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Conflict of interest disclosure (Potential) conflict of interest None Relationships with companies of Company names relevance for this meeting Sponsoring or research funding Consultancy fee or other (financial)

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(Potential) conflict of interest None Relationships with companies of relevance for this meeting Company names  Sponsoring or research funding  Consultancy fee or other (financial) reimbursement  Shareholder  Other relationship, namely …     Conflict of interest disclosure

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mHealth to improve maternal and neonatal care in LMICs

Stephanie Sondaal & Alexander Borgstein Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Centre Utrecht, The Netherlands.

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Early neonatal mortality Maternal mortality Physician workforce Births attended

Lawn et al., 2010

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Challenges of LMICs

  • Shortage of health workers (Lawn et al., 2010)
  • Specific LMIC factors (Chen et al., 2004):

– migration of qualified health workers to richer countries – inadequate investment in national health systems resulting in low capacity to health needs (people and resources) – double burden of disease (NCDs and communicable diseases)

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Opportunities in LMICs

  • High number of mobile phone subscriptions (ITU, 2014)
  • High mobile-cellular penetration, reaching 90% by the end
  • f 2014 (ITU, 2014)
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Possible solution

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mHealth

“medical and public health practice supported by mobile phones” (WHO) and tablets for the exchange of health related information in the form of coded data, text, images, audio, and video

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Research question:

to assess the potential of mHealth interventions focused on supporting (1) pregnant women during the antenatal, delivery and postnatal period and (2) health care providers bestowing maternal and neonatal care in LMICs in improving maternal and neonatal

  • utcomes
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Methods

  • Systematic review

– The Cochrane Library (Cochrane Database of Systematic Reviews) – PubMed/MEDLINE – EMBASE – Global Health Library – Popline

  • Two reviewers
  • Quality assessment
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Flow chart

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Intervention studies included in qualitative synthesis:

  • Pregnant women, n = 12
  • Health care providers, n = 11
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Observational studies on feasibility and usage

  • Pregnant women, n = 11
  • Health care providers, n = 6
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Results - Overview of scope of research

55,6 11,1 11,1 11,1 11,1

Form of mHealth targeting pregnant women

Unidirectional text (and voice) messaging Direct two-way communication Both unidirectional and direct two-way communication Multidirectional text messaging Unidirectional telephone counselling

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Results - Overview of scope of research

36,4 18,2 9,1 18,2 9,1 9,1

Form of mHealth targeting health care providers

Unidirectional text messaging Unidirectional text messaging & web-based technology Two-way text messaging Multidirectional text and voice messages Smartphone health applications Smartphone recording

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Results - Overview of scope of research

47,4 5,3 15,8 15,8 15,8

Function of mHealth targeting pregnant women (%)

Educational Monitoring Reminder Communication and support Emergency medical response system

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Results - Overview of scope of research

9,1 9,1 9,1 27,3 63,6

Function of mHealth targeting health care providers

Educational Transmission of test results Appointment reminder Communication and support Data collection

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Key messages – mHealth interventions targeted at pregnant women

  • Access to and experience of care improved

– ANC visits (Lund et al., 2014, Kaewkungwal et al., 2010) – Skilled attendance at birth (Lund et al., 2012) – Immunization services received (Kaewkungwal et al., 2010) – Facility utilization rate (Oyeyemi and Wynn, 2014) – Depressive symptoms amongst HIV+ pregnant women (Ross

et al., 2013)

– Confidence scores and anxiety levels (Jareethum et al., 2008)

  • Pregnancy related outcomes

– Perinatal mortality (OR, 0.50; 95% CI, 0,27-0,90) (Lund et al.,

2014)

– Compliance to iron supplementation (Khorshid et al., 2014)

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Key messages – mHealth interventions targeted at health care providers

  • Data collection tool:

– Positive effect on reporting postpartum haemorrhage and recorded birth weights (Andretta et al., 2011; Gisore et al., 2012)

  • Communication tool:

– Reduced communication gap between CHWs and higher health institutions (Lemay et al., 2012; Ngabo et al., 2012)

