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The technological, organizational and environmental determinants of adoption of mobile health applications (m-health) by hospitals in Kenya


Autoři: Bahati Prince Ngongo aff001;  Phares Ochola aff001;  Joyce Ndegwa aff001;  Paul Katuse aff001
Působiště autorů: Chandaria School of Business, United States International University- Africa, Nairobi, Nairobi, Kenya aff001
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0225167

Souhrn

Introduction

Sub-Saharan Africa lags in adoption of mobile health (m-health) applications and in leveraging m-health for sustainable development goals. There is a need for a comprehensive investigation of determinants of hospitals’ adoption of m-health in Sub-Saharan Africa to inform policies, practices and investments.

Methods

This investigation used a logit regression model to analyze the determinants of m-health adoption in Kenyan hospitals applying the Technological, Organizational and Environmental (TOE) framework and the Diffusion of Innovation (DOI) theory. A representative sample of 211 executives of Level 4–6 hospitals in 24 counties provided primary data on Patient-Centered (PC) and Facility-Centered (FC) m-health applications.

Results

Both PC and FC m-health adoption were predicted by competition for patients (PC p = 0.041, FC p = 0.021), IT human resource capacity (PC p = 0.048, FC p = 0.037), and hospital pursuit of market growth through technological leadership (PC p = 0.010, FC p = 0.020). Further determinants of PC m-health adoption included hospital access to slack financial resources (p = 0.006), acquisition strategy (p = 0.011), compatibility with the hospital systems (p = 0.015), trialability (p = 0.019), medical insurance company support (p = 0.025),patient pressure (p = 0.036), and perceived effect of global medical tourism (p = 0.039). FC m-health adoption was predicted by hospital size (p = 0.008), ICT infrastructure capacity (p = 0.041), and government support (p = 0.013).

Conclusion

A differentiated approach is required to scale up m-health adoption. PC m-health requires emphasis on establishing national and regional compatibility and interoperability, developing trialability processes and validation mechanisms, incentivizing patient competition and mobility, establishing innovative and cost-effective acquisition strategies, and ensuring integration of digital services within national insurance schemes and policies. These policies require support from patients and communities to drive demand and spur investment in adequate IT human resources to maintain reliability. Pilot PC m-health projects should prioritize hospitals with slack financial resources, while FC m-health should target large facility size. FC m-health applications are more complex and costly than PC, requiring government incentives to trigger hospital investments and national investment in ICT infrastructure. Investors and hospital managers should integrate m-health into market growth strategies for sustainable m-health scale-up in Kenya and beyond.

Klíčová slova:

Kenya – Finance – Health care policy – Health insurance – Decision making – Communication in health care – Structure of markets


Zdroje

1. Pankomera R, van Greunen D. A model for implementing sustainable mHealth applications in a resource-constrained setting: A case of Malawi. The Electronic Journal of Information Systems in Developing Countries. 2018;84: e12019.

2. Asi YM, Williams C. The role of digital health in making progress toward Sustainable Development Goal (SDG) 3 in conflict-affected populations. Int J Med Inform. 2018;114: 114–120. doi: 10.1016/j.ijmedinf.2017.11.003 29126701

3. Gagnon M-P, Ngangue P, Payne-Gagnon J, Desmartis M. m-Health adoption by healthcare professionals: a systematic review. J Am Med Inform Assoc. 2016;23: 212–220. doi: 10.1093/jamia/ocv052 26078410

4. Akter S, Ray P. mHealth—an Ultimate Platform to Serve the Unserved. Yearb Med Inform. 2010; 94–100. 20938579

5. Mehl G, Labrique A. Prioritizing integrated mHealth strategies for universal health coverage. Science. 2014;345: 1284–1287. doi: 10.1126/science.1258926 25214614

6. Kay M, Santos J, Takane M. mHealth: New horizons for health through mobile technologies. World Health Organization. 2011;64: 66–71.

