.04), 72% (13/18) of mothers used NeMo at least once per day. In total, 64% (9/14) of mothers who received an alert from the NeMo system to seek care for their infants either called the health care professional working with the study team or reused the system immediately and found no danger signs. All 18 mothers agreed or strongly agreed that the NeMo system was easy to use and helped them know when to seek care for their babies.ConclusionsNeMo is a feasible and acceptable tool to aid mothers in rural Uganda to assess their infant's health.

Project description:BACKGROUND:Digital health technologies, including telemedicine, mobile health (mHealth), and remote monitoring, are playing a greater role in medical practice. Safe and accurate management of medical information leads to the advancement of digital health, which in turn results in a number of beneficial effects. Furthermore, mHealth can help lower costs by facilitating the delivery of care and connecting people to their health care providers. Mobile apps help empower patients and health care providers to proactively address medical conditions through near real-time monitoring and treatment, regardless of the location of the patient or the health care provider. Additionally, mHealth data are stored in servers, and consequently, data management that prevents all forms of manipulation is crucial for both medical practice and clinical trials. OBJECTIVE:The aim of this study was to develop and evaluate a tamper-resistant mHealth system using blockchain technology, which enables trusted and auditable computing using a decentralized network. METHODS:We developed an mHealth system for cognitive behavioral therapy for insomnia using a smartphone app. The volunteer data collected with the app were stored in JavaScript Object Notation format and sent to the blockchain network. Thereafter, we evaluated the tamper resistance of the data against the inconsistencies caused by artificial faults. RESULTS:Electronic medical records collected using smartphones were successfully sent to a private Hyperledger Fabric blockchain network. We verified the data update process under conditions where all the validating peers were running normally. The mHealth data were successfully updated under network faults. We further ensured that any electronic health record registered to the blockchain network was resistant to tampering and revision. The mHealth data update was compatible with tamper resistance in the blockchain network. CONCLUSIONS:Blockchain serves as a tamperproof system for mHealth. Combining mHealth with blockchain technology may provide a novel solution that enables both accessibility and data transparency without a third party such as a contract research organization.

Dataset Information

Using mobile health technology and community health workers to identify and refer caesarean-related surgical site infections in rural Rwanda: a randomised controlled trial protocol.

Publications

Using mobile health technology and community health workers to identify and refer caesarean-related surgical site infections in rural Rwanda: a randomised controlled trial protocol.

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