Skip to main content

The Healthcare System Perspective in mHealth

  • Chapter
  • First Online:
m_Health Current and Future Applications

Abstract

mHealth is gradually leveraging changes in the way health care can be delivered. This transformation is driven by increased mobile devices’ penetration and capabilities, along with growing patient data demand. New opportunities arise in the areas of telemedicine and patient monitoring as conventional clinical services (including Electronic Medical Record systems) can be integrated with mHealth devices and applications at the patient level. The benefits of mHealth can be enhanced by patient segmentation strategies and customization of services, in a way that is intended to be patient centered to meet the individual needs. Current trends and developments in technology such as rapid advances in the use of blockchains, machine learning, and artificial intelligence technologies have the potential to open unprecedented opportunities in mHealth and healthcare services. For these opportunities to translate into real benefits, further research and multi-stakeholder efforts are needed, for example, to address the issues of interoperability, information governance mechanisms, regulation and certification, and the sustainability of mHealth over the long term.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Amazon Web Services, Inc.: Machine Learning at AWS. https://aws.amazon.com/machine-learning/ (2018). Accessed 30 Jan 2018

  2. Balouchi, S., Keshavjee, K., Zbib, A., Vassanji, K.: Creating a supportive environment for self-management in healthcare via patient electronic tools. In: Househ, M., Borycki, E., Kushniruk, A. (eds.) Social Media and Mobile Technologies for Healthcare, pp. 109–125. IGI Global (2014)

    Google Scholar 

  3. Bastawrous, A., Armstrong, M.J.: Mobile health use in low- and high-income countries: an overview of the peer-reviewed literature. J. R. Soc. Med. 106(4), 130–142 (2013)

    Article  Google Scholar 

  4. Better Care Fund (BCF) NHS England: How to Guide: The BCF Technical Toolkit Section 1: Population Segmentation, Risk Stratification and Information Governance. https://www.england.nhs.uk/wp-content/uploads/2014/09/1-seg-strat.pdf (2014). Accessed 30 Jan 2018

  5. Butcher, L.: Consumer segmentation has hit health care. Heres how it works. https://www.hhnmag.com/articles/6932-consumer-segmentation-just-hit-health-care-heres-how-it-works (2016). Accessed 30 Jan 2018

  6. c2B solutions: Psychographic Segmentation—Changing Healthcare Consumer Behaviour by Engaging Their Motivations. https://www.c2bsolutions.com/psychographic-segmentation (2017). Accessed 30 Jan 2018

  7. Caremichael, S.G. (Interviewer), Christensen, C. (Interviewee).: The Jobs to be Done Theory of Innovation [Interview transcript]. Retrieved from the Harvard Business (2016) Review Website: https://hbr.org/ideacast/2016/12/the-jobs-to-be-done-theory-of-innovation. Accessed 30 Jan 2018

  8. Chindalo, P., Karim, A., Brahmbhatt, Saha, N., Keshavjee, K.: Health apps by design: a reference architecture for mobile engagement. Int. J. Handheld Comput. Res. (IJHCR) 7(2), 34–43 (2016)

    Article  Google Scholar 

  9. Cocosila, M., Coursaris, C., Yuan, Y.: M-healthcare for patient self-management: a case for diabetics. Int. J. Electron. Healthc. 1(2), 221–241 (2004)

    Article  Google Scholar 

  10. Cunningham, J., Ainsworth, J.: Enabling patient control of personal electronic health records through distributed ledger technology. Stud. Health Technol. Inform. 245, 45–48 (2017)

    Google Scholar 

  11. Dong, L., Keshavjee, K.: Why is information governance important for electronic healthcare systems? A Canadian experience. J. Adv. Humanit. Soc. Sci. 2016, 250–260 (2016)

    Google Scholar 

  12. Van Dongen, N.: The patient segmentation model. https://pharmaphorum.com/views-and-analysis/the-patient-segmentation-model/ (2014). Accessed 30 Jan 2018

  13. Esposito, M., Minutolo, A., Megna, R., Forastiere, M., Magliulo, M., De Pietro, G.: A smart mobile, self-configuring, context-aware architecture for personal health monitoring. Eng. Appl. Artif. Intell. 67, 136–156 (2018)

    Article  Google Scholar 

  14. Federal Communications Commission (FCC). mHealth Task Force findings and recommendations. http://www2.itif.org/2012-mhealth-taskforce-recommendations.pdf (2012). Accessed 30 Jan 2018