7. Tomlinson M, Rotheram-Borus MJ, Swartz L, Tsai AC. Scaling Up mHealth: Where Is the Evidence? PLoS Medicine. 2013. p. e1001382. doi: 10.1371/journal.pmed.1001382 23424286

8. Task Force Health Care, Kenya Healthcare Federation. Kenyan Healthcare Sector Market Study Report: Opportunities for the Dutch Life Sciences & Health sector. 2016. Available: https://www.tfhc.nl/wp-content/uploads/2016/09/2016-Kenyan-Healthcare-Sector-Report.pdf

9. Wesolowski A, Eagle N, Noor AM, Snow RW, Buckee CO. Heterogeneous Mobile Phone Ownership and Usage Patterns in Kenya. PLoS ONE. 2012. p. e35319. doi: 10.1371/journal.pone.0035319 22558140

10. Dwivedi YK, Shareef MA, Simintiras AC, Lal B, Weerakkody V. A generalised adoption model for services: A cross-country comparison of mobile health (m-health). Gov Inf Q. 2016;33: 174–187.

11. Hwang J, Christensen CM. Disruptive innovation in health care delivery: a framework for business-model innovation. Health Aff. 2008;27: 1329–1335.

12. Berwick DM. Improvement, trust, and the healthcare workforce. Qual Saf Health Care. 2003;12: 448–452. doi: 10.1136/qhc.12.6.448 14645761

13. Hoti E. The technological, organizational and environmental framework of IS innovation adaption in small and medium enterprises. Evidence from research over the last 10 years. International Journal of Business and Management. 2015. pp. 1–14. doi: 10.20472/bm.2015.3.4.001

14. Rogers EM. Diffusion of Innovations, 5th Edition. Simon and Schuster; 2003.

15. Tornatzky LG, Fleischer M, Chakrabarti AK. The processes of technological innovation. Lexington Books; 1990.

16. Zurovac D, Sudoi RK, Akhwale WS, Ndiritu M, Hamer DH, Rowe AK, et al. The effect of mobile phone text-message reminders on Kenyan health workers’ adherence to malaria treatment guidelines: a cluster randomised trial. The Lancet. 2011. pp. 795–803. doi: 10.1016/S1470-2045(11)70189-9 21782507

17. Govindarajulu C, Lippert SK. The Status of End-User Computing Support: An Exploratory Study. Proceedings of the 2002 InSITE Conference. 2002. doi: 10.28945/2490

18. Racherla P, Hu C. eCRM System Adoption by Hospitality Organizations: A Technology-Organization-Environment (TOE) Framework. Journal of Hospitality & Leisure Marketing. 2008. pp. 30–58. doi: 10.1080/10507050801978372

19. Lian J-W, Yen DC, Wang Y-T. An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital. International Journal of Information Management. 2014. pp. 28–36. doi: 10.1016/j.ijinfomgt.2013.09.004

20. Ramdani B, Lorenzo O, Kawalek P. Information Systems Innovations Adoption and Diffusion Among SMEs. E-Adoption and Socio-Economic Impacts. 2011. pp. 57–70. doi: 10.4018/978-1-60960-597-1.ch004

21. Ramdani B, Kawalek P, Lorenzo O. Predicting SMEs’ adoption of enterprise systems. Journal of Enterprise Information Management. 2009. pp. 10–24. doi: 10.1108/17410390910922796

22. Ochola P. An empirical study of determinants of e-commerce adoption amongst micro, small and medium enterprises (MSMEs) in Kenya. Internal Journal of Economics, Commerce and Management, 3 (12). 2015; 223–240.

23. Rye CB, Kimberly JR. The Adoption of Innovations by Provider Organizations in Health Care. Medical Care Research and Review. 2007. pp. 235–278. doi: 10.1177/1077558707299865 17507458

24. Porter ME. On Competition. Harvard Business Press; 2008.

25. Adams R, Bessant J, Phelps R. Innovation management measurement: A review. International Journal of Management Reviews. 2006;8: 21–47.

26. Hodges JR, Kimball AM, Turner L. Risks and Challenges in Medical Tourism: Understanding the Global Market for Health Services: Understanding the Global Market for Health Services. ABC-CLIO; 2012.

