Healthc Inform Res.  2020 Apr;26(2):119-128. 10.4258/hir.2020.26.2.119.

Qualitative and Quantitative Analysis of Definitions of e-Health and m-Health

Affiliations
  • 1Department of Communication, Faculty of Letters and Humanities, University of Douala, Douala,
  • 2EitiCol Networks, Jönköping,

Abstract

Objectives

Skills to employ nursing informatics to promote the health of individuals is of such importance that it is considered a core competence. Although investments are made to increase the use of e-health, there is no full understanding of the usability of e-health for healthcare. This paper presents a current picture of how e-health and m-health are defined and used as well as the effects their usage may have on the intended target group.

Methods

Peer-reviewed open-access papers and grey literature that define e-health and m-health from PubMed, SpringerLink, and Google.com were randomized. A mixed method design with an inductive approach was employed. Open-source software were used for analysis.

Results

The overview includes 30 definitions of e-health and m-health, respectively. The definitions were thematised into 14 narrative themes. The results of the study, and primarily a three-level model, provide an understanding of how different types of e-health and m-health can be put into practice, and the effects or consequences of using them, which may be either positive or negative.

Conclusions

Mobility and flexibility is important for both m-health and e-health. Five keywords that characterize the definitions of e-health and m-health are “health”, “mobile”, “use”, “information”, and “technology”. E-health or m-health cannot replace human actors because e-health and m-health consist of social and material interactions. Using e-health and m-health is, thus, about developing healthcare without compromising native relics.


Keyword

Data Mining; Meaningful Use; Health Information Exchange; Health Information Systems; Terminology as Topic

Figure

  • Figure 1 Flow diagram for the search process.

  • Figure 2 Themes and frequency in definitions.

  • Figure 3 Dendrogram: cluster and distance between terms.

  • Figure 4 Frequency of the terms in the definitions.


Cited by  1 articles

Modification of Case-Based Reasoning Similarity Formula to Enhance the Performance of Smart System in Handling the Complaints of in vitro Fertilization Program Patients
Paminto Agung Christianto, Eko Sediyono, Irwan Sembiring
Healthc Inform Res. 2022;28(3):267-275.    doi: 10.4258/hir.2022.28.3.267.


Reference

References

1. International Telecommunication Union. Fast-forward progress leveraging tech to achieve the global goals [Internet]. Geneva, Switzerland: International Telecommunication Union;2017. [cited at 2020 Apr 28]. Available from: https://www.itu-ilibrary.org/science-andtechnology/fast-forward-progress_pub/80f4cf5d-en.
2. Baines D, Gahir IK, Hussain A, Khan AJ, Schneider P, Hasan SS, et al. A scoping review of the quality and the design of evaluations of mobile health, telehealth, smart pump and monitoring technologies performed in a pharmacy-related setting. Front Pharmacol. 2018; 9:678.
Article
3. Titilayo OD, Okanlawon FA. Assessment of mobile health nursing intervention knowledge among community health nurses in Oyo State, Nigeria. Afr J Med Med Sci. 2014; 43(Suppl 1):147–55.
4. Tran BX, Le XT, Nguyen PN, Le QN, Mai HT, Nguyen HL, et al. Feasibility of e-health interventions on smoking cessation among vietnamese active internet users. Int J Environ Res Public Health. 2018; 15(1):165.
Article
5. Bacigalupe G, Askari SF. E-Health innovations, collaboration, and healthcare disparities: developing criteria for culturally competent evaluation. Fam Syst Health. 2013; 31(3):248–63.
Article
6. Celes RS, Rossi TR, de Barros SG, Santos CM, Cardoso C. Telehealth as state response strategy: systematic review. Rev Panam Salud Publica. 2018; 42:e84.
7. Gholamhosseini L, Ayatollahi H. The design and application of an e-health readiness assessment tool. Health Inf Manag. 2017; 46(1):32–41.
Article
8. Bernardes AC, Coimbra LC, Serra HO. Use of telehealth as a tool to support continuing health education. Rev Panam Salud Publica. 2018; 42:e134.
9. Raiha T, Tossavainen K, Enkenberg J, Turunen H. Implementation of an ICT-based learning environment in a nutrition health project. Health Educ. 2012; 112(3):217–35.
10. Solli H, Bjork IT, Hvalvik S, Helleso R. Like an extended family: relationships that emerge when older caregivers use written messages to communicate in an ICT-based healthcare service. Inform Health Soc Care. 2018; 43(2):207–17.
Article
11. Ministry of Health and Social Affairs. Vision for eHealth 2025: common starting points for digitisation of social services and health care [Internet]. Stockholm, Sweden: Ministry of Health and Social Affairs;2016.
12. Mattsson S, Olsson EM, Carlsson M, Johansson BB. Identification of anxiety and depression symptoms in patients with cancer: comparison between short and long web-based questionnaires. J Med Internet Res. 2019; 21(4):e11387.
Article
13. Gund A, Lindecrantz K, Schaufelberger M, Patel H, Sjoqvist BA. Attitudes among healthcare professionals towards ICT and home follow-up in chronic heart failure care. BMC Med Inform Decis Mak. 2012; 12:138.
Article
14. Oh H, Rizo C, Enkin M, Jadad A. What is eHealth (3): a systematic review of published definitions. J Med Internet Res. 2005; 7(1):e1.
Article
15. Skar L, Soderberg S. The importance of ethical aspects when implementing eHealth services in healthcare: a discussion paper. J Adv Nurs. 2018; 74(5):1043–50.
Article
16. Apolinario-Hagen J, Fritsche L, Bierhals C, Salewski C. Improving attitudes toward e-mental health services in the general population via psychoeducational information material: a randomized controlled trial. Internet Interv. 2018; 12:141–9.
17. Oberg U, Orre CJ, Isaksson U, Schimmer R, Larsson H, Hornsten A. Swedish primary healthcare nurses’ perceptions of using digital eHealth services in support of patient self-management. Scand J Caring Sci. 2018; 32(2):961–70.
Article
18. Stroetmann VN, Kalra D, Lewalle P, Rector A, Rodrigues JM, Stroetmann KA, et al. Semantic interoperability for better health and safer healthcare-deployment and research roadmap for Europe. Brussels, Belgium: European Communities;2009.
19. Zhao X, Li X, Yang W, Feng Q, Zhou Y, Wang Q. Primary health information standard system based on semantic interoperability. BMC Med Inform Decis Mak. 2018; 18(Suppl 5):112.
Article
20. Grant MJ, Booth A. A typology of reviews: an analysis of 14 review types and associated methodologies. Health Info Libr J. 2009; 26(2):91–108.
Article
21. Pang B, Lee L. Movie Review Data [Internet]. Ithaca (NY): Cornell University;c2019. [cited at 2020 Apr 28]. Available from: http://www.cs.cornell.edu/people/pabo/movie-review-data/.
22. Chan M. A short R package review: RQDA [Internet]. [place unknown]. R-bloggers;2018. [cited at 2020 Apr 28]. Available from: https://www.r-bloggers.com/a-short-r-package-review-rqda/.
23. Bailey KD. A three-level measurement model. Qual Quant. 1984; 18(3):225–45.
