Problem

Each year more than 220 million women worldwide have an unmet need for contraception, resulting in over 300,000 maternal deaths from pregnancy-related complications. Unmet need for family planning can be attributed to insufficient knowledge about family planning and access to family planning services. 

During our pilot program in 2022, we noticed that this problem is only more prevalent among rural women. Rural women in Nigeria have fewer years of education, lower income, and worse health outcomes than their urban counterparts. The prevailing barriers to access family planning information and services faced particularly by rural women are: lack of trained medical personnel, stockouted healthcare facilities located far from their communities. For example, Kebbi state has only 144 doctors to support the population of over 5 million people, which translates to 1 doctor per every 50,000; a far cry from the WHO recommended figure of 1 doctor per every 1000 people.

Lafiya Nigeria offers in-person family planning counselling and administration of contraceptives free of charge. This model has proven to be highly cost-effective and is currently replicated in another state. However, we have identified one missing part of the solution - an mHealth component that can be used to offer educational information about sexual and reproductive health, send reminders for next doses of contraception, connect patients with the locations of family planning service providers, and provide up-to-date information about the stock levels. We believe that an mHealth component has a potential to become a key part of our comprehensive solution for a cost-effective family planning solution.

Evidence 

The proliferation of mobile phone ownership in LMICs has enabled digital technologies to provide family health information among users living in hard-to-reach areas. Mobile health solutions have been found to reduce costs of health care whilst improving the quality of care. The evidence has been so robust that it has resulted in the WHO releasing the guideline Recommendations on Digital Interventions for Health System Strengthening and endorsing the use of mobile health technologies in interventions targeting communities in LMICs.

The previous uses of mHealth family planning platforms showed their effectiveness in the increase of the contraceptive uptake. The users of mHealth platforms could seek information about family planning and related resources from the comfort of their home rather than going to a clinic or a health care provider. 

Family planning mHealth interventions have shown promising results across different demographic and geographies, adopting unique solutions to best match the needs of the targeted communities:

• A study of SMS reminders encouraging women in urban Mozambique to use family planning services showed that text message reminders are a promising nudge that increases the probability that women receive contraception.
• A study of SMS reminders encouraging families in Indonesia to use family planning services has showed the importance of text reminders on improved results of contraceptive usage.
• A study analysing program data and promotional approaches to inform best practices from a mobile phone-based reproductive health message program in Afghanistan highlighted SMS blast promotions as one of the most effective strategies
• A formative study of mobile phone use for family planning among young people in Sierra Leone showed that SMS was the scalable channel for demand creation
• An RCT of the impact of a family planning mHealth service in Kenya found that a mobile messaging service significantly improved knowledge of family planning among consumers. The data shows an increase in knowledge by 13%.
• A study of impact on mHealth on contraceptive usage in LMICs collected evidence to suggest that mobile phone interventions utilising behavioural change technique are an effective method of increasing modern contraceptive use.
• A study of the effects of a digital health tool (Smart Couple) among couples of reproductive age in Kaduna City in Nigeria showed that modern method use increased significantly from 36% to 50% among women and from 35% to 41% among men.
• A study of the effects of the smart client digital health tool among women of reproductive age in Kaduna city in Nigeria showed that a significant increase in modern contraceptive use.
• A study of the development of a mHealth intervention to support post-abortion family planning in Cambodia showed a significant increase in contraceptive usage between the intervention and control group at 4 months.
• A systematic review and meta-analysis of mobile health intervention for contraceptive use showed that mHealth intervention significantly improves contraceptive use, particularly app-based intervention as compared to text-based one.
• A qualitative study in peri-urban Nairobi on the use of digital media for family planning information showed that women felt more comfortable sharing FP information in digital spaces due to greater privacy and reduced stigma.
• A feasibility study on providing support to pregnant women and new mothers through moderated WhatsApp groups found that participants of a mobile-based support group reported a higher rate of postpartum long acting reversible contraception uptake than the general patient population.

There is a strong evidence base that mHealth interventions can result in the significant increase in contraceptive uptake. The level of impact achieved depends on the exact program design and the needs of the targeted demographic. 