  15. Foster, K.R., Callans, D.J.: Smartphone apps meet evidence based medicine. IEEE Pulse 8(6), 34–39 (2017)

    Article  Google Scholar 

  16. Gay, V., Leijdekkers, P.: A health monitoring system using smart phones and wearable sensors. Int. J. ARM 8(2), 2935 (2017)

    Google Scholar 

  17. Ghany, A., Keshavjee, K.: A platform to collect structured data from multiple EMRs. Stud. Health Technol. Inform. 208, 142–146 (2015)

    Google Scholar 

  18. Habetha, J.: The MyHeart project-fighting cardiovascular diseases by prevention and early diagnosis. In: International Conference of the IEEE Engineering in Medicine and Biology Society 2006, pp. 6746–6749 (2006)

    Google Scholar 

  19. Van Halteren, A., Bults, R.G.A., Wac, K.E., Konstantas, D, Widya, I.A., Dokovski, N.T., Koprinkov, G.T., Jones, V.M., Herzog, R.: Mobile patient monitoring: the Mobihealth system. J. Inform. Technol. Healthc. 2(5), 365–373 (2004)

    Google Scholar 

  20. Health Affairs. Health Policy Brief: Patient Engagement. https://www.healthaffairs.org/action/showDoPubSecure?doi=10.1377%2Fhpb20130214.898775&format=full (2013). Accessed 30 Jan 2018

  21. Health Level Seven International (HL7). http://www.hl7.org/ (2018). Accessed 30 Jan 2018

  22. Health Level Seven International (HL7) Argonaut Project Wiki. Argonautwiki.hl7.org. http://argonautwiki.hl7.org/index.php?title=MainPage (2018). Accessed 30 Jan 2018

  23. HealthIT.gov. What is HIE? https://www.healthit.gov/providers-professionals/healthinformation-exchange/what-hie (2016). Accessed 30 Jan 2018

  24. Hult Marketing. Know Your Audience: Building Patient Personas [Weblog comment]. https://blog.hultmarketing.com/blog/building-patient-personas (2017). Accessed 30 Jan 2018

  25. Ichikawa, D., Kashiyama, M., Ueno, T.: Tamper-resistant mobile health using blockchain technology. JMIR Mhealth Uhealth 5(7), e111 (2017)

    Article  Google Scholar 

  26. Institute for Healthcare Improvement (IHI). One Size Does Not Fit All: Think Segmentation. http://www.ihi.org/resources/Pages/ImprovementStories/OneSizeDoesNotFitAllThinkSegmentation.aspx. Accessed 30 Jan 2018

  27. ISO 13606. http://www.en13606.org/. Accessed 30 Jan 2018

  28. Kalra, D., Blobel, B.: Semantic interoperability of EHR systems. Stud. Health Technol. Inform. 127, 231 (2007)

    Google Scholar 

  29. Kelli, H.M., Witbrodt, B., Shah, A.: The future of mobile health applications and devices in cardiovascular health. Euro. Med. J. Innov. 2017, 92–97 (2017)

    Google Scholar 

  30. Keshavjee, K., Mirza, K., Martin, K.: The next generation EMR. Stud. Health Technol. Inform. 208, 210–214 (2015)

    Google Scholar 

  31. Kher, R.K.: Mobile and e-Healthcare: recent trends and future directions. J. Health Med. Econ. 2(3), 10 (2016)

    Google Scholar 

  32. Knight Marketing. Using Patient Personas for More Effective Healthcare Marketing. http://knightmarketing.com/blog/using-patient-personas-for-more-effective-healthcare-marketing/ (2016). Accessed 30 Jan 2018

  33. Laxman, K., Krishnan, S.B., Dhillon, J.S.: Barriers to adoption of consumer health informatics applications for health self management. Health Sci. J. 9(5), 1–7 (2015)

    Google Scholar 

  34. Marceglia, S., Fontelo, P., Rossi, E., Ackerman, M.J.: A standards-based architecture proposal for integrating patient mHealth apps to electronic health record systems. Appl. Clin. Inform. 6, 488505 (2015)

    Google Scholar 

  35. McKinsey&Company. A 360-degree approach to patient adherence. http://www.mckinsey.com/industries/pharmaceuticals-and-medical-products/our-insights/a-360-degree-approach-to-patient-adherence (2017). Accessed 30 Jan 2018

  36. NHS England. (2017). List of risk stratification approved organizations. https://www.england.nhs.uk/wp-content/uploads/2017/03/risk-stratification-approved-orgs-290317.pdf. Accessed 30 Jan 2018

  37. Ozdalga, E., Ozdalga, A., Ahuja, N.: The smartphone in medicine: a review of current and potential use among physicians and students. J. Med. Internet Res. 14(5), e128 (2012)

    Article  Google Scholar 

  38. Paglialonga, A., Mastropietro, A., Scalco, E., Rizzo, G.: The mHealth. Chapter 2, this volume. (2019)

    Google Scholar 

  39. Paglialonga, A., Lugo, A., Santoro, E.: An overview on the emerging area of identification, characterization, and assessment of health apps. J. Biomed. Inform. 83, 97–102 (2018)

    Article  Google Scholar 

  40. Paradiso, R., Loriga, G., Taccini, N.: Wearable system for vital signs monitoring. Stud. Health Technol. Inform. 108, 253–259 (2004)

    Google Scholar 

  41. PATH (Patterns of Adapting to Health) Institute. Patterns of Adapting to Health. http://www.pathinstitute.life/patterns-of-adapting-to-health.html (2017). Accessed 30 Jan 2018

  42. Philpott, D., Guergachi, A., Keshavjee, K.: Design and validation of a platform to evaluate mHealth apps. Stud. Health Technol. Inform. 235, 3–7 (2017)

    Google Scholar 

  43. Pyxl. Buyer Personas for Healthcare Digital Marketing. https://pyxl.com/articles/buyer-personas-healthcare-digital-marketing/ (2015). Accessed 30 Jan 2018

  44. Roess, A.: The promise, growth, and reality of mobile health another data-free zone. N. Engl. J. Med. 377, 2010–2011 (2017)

    Article  Google Scholar 

  45. Ruiz-Zafra, Benghazi, K., Noguera, M., Garrido, J.L.: Zappa: an open mobile platform to build cloud-based m-health systems. In: Ambient Intelligence-Software and Applications, p. 8794 (2013)

    Chapter  Google Scholar 

  46. SMART Health IT. SMART Health IT. https://smarthealthit.org/ (2018). Accessed 30 Jan 2018

  47. Smith, C.E., Spaulding, R., Piamjariyakul, U., Werkowitch, M., Yadrich, D.M., Hooper, D., Moore, T., Gilroy, R.: mHealth clinic appointment PC tablet: implementation, challenges and solutions. J. Mob. Technol. Med. 4(2), 21–32 (2015)

    Article  Google Scholar 

  48. Steinhubl, S.R., Muse, E.D., Topol, E.J.: The emerging field of mobile health. Sci. Transl. Med. 7(283), 283rv3 (2015)

    Article  Google Scholar 

  49. Tuckwell, K.J., Jaffey, M.: Market segmentation and target marketing. In: THINK Marketing, 2nd edn. Chapter 6. http://www.pearsoncanada.ca/media/highered-showcase/multi-product-showcase/tuckwell-think-ch06.pdf 2014. Accessed 30 Jan 30 2018

  50. Vuik, S.I., Mayer, E.K., Darzi, A.: Patient segmentation analysis offers significant benefits for integrated care and support. Health Aff. 35(5), 769–775 (2016)

    Article  Google Scholar 

  51. Williams, C., Mostashari, F., Mertz, K., Hogin, E., Atwal, P.: From the office of the national coordinator: the strategy for advancing the exchange of health information. Health Aff. (Millwood) 31(3), 527–536 (2012)

    Article  Google Scholar 

  52. Willison, D.J., Keshavjee, K., Nair, K., Goldsmith, C., Holbrook, A.M.: Computerization of medical practices for the enhancement of therapeutic effectiveness investigators. Patients’ consent preferences for research uses of information in electronic medical records: interview and survey data. BMJ 326(7385):373 (2003)

    Article  Google Scholar 

  53. World Health Organization (WHO).: mHealth: new horizons for health through mobile technologies: second global survey on eHealth. WHO Press, Geneva, Switzerland (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alessia Paglialonga .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Paglialonga, A., Patel, A.A., Pinto, E., Mugambi, D., Keshavjee, K. (2019). The Healthcare System Perspective in mHealth. In: Andreoni, G., Perego, P., Frumento, E. (eds) m_Health Current and Future Applications. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-02182-5_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-02182-5_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-02181-8

  • Online ISBN: 978-3-030-02182-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics