Table 4.

Case study characteristics for investigating the technological and behavioral performance of MOTECH in Ghana

Context	Despite the growing use of technology in the health sector, little evidence is available on the technological performance of mobile health programs nor on the willingness of target users to utilize these technologies as intended (behavioral performance). In this case study of the Mobile Technology for Health (MOTECH) program in Ghana, we assess the platform’s effectiveness in delivering messages, along with user response across sites in five districts from 2011–2014.
Objective	1. Determine what proportion of expected messages are successfully ‘pushed’ out of the MOTECH platform; and 2. Describe differences in rates of active listening among users across study sites, during pregnancy and postpartum, and across thematic content areas.
Study design	Naturalistic
The case	The technological and behavioral performance of the MOTECH program in Ghana
Data collection	System generated data on patient uploads, registration, message delivery and user engagement
Data analysis	Proportions and frequencies; Confidence intervals at the 95% level to assess statistical differences in rates of active listening across thematic content areas.
Key findings	• A total of 7,370 women were enrolled in MM during pregnancy and 14,867 women were enrolled postpartum. • While providers were able to register and upload patient-level health information using CDA, the majority of these uploads occurred in Community-based facilities versus Health Centers where RMNCH client loads are higher. • For MM, 25% or less of expected messages were received by pregnant women, despite the majority (>77%) owning a private mobile phone. • While over 80% of messages received by pregnant women were listened to, postpartum rates of listening declined over time. • Only 25% of pregnant women received and listened to at least 1 first trimester message. • By 6–12 months postpartum, less than 6% of enrolled women were exposed to at least one message.
Limitations	• While data on the number of individuals enrolled into MOTECH are presented, the true denominator from which these individuals are drawn remains unknown. Further details on the characteristics of pregnant and postpartum women not enrolled into Mobile Midwife are also not available. Research at a household level is recommended to better measure the population level coverage and sustained engagement in the program. • Client level analyses of active listening were restricted to unique phone numbers and women with their own phones or access to a phone in their household. Given the common practice of sharing phones and phone numbers, this may have introduced selection bias and led to an overestimate of active listening status. • While we sought to extract data on reminders sent to clients and nurses, these efforts were unsuccessful. Future mHealth platforms should consider ways to improve routine data extraction and use of data to allow for continuous program monitoring. • Finally, efforts to explore linkages between messaging exposure and careseeking were mired by missing data. Future programs should consider ways to improve the accuracy and completeness in data reporting as well as linkages with existing health information systems which collect data on service utilization and reported practices.