  • Education:

– Positive outcome (Woods et al., 2012)

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Key messages of observational studies

  • Important to conduct prior to intervention, as they:

– Give insight into possible barriers

  • E.g. illiteracy, equity, costs for participants, technological issues,

maintenance of mobile phones, privacy not always guaranteed (Munro et al., 2014; Jennings et al., 2013; Ngabo et al., 2012; Woods et

al., 2012)

– Give insight into needs of the target population

  • Customized programs: SMS combined with phone calls (Jennings

et al., 2013) and, timing and amount of SMS sent (Cormick et al., 2013)

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Key messages of observational studies

  • Important to conduct prior to intervention, as they:

– Give insight into possible barriers

  • E.g. illiteracy, equity, costs for participants, technological issues,

maintenance of mobile phones, privacy not always guaranteed (Jennings et al., 2013)

– Give insight into needs of the target population

  • Customized programs: SMS combined with phone calls (Jennings

et al., 2013) and, timing and amount of SMS sent (Cormick et al., 2013)

  • Important to conduct during and after intervention, as

they:

– Give insight into areas of improvement

  • Private-public partnerships could play an important role in the

expansion of mHealth interventions in LMICs (Ngabo et al., 2012)

– Allow for a fuller interpretation of the data

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Discussion/Limitations

  • Study and outcome level

– Risk of bias increased as study design became less experimental – Only post-analysis of mHealth activities (no clear outcome) – Comparison between interventions not possible (differing

  • utcomes)
  • Review level

– Thorough systematic search (+) – Grey literature (i.e. NGO activities) (-)

  • Domain

– Neonatal defined as newborn up to the age of 28 days (immunization, retinopathy of immaturity, feeding) – LMICs

  • Lessons learnt from high income countries lacking
  • Interesting group not included: low-income women in high-income

countries

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Discussion/Limitations

  • Study and outcome level

– Risk of bias increased as study design became less experimental – Only post-analysis of mHealth activities (no clear outcome) – Comparison between interventions not possible (differing

  • utcomes)
  • Review level

– Thorough systematic search (+) – Grey literature (i.e. NGO activities) (-, but currently ongoing)

  • Domain

– Neonatal defined as newborn up to the age of 28 days (immunization, retinopathy of immaturity, feeding) – LMICs

  • Lessons learnt from high income countries lacking
  • Interesting group not included: low-income women in high-income

countries

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Discussion/Limitations

  • Study and outcome level

– Risk of bias increased as study design became less experimental – Only post-analysis of mHealth activities (no clear outcome) – Comparison between interventions not possible (differing

  • utcomes)
  • Review level

– Thorough systematic search (+) – Grey literature (i.e. NGO activities) (-)

  • Domain

– Neonatal defined as newborn up to the age of 28 days (immunization, retinopathy of immaturity, feeding) – LMICs

  • Lessons learnt from high income countries lacking
  • Interesting group not included: low-income women in high-income

countries

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Key messages

  • mHealth interventions can be effective solutions

– Improve access to and experience of maternal and neonatal care for pregnant women – Improve data collection by, communication between, and education of health care providers

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Key messages

  • mHealth interventions can be effective solutions

– Improve access to and experience of maternal and neonatal care for pregnant women – Improve data collection by, communication between, and education of health care providers

  • mHealth programs featuring alongside investments in

infrastructure and human resources are needed to improve maternal and neonatal outcomes

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Key messages

  • mHealth interventions can be effective solutions

– Improve access to and experience of maternal and neonatal care for pregnant women – Improve data collection by, communication between, and education of health care providers

  • mHealth programs featuring alongside investments in

infrastructure and human resources are needed to improve maternal and neonatal outcomes

  • Important role for qualitative research alongside

experimental studies

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Key messages

  • mHealth interventions can be effective solutions

– Improve access to and experience of maternal and neonatal care for pregnant women – Improve data collection by, communication between, and education of health care providers

  • mHealth programs featuring alongside investments in

infrastructure and human resources are needed to improve maternal and neonatal outcomes

  • Important role for qualitative research alongside

experimental studies

  • Strong experimental research was lacking, but more and

more examples are available

– What is needed for it to become the standard method?

  • Research “know-how”
  • Improved collaboration between NGOs and academic institutions
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Acknowledgements

Joyce L. Browne (MD, MSc)1 Mary Amoakoh-Coleman (MD, MPH)1,2 Kerstin Klipstein-Grobusch (PhD)1,3

1Julius Global Health, Julius Center for Health Sciences and Primary Care,

University Medical Centre Utrecht, The Netherlands.

2University of Ghana, School of Public Health, Accra, Ghana. 3Division of Epidemiology and Biostatistics, School of Public Health, Faculty

  • f Health Sciences, University of Witwatersrand, Johannesburg, South

Africa.

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Questions?

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Inclusion and exclusion criteria

Inclusion criteria Articles must be peer reviewed and written in English, Dutch, French, German or Spanish and all primary study designs. Articles include the pre-defined domains and determinants, and concern an intervention. Exclusion criteria Articles were excluded when they did not match the domains and determinants defined, or are reports of proceedings, project protocols or secondary analysis. Interventions relating to the termination of pregnancy were excluded when they targeted the termination of pregnancy below 26 weeks, as the fetus is then not yet regarded as viable.

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Results - Overview of scope of research

Asia: 2/20

Middle-East: 1/20

Africa: 12/20

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Urban: 5/10 Rural: 3/10

Results - Overview of scope of research

Both: 1/10; Unclear: 1/10

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Results - Overview of scope of research

Number of articles of mHealth studies targeting pregnant women

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1 2 3 4 5 6 7 2010 2011 2012 2013 2014 Studies

Number of articles of mHealth studies targeting health care providers

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Results - Overview of scope of research

45,5 9,1 18,2 9,1 9,1

Educational topics addressed of mHealth interventions targeting pregnant women (%)

General maternal and newborn health information Pregnancy danger signs Breast- and/or infant feeding practices HIV and pregnancy Family planning

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Key messages – pregnant women

  • Education/antenatal health knowledge

– No change (Lau et al., 2014) – Significant increase (Datta et al., 2014)

  • Breastfeeding

– Slight effect on exclusive breastfeeding rates (Jiang et al., 2014; Tahir and Al-Sadat, 2013)

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References

  • Lawn JE, Kerber K, Enweronu-Laryea C, Cousens S. 3.6 Million Neonatal Deaths-What Is Progressing and What Is Not? Semin Perinatol. 2010;34(6):371-386.

doi:10.1053/j.semperi.2010.09.011.

  • Chen L, Evans T, Anand S, et al. Human resources for health: overcoming the crisis. Lancet. 2004;364(9449):1984-90. doi:10.1016/S0140-6736(04)17482-5.
  • WHO. (2010). Telemedicine: opportunities and developments in Member States: report on the second global survey on eHealth. In Global Observatory for eHealth
  • series. 2nd edition. Geneva: World Health Organization
  • Sanou B. The World in 2014: ICT Facts and Figures.; 2014.
  • Lund S, Nielsen BB, Hemed M, et al. Mobile phones improve antenatal care attendance in Zanzibar: a cluster randomized controlled trial. BMC Pregnancy Childbirth.

2014;14:29. doi:10.1186/1471-2393-14-29.

  • Lund S, Rasch V, Hemed M, et al. Mobile phone intervention reduces perinatal mortality in zanzibar: secondary outcomes of a cluster randomized controlled trial. JMIR

mHealth uHealth. 2014;2(1):e15. doi:10.2196/mhealth.2941.

  • Kaewkungwal J, Singhasivanon P, Khamsiriwatchara A, Sawang S, Meankaew P, Wechsart A. Application of smart phone in “Better Border Healthcare Program”: a

module for mother and child care. BMC Med Inform Decis Mak. 2010;10(1):69. doi:10.1186/1472-6947-10-69.

  • Oyeyemi SO, Wynn R. Giving cell phones to pregnant women and improving services may increase primary health facility utilization: a case-control study of a Nigerian
  • project. Reprod Health. 2014;11(1):8. doi:10.1186/1742-4755-11-8.
  • Ross R, Sawatphanit W, Suwansujarid T, Stidham AW, Drew BL, Creswell JW. The effect of telephone support on depressive symptoms among HIV-infected pregnant

women in Thailand: an embedded mixed methods study. J Assoc Nurses AIDS Care. 2013;24(5):e13-24. doi:10.1016/j.jana.2012.08.005.

  • Jareethum R, Titapant V, Chantra T, Sommai V, Chuenwattana P, Jirawan C. Satisfaction of healthy pregnant women receiving short message service via mobile phone

for prenatal support: A randomized controlled trial. J Med Assoc Thai. 2008;91(4):458-63. Available at: http://www.ncbi.nlm.nih.gov/pubmed/18556852.

  • Khorshid MR, Afshari P, Abedi P. The effect of SMS messaging on the compliance with iron supplementation among pregnant women in Iran: a randomized controlled
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  • Andreatta P, Debpuur D, Danquah A, Perosky J. Using cell phones to collect postpartum hemorrhage outcome data in rural Ghana. Int J Gynaecol Obstet.

2011;113(2):148-51. doi:10.1016/j.ijgo.2010.11.020.

  • Gisore P, Shipala E, Otieno K, et al. Community based weighing of newborns and use of mobile phones by village elders in rural settings in Kenya: a decentralised

approach to health care provision. BMC Pregnancy Childbirth. 2012;12(1):15. doi:10.1186/1471-2393-12-15.

  • Ngabo F, Nguimfack J, Nwaigwe F, et al. Designing and Implementing an Innovative SMS-based alert system (RapidSMS-MCH) to monitor pregnancy and reduce

maternal and child deaths in Rwanda. Pan Afr Med J. 2012;13:31. Available at: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3542808&tool=pmcentrez&rendertype=abstract. Accessed September 19, 2014.

  • Lemay NV, Sullivan T, Jumbe B, Perry CP. Reaching remote health workers in Malawi: baseline assessment of a pilot mHealth intervention. J Health Commun. 2012;17

Suppl 1(sup1):105-17. doi:10.1080/10810730.2011.649106.

  • Woods D, Attwell A, Ross K, Theron G. Text messages as a learning tool for midwives. South African Med J. 2012;102(2). Available at:

http://www.ajol.info/index.php/samj/article/view/74600. Accessed September 19, 2014.

  • Munro ML, Lori JR, Boyd CJ, Andreatta P. Knowledge and skill retention of a mobile phone data collection protocol in rural Liberia. J Midwifery Womens Health.

59(2):176-83. doi:10.1111/jmwh.12155.

  • Jennings L, Ong’ech J, Simiyu R, Sirengo M, Kassaye S. Exploring the use of mobile phone technology for the enhancement of the prevention of mother-to-child

transmission of HIV program in Nyanza, Kenya: a qualitative study. BMC Public Health. 2013;13:1131. doi:10.1186/1471-2458-13-1131.

  • Cormick G, Kim N a, Rodgers A, et al. Interest of pregnant women in the use of SMS (short message service) text messages for the improvement of perinatal and

postnatal care. Reprod Health. 2012;9:9. doi:10.1186/1742-4755-9-9.

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Images

  • Slide 3: http://www.worldmapper.org (map Numbers 260,

258, 219, and 215, respectively)

  • Slide 6: background photo is property of Stephanie

Sondaal; http://www.internetactu.net/2010/11/25/la- technologie-peut-elle-eliminer-la-pauvrete-22-distinguer- le-potentiel-des-machines-de-celui-des-hommes

  • Slide 29: http://ihealthcomms.wordpress.com/tag/wired-

mothers/

  • Slide 31:

http://www.vectortemplates.com/imgtemplate.php?iid=65

  • Slide 32: property of Stephanie Sondaal