mHealth Phone Intervention to Reduce Maternal Deaths and Morbidity in Cameroon: Protocol for Translational Adaptation

International Journal of Women's Health, Volume 14, Year 2022

Interpretation

Purpose: The purpose of this NIH-funded protocol is to adapt (Aim 1) and pilot test (Aim 2) an mHealth intervention to improve maternal and child health in Cameroon. We will adapt the 24/7 University of Alabama at Birmingham Medical Information Service via Telephone (MIST) provider support system to mMIST (mobile MIST) for peripheral providers who provide healthcare to pregnant and postpartum women and newborns in Cameroon. Methods: In Aim 1, we apply qualitative and participatory methods (in-depth interviews and focus groups with key stakeholders) to inform the adaptation of mMIST for use in Cameroon. We use the sequential phases of the ADAPT-ITT framework to iteratively adapt mMIST incorporating qualitative findings and tailoring for local contexts. In Aim 2, we test the adapted intervention for feasibility and acceptability in Ndop, Cameroon. Results: This study is ongoing at the time that this protocol is published. Conclusion: The adaptation, refinement, and pilot testing of mMIST will be used to inform a larger-scale stepped wedged cluster randomized controlled effectiveness trial. If successful, this mHealth intervention could be a powerful tool enabling providers in low-resource settings to deliver improved pregnancy care, thereby reducing maternal and fetal deaths. Ethics approval was provided by the Cameroon Baptist Convention Health Board Institutional Review Board, under IRB study number: IRB2020-49 and the UAB Institutional Review Board under number: IRB-300006254. Informed consent will be obtained from human study participants, and this protocol is in compliance with all guidelines outlined in the Declaration of Helsinki. We will establish community and stakeholder committees and working groups, with members from both the United States and Cameroon, to inform all steps of this study. The Local Advisory Committee (LAC) will meet monthly to provide local perspectives and troubleshoot any arising issues, as needed. The LAC will include 10–12 stakeholders who will provide insight to all aspects of the mMIST adaptation. An Expert Providers Committee (EPC) will include 12–15 expert clinical providers in Cameroon; all EPC members will be practicing OB/GYNs, pediatricians, nurses, and midwives. The EPC will be convened about every two months. A Technology Working Group (TWG) will be established to provide guidance on the mMIST prototype. The TWG will include US and Cameroon-based technology experts and will assist the principal investigators to troubleshoot barriers related to infrastructure and prototyping. The TWG will include no more than 10 members. Feedback from these groups will enhance the rigor, replicability, and scalability of the adapted mMIST intervention. Our key partner, the Cameroon Baptist Convention Health System (CBCHS), is a major healthcare provider responsible for over 90 health facilities (7 hospitals and 85 health centers) in six of the ten administrative regions of Cameroon. The first step in adapting MIST is to conduct interviews and focus groups with key stakeholders to inform the adaptation of UAB’s MIST to the local context of Cameroon. In order to do so, participants will be recruited from six different categories: the Ministry of Health, primary providers, currently pregnant women, previously pregnant women, and mobile service provider leadership. We estimate that in-depth interviews will be conducted with around 12 maternity providers, 10 previously pregnant women who suffered an adverse outcome, 10 health system administrators and clinical staff, 8 mobile service providers, and 6 representatives with the Ministry of Health. Three focus groups are planned with currently pregnant women. Although estimates are presented data collection will continue until the team achieves data saturation. Qualitative data collection will occur in English and Pidgin English, depending on the preference of the study participant. In-depth interviews and focus groups will be audio-recorded using digital recorders; audio files will be uploaded to a protected UAB server. Audio files will first be transcribed into Microsoft Word by an expert transcriptionist. Transcribed files in Pidgin will then be translated to American English. Qualitative coding and analysis will be conducted using a modified Grounded Theory47 approach in which key conceptual domains are inductively derived from the data. NVivo software will be used for coding and analysis. A preliminary coding scheme will be developed based on the topics in the interview guide and relevant literature. The coding scheme will be appended during review based on emerging themes and topics, resulting in a refined qualitative coding scheme. Transcripts will be re-reviewed for more detailed, second-level fine coding. Attention to trustworthiness (credibility, dependability and transferability) will be given though inclusivity of participant invitation, recruitment being conducted by a known an trusted local research team member, and during data analysis, seeking agreement and consensus of meaning among co-researchers, experts, and research participants.48 Results will inform the adaptation of MIST to mMIST. We will use the sequential phases of the ADAPT-ITT framework to iteratively adapt MIST to mMIST to incorporate the qualitative findings and adapt for local contexts. ADAPT-ITT is a pragmatic 8-step model developed for the adaptation and tailoring on HIV interventions that has been extended to other areas of research.49 Adaptation is the process of modifying an intervention without contradicting its core elements or internal logic.20 Attention to culture and contexts (both inner and outer) of a new environment or group promote relevance and acceptability of interventions.20,49 ADAPT-ITT phases and tasks for mMIST are listed in Table 1. Steps of ADAPT-ITT for the mMIST Adaptation51 After a draft of mMIST is developed (technical design in Figure 1), we will share process documents and demonstrate mMIST to members of our community groups. We will collect verbal feedback using a standardized question set to assess the quality and acceptability of the adaptation. After evaluating responses, we will make additional refinements to mMIST to test for feasibility and acceptability. mMIST system structure with call flow process. The goal in conducting a small-scale implementation of mMIST is to refine the adaptation using constructs from Bowen’s model of feasibility and acceptability, see Table 2, prior to large-scale implementation and evaluation of mMIST. Feasibility of mMIST in one health district (Ndop) will be assessed with a primary focus on demand and acceptability.50 Demand will be assessed using an inventory system of the number of times providers access the hotline and electronic files. Acceptability will be assessed through satisfaction surveys and medical record reviews to determine adherence to advice received. The satisfaction survey will include structured and semi-structured sections; the structured section will consist of five Likert scale items that will be analyzed descriptively to determine measures of central tendency. The open-ended section will consist of four questions on recommended changes that will be analyzed through content analyses. The secondary outcome is feasibility, while demand and acceptability will be primary. Bowen’s Model of Feasibility and Assessment Measures In order to test mMIST on a smaller scale in the pilot, all maternity providers at a minimum of five maternity centers in one district in Cameroon will be selected to utilize the system. This will include approximately 25–30 providers who will be trained via Zoom on study protocols and intervention functionality. Once mMIST is launched, we expect, on average, a minimum of 1 call every 2 days as an acceptable demand level. We expect that in the survey, at least 70% of providers will find mMIST acceptable. Training will also be provided to support staff who will answer the mMIST line, primary maternity and pediatric providers, and administrators (who will be involved in supporting timely transfer of high-risk patients). Maternity healthcare workers who answer the mMIST line, called first line responders, and maternity service heads (responsible for the target health units) will attend a 1-day workshop on mMIST. Other providers will be trained by their maternity service leads (train-the-trainer model). Trained maternity service leads will be provided with detailed training and marketing materials (eg cards to be kept by providers, clinic posters, etc.) to train their maternity providers (eg physicians, nurses, skilled birth attendants, etc.) and monitored by the research team. Electronic logs from mMIST will be assessed for number, type, and location of providers using the system and number of calls made in total, regardless of which provider initiates the call. mMIST first line responders will keep a paper record of the reason for each call, advice or referral given to the patient post-call, and assessment of whether the patient followed the advice or referral. An oversight team consisting of investigators and providers will monitor accuracy of advice given through auditing of a random sample of taped calls quarterly. Qualtrics surveys, record reviews guided by an assessment matrix, and follow-up in-depth interviews using a standardized guide will be used to assess acceptability, demand, implementation, practicality, adaptation, integration, and expansion. Administrative data collection on maternal and perinatal deaths will be optimized at start of project and collected on a rolling basis through the project. A database will be developed to log provider call information. Data collected through a log or auditing of taped calls will include date, time, call duration, caller type (eg, nurse, midwife, physician, etc.) location, patient type (eg, pregnant, postpartum, or baby), call reason, respondent (eg, maternity worker, specialist expert, both), recommendation, and follow-up on advice. Provider demand will be quantified by the number of calls by location. Satisfaction survey and follow up interview data will be analyzed to gauge acceptability and feasibility. Once all providers have been trained, the research team will supplement the existing data collection processes as needed to ensure that all components of feasibility can be evaluated as planned. Implementation will be on a rolling basis with lessons learned from each center informing the roll out in the next center. After the implementation cycle, structured surveys on feasibility domains will be shared with providers (peripheral and experts). Findings from survey data, chart reviews, and interviews with experts and related stakeholders will be used to inform updates to mMIST prior to testing through a subsequent cluster stepped wedge randomized controlled trial.

AI Digest

Study Justification:

– The purpose of this study is to adapt and pilot test an mHealth intervention to improve maternal and child health in Cameroon.
– The study aims to reduce maternal and fetal deaths by enabling healthcare providers in low-resource settings to deliver improved pregnancy care.

Highlights:

– The study will adapt the University of Alabama at Birmingham Medical Information Service via Telephone (MIST) provider support system to mMIST (mobile MIST) for peripheral providers in Cameroon.
– Qualitative and participatory methods will be used to inform the adaptation of mMIST for use in Cameroon.
– The adapted intervention will be tested for feasibility and acceptability in Ndop, Cameroon.
– The results of this study will inform a larger-scale effectiveness trial to evaluate the impact of the mHealth intervention on maternal and child health outcomes.

Recommendations:

– Based on the results of the study, it is recommended to implement the adapted mMIST intervention on a larger scale to assess its effectiveness in reducing maternal and fetal deaths.
– Policy makers should consider integrating mHealth interventions into healthcare systems in low-resource settings to improve pregnancy care and reduce maternal and child mortality.

Key Role Players:

– Local Advisory Committee (LAC): 10-12 stakeholders providing local perspectives and insight to the mMIST adaptation.
– Expert Providers Committee (EPC): 12-15 expert clinical providers in Cameroon, including OB/GYNs, pediatricians, nurses, and midwives.
– Technology Working Group (TWG): US and Cameroon-based technology experts providing guidance on the mMIST prototype.

Cost Items for Planning Recommendations:

– Training: Budget for training maternity providers, support staff, and administrators on study protocols and intervention functionality.
– Technology Infrastructure: Budget for necessary technology infrastructure to support the mMIST intervention.
– Marketing Materials: Budget for materials such as cards, posters, etc. to promote and train providers on mMIST.
– Data Collection and Analysis: Budget for data collection tools, transcription services, software licenses, and data analysis.
– Monitoring and Oversight: Budget for oversight team activities, including auditing of calls and monitoring accuracy of advice given.
– Implementation and Rollout: Budget for implementing the mMIST intervention in multiple centers, including lessons learned and updates to the system.
– Evaluation: Budget for surveys, chart reviews, interviews, and other evaluation activities to assess feasibility and acceptability of mMIST.
Please note that the provided information is based on the given description and may not include all details.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on an ongoing study protocol and describes the methods and plans for adapting and pilot testing an mHealth intervention. The abstract provides information on the study design, ethics approval, recruitment, data collection, and analysis methods. However, since the study is ongoing, there are no results or conclusions presented. To improve the strength of the evidence, the abstract could include preliminary findings or expected outcomes based on the study design and methods. Additionally, providing more details on the sample size, inclusion criteria, and potential limitations of the study would enhance the clarity and robustness of the evidence.

Abstract

Ethics approval was provided by the Cameroon Baptist Convention Health Board Institutional Review Board, under IRB study number: IRB2020-49 and the UAB Institutional Review Board under number: IRB-300006254. Informed consent will be obtained from human study participants, and this protocol is in compliance with all guidelines outlined in the Declaration of Helsinki. We will establish community and stakeholder committees and working groups, with members from both the United States and Cameroon, to inform all steps of this study. The Local Advisory Committee (LAC) will meet monthly to provide local perspectives and troubleshoot any arising issues, as needed. The LAC will include 10–12 stakeholders who will provide insight to all aspects of the mMIST adaptation. An Expert Providers Committee (EPC) will include 12–15 expert clinical providers in Cameroon; all EPC members will be practicing OB/GYNs, pediatricians, nurses, and midwives. The EPC will be convened about every two months. A Technology Working Group (TWG) will be established to provide guidance on the mMIST prototype. The TWG will include US and Cameroon-based technology experts and will assist the principal investigators to troubleshoot barriers related to infrastructure and prototyping. The TWG will include no more than 10 members. Feedback from these groups will enhance the rigor, replicability, and scalability of the adapted mMIST intervention. Our key partner, the Cameroon Baptist Convention Health System (CBCHS), is a major healthcare provider responsible for over 90 health facilities (7 hospitals and 85 health centers) in six of the ten administrative regions of Cameroon. The first step in adapting MIST is to conduct interviews and focus groups with key stakeholders to inform the adaptation of UAB’s MIST to the local context of Cameroon. In order to do so, participants will be recruited from six different categories: the Ministry of Health, primary providers, currently pregnant women, previously pregnant women, and mobile service provider leadership. We estimate that in-depth interviews will be conducted with around 12 maternity providers, 10 previously pregnant women who suffered an adverse outcome, 10 health system administrators and clinical staff, 8 mobile service providers, and 6 representatives with the Ministry of Health. Three focus groups are planned with currently pregnant women. Although estimates are presented data collection will continue until the team achieves data saturation. Qualitative data collection will occur in English and Pidgin English, depending on the preference of the study participant. In-depth interviews and focus groups will be audio-recorded using digital recorders; audio files will be uploaded to a protected UAB server. Audio files will first be transcribed into Microsoft Word by an expert transcriptionist. Transcribed files in Pidgin will then be translated to American English. Qualitative coding and analysis will be conducted using a modified Grounded Theory47 approach in which key conceptual domains are inductively derived from the data. NVivo software will be used for coding and analysis. A preliminary coding scheme will be developed based on the topics in the interview guide and relevant literature. The coding scheme will be appended during review based on emerging themes and topics, resulting in a refined qualitative coding scheme. Transcripts will be re-reviewed for more detailed, second-level fine coding. Attention to trustworthiness (credibility, dependability and transferability) will be given though inclusivity of participant invitation, recruitment being conducted by a known an trusted local research team member, and during data analysis, seeking agreement and consensus of meaning among co-researchers, experts, and research participants.48 Results will inform the adaptation of MIST to mMIST. We will use the sequential phases of the ADAPT-ITT framework to iteratively adapt MIST to mMIST to incorporate the qualitative findings and adapt for local contexts. ADAPT-ITT is a pragmatic 8-step model developed for the adaptation and tailoring on HIV interventions that has been extended to other areas of research.49 Adaptation is the process of modifying an intervention without contradicting its core elements or internal logic.20 Attention to culture and contexts (both inner and outer) of a new environment or group promote relevance and acceptability of interventions.20,49 ADAPT-ITT phases and tasks for mMIST are listed in Table 1. Steps of ADAPT-ITT for the mMIST Adaptation51 After a draft of mMIST is developed (technical design in Figure 1), we will share process documents and demonstrate mMIST to members of our community groups. We will collect verbal feedback using a standardized question set to assess the quality and acceptability of the adaptation. After evaluating responses, we will make additional refinements to mMIST to test for feasibility and acceptability. mMIST system structure with call flow process. The goal in conducting a small-scale implementation of mMIST is to refine the adaptation using constructs from Bowen’s model of feasibility and acceptability, see Table 2, prior to large-scale implementation and evaluation of mMIST. Feasibility of mMIST in one health district (Ndop) will be assessed with a primary focus on demand and acceptability.50 Demand will be assessed using an inventory system of the number of times providers access the hotline and electronic files. Acceptability will be assessed through satisfaction surveys and medical record reviews to determine adherence to advice received. The satisfaction survey will include structured and semi-structured sections; the structured section will consist of five Likert scale items that will be analyzed descriptively to determine measures of central tendency. The open-ended section will consist of four questions on recommended changes that will be analyzed through content analyses. The secondary outcome is feasibility, while demand and acceptability will be primary. Bowen’s Model of Feasibility and Assessment Measures In order to test mMIST on a smaller scale in the pilot, all maternity providers at a minimum of five maternity centers in one district in Cameroon will be selected to utilize the system. This will include approximately 25–30 providers who will be trained via Zoom on study protocols and intervention functionality. Once mMIST is launched, we expect, on average, a minimum of 1 call every 2 days as an acceptable demand level. We expect that in the survey, at least 70% of providers will find mMIST acceptable. Training will also be provided to support staff who will answer the mMIST line, primary maternity and pediatric providers, and administrators (who will be involved in supporting timely transfer of high-risk patients). Maternity healthcare workers who answer the mMIST line, called first line responders, and maternity service heads (responsible for the target health units) will attend a 1-day workshop on mMIST. Other providers will be trained by their maternity service leads (train-the-trainer model). Trained maternity service leads will be provided with detailed training and marketing materials (eg cards to be kept by providers, clinic posters, etc.) to train their maternity providers (eg physicians, nurses, skilled birth attendants, etc.) and monitored by the research team. Electronic logs from mMIST will be assessed for number, type, and location of providers using the system and number of calls made in total, regardless of which provider initiates the call. mMIST first line responders will keep a paper record of the reason for each call, advice or referral given to the patient post-call, and assessment of whether the patient followed the advice or referral. An oversight team consisting of investigators and providers will monitor accuracy of advice given through auditing of a random sample of taped calls quarterly. Qualtrics surveys, record reviews guided by an assessment matrix, and follow-up in-depth interviews using a standardized guide will be used to assess acceptability, demand, implementation, practicality, adaptation, integration, and expansion. Administrative data collection on maternal and perinatal deaths will be optimized at start of project and collected on a rolling basis through the project. A database will be developed to log provider call information. Data collected through a log or auditing of taped calls will include date, time, call duration, caller type (eg, nurse, midwife, physician, etc.) location, patient type (eg, pregnant, postpartum, or baby), call reason, respondent (eg, maternity worker, specialist expert, both), recommendation, and follow-up on advice. Provider demand will be quantified by the number of calls by location. Satisfaction survey and follow up interview data will be analyzed to gauge acceptability and feasibility. Once all providers have been trained, the research team will supplement the existing data collection processes as needed to ensure that all components of feasibility can be evaluated as planned. Implementation will be on a rolling basis with lessons learned from each center informing the roll out in the next center. After the implementation cycle, structured surveys on feasibility domains will be shared with providers (peripheral and experts). Findings from survey data, chart reviews, and interviews with experts and related stakeholders will be used to inform updates to mMIST prior to testing through a subsequent cluster stepped wedge randomized controlled trial.

Materials

N/A

Innovations

The recommendation described in the publication is to develop an mHealth phone intervention called mMIST (mobile MIST) to improve access to maternal health in Cameroon. The mMIST intervention is an adaptation of the 24/7 University of Alabama at Birmingham Medical Information Service via Telephone (MIST) provider support system. The goal of mMIST is to enable peripheral healthcare providers in Cameroon to deliver improved pregnancy care, thereby reducing maternal and fetal deaths.

The development of mMIST involves two aims. In Aim 1, qualitative and participatory methods such as in-depth interviews and focus groups with key stakeholders are used to inform the adaptation of mMIST for use in Cameroon. The ADAPT-ITT framework, which is a pragmatic 8-step model for adaptation and tailoring of interventions, is used to iteratively adapt mMIST incorporating qualitative findings and tailoring for local contexts.

In Aim 2, the adapted mMIST intervention is pilot tested for feasibility and acceptability in Ndop, Cameroon. The pilot testing aims to refine the adaptation using constructs from Bowen’s model of feasibility and acceptability. Feasibility is assessed through demand and acceptability, which are measured using an inventory system, satisfaction surveys, and medical record reviews. The goal is to assess the demand for mMIST and determine the acceptability of the intervention among healthcare providers.

The results of the pilot testing will inform the adaptation of mMIST for a larger-scale stepped wedged cluster randomized controlled effectiveness trial. If successful, mMIST could be a powerful tool to improve access to maternal health in low-resource settings by enabling healthcare providers to deliver better pregnancy care and reduce maternal and fetal deaths.

The publication describing this recommendation is titled “mHealth Phone Intervention to Reduce Maternal Deaths and Morbidity in Cameroon: Protocol for Translational Adaptation” and was published in the International Journal of Women’s Health in 2022.

AI Innovations Description

The publication describing this recommendation is titled “mHealth Phone Intervention to Reduce Maternal Deaths and Morbidity in Cameroon: Protocol for Translational Adaptation” and was published in the International Journal of Women’s Health in 2022.

AI Innovations Methodology

The methodology to simulate the impact of the main recommendations described in the abstract on improving access to maternal health could involve the following steps:

1. Define the target population: Identify the specific population in Cameroon that would benefit from improved access to maternal health. This could include pregnant women, postpartum women, and newborns, as well as peripheral healthcare providers who deliver pregnancy care.

2. Collect baseline data: Gather existing data on maternal and fetal deaths, as well as the current state of access to maternal health services in the target population. This could include data on healthcare infrastructure, availability of trained healthcare providers, and utilization of existing services.

3. Develop a simulation model: Create a simulation model that represents the target population and the healthcare system in Cameroon. The model should incorporate relevant factors such as population demographics, healthcare infrastructure, availability of healthcare providers, and utilization patterns.

4. Incorporate the mMIST intervention: Introduce the mMIST intervention into the simulation model. This could involve simulating the implementation of the mMIST system in Ndop, Cameroon, as described in the publication. The model should consider the potential impact of mMIST on improving access to maternal health, such as increased availability of provider support, timely advice and referrals, and improved adherence to recommended care.

5. Simulate the intervention’s impact: Run the simulation model with the mMIST intervention implemented and observe the impact on access to maternal health. This could include measuring outcomes such as reduction in maternal and fetal deaths, increased utilization of maternal health services, and improved pregnancy care delivery by peripheral healthcare providers.

6. Sensitivity analysis: Conduct sensitivity analyses to explore the robustness of the simulation results. This could involve varying key parameters in the model, such as the demand for mMIST, acceptability among healthcare providers, and the effectiveness of the intervention, to assess the range of potential outcomes.

7. Interpret and communicate results: Analyze the simulation results and interpret the findings in terms of the impact of the mMIST intervention on improving access to maternal health in Cameroon. Communicate the results in a clear and concise manner, highlighting the potential benefits and limitations of the intervention.

It is important to note that this is a hypothetical methodology based on the information provided in the abstract. The actual simulation methodology may vary depending on the specific details and data available for the target population and context in Cameroon.

Author

Dima Health

Identifiers:

DOI: 10.2147/IJWH.S353919

Research Areas:

Community Interventions, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Technology and Innovations, Workforce

Study Countries:

Cameroon

Study Design:

Cohort Study, Cross Sectional Study, Grounded Theory, Phenomenological Study, randomised-control-trial

Study Approach:

Mixed-methods, Qualitative, Quantitative

Participants Gender:

Female