Theoretical framework

The ‘three delays’ model developed by Thaddeus and Maine9 provides a suitable framework for understanding the causes of maternal deaths. These are1 delay in recognising danger signs/decision to seek care,2 delays in reaching a medical facility and3 delay in receiving appropriate care once a facility is reached. We adopted the ‘three delays’ model as a framework to identify the barriers to obstetric care and assess whether a mobile phone-enhanced community-based maternal newborn health intervention that addressed delays 1 and 2 can help women to overcome these barriers. The ‘three delays’ model allows for an objective way to examine the complex interactions that may occur between women’s ability to make decisions to attend antenatal services, choose facility-based delivery services, recognise danger signs, travel to the health facility and ultimately receive quality care at the health facility during pregnancy and childbirth. This model has been applied previously in analyses of newborn death in several countries, including Tanzania and Uganda.10 11

Study design

We conducted a prospective cohort study utilising quantitative methods.

Study setting and participants

The study was done in East Rachuonyo within Homa Bay County, which is located in rural western Kenya beginning from May 2016 to March 2018. Homa Bay County has one of the highest maternal and neonatal mortality rates in the country. Homa Bay’s MMR is estimated at 583, compared with the national average of 488 and Kenya’s least-deprived counties that have rates below 200. East Rachuonyo was selected as it was implementing community maternal newborn health (CMNH) in which CHWs conduct home visits during pregnancy and the postpartum. CHWs in Kenya are unsalaried male and female persons, over the age of 18 years and with at least primary level education. CHWs are selected by local community members and then trained over a period of 6 weeks in basic modules on promotion of maternal, newborn and child health, prevention of preventable diseases, promotion of healthy lifestyle, prevention of injuries and accidents, community support for vulnerable people and addressing sexual-based and gender-based violence.12 CHWs work from community health units, which serve a population of 5000 people. Each community unit is linked to one health facility. One community unit has 6–16 CHWs, with each CHW responsible for approximately 500 people.13 14 Quarterly community dialogue days are in the community units to discuss on the performance of selected indicators and come up with an action plan. CHWs conduct two antenatal home visits at 12–16 and 32–34 weeks to promote birth and newborn care preparedness.15 They also conduct postnatal home visits on day 1, 3 and 7 to reinforce birth and newborn care and provide counselling for breastfeeding difficulties.15 The record of each home visit is entered longitudinally into a WHO-adapted CMNH register. Women registered in this CMNH register comprised the sampling frame for this study.

Eligibility and recruitment

Women were eligible to participate in the study if they were 15 years or older, less than or equal to 28 weeks gestation, planning to remain in the study area (up to 6 weeks postpartum), had access to a mobile phone and reported ability to read or had someone who could read SMS on their behalf.

The recruitment of participant started in the community when CHWs identified eligible women during their routine home visits. All women were enrolled into the CMNH register The CHWs briefly described the study and invited women to receive additional information at the respective Ministry of Health antenatal clinic. At the clinics, eligible women’s phone numbers and SMS preferences were recorded by sending a text message from their phone. This message included date of last normal menstrual period, preferred language (English, Kiswahili or Dholuo), preferred time for receiving SMS and preferred name. This text registered them within the mAccess platform. Participants were followed up to 6 weeks postpartum.

Sampling and intervention allocation

The sampling frame was all pregnant women living in East Rachuonyo during the study period and registered by the CHWs in the CMNH register. Cases were selected using convenience sampling into the study until the sample size was met. To avoid clustering of intervention participants in one region, each location within East Rachuonyo was allocated a weighted number of intervention participants to enrol based on its population density. We defined cases as those who received the standard of care that is, CMNH plus the mAccess intervention and the control group as those who received the standard of care only.

Intervention description

The core of mAccess is a two-way SMS messaging system that coordinates the sending of messages between a pregnant woman and staff. To start, a CHW uses a mobile survey to enrol a woman into the mAccess system during one of her monthly visits, specifying the woman’s estimated gestation. After enrolment, the woman automatically receives weekly messages describing what she can expect during her specific week of pregnancy. Participants received messages updating them how the baby was developing, how their bodies were responding, the different danger signs, need to identify a health facility and/or skilled birth attendant and birth partner of choice, and how to save money and prepare for the birth. After each message, the woman is prompted to ask questions from a live nurse. If she chooses this option, a live nurse is contacted and continues to follow-up with the woman through SMS text messaging until the woman’s questions are resolved. This is known as m-convo. Women participating in m-convo were eligible to receive National Health Insurance Fund (NHIF) yearly premiums, transport to the hospital and mother–baby care packs. M-convo also ensured that women had an interaction with the system and build-up trust in the system before they actually needed a service. The woman is also able to SMS the word ‘mHelp’ to ‘call for help’ if she has questions, feels ill or is in labour. In the case of illness or labour, a central dispatch sends an SMS survey to all trained motorcycle riders in the woman’s area asking a series of questions about their location and availability. Once a rider has been identified and is on his way, dispatch sends an SMS to the woman reassuring her that transport is on the way and to the woman’s preferred health facility notifying them to prepare for her arrival. This transport system is doubly innovative in that as it is not like the regular ‘Uber’ as it is firmly embedded within the national community health strategy. In the same way, CHWs are vetted for selection, the riders apply to the community health committee in charge of community units and undergo a vetting exercise after which they are trained on the importance of a quick response. Transport fares are agreed on on a community level and each community unit has 2–3 motorcycle riders. The riders are, thus, people that the community know and have vetted. Figure 1 summarises the process.

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Figure 1

Twenty-four-hour transport navigation system (Uber redefined).

Patient and public involvement statement

The development and implementation of the mAccess project and research questions was done collaboratively, involving the target population of pregnant and postpartum women, and private and public stakeholders (including mobile phone operators, the Homa Bay transport owners association, national and county health management teams, county communication and transport team, and the Homa Bay NHIF office). The project was in direct response to an existing gap in CMNH in the county. Prior to launching the mAccess project, the investigators on this project had worked with the local community members and the county health management team and launched a mobile phone-enhanced integrated community case management (iCCM) of pneumonia, malaria, diarrhoea and vitamin A supplementation in children aged 2–59 months in Homa Bay County.16 The team trained ~90 County and subcounty healthcare workers to be trainers of trainers in iCCM and CMNH, and further trained a total of 2604 CHWs and 251 community health extension workers in 245 community units across eight subcounties ensuring 100% coverage of the county with essential community child-based interventions.17 Unfortunately, pregnant and postpartum women were not covered by these services and there was a need to address this population while leveraging the existing structures that had been set up. The mAccess project was designed to use this existing framework of mobile phone-enhanced community-based health services and address a community-identified need. The team leveraged the existing CHWs to recruit participants. While participants were not involved in recruitment, they participated in the quarterly community dialogue meetings in which progress on CMNH was discussed and motorcycle vendors vetted and issues raised. Preliminary lay results, including video documentation, were presented to the county health management team as well as to each of the participating community units in which women came from. Final results will be provided to all stakeholders including participants involved in the study.

Sample size

Sample size was estimated based on the assumption that at baseline about 60.4% of women are delivered by a skilled birth attendant18 and hypothesised a 10% increase in the number of women delivered by a skilled birth attendant as a result of mAccess implementation. Using this difference in proportions, uncorrected χ² test and 80% power to detect a statistically significant difference at 5% significance level, the estimated required sample size was 353 each in control and intervention arm.

Statistical analysis

Frequencies with percentages were used to summarise categorical variables. Means and medians reporting the respective SDs and IQR were used to summarise continuous variables. Logistic regression analysis was used to assess whether mAccess intervention had any impact on cost of transport, time to delivery, number of ANC visits, PNC visits visits and adverse pregnancy outcomes, and control for the effect of confounding variables. A crude OR and 95% CI was determined for each of the outcomes. For all the adjusted analysis, we controlled for age and education level of women, which are known determinants of maternal healthcare seeking.19 Scrutiny of our data revealed that the missing values were randomly distributed across all observations. On the basis of the missing data pattern and critical peer-review of similar data, we assumed that the missing data did not depend on the unobserved data and were missing completely at random. Subsequently, we partitioned the data into two parts, one set containing the missing values and the other containing the non-missing values. A t-test of mean difference was carried out to test whether there existed any difference in the sample between the two data sets. The missing data did not bias the OR implying that the estimated parameters are not biassed by the absenteeism of the data. All analyses were done using STATA V.13.

Variables

The exposure variable of interest was receipt of the mAccess intervention.

The main outcome variables were cost of transport to place of delivery (measured in Kenyan Shillings), time taken to reach facility for delivery (measured in minutes and hours from the time the woman or birth partner makes a call for transport), number of ANC visits, number of PNC visits, pregnancy outcomes (defined as either miscarriage, stillbirth and live) and status of mother after birth (alive, dead and unknown). Potential confounders considered included age and education level of women.

Data sources

Data were derived from the CMNH registers that were compiled by CHWs during the routine implementation of CMNH service delivery. Study nurses abstracted the data collected and entered it into password-protected computers.