Can we design the next generation of digital health communication programs by leveraging the power of artificial intelligence to segment target audiences, bolster impact and deliver differentiated services? A machine learning analysis of survey data from rural India.

OBJECTIVES: Direct to beneficiary (D2B) mobile health communication programmes have been used to provide reproductive, maternal, neonatal and child health information to women and their families in a number of countries globally. Programmes to date have provided the same content, at the same frequency, using the same channel to large beneficiary populations. This manuscript presents a proof of concept approach that uses machine learning to segment populations of women with access to phones and their husbands into distinct clusters to support differential digital programme design and delivery. SETTING: Data used in this study were drawn from cross-sectional survey conducted in four districts of Madhya Pradesh, India. PARTICIPANTS: Study participant included pregnant women with access to a phone (n=5095) and their husbands (n=3842) RESULTS: We used an iterative process involving K-Means clustering and Lasso regression to segment couples into three distinct clusters. Cluster 1 (n=1408) tended to be poorer, less educated men and women, with low levels of digital access and skills. Cluster 2 (n=666) had a mid-level of digital access and skills among men but not women. Cluster 3 (n=1410) had high digital access and skill among men and moderate access and skills among women. Exposure to the D2B programme 'Kilkari' showed the greatest difference in Cluster 2, including an 8% difference in use of reversible modern contraceptives, 7% in child immunisation at 10 weeks, 3% in child immunisation at 9 months and 4% in the timeliness of immunisation at 10 weeks and 9 months. CONCLUSIONS: Findings suggest that segmenting populations into distinct clusters for differentiated programme design and delivery may serve to improve reach and impact. TRIAL REGISTRATION NUMBER: NCT03576157.

Cost-effectiveness of a direct to beneficiary mobile communication programme in improving reproductive and child health outcomes in India.

INTRODUCTION: Kilkari is the largest maternal messaging programme of its kind globally. Between its initiation in 2012 in Bihar and its transition to the government in 2019, Kilkari was scaled to 13 states across India and reached over 10 million new and expectant mothers and their families. This study aims to determine the cost-effectiveness of exposure to Kilkari as compared with no exposure across 13 states in India. METHODS: The study was conducted from a programme perspective using an analytic time horizon aligned with national scale-up efforts from December 2014 to April 2019. Economic costs were derived from the financial records of implementing partners. Data on incremental changes in the practice of reproductive maternal newborn and child health (RMNCH) outcomes were drawn from an individually randomised controlled trial in Madhya Pradesh and inputted into the Lives Saved Tool to yield estimates of maternal and child lives saved. One-way and probabilistic sensitivity analyses were carried out to assess uncertainty. RESULTS: Inflation adjusted programme costs were US$8.4 million for the period of December 2014-April 2019, corresponding to an average cost of US$264 298 per year of implementation in each state. An estimated 13 842 lives were saved across 13 states, 96% among children and 4% among mothers. The cost per life saved ranged by year of implementation and with the addition of new states from US$392 ($385-$393) to US$953 ($889-$1092). Key drivers included call costs and incremental changes in coverage for key RMNCH practices. CONCLUSION: Kilkari is highly cost-effective using a threshold of India's national gross domestic product of US$1998. Study findings provide important evidence on the cost-effectiveness of a national maternal messaging programme in India. TRIAL REGISTRATION: NCT03576157.

The impact of a direct to beneficiary mobile communication program on reproductive and child health outcomes: a randomised controlled trial in India.

BACKGROUND: Direct-to-beneficiary communication mobile programmes are among the few examples of digital health programmes to have scaled widely in low-resource settings. Yet, evidence on their impact at scale is limited. This study aims to assess whether exposure to mobile health information calls during pregnancy and postpartum improved infant feeding and family planning practices. METHODS: We conducted an individually randomised controlled trial in four districts of Madhya Pradesh, India. Study participants included Hindi speaking women 4-7 months pregnant (n=5095) with access to a mobile phone and their husbands (n=3842). Women were randomised to either an intervention group where they received up to 72 Kilkari messages or a control group where they received none. Intention-to-treat (ITT) and instrumental variable (IV) analyses are presented. RESULTS: An average of 65% of the 2695 women randomised to receive Kilkari listened to ≥50% of the cumulative content of calls answered. Kilkari was not observed to have a significant impact on the primary outcome of exclusive breast feeding (ITT, relative risk (RR): 1.04, 95% CI 0.88 to 1.23, p=0.64; IV, RR: 1.10, 95% CI 0.67 to 1.81, p=0.71). Across study arms, Kilkari was associated with a 3.7% higher use of modern reversible contraceptives (RR: 1.12, 95% CI 1.03 to 1.21, p=0.007), and a 2.0% lower proportion of men or women sterilised since the birth of the child (RR: 0.85, 95% CI 0.74 to 0.97, p=0.016). Higher reversible method use was driven by increases in condom use and greatest among those women exposed to Kilkari with any male child (9.9% increase), in the poorest socioeconomic strata (15.8% increase), and in disadvantaged castes (12.0% increase). Immunisation at 10 weeks was higher among the children of Kilkari listeners (2.8% higher; RR: 1.03, 95% CI 1.00 to 1.06, p=0.048). Significant differences were not observed for other maternal, newborn and child health outcomes assessed. CONCLUSION: Study findings provide evidence to date on the effectiveness of the largest mobile health messaging programme in the world. TRIAL REGISTRATION NUMBER: Trial registration clinicaltrials.gov; ID 90075552, NCT03576157.

'[We] learned how to speak with love': a qualitative exploration of accredited social health activist (ASHA) community health worker experiences of the Mobile Academy refresher training in Rajasthan, India.

INTRODUCTION: Mobile Academy is a mobile-based training course for India's accredited social health activist (ASHA) community health workers (CHW). The course, which ASHAs access by dialling a number from their phones, totals 4 hours of audio content. It consists of 11 chapters, each with their own quiz, and provides a cumulative pass or fail score at the end. This qualitative study of Mobile Academy explores how the programme was accessed and experienced by CHWs, and how they perceive it to have influenced their work. METHODS: We conducted in-depth interviews (n=25) and focus group discussions (n=5) with ASHAs and other health system actors. Open-ended questions explored ASHA perspectives on Mobile Academy, the course's perceived influence on ASHAs and preferences for future training programmes. After applying a priori codes to the transcripts, we identified emergent themes and grouped them according to our CHW mLearning framework. RESULTS: ASHAs reported enjoying Mobile Academy, specifically praising its friendly tone and the ability to repeat content. They, and higher level health systems actors, conceived it to primarily be a test not a training. ASHAs reported that they found the quizzes easy but generally did not consider the course overly simplistic. ASHAs considered Mobile Academy's content to be a useful knowledge refresher but said its primary benefit was in modelling a positive communications approach, which inspired them to adopt a kinder, more 'loving' communication style when speaking to beneficiaries. ASHAs and health system actors wanted follow-on mLearning courses that would continue to compliment but not replace face-to-face training. CONCLUSION: This mLearning programme for CHWs in India was well received by ASHAs across a wide range of education levels and experience. Dial-in audio training has the potential to reinforce topical knowledge and showcase positive ways to communicate.

Assessing the reliability of phone surveys to measure reproductive, maternal and child health knowledge among pregnant women in rural India: a feasibility study.

OBJECTIVES: Efforts to understand the factors influencing the uptake of reproductive, maternal, newborn, child health and nutrition (RMNCH&N) services in high disease burden low-resource settings have often focused on face-to-face surveys or direct observations of service delivery. Increasing access to mobile phones has led to growing interest in phone surveys as a rapid, low-cost alternatives to face-to-face surveys. We assess determinants of RMNCH&N knowledge among pregnant women with access to phones and examine the reliability of alternative modalities of survey delivery. PARTICIPANTS: Women 5-7 months pregnant with access to a phone. SETTING: Four districts of Madhya Pradesh, India. DESIGN: Cross-sectional surveys administered face-to-face and within 2 weeks, the same surveys were repeated among two random subsamples of the original sample: face-to-face (n=205) and caller-attended telephone interviews (n=375). Bivariate analyses, multivariable linear regression, and prevalence and bias-adjusted kappa scores are presented. RESULTS: Knowledge scores were low across domains: 52% for maternal nutrition and pregnancy danger signs, 58% for family planning, 47% for essential newborn care, 56% infant and young child feeding, and 58% for infant and young child care. Higher knowledge (≥1 composite score) was associated with older age; higher levels of education and literacy; living in a nuclear family; primary health decision-making; greater attendance in antenatal care and satisfaction with accredited social health activist services. Survey questions had low inter-rater and intermodal reliability (kappa<0.70) with a few exceptions. Questions with the lowest reliability included true/false questions and those with unprompted, multiple response options. Reliability may have been hampered by the sensitivity of the content, lack of privacy, enumerators' and respondents' profile differences, rapport, social desirability bias, and/or enumerator's ability to adequately convey concepts or probe. CONCLUSIONS: Phone surveys are a reliable modality for generating population-level estimates data about pregnant women's knowledge, however, should not be used for individual-level tracking. TRIAL REGISTRATION NUMBER: NCT03576157.

At the frontlines of digitisation: a qualitative study on the challenges and opportunities in maintaining accurate, complete and timely digital health records in India's government health system.

OBJECTIVES: To understand factors underpinning the accuracy and timeliness of mobile phone numbers and other health information captured in India's government registry for pregnant and postpartum women. Accurate and timely registration of mobile phone numbers is necessary for beneficiaries to receive mobile health services. SETTING: Madhya Pradesh and Rajasthan states in India at the community, clinical, and administrative levels of the health system. PARTICIPANTS: Interviews (n=59) with frontline health workers (FLHWs), data entry operators, and higher level officials. Focus group discussions (n=12) with pregnant women to discuss experiences with sharing data in the health system. Observations (n=9) of the process of digitization and of interactions between stakeholders for data collection. PRIMARY AND SECONDARY OUTCOME MEASURES: Thematic analysis identified how key actors experienced the data collection and digitisation process, reasons for late or inaccurate data, and mechanisms that can bolster timeliness and accuracy. RESULTS: Pregnant women were comfortable sharing mobile numbers with health workers, but many were unaware that their data moved beyond their FLHW. FLHWs valued knowing up-to-date beneficiary mobile numbers, but felt little incentive to ensure accuracy in the digital record system. Delays in registering pregnant women in the online portal were attributed to slow movement of paper records into the digital system and difficulties in gathering required documents from beneficiaries. Data, including women's phone numbers, were handwritten and copied multiple times by beneficiaries and health workers with variable literacy. Supervision tended to focus on completeness rather than accuracy. Health system actors noted challenges with the digital system but valued the broader project of digitisation. CONCLUSIONS: Increased focus on training, supportive supervision, and user-friendly data processes that prioritise accuracy and timeliness should be considered. These inputs can build on existing positive patient-provider relationships and health system actors' enthusiasm for digitisation.

Freedom within a cage: how patriarchal gender norms limit women's use of mobile phones in rural central India.

INTRODUCTION: India has one of the highest gender gaps in mobile phone access in the world. As employment opportunities, health messaging (mHealth), access to government entitlements, banking, civic participation and social engagement increasingly take place in the digital sphere, this gender gap risks further exacerbating women's disadvantage in Indian society. This study identifies the factors driving women's unequal use of phones in rural Madhya Pradesh, India. METHODS: We interviewed mothers of 1-year-old children (n=29) who reported that they had at least some access to a mobile phone. Whenever possible, we also spoke to their husbands (n=23) and extended family members (n=34) through interviews or family group discussions about the use of phones in their households, as well as their perspectives on gender and phone use more broadly. Our analysis involved comparing wife-husband pairs to assess differences in phone access and use, and thematic coding on the determinants of women's phone use using an iteratively developed conceptual framework. RESULTS: While respondents reported that women could use the phone without needing permission, this apparent 'freedom' existed in a context that severely constrained women's actual use, most directly through: (1) narrow expectations and desires around how women would use phones, (2) women's dependence on men for phone ownership and lower proximity to phones, (3) the poorer functionality of women's phones; (4) women's limited digital skills, and (5) time allocation constraints, wherein women had less leisure time and were subject to social norms that discouraged using a phone for leisure. CONCLUSION: Our framework, presenting the distal and proximate determinants of women's phone use, enables more nuanced understanding of India's digital divide. Addressing these determinants is vital to shift from re-entrenching unequal gender relations to transforming them through digital technology.

Examining the reach and exposure of a mobile phone-based training programme for frontline health workers (ASHAs) in 13 states across India.

Mobile phones are increasingly used to facilitate in-service training for frontline health workers (FLHWs). Mobile learning (mLearning) programmes have the potential to provide FLHWs with high quality, inexpensive, standardised learning at scale, and at the time and location of their choosing. However, further research is needed into FLHW engagement with mLearning content at scale, a factor which could influence knowledge and service delivery. Mobile Academy is an interactive voice response training course for FLHWs in India, which aims to improve interpersonal communication skills and refresh knowledge of preventative reproductive, maternal, neonatal and child health. FLHWs dial in to an audio course consisting of 11 chapters, each with a 4-question true/false quiz, resulting in a cumulative pass/fail score. In this paper, we analyse call data records from the national version of Mobile Academy to explore coverage, user engagement and completion. Over 158 596 Accredited Social Health Activists (ASHAs) initiated the national version, while 111 994 initiated the course on state-based platforms. Together, this represents 41% of the estimated total number of ASHAs registered in the government database across 13 states. Of those who initiated the national version, 81% completed it; and of those, over 99% passed. The initiation and completion rates varied by state, with Rajasthan having the highest initiation rate. Many ASHAs made multiple calls in the afternoons and evenings but called in for longer durations earlier in the day. Findings from this analysis provide important insights into the differential reach and uptake of the programme across states.

Assessing exposure to Kilkari: a big data analysis of a large maternal mobile messaging service across 13 states in India.

The Kilkari programme is being implemented by the Government of India in 13 states. Designed by BBC Media Action and scaled in collaboration with the Ministry of Health and Family Welfare from January 2016, Kilkari had provided mobile health information to over 10 million subscribers by the time BBC Media Action transitioned the service to the government in April 2019. Despite the reach of Kilkari in terms of the absolute number of subscribers, no longitudinal analysis of subscriber exposure to health information content over time has been conducted, which may underpin effectiveness and changes in health outcomes. In this analysis, we draw from call data records to explore exposure to the Kilkari programme in India for the 2018 cohort of subscribers. We start by assessing the timing of the first successful call answered by subscribers on entry to the programme during pregnancy or postpartum, and then assess call volume, delivery, answering and listening rates over time. Findings suggest that over half of subscribers answer their first call after childbirth, with the remaining starting in the pregnancy period. The system handles upwards of 1.2 million calls per day on average. On average, 50% of calls are picked up on the first call attempt, 76% by the third and 99.5% by the ninth call attempt. Among calls picked up, over 48% were listened to for at least 50% of the total content duration and 43% were listened to for at least 75%. This is the first analysis of its kind of a maternal mobile messaging programme at scale in India. Study analyses suggest that multiple call attempts may be required to reach subscribers. However, once answered, subscribers tend to listen the majority of the call-a figure consistent across states, over time, and by health content area.

SMS feedback system as a quality assurance mechanism: experience from a household survey in rural India.

The increasing use of digital health solutions to support data capture both as part of routine delivery of health services and through special surveys presents unique opportunities to enhance quality assurance measures. This study aims to demonstrate the feasibility and acceptability of using back-end data analytics and machine learning to identify impediments in data quality and feedback issues requiring follow-up to field teams using automated short messaging service (SMS) text messages. Data were collected as part of a postpartum women's survey (n=5095) in four districts of Madhya Pradesh, India, from October 2019 to February 2020. SMSs on common errors found in the data were sent to supervisors and coordinators. Before/after differences in time to correction of errors were examined, and qualitative interviews conducted with supervisors, coordinators, and enumerators. Study activities resulted in declines in the average number of errors per week after the implementation of automated feedback loops. Supervisors and coordinators found the direct format, complete information, and automated nature of feedback convenient to work with and valued the more rapid notification of errors. However, coordinators and supervisors reported preferring group WhatsApp messages as compared with individual SMSs to each supervisor/coordinator. In contrast, enumerators preferred the SMS system over in-person group meetings where data quality impediments were discussed. This study demonstrates that automated SMS feedback loops can be used to enhance survey data quality at minimal cost. Testing is needed among data capture applications in use by frontline health workers in India and elsewhere globally.

Connecting the dots: Kerala's use of digital technology during the COVID-19 response.

Digital tools are increasingly being applied to support the response to the ongoing COVID-19 pandemic in India and elsewhere globally. This article draws from global frameworks to explore the use of digital tools in the state of Kerala across the domains of communication, surveillance, clinical management, non-clinical support, and core health system readiness and response. Kerala is considered India's first digital state, with the highest percentage of households with computers (24%) and the internet (51%) in India, 95% mobile phone penetration, 62% smartphone penetration and 75% digital literacy. Kerala has long been a model for the early adoption of digital technology for education and health. As part of the pandemic response, technology has been used across private and public sectors, including law enforcement, health, information technology and education. Efforts have sought to ensure timely access to health information, facilitate access to entitlements, monitor those under quarantine and track contacts, and provide healthcare services though telemedicine. Kerala's COVID-19 pandemic response showcases the diverse potential of digital technology, the importance of building on a strong health system foundation, the value of collaboration, and the ongoing challenges of data privacy and equity in digital access.

Does exposure to health information through mobile phones increase immunisation knowledge, completeness and timeliness in rural India?

INTRODUCTION: Immunisation plays a vital role in reducing child mortality and morbidity against preventable diseases. As part of a randomised controlled trial in rural Madhya Pradesh, India to assess the impact of Kilkari, a maternal messaging programme, we explored determinants of parental immunisation knowledge and immunisation practice (completeness and timeliness) for children 0-12 months of age from four districts in Madhya Pradesh. METHODS: Data were drawn from a cross-sectional survey of women (n=4423) with access to a mobile phone and their spouses (n=3781). Parental knowledge about immunisation and their child's receipt of vaccines, including timeliness and completeness, was assessed using self-reports and vaccination cards. Ordered logistic regressions were used to analyse the factors associated with parental immunisation knowledge. A Heckman two-stage probit model was used to analyse completeness and timeliness of immunisation after correcting for selection bias from being able to produce the immunisation card. RESULTS: One-third (33%) of women and men knew the timing for the start of vaccinations, diseases linked to immunisations and the benefits of Vitamin-A. Less than half of children had received the basic package of 8 vaccines (47%) and the comprehensive package of 19 vaccines (44%). Wealth was the most significant determinant of men's knowledge and of the child receiving complete and timely immunisation for both basic and comprehensive packages. Exposure to Kilkari content on immunisation was significantly associated with an increase in men's knowledge (but not women's) about child immunisation (OR: 1.23, 95% CI 1.02 to1.48) and an increase in the timeliness of the child receiving vaccination at birth (Probit coefficient: 0.08, 95% CI 0.08 to 0.24). CONCLUSION: Gaps in complete and timely immunisation for infants persist in rural India. Mobile messaging programmes, supported by mass media messages, may provide one important source for bolstering awareness, uptake and timeliness of immunisation services. TRIAL REGISTRATION NUMBER: NCT03576157.

Can health information through mobile phones close the divide in health behaviours among the marginalised? An equity analysis of Kilkari in Madhya Pradesh, India.

Kilkari is one of the largest maternal mobile messaging programmes in the world. It makes weekly prerecorded calls to new and expectant mothers and their families from the fourth month of pregnancy until 1-year post partum. The programme delivers reproductive, maternal, neonatal and child health information directly to subscribers' phones. However, little is known about the reach of Kilkari among different subgroups in the population, or the differentiated benefits of the programme among these subgroups. In this analysis, we assess differentials in eligibility, enrolment, reach, exposure and impact across well-known proxies of socioeconomic position-that is, education, caste and wealth. Data are drawn from a randomised controlled trial (RCT) in Madhya Pradesh, India, including call data records from Kilkari subscribers in the RCT intervention arm, and the National Family Health Survey-4, 2015. The analysis identifies that disparities in household phone ownership and women's access to phones create inequities in the population eligible to receive Kilkari, and that among enrolled Kilkari subscribers, marginalised caste groups and those without education are under-represented. An analysis of who is left behind by such interventions and how to reach those groups through alternative communication channels and platforms should be undertaken at the intervention design phase to set reasonable expectations of impact. Results suggest that exposure to Kilkari has improved levels of some health behaviours across marginalised groups but has not completely closed pre-existing gaps in indicators such as wealth and education.

Another voice in the crowd: the challenge of changing family planning and child feeding practices through mHealth messaging in rural central India.

INTRODUCTION: Kilkari is one of the world's largest mobile phone-based health messaging programmes. Developed by BBC Media Action, it provides weekly stage-based information to pregnant and postpartum women and their families, including on infant and young child feeding (IYCF) and family planning, to compliment the efforts of frontline health workers. The quantitative component of a randomised controlled trial (RCT) in the Indian state of Madhya Pradesh found that exposure to Kilkari increased modern contraceptive uptake but did not change IYCF practices. This qualitative research complements the RCT to explore why these findings may have emerged. METHODS: We used system generated data to identify households within the RCT with very high to medium Kilkari listenership. Mothers (n=29), as well as husbands and extended family members (n=25 interviews/family group discussions) were interviewed about IYCF and family planning, including their reactions to Kilkari's calls on these topics. Analysis was informed by the theory of reciprocal determinism, which positions behaviour change within the interacting domains of individual attributes, social and environmental determinants, and existing practices. RESULTS: While women who owned and controlled their own phones were the Kilkari listeners, among women who did not own their own phones, it was often their husbands who listened. Spouses did not discuss Kilkari messages. Respondents retained and appreciated Kilkari messages that aligned with their pre-existing worldviews, social norms, and existing practices. However, they overlooked or de-emphasised content that did not. In this way, they reported agreeing with and trusting Kilkari while persisting with practices that went against Kilkari's recommendations, particularly non-exclusive breastfeeding and inappropriate complementary feeding. CONCLUSION: To deepen impact, digital direct to beneficiary services need to be complimented by wider communication efforts (e.g., sustained face-to-face, media, community engagement) to change social norms, taking into account the role of socio-environmental, behavioural, and individual determinants.

Using Machine Learning to Optimize the Quality of Survey Data: Protocol for a Use Case in India.

BACKGROUND: Data quality is vital for ensuring the accuracy, reliability, and validity of survey findings. Strategies for ensuring survey data quality have traditionally used quality assurance procedures. Data analytics is an increasingly vital part of survey quality assurance, particularly in light of the increasing use of tablets and other electronic tools, which enable rapid, if not real-time, data access. Routine data analytics are most often concerned with outlier analyses that monitor a series of data quality indicators, including response rates, missing data, and reliability of coefficients for test-retest interviews. Machine learning is emerging as a possible tool for enhancing real-time data monitoring by identifying trends in the data collection, which could compromise quality. OBJECTIVE: This study aimed to describe methods for the quality assessment of a household survey using both traditional methods as well as machine learning analytics. METHODS: In the Kilkari impact evaluation's end-line survey amongst postpartum women (n=5095) in Madhya Pradesh, India, we plan to use both traditional and machine learning-based quality assurance procedures to improve the quality of survey data captured on maternal and child health knowledge, care-seeking, and practices. The quality assurance strategy aims to identify biases and other impediments to data quality and includes seven main components: (1) tool development, (2) enumerator recruitment and training, (3) field coordination, (4) field monitoring, (5) data analytics, (6) feedback loops for decision making, and (7) outcomes assessment. Analyses will include basic descriptive and outlier analyses using machine learning algorithms, which will involve creating features from time-stamps, "don't know" rates, and skip rates. We will also obtain labeled data from self-filled surveys, and build models using k-folds cross-validation on a training data set using both supervised and unsupervised learning algorithms. Based on these models, results will be fed back to the field through various feedback loops. RESULTS: Data collection began in late October 2019 and will span through March 2020. We expect to submit quality assurance results by August 2020. CONCLUSIONS: Machine learning is underutilized as a tool to improve survey data quality in low resource settings. Study findings are anticipated to improve the overall quality of Kilkari survey data and, in turn, enhance the robustness of the impact evaluation. More broadly, the proposed quality assurance approach has implications for data capture applications used for special surveys as well as in the routine collection of health information by health workers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17619.

A systematic review of monitoring and evaluation indicators for sexual and reproductive health in humanitarian settings.

OBJECTIVE: To conduct a comprehensive mapping of published indicators for monitoring and evaluation (M&E) of sexual and reproductive health (SRH) services and outcomes in humanitarian settings. METHODS: A systematic search of the peer-reviewed and grey literature published between January 2008 and May 2018 was conducted to identify all references describing indicator sets for M&E of SRH services and outcomes in humanitarian settings. The databases MEDLINE, Web of Science, and Global Health, as well as 85 websites of relevant organizations involved in humanitarian response were searched. Characteristics of identified indicator sets and data from individual indicators was extracted. FINDINGS: Of 3278 records identified, 20 met the review's inclusion criteria and 9 existing indicator sets were identified. A total of 179 relevant indicators were included in the mapping, and removal of duplicates yielded 132 unique indicators. Twenty-seven percent fell within the maternal health domain, followed by the HIV/AIDS domain (26%) and the gender-based violence domain (23%). The distribution of indicators by type (process/output, outcome, impact) was balanced overall but varied substantially across domains. The most commonly used data collection platforms were facility-based systems or population-based surveys. Domains covered and indicator definitions were inconsistent across indicator sets. CONCLUSION: Results demonstrate the need to standardize data collection efforts for M&E of SRH services and outcomes in humanitarian settings and to critically appraise the extent to which different domains should be covered. A core list of indicators is essential for assessing response status over time as well as across countries.