mHealth tool to improve community health agent performance for child development: study protocol for a cluster-randomised controlled trial in Peru

Lay health workers in primary and community health care for maternal and child health: identification and treatment of wasting in children

BACKGROUND

Since the early 2010s, there has been a push to enhance the capacity to effectively treat wasting in children through community-based service delivery models and thus reduce morbidity and mortality.

OBJECTIVES

To assess the effectiveness of identification and treatment of moderate and severe wasting in children aged five years or under by lay health workers working in the community compared with health providers working in health facilities.

SEARCH METHODS

We searched MEDLINE, CENTRAL, two other databases, and two ongoing trials registers to 24 September 2021. We also screened the reference lists of related systematic reviews and all included studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) and non-randomised studies in children aged five years or under with moderate wasting (defined as weight-for-height Z-score (WHZ) below -2 but no lower than ≥ -3, or mid-upper-arm circumference (MUAC) below 125 mm but no lower than 115 mm, and no nutritional oedema) or severe wasting (WHZ below -3 or MUAC below 115 mm or nutritional oedema). Eligible interventions were: • identification by lay health workers (LHWs) of children with wasting (intervention 1); • identification by LHWs of children with wasting and medical complications needing referral (intervention 2); and • identification by LHWs of children with wasting without medical complications needing referral (intervention 3). Eligible comparators were: • identification and treatment of wasting by health professionals such as nurses or doctors (at health facilities); and • identification and treatment of wasting by health facility-based teams, including health professionals and LHWs.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened trials, extracted data and assessed risk of bias using the Cochrane risk of bias tool (RoB 2) and Cochrane Effective Practice and Organisation of Care (EPOC) guidelines. We used a random-effects model to meta-analyse data, producing risk ratios (RRs) for dichotomous outcomes in trials with individual allocation, adjusted RRs for dichotomous outcomes in trials with cluster allocation (using the generic inverse variance method in Review Manager 5), and mean differences (MDs) for continuous outcomes. We used the GRADE approach to assess the certainty of the evidence.

MAIN RESULTS

We included two RCTs and five non-RCTs. Six studies were from African countries, and one was from Pakistan. Six studies included children with severe wasting, and one included children with moderate wasting. All studies offered home-based ready-to-use therapeutic food treatment and monitoring. Children received antibiotics in three studies, vitamins or micronutrients in three studies, and deworming treatment in two studies. In three studies, the comparison arm involved LHWs screening children for malnutrition and referring them to health facilities for diagnosis and treatment. All the non-randomised studies had a high overall risk of bias. Interventions 1 and 2 Identification and referral for treatment by LHWs, compared with treatment by health professionals following self-referral, may result in little or no difference in the percentage of children who recover from moderate or severe wasting (MD 1.00%, 95% confidence interval (CI) -2.53 to 4.53; 1 RCT, 29,475 households; low certainty). Intervention 3 Compared with treatment by health professionals following identification by LHWs, identification and treatment of severe wasting in children by LHWs: • may slightly reduce improvement from severe wasting (RR 0.93, 95% CI 0.86 to 0.99; 1 RCT, 789 participants; low certainty); • may slightly increase non-response to treatment (RR 1.44, 95% CI 1.04 to 2.01; 1 RCT, 789 participants; low certainty); • may result in little or no difference in the number of children with WHZ above -2 on discharge (RR 0.94, 95% CI 0.28 to 3.18; 1 RCT, 789 participants; low certainty); • probably results in little or no difference in the number of children with WHZ between -3 and -2 on discharge (RR 1.09, 95% CI 0.87 to 1.36; 1 RCT, 789 participants; moderate certainty); • probably results in little or no difference in the number of children with WHZ below -3 (severe wasting) on discharge (RR 1.23, 95% CI 0.75 to 2.04; 1 RCT, 789 participants; moderate certainty); • probably results in little or no difference in the number of children with MUAC equal to or greater than 115 mm on discharge (RR 0.99, 95% CI 0.93 to 1.06; 1 RCT, 789 participants; moderate certainty); • results in little or no difference in weight gain per day (mean weight gain 0.50 g/kg/day higher, 95% CI 1.74 lower to 2.74 higher; 1 RCT, 571 participants; high certainty); • probably has little or no effect on relapse of severe wasting (RR 1.03, 95% CI 0.69 to 1.54; 1 RCT, 649 participants; moderate certainty); • may have little or no effect on mortality among children with severe wasting (RR 0.46, 95% CI 0.04 to 5.98; 1 RCT, 829 participants; low certainty); • probably has little or no effect on the transfer of children with severe wasting to inpatient care (RR 3.71, 95% CI 0.36 to 38.23; 1 RCT, 829 participants; moderate certainty); and • probably has little or no effect on the default of children with severe wasting (RR 1.48, 95% CI 0.65 to 3.40; 1 RCT, 829 participants; moderate certainty). The evidence was very uncertain for total MUAC gain, MUAC gain per day, total weight gain, treatment coverage, and transfer to another LHW site or health facility. No studies examined sustained recovery, deterioration to severe wasting, appropriate identification of children with wasting or oedema, appropriate referral of children with moderate or severe wasting, adherence, or adverse effects and other harms.

AUTHORS' CONCLUSIONS

Identification and treatment of severe wasting in children who do not require inpatient care by LHWs, compared with treatment by health professionals, may lead to similar or slightly poorer outcomes. We found only two RCTs, and the evidence from non-randomised studies was of very low certainty for all outcomes due to serious risks of bias and imprecision. No studies included children aged under 6 months. Future studies must address these methodological issues.

An mHealth tool for community health workers to improve caregiver knowledge of child health in the Amazon: An effectiveness-implementation hybrid evaluation

When community health workers (CHWs) are effective, they can teach healthy child rearing practices in their communities and improve child health and development outcomes. An effective mHealth tool can improve the capacity of CHWs to transmit knowledge to caregivers. This article evaluates the implementation of an mHealth tool in a CHW program in the Amazon of Peru. The intervention was designed, implemented, and evaluated with the guidance of multiple implementation science tools. A Hybrid Type 3 evaluation design was used to test the effectiveness of the implementation strategies and appropriateness of the intervention. The implementation outcomes: acceptability, adoption, dosage, and fidelity were analyzed with mixed methods approach to determine if the intervention was successfully installed in the CHW program. The service outcome, knowledge scores, was analyzed with an independent samples t-test and one way ANOVA to determine the effect of the program. The implementation strategies resulted in high degrees of acceptability, adoption, and fidelity of the mHealth tool. The surveillance component of the mHealth tools was not adequately adopted. The group of caregivers that received home visits with the mHealth tool (N = 48) had significantly higher knowledge scores (+1.26 standard deviations) than those in the control group (N = 138) (t(184) = -4.39, p<0.001). The COVID-19 pandemic significantly decreased the dosage of the intervention received by the participants. The CHEST App intervention is a promising tool to improve the capacity of CHWs during their home visits. Trial registered with ISRCTN on 11/29/2018 at https://doi.org/10.1186/ISRCTN43591826.

The Use of Implementation Science Tools to Design, Implement, and Monitor a Community-Based mHealth Intervention for Child Health in the Amazon

It is essential to analyze the local context and implementation components to effectively deliver evidence-based solutions to public health problems. Tools provided by the field of implementation science can guide practitioners through a comprehensive implementation process, making innovations more adaptable, efficient, and sustainable. It is equally important to report on the design and implementation process so others can analyze, replicate, and improve on the progress made from an intervention. The current study reports on the design and implementation of an mHealth intervention to improve child health in the Amazon of Peru. The study aims to provide insight into how an implementation science tool can be used to improve implementation and reporting of an evidence-based intervention in a global health setting.

Methods: Implementation of a community-based mHealth intervention is analyzed and reported through the lens of the Active Implementation Frameworks (AIF). The AIF is used to analyze the design, implementation, adaptation, and monitoring of the intervention. The implementation process is categorized in the four stages of implementation. The results of the analysis and subsequent implementation activities are reported.

Results: The exploration stage was used to learn about the local context in the Amazonian communities and identify an evidence-based solution to address poor child health. Several potential solutions were combined to create an innovative mHealth tool. During the installation stage, the stakeholders worked together to improve the intervention and plan for implementation through human-centered design. The providers in the field were trained and data was gathered to monitor implementation. During initial implementation stage, electronic tablets were distributed to community health agents and continuous quality improvement activities allowed for rapid improvements to be implemented. The intervention moved on to full implementation stage as acceptance and fidelity approached 100%.

Conclusion: The AIF highlighted several potential barriers to implementation that may have been overlooked without the guidance of a science-based implementation tool. Reporting on the implementation process shows how implementation science tools can be used to foresee and address potential threats to successful implementation. The results of this study provide insight into the components of implementation in Amazonian communities, as well as the process of using implementation science tools in any global health setting.