27. Michael Hall C. Medical Tourism: The Ethics, Regulation, and Marketing of Health Mobility. Routledge; 2012.

28. Creswell JW, Hanson WE, Clark Plano VL, Morales A. Qualitative Research Designs. The Counseling Psychologist. 2007. pp. 236–264. doi: 10.1177/0011000006287390

29. Andy Fields JM. Discovering statistics using SPSS. Sage Publications; 2010.

30. Foxcroft C, Paterson H, Le Roux N, Herbst D. Psychological assessment in South Africa: a needs analysis: the test use patterns and needs of psychological assessment practitioners: final report. July. 2015 [cited 20 Nov 2019]. Available: http://repository.hsrc.ac.za/handle/20.500.11910/7498

31. Fincham JE. Response rates and responsiveness for surveys, standards, and the Journal. American journal of pharmaceutical education. 2008. p. 43. doi: 10.5688/aj720243 18483608

32. Lee Y-H, Hsieh Y-C, Hsu C-N. Adding Innovation Diffusion Theory to the Technology Acceptance Model: Supporting Employees’ Intentions to Use E-Learning Systems. Educational Technology & Society. 2011;14: 124–137.

33. Buonanno G. Factors affecting ERP system adoption. Journal of Enterprise Information Management. 2005;18: 384–426.

34. Alshamaila Y, Papagiannidis S, Li F. Cloud computing adoption by SMEs in the north east of England. Journal of Enterprise Information Management. 2013. pp. 250–275. doi: 10.1108/17410391311325225

35. Parker CM, Castleman T. Small firm e‐business adoption: a critical analysis of theory. Journal of Enterprise Information Management. 2009. pp. 167–182. doi: 10.1108/17410390910932812

36. Scupola A. SMEs’ e‐commerce adoption: perspectives from Denmark and Australia. Journal of Enterprise Information Management. 2009. pp. 152–166. doi: 10.1108/17410390910932803

37. Van Huy L, Rowe F, Truex D, Huynh MQ. An Empirical Study of Determinants of E-Commerce Adoption in SMEs in Vietnam. Journal of Global Information Management. 2012. pp. 23–54. doi: 10.4018/jgim.2012070102

38. Alam SS, Noor MKM. ICT Adoption in Small and Medium Enterprises: an Empirical Evidence of Service Sectors in Malaysia. International Journal of Business and Management. 2009. doi: 10.5539/ijbm.v4n2p112

39. Grandon EE, Michael Pearson J. Electronic commerce adoption: an empirical study of small and medium US businesses. Information & Management. 2004. pp. 197–216. doi: 10.1016/j.im.2003.12.010

40. Ghobakhloo M, Arias‐Aranda D, Benitez‐Amado J. Adoption of e‐commerce applications in SMEs. Industrial Management & Data Systems. 2011. pp. 1238–1269. doi: 10.1108/02635571111170785

41. Stockdale R, Standing C. Benefits and barriers of electronic marketplace participation: an SME perspective. Journal of Enterprise Information Management. 2004. pp. 301–311. doi: 10.1108/17410390410548715

42. Herzlinger RE. Why Innovation in Health Care Is So Hard. Harvard Business Review. 1 May 2006. Available: https://hbr.org/2006/05/why-innovation-in-health-care-is-so-hard Accessed 20 Nov 2019.

43. Mechael P, Batavia H, Kaonga N, Searle S, Kwan A, Goldberger A, et al. Barriers and gaps affecting mHealth in low and middle income countries: Policy white paper. Columbia university. Earth institute. Center for global health and economic …; 2010.

44. Ferlie E, Fitzgerald L, Wood M, Hawkins C. The Nonspread of Innovations: the Mediating Role of Professionals. Academy of Management Journal. 2005. pp. 117–134. doi: 10.5465/amj.2005.15993150

45. Househ M, Borycki EM, Kushniruk AW. mHealth: a passing fad or here to stay? and e-health services …. 2012. Available: https://www.igi-global.com/chapter/mhealth-passing-fad-here-stay/64988


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