Skip to main content

Advertisement

SpringerLink
Log in

Guidelines for developing geographically sensitive mobile health applications

  • Original Paper
  • Published:
Health and Technology Aims and scope Submit manuscript

Abstract

Background

Seventeen (17) Sustainable Development Goals (SDGs) were promulgated in 2016 following the end of the Millennium Development Goals (MDGs) era. SDG 3 aims to ensure health lives and promote well-being for all ages. Increasing use of geo-enabled mobile health applications can positively contribute to the realisation of SDG 3 targets. Health facilities and the communities that require health care are connected by geography. Digital technologies are increasingly becoming an important resource for health service delivery and public health. However, there is need for a framework that guide the development and deployment of context relevant location based digital technologies. This paper presents recommendations for guidelines that can be adopted for developing geographically sensitive mobile health applications. These guidelines were formulated based on experience from the RoadMApp project in Kwekwe District of Zimbabwe. RoadMApp is an mHealth location aware application that reduces the negative effects of long travel times to health care facilities by pregnant women. The developed guidelines for developing geographically sensitive mobile applications start with user requirements assessment followed by geographic information systems data needs and modelling then database development, and finally frontend mobile application development. In line with the new global health policy drive for locally driven and context relevant health interventions, the guidelines present new opportunities that take advantage of the ubiquity of mobile telephony and could be adopted in health policy formulations to contribute to SDG3.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Abbreviations

LMIC:

Low to medium income countries

HIC:

High income countries

SDG:

Sustainable Development Goals

MDG:

Millennium Development Goals

mHealth:

Mobile health

GIS:

Geographic information systems

RoadMApp:

Road Mobile Application

SQL:

Structured Query Language

ANC:

Antenatal care

UN:

United Nations

FGDs:

Focus Group Discussions

CHW:

Community health workers

References

  1. Nunes AR, Lee K, Riordan TO. The importance of an integrating framework for achieving the Sustainable Development Goals : the example of health and well-being. 2016.

  2. Novillo-Ortiz D, De Fátima Marin H, Saigí-Rubió F. The role of digital health in supporting the achievement of the Sustainable Development Goals (SDGs). Int J Med Inform. 2018;114:106–7.

    Article  Google Scholar 

  3. Hwang WJ, Park YM, Factors Influencing the Accessibility of Maternal Health Service in Cambodia. 2020.

  4. Makanga PT et al. Seasonal variation in geographical access to maternal health services in regions of southern Mozambique. Int J Health Geogr. 2017;16(1).

  5. World Health Organization, mHealth, use of appropriate digital technologies for public health., Seventy-first World Heal. Assem. - Provisional agenda item 12.4. 2018;28.

  6. Kahn JG, Yang JS, KJS. Mobile’ Health Needs and Opportunities in Developing Countries. Health Aff. 2005;2(1):699–706.

    Google Scholar 

  7. GSMA Intelligence The Mobile Economy Sub-Saharan Africa London. 2019.

  8. World Bank, DIGITAL DIVIDENDS 2016.

  9. Qureshi SS, Afzali FM. Role of Mobile Phone Penetration and the Health Index in Human Development. 2017:0–10.

  10. Boulos MNK, Anastasiou A. Geo-enabled technologies for independent living : Examples from four European projects Author’s final version as accepted in September 2010 for publication in : Journal Technology and Disability Publisher : IOS Press Volume 23, Number 1 / 2011 Pages,” Technol Disabil. 2011;23:7–17.

  11. Boulos MNK, et al. CAALYX : a new generation of location-based services in healthcare. Int J Health Georg. 2007;6:1–6.

    Article  Google Scholar 

  12. Working Group on Planning (GTplan), Spatial Data Infrastructure ( SDI ) Manual for the Americas 2013.

  13. Dykes PC, et al. Participatory Design and Development of a Patient-centered Toolkit to Engage Hospitalized Patients and Care Partners in their Plan of Care. AMIA Annu Symp Proc. 2014;8:486–95.

    Google Scholar 

  14. Arskey H, O’Malley L. Scoping Studies: Towards a Methodological Framework. Int J Soc Res Methodol Theory Pract. 2005;22(1):29–49.

    Google Scholar 

  15. Devogele T, Géographique I, Cogit N, Saint Mandé F, Parent C, Spaccapietra S. On spatial database integration. 1998;12(3):1–20.

    Google Scholar 

  16. Makanga PT, Schuurman N, Sacoor C, Boene H, von Dadelszen P, Firoz T. Guidelines for creating framework data for GIS analysis in low- and middle-income countries. Can Geogr. 2016;60(3):320–32.

    Article  Google Scholar 

  17. Maina J, et al. A spatial database of health facilities managed by the public health sector in sub Saharan Africa. Sci data. 2019;6(1):134.

    Article  Google Scholar 

  18. Ming W, Qingquan LI, Qingwu HU, Meng Z. Quality Analysis of Open Street Map Data. Int Arch Photogramm Remote Sens Spat Inf Sci. 2013;XL(June):155–8.

    Google Scholar 

  19. See L, et al. Crowdsourcing, Citizen Science or Volunteered Geographic Information ? The Current State of Crowdsourced Geographic Information. Int J Geo-Information. 2016;5(55):23.

    Google Scholar 

  20. Mokgalaka H. Measuring Access to Primary Health Care : Use of a GIS-Based Accessibility Analysis in Planning Africa 2014 Conference. 2014.

  21. Makanga PT, Schuurman N, Von Dadelszen P, Firoz T. A scoping review of geographic information systems in maternal health. Int J Gynecol Obstet. 2016;134(1):13–7.

    Article  Google Scholar 

  22. Ebener S. et al. The geography of maternal and newborn health : the state of the art. ???. 2015.

  23. Data H. et al. Health Data in the Information Age. 1994.

  24. Baynon-Davies P. Database systems. 3rd ed. New York: Palgrave Macmillan; 2004.

    Book  Google Scholar 

  25. Baktha K. Mobile Application Development : All the Steps and Guidelines for Successful Creation of Mobile App : Case Study, 2017;6(9):15–20.

  26. Stoica M, Mircea M, Ghilic-micu B. Software Development: Agile vs. Traditional, no. December, 2013.

  27. Abrahamsson P, Salo O, Ronkainen J, Warsta J. Agile software development methods: Review and analysis. VTT Publ. 2002;478:3–107.

    Google Scholar 

  28. Rajput GS, Litoriya R. Corad Agile Method for Agile Software Cost Estimation. 2014:1–13.

  29. Amen BM, Mahmood SM, Lu J. Mobile Application Testing Matrix and Challenges. 2015:27–40.

  30. Pan American Health Organisation, Health in all Policies. From the Global to the Local, Washington DC. 2009.

  31. Syed ST, Gerber BS, Sharp LK. Traveling Towards Disease: Transportation Barriers to Health Care Access. J Community Heal. 2013;38(5):976–93.

    Article  Google Scholar 

  32. Artiga S, Hinton E. Beyond Health Care: The Role of Social Determinants in Promoting Health and Health Equity | The Henry J. Kaiser Family Foundation, Kaiser Family Foundation. 2018.

  33. Olstad DL, McIntyre L. Reconceptualising precision public health. BMJ Open. 2019;9(9):1–9.

    Article  Google Scholar 

  34. Howitt P, et al. Technologies for global health. Lancet. 2012;380(9840):507–35.

    Article  Google Scholar 

  35. Maguire M, Bevan N. User requirements analysis: A review of supporting methods in Proceedings of IFIP 17th World Computer Congres. 2002:133–148.

Download references

Acknowledgements

The authors gratefully acknowledge front end application developers from Moorfield Investments for sharing some of their application development cycles. We would also like to sincerely thank the manuscript reviewers for their time, interest, and thoughtful feedback.

Funding

This manuscript is drawn from the RoadMApp project which is currently being funded by Grand Challenges Canada (GCC), Grant No. R-ST-POC-1807–12966 Stars in Global Health.

Author information

Authors and Affiliations

  1. Surveying and Geomatics Department, Faculty of Science and Technology, Midlands State University, Gweru, Zimbabwe

    Newton Nyapwere, Yolisa P. Dube & Prestige T. Makanga

Authors
  1. Newton Nyapwere
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yolisa P. Dube
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Prestige T. Makanga
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

NN conceived and designed the guidelines, as well as drafting the first version of the manuscript. All authors contributed in findings and read and approved the final draft.

Corresponding author

Correspondence to Newton Nyapwere.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nyapwere, N., Dube, Y.P. & Makanga, P.T. Guidelines for developing geographically sensitive mobile health applications. Health Technol. 11, 379–387 (2021). https://doi.org/10.1007/s12553-020-00518-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12553-020-00518-2

Keywords

Search

Navigation