Article
24. Bailey KD. Philosophical foundations of sociological measurement: a note on the three level model. Qual Quant. 1986; 20(4):327–37.
Article
25. Kjellstrom S, Golino H. Mining concepts of health responsibility using text mining and exploratory graph analysis. Scand J Occup Ther. 2019; 26(6):395–410.
26. Galili T. Dendextend: an R package for visualizing, adjusting and comparing trees of hierarchical clustering. Bioinformatics. 2015; 31(22):3718–20.
Article
27. Mandujano S. Analysis and trends of photo-trapping in Mexico: text mining in R. Therya. 2019; 10(1):25–32.
Article
28. Al-Ozairi E, Ridge K, Taghadom E, de Zoysa N, Tucker C, Stewart K, et al. Diabetes and TelecommunicationS (DATES) study to support self-management for people with type 2 diabetes: a randomized controlled trial. BMC Public Health. 2018; 18(1):1249.
Article
29. Han HR, Hong H, Starbird LE, Ge S, Ford AD, Renda S, et al. eHealth literacy in people living with HIV: systematic review. JMIR Public Health Surveill. 2018; 4(3):e64.
Article
30. Fysioterapeuterna. Strategy for e-health and digitalisation developed [Internet]. Stockholm, Sweden: Fysioterapeuterna;2018. [cited at 2020 Apr 28]. Available from: https://www.fysioterapeuterna.se/Om-forbundet/nyheter/2018/2018/strategi-for-e-halsa-och-digitalisering/.
31. Soderkoping Municipality. E-health and welfare technology [Internet]. Soderkoping, Sweden: Soderkoping Municipality;c2019. [cited at 2020 Apr 28]. Available from: https://www.soderkoping.se/stod-omsorg/e-halsa-och-valfardsteknik/.
32. Ilozumba O, Dieleman M, Kraamwinkel N, Van Belle S, Chaudoury M, Broerse JE. “I am not telling. The mobile is telling”: factors influencing the outcomes of a community health worker mHealth intervention in India. PLoS One. 2018; 13(3):e0194927.
Article
33. Phillips JL, Heneka N, Lovell M, Lam L, Davidson P, Boyle F, et al. A phase III wait-listed randomised controlled trial of novel targeted inter-professional clinical education intervention to improve cancer patients’ reported pain outcomes (The Cancer Pain Assessment (CPAS) Trial): study protocol. Trials. 2019; 20(1):62.
Article
34. Nelissen HE, Cremers AL, Okwor TJ, Kool S, van Leth F, Brewster L, et al. Pharmacy-based hypertension care employing mHealth in Lagos, Nigeria: a mixed methods feasibility study. BMC Health Serv Res. 2018; 18(1):934.
Article
35. MidCentral Digital Health Board. Te Awa – MidCentral Digital Health Strategy [Internet]. Palmerston North, New Zealand: MidCentral District Health Board;c2020. [cited at 2020 Apr 28]. Available from: http://www.midcentraldhb.govt.nz/Planning/localPlan/Pages/DigitalStrategy.aspx#.
36. Howley K. Role of mHealth in PHC [Internet]. Durham (NC): Duke Center for Personalized Health Care;2018. [cited at 2020 Apr 28]. Available from: https://dukeper-sonalizedhealth.org/2018/10/role-of-mhealth-in-phc/.
37. International Telecommunication Union. What is mHealth, what does it do & how does it benefit countries? [Internet]. Geneva, Switzerland: International Telecommunication Union;2019. [cited at 2020 Apr 28]. Available from: https://www.itu.int/en/ITU-D/ICT-Applications/eHEALTH/Be_healthy/Pages/guide-01.aspx.
38. Chagas CM, Pontes E, Silva TB, Reffatti LM, Botelho RB, Toral N. Rango Cards, a digital game designed to promote a healthy diet: a randomized study protocol. BMC Public Health. 2018; 18(1):910.
Article
39. US Agency for International Development. Digital health [Internet]. Washington (DC): US Agency for International Development;2018. [cited at 2020 Apr 28]. Available from: https://www.usaid.gov/global-health/global-health-newsletter/digital-health-2018.
40. Lupianez-Villanueva F, Anastasiadou D, Codagnone C, Nuno-Solinis R, Garcia-Zapirain Soto MB. Electronic health use in the European Union and the effect of multimorbidity: cross-sectional survey. J Med Internet Res. 2018; 20(5):e165.
Article
41. Samerski S. Individuals on alert: digital epidemiology and the individualization of surveillance. Life Sci Soc Policy. 2018; 14(1):13.
Article
42. Malasinghe LP, Ramzan N, Dahal K. Remote patient monitoring: a comprehensive study. J Ambient Intell Humaniz Comput. 2019; 10(1):57–76.
Article
43. Zielinski B, Iwanowski M. Tree-based binary image dissimilarity measure with meta-heuristic optimization. Pattern Anal Appl. 2016; 19(1):1–10.
44. Glinkowski WM, Karlinska M, Karlinski M, Krupinski EA. Telemedicine and eHealth in Poland from 1995 to 2015. Adv Clin Exp Med. 2018; 27(2):277–82.
Article
Full Text Links
  • HIR
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr