Impact of smartphone-assisted prenatal home visits on women's use of facility delivery: Results from a cluster-randomized trial in rural Tanzania

Kristy Hackett, Curtis Lafleur, Peter Nyella, Ophira Ginsburg, Wendy Lou, Daniel Sellen, Kristy Hackett, Curtis Lafleur, Peter Nyella, Ophira Ginsburg, Wendy Lou, Daniel Sellen

Abstract

Background: About half of births in rural Tanzania are assisted by skilled providers. Point-of-care mobile phone applications hold promise in boosting job support for community health workers aiming to ensure safe motherhood through increased facility delivery awareness, access and uptake. We conducted a controlled comparison to evaluate a smartphone-based application designed to assist community health workers with data collection, education delivery, gestational danger sign identification, and referrals.

Methods: Community health workers in 32 randomly selected villages were cluster-randomized to training on either smartphone (intervention) or paper-based (control) protocols for use during household visits with pregnant women. The primary outcome measure was postnatal report of delivery location by 572 women randomly selected to participate in a survey conducted by home visit. A mixed-effects model was used to account for clustering of subjects and other measured factors influencing facility delivery.

Findings: The smartphone intervention was associated with significantly higher facility delivery: 74% of mothers in intervention areas delivered at or in transit to a health facility, versus 63% in control areas. The odds of facility delivery among women counseled by smartphone-assisted health workers were double the odds among women living in control villages (OR, 1.96; CI, 1.21-3.19; adjusted analyses). Women in intervention areas were more likely to receive two or more visits from a community health worker during pregnancy than women in the control group (72% vs. 60%; chi-square = 6.9; p < 0.01). Previous facility delivery, uptake of antenatal care, and distance to the nearest facility were also strong independent predictors of facility delivery.

Interpretation: Community health worker use of smartphones increased facility delivery, likely through increased frequency of prenatal home visits. Smartphone-based job aids may enhance community health worker support and effectiveness as one component of intervention packages targeting safe motherhood.

Trial registration: NCT03161184.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. Study design overview (attached as…
Fig 1. Study design overview (attached as separate file).
Fig 2. Study flow diagram outlining sample…
Fig 2. Study flow diagram outlining sample size achieved in each study arm.
Fig 3. Facility delivery in each study…
Fig 3. Facility delivery in each study group, stratified by parity, previous facility delivery, and ANC uptake.
*Significance assessed by Chi-square tests for proportions. **Significance assessed by Fisher’s exact test for proportions.

References

    1. Mahler H. The safe motherhood initiative: a call to action. Lancet. 1987;1(8534):668–70. .
    1. Campbell OM, Graham WJ. Strategies for reducing maternal mortality: getting on with what works. Lancet. 2006;368(9543):1284–99. Epub 2006/10/10. doi: .
    1. Fournier P, Dumont A, Tourigny C, Dunkley G, Dramé S. Improved access to comprehensive emergency obstetric care and its effect on institutional maternal mortality in rural Mali. Bulletin of the World Health Organization. 2009;87(1):30–8. doi: PubMed PMID: PMC2649605.
    1. Lawn JE, Cousens S, Zupan J. 4 million neonatal deaths: When? Where? Why? The Lancet. 365(9462):891–900. doi:
    1. Say L, Chou D, Gemmill A, Tuncalp O, Moller AB, Daniels J, et al. Global causes of maternal death: a WHO systematic analysis. Lancet Glob Health. 2014;2(6):e323–33. doi: .
    1. Diamond-Smith N, Sudhinaraset M. Drivers of facility deliveries in Africa and Asia: regional analyses using the demographic and health surveys. Reproductive Health. 2015;12:6 doi: PubMed PMID: PMC4320522.
    1. Gebrehiwot T, San Sebastian M, Edin K, Goicolea I. Health workers’ perceptions of facilitators of and barriers to institutional delivery in Tigray, Northern Ethiopia. BMC Pregnancy and Childbirth. 2014;14(1):137 doi:
    1. Metcalfe R, Adegoke AA. Strategies to increase facility-based skilled birth attendance in South Asia: a literature review. International health. 2013;5(2):96–105. Epub 2013/09/14. doi: .
    1. Mrisho M, Schellenberg JA, Mushi AK, Obrist B, Mshinda H, Tanner M, et al. Factors affecting home delivery in rural Tanzania. Trop Med Int Health. 2007;12(7):862–72. doi: .
    1. Pfeiffer C, Mwaipopo R. Delivering at home or in a health facility? health-seeking behaviour of women and the role of traditional birth attendants in Tanzania. BMC Pregnancy and Childbirth. 2013;13:55–. doi: PubMed PMID: PMC3599352.
    1. Shiferaw S, Spigt M, Godefrooij M, Melkamu Y, Tekie M. Why do women prefer home births in Ethiopia? BMC Pregnancy and Childbirth. 2013;13(1):5 doi:
    1. Titaley CR, Hunter CL, Heywood P, Dibley MJ. Why don't some women attend antenatal and postnatal care services?: a qualitative study of community members' perspectives in Garut, Sukabumi and Ciamis districts of West Java Province, Indonesia. BMC Pregnancy Childbirth. 2010;10:61 Epub 2010/10/13. doi: ; PubMed Central PMCID: PMCPmc2964562.
    1. Perry HB, Zulliger R, Rogers MM. Community health workers in low-, middle-, and high-income countries: an overview of their history, recent evolution, and current effectiveness. Annu Rev Public Health. 2014;35:399–421. doi: .
    1. Florez-Arango JF, Iyengar MS, Dunn K, Zhang J. Performance factors of mobile rich media job aids for community health workers. J Am Med Inform Assoc. 2011;18(2):131–7. doi: ; PubMed Central PMCID: PMCPMC3116248.
    1. Haines A, Sanders D, Lehmann U, Rowe AK, Lawn JE, Jan S, et al. Achieving child survival goals: potential contribution of community health workers. Lancet. 2007;369(9579):2121–31. doi: .
    1. Labrique A, Vasudevan L, Chang LW, Mehl G. H_pe for mHealth: more "y" or "o" on the horizon? Int J Med Inform. 2013;82(5):467–9. doi: ; PubMed Central PMCID: PMCPMC3849805.
    1. Agarwal S, Perry HB, Long LA, Labrique AB. Evidence on feasibility and effective use of mHealth strategies by frontline health workers in developing countries: systematic review. Trop Med Int Health. 2015;20(8):1003–14. doi: ; PubMed Central PMCID: PMCPMC4692099.
    1. Mehl G, Labrique A. Prioritizing integrated mHealth strategies for universal health coverage. Science. 2014;345(6202):1284 doi:
    1. Tamrat T, Kachnowski S. Special delivery: an analysis of mHealth in maternal and newborn health programs and their outcomes around the world. Matern Child Health J. 2012;16(5):1092–101. doi: .
    1. Higgs ES, Goldberg AB, Labrique AB, Cook SH, Schmid C, Cole CF, et al. Understanding the role of mHealth and other media interventions for behavior change to enhance child survival and development in low- and middle-income countries: an evidence review. Journal of health communication. 2014;19 Suppl 1:164–89. Epub 2014/09/11. doi: ; PubMed Central PMCID: PMCPmc4255285.
    1. Free C, Phillips G, Galli L, Watson L, Felix L, Edwards P, et al. The effectiveness of mobile-health technology-based health behaviour change or disease management interventions for health care consumers: a systematic review. PLoS Med. 2013;10(1):e1001362 doi: ; PubMed Central PMCID: PMCPMC3548655.
    1. L'Engle KL, Vahdat HL, Ndakidemi E, Lasway C, Zan T. Evaluating feasibility, reach and potential impact of a text message family planning information service in Tanzania. Contraception. 2013;87(2):251–6. Epub 2012/09/01. doi: .
    1. Lester RT, Ritvo P, Mills EJ, Kariri A, Karanja S, Chung MH, et al. Effects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial. Lancet. 2010;376(9755):1838–45. doi: .
    1. Mbuagbaw L, Thabane L, Ongolo-Zogo P, Lester RT, Mills E, Volmink J, et al. The Cameroon mobile phone SMS (CAMPS) trial: a protocol for a randomized controlled trial of mobile phone text messaging versus usual care for improving adherence to highly active anti-retroviral therapy. Trials. 2011;12:5 doi: ; PubMed Central PMCID: PMCPMC3023676.
    1. Sellen D, Mbugua S, Webb-Girard A, Lou W, Duan W, Kamau-Mbuthia E. Cell phone based peer counselling can support exclusive breastfeeding: a randomized controlled trial in Kenya (119.5). The FASEB Journal. 2014;28(1_supplement):119.5 doi:
    1. Chaiyachati KH, Loveday M, Lorenz S, Lesh N, Larkan LM, Cinti S, et al. A pilot study of an mHealth application for healthcare workers: poor uptake despite high reported acceptability at a rural South African community-based MDR-TB treatment program. PLoS One. 2013;8(5):e64662 doi: ; PubMed Central PMCID: PMCPMC3665589.
    1. Crawford J, Larsen-Cooper E, Jezman Z, Cunningham SC, Bancroft E. SMS versus voice messaging to deliver MNCH communication in rural Malawi: assessment of delivery success and user experience. Glob Health Sci Pract. 2014;2(1):35–46. doi: ; PubMed Central PMCID: PMCPMC4168599.
    1. Kallander K, Tibenderana JK, Akpogheneta OJ, Strachan DL, Hill Z, ten Asbroek AH, et al. Mobile health (mHealth) approaches and lessons for increased performance and retention of community health workers in low- and middle-income countries: a review. J Med Internet Res. 2013;15(1):e17 doi: ; PubMed Central PMCID: PMCPMC3636306.
    1. Lund S, Hemed M, Nielsen BB, Said A, Said K, Makungu MH, et al. Mobile phones as a health communication tool to improve skilled attendance at delivery in Zanzibar: a cluster-randomised controlled trial. BJOG. 2012;119(10):1256–64. doi: .
    1. Balakrishnan R, Gopichandran V, Chaturvedi S, Chatterjee R, Mahapatra T, Chaudhuri I. Continuum of Care Services for Maternal and Child Health using mobile technology—a health system strengthening strategy in low and middle income countries. BMC medical informatics and decision making. 2016;16:84 Epub 2016/07/09. doi: ; PubMed Central PMCID: PMCPmc4937606.
    1. National Bureau of Statistics, Ministry of Finance, Office of Chief Government Statistician. Mortality and Health. Dar es Salaam: 2015.
    1. Ministry of Health CD, Gender, Elderly and Children [Tanzania Mainland], Ministry of Health (MoH) [Zanzibar], National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), ICF. Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) 2015–16. Dar es Salaam: 2016.
    1. Ndao-Brumblay SK, Mbaruku G, Kruk ME. Parity and institutional delivery in rural Tanzania: a multilevel analysis and policy implications. Health Policy Plan. 2013;28(6):647–57. doi: ; PubMed Central PMCID: PMCPMC3753883.
    1. Manji K. Situation analysis of newborn health in Tanzania: Current situation, existing plans and strategic next steps for newborn health. Dar es Salaam: Ministry of Health and Social Welfare, Save the Children, 2009.
    1. United Republic of Tanzania. The National Road Map Strategic Plan To Accelerate Reduction of Maternal, Newborn and Child Deaths in Tanzania. Dar es Salaam: Ministry of Health and Social Welfare, 2008.
    1. Mpembeni RNM, Bhatnagar A, LeFevre A, Chitama D, Urassa DP, Kilewo C, et al. Motivation and satisfaction among community health workers in Morogoro Region, Tanzania: nuanced needs and varied ambitions. Human Resources for Health. 2015;13(1):44 doi:
    1. Dimagi Inc. CommCare 2018 [cited 2018 8 April 2018]. Available from: .
    1. Campbell MK, Thomson S, Ramsay CR, MacLennan GS, Grimshaw JM. Sample size calculator for cluster randomized trials. Comput Biol Med. 2004;34(2):113–25. doi: .
    1. Pagel C, Prost A, Lewycka S, Das S, Colbourn T, Mahapatra R, et al. Intracluster correlation coefficients and coefficients of variation for perinatal outcomes from five cluster-randomised controlled trials in low and middle-income countries: results and methodological implications. Trials. 2011;12:151 doi: ; PubMed Central PMCID: PMCPMC3136407.
    1. Lewycka S, Mwansambo C, Kazembe P, Phiri T, Mganga A, Rosato M, et al. A cluster randomised controlled trial of the community effectiveness of two interventions in rural Malawi to improve health care and to reduce maternal, newborn and infant mortality. Trials. 2010;11:88 Epub 2010/09/21. doi: ; PubMed Central PMCID: PMCPmc2949851.
    1. USAID, MCHIP. Rapid Health Facility Assessment 2.1 (R-HFA) 2016 [cited 2016 June 1]. Available from: .
    1. Service Provision Assessment (SPA) [Internet]. The DHS Program. Available from: .
    1. Guliani H, Sepehri A, Serieux J. What impact does contact with the prenatal care system have on women's use of facility delivery? Evidence from low-income countries. Social science & medicine (1982). 2012;74(12):1882–90. Epub 2012/04/10. doi: .
    1. Kruk ME, Hermosilla S, Larson E, Vail D, Chen Q, Mazuguni F, et al. Who is left behind on the road to universal facility delivery? A cross-sectional multilevel analysis in rural Tanzania. Trop Med Int Health. 2015;20(8):1057–66. Epub 2015/04/17. doi: ; PubMed Central PMCID: PMCPmc4490971.
    1. Ng’anjo Phiri S, Kiserud T, Kvåle G, Byskov J, Evjen-Olsen B, Michelo C, et al. Factors associated with health facility childbirth in districts of Kenya, Tanzania and Zambia: a population based survey. BMC Pregnancy and Childbirth. 2014;14(1):219 doi:
    1. Wagle RR, Sabroe S, Nielsen BB. Socioeconomic and physical distance to the maternity hospital as predictors for place of delivery: an observation study from Nepal. BMC Pregnancy Childbirth. 2004;4(1):8 Epub 2004/05/25. doi: ; PubMed Central PMCID: PMCPmc425583.
    1. Mpembeni RNM, Killewo JZ, Leshabari MT, Massawe SN, Jahn A, Mushi D, et al. Use pattern of maternal health services and determinants of skilled care during delivery in Southern Tanzania: implications for achievement of MDG-5 targets. BMC Pregnancy and Childbirth. 2007;7(1):29 doi:

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