Solution

Lafiya Nigeria team has identified the existing gaps in the current family planning landscape and the potential of a well-designed mHealth component to address the barriers faced by women with unmet need for contraception. An example of a mHealth solution within the existing Lafiya Nigeria model could fulfil some or all of the following functions:

1. It would act as a first level of a client funnel by reaching women with an unmet need for contraception. The service would provide a dual role for new users: 
   (i) offer information about family planning options, side effects, and benefits;
   (ii) connect them with a Lafiya Sister or another healthcare provider located nearby to facilitate the access to an in-person family planning counselling.
   
   Our team has some initial ideas in regards to social marketing strategies that could be used to spread the awareness of the tool among the targeted communities by leveraging female only networks in rural areas. 
    
2. It would send reminders to the existing users of Lafiya Nigeria program to notify them about the timing of their next dose. Lafiya Nigeria is currently focusing on the distribution of DMPA-SC, which needs to be reinjected every 13 weeks for continued usage; however, the reminders could also be sent to users of other types of contraceptives requiring regular visits. 
    
3. It would provide up-to-date information about the level of stock of different family planning products located in nearby health care clinics, allowing women to make an autonomous choice of their preferred contraceptive option.
   
   This version of an mHealth solution would require working closely with the state governments to ensure that there is an effective management of health data across clinics and providers. Our team has a strong working relationship with the government and could leverage that to build a comprehensive solution, addressing both the gaps in knowledge about family planning and the availability of products and trained medical personnel. 

Theory of Change

The following theory of change shows the impact of an mHealth component of the Lafiya Nigeria model.

Updates and plans

The initial research on this idea has demonstrated a strong evidence base and a good organisational fit to solve the problem. This fit comes from a successful pilot project that Lafiya Nigeria rolled out, culminating in:

(i) a database of rural Nigerian women with the unmet demand for contraception;

(ii) a network of health providers across different clinics and health facilities in over 60% of LGAs within targeted states;

(iii) strong relationships with the Ministry of Health on state and federal level;

(iv) an experienced and dedicated team with a proven track record of delivering global health interventions. 

Activities conducted

The Lafiya Nigeria team has conducted an initial round of expert interviews from IDInsights and Center for Global Development; and practitioners of mobile-based interventions from India (Suvita) and Kenya (M-Schule). 

Those interviews have given us a good starting point to evaluate existing tools and identify any technological challenges this project would entail. We have also recruited volunteers with backgrounds in programming and software development from Stanford and Berkeley to bridge the capability gap within our team.

Next steps

Our team will now conduct deeper analysis of the identified solutions, including assessing their feasibility, building a cost-effectiveness model, and conducting initial conversations with the state governments to understand how this project would align with their current priorities. 

To identify the features and format of the tool, we are seeking to answer the following questions:

1. Who is the targeted demographic (urban/rural, age, level of literacy) at scale?
2. What is the preferred channel for this solution (SMS, Whatsapp, chatbot, app)? What is the cost and feasibility of developing a solution using this channel?
3. What are the human capital gaps within the team to develop and manage this tool?
4. What is the most impactful use case of this tool for our users?
5. What is the vision for scaling this solution across the country?
6. How does this project align with the priorities of the Nigerian Ministry of Health on the federal and state level?
7. Can this solution be used in other interventions beyond Lafiya Nigeria? Which stakeholders would be interested in paying to adopt, adapt, and scale this solution in other contexts?
8. What is the cost-effectiveness of this tool and its forecasted impact on reducing maternal mortality?
9. What is the success metric of this tool and how can it be measured on the pilot level? 

We anticipate adding more follow-up and detailed questions as we conduct our in-depth research.

How you can help

If you are interested in this cause area and would like to support this project, you can help in three ways:

1. We are looking for technical experts with experience in mHealth interventions, particularly in the context of LMICs, to provide feedback and expertise to support the development of this project. 
2. We are looking for volunteers to share with us their time to conduct further research. Individuals with experience in mobile interventions.
3. Since we are still evaluating the exact rollout of the programme, we are putting together different scenarios of how the tool would impact our base-case budget. We are seeking funding to aid us to move ahead from desk research to an MVP, after our deep-dive research.