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BMC Medical Informatics and Decision Making

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Open Access 01-12-2019 | Research article

Multi-part quality evaluation of a customized mobile application for monitoring elderly patients with functional loss and helping caregivers

Authors: Matheus Costa Stutzel, Michel Pedro Filippo, Alexandre Sztajnberg, Rosa Maria E.M. da Costa, André da Silva Brites, Luciana Branco da Motta, Célia Pereira Caldas

Published in: BMC Medical Informatics and Decision Making | Issue 1/2019

Abstract

Background

The challenges faced by caregivers of the elderly with chronic diseases are always complex. In this context, mobile technologies have been used with promising results, but often have restricted functionality, or are either difficult to use or do not provide the necessary support to the caregiver - which leads to declining usage over time. Therefore, we developed the Mobile System for Elderly Monitoring, SMAI. The purpose of SMAI is to monitor patients with functional loss and to improve the support to caregivers’ communication with the health team professionals, informing them the data related to the patients’ daily lives, while providing the health team better tools.

Method

SMAI is composed of mobile applications developed for the caregivers and health team, and a web portal that supports management activities. Caregivers use an Android application to send information and receive care advice and feedback from the health team. The system was constructed using a refinement stage approach. Each stage involved caregivers and the health team in prototype release-test-assessment-refinement cycles. SMAI was evaluated during 18 months. We studied which features were being used the most, and their use pattern throughout the week. We also studied the users’ qualitative perceptions. Finally, the caregiver application was also evaluated for usability.

Results

SMAI functionalities showed to be very useful or useful to caregivers and health professionals. The Focus Group interviews reveled that among caregivers the use of the application gave them the sensation of being connected to the health team. The usability evaluation identified that the interface design and associated tasks were easy to use and the System Usability Scale, SUS, presented very good results.

Conclusions

In general, the use of SMAI represented a positive change for the family caregivers and for the NAI health team. The overall qualitative results indicate that the approach used to construct the system was appropriate to achieve the objectives.

Prince M, Wimo A, Guerchet M, Ali G-C, Wu Y-T, Prina M, Prince M. World Alzheimer Report 2016. Improving healthcare for people living with dementia: Coverage, quality and costs now and in the future. London: Alzheimer’s Disease International (ADI); 2016. https://www.alz.co.uk/research/world-report-2016. Accessed Jun 2017

Alzheimer’s Disease International (ADI). Dementia in the Americas: Current and future cost and prevalence of Alzheimer’s disease and other dementias. ADI/Bupa Rep. 2013. https://www.alz.co.uk/sites/default/files/pdfs/dementia-in-the-americas-ENGLISH.pdf. Accessed Feb 2017

Gragnolati M, Jorgensen OH, Rocha R, Fruttero A. Growing Old in an Older Brazil. Implications of Population Ageing on Growth, Poverty, Public Finance, and Service Delivery. Washington, DC: EUA; 2017. The World Bank. https://openknowledge.worldbank.org/handle/10986/2351. Accessed Sep 2017.

de Saúde Suplementar (ANS) AN. Plano de Cuidado para o idoso na saúde suplementar [in portuguese]. Brasil: Min. Saúde; 2012. http://bvsms.saude.gov.br/bvs/publicacoes/plano_cuidado_idosos.pdf. Accessed Oct 2013.

da Saúde do Brasil M. Política Nacional de Saúde da Pessoa Idosa, Portaria n ^∘ordm; 2.528/2006 [in portuguese]. 2006. http://dtr2001.saude.gov.br/sas/PORTARIAS/Port2006/GM/GM-2528.htm. Accessed Oct 2013.

(UNFPA) UNPF. Aging in the Twenty-First Century: A Celebration and A Challenge. 2012. http://www.unfpa.org/webdav/site/global/shared/documents/publications/2012/UNFPA-Exec-Summary.pdf. Accessed Oct 2013.

Moussa Y, Mahdanian AA, Yu C, Segal M, Looper KJ, Vahia IV, Rej S. Mobile health technology in late-life mental illness: a focused literature review. Am J Geriatr Psychiatr. 2017; 25(8):865–72.CrossRef

Bateman DR, Srinivas B, Emmett TW, Schleyer TK, Holden RJ, Hendrie HC, Callahan CM. Categorizing health outcomes and efficacy of mhealth apps for persons with cognitive impairment: a systematic review. J Med Internet Res. 2017; 19(8):301.CrossRef

Gartrell K, Brennan CW, Wallen GR, Liu F, Smith KG, Fontelo P. Clinicians’ perceptions of usefulness of the pubmed4hh mobile device application for clinical decision making at the point of care: a pilot study. BMC Med Inf Decis Making. 2018; 18(1):27.CrossRef

10.

Kim S, Shaw C, Williams KN, Hein M. Typology of technology-supported dementia care interventions from an in-home telehealth trial. West J Nurs Res. 2019. https://doi.org/10.1177/0193945919825861.

11.

Dorsey ER. Randomized controlled trial of “virtual houses calls” for Parkinson disease. JAMA Neurol. 2013; 70(5):565–70. https://doi.org/10.1001/jamaneurol.2013.123.CrossRef

12.

Celler EG, Basilakis J, Budge M, Lovell NH. A clinical monitoring and management system for residential aged care facilities. In: 28th IEEE EMBS Annual International Conferences. New York: IEEE: 2006. p. 3301–04. https://doi.org/10.1109/IEMBS.2006.259974.

13.

Keränen T, Liikkanen S. Medication reminder service for mobile phones: an open feasibility study in patients with Parkinson’s disease. Telemed E-Health J. 2013; 19(11):888–90. https://doi.org/10.1089/tmj.2013.0014.CrossRef

14.

Finkelstein SM, Speedie SM, Potthoff S. Home telehealth improves clinical outcomes at lower cost for home healthcare. Telemed E-Health J. 2006; 12(2):128–36. https://doi.org/10.1089/tmj.2006.12.128.CrossRef

15.

Fischer GS, Hess R, Landeen BM, Weimer M, Zieth CR, Dong X, Clark S, Roberts MS. Electronic reminders to patients within an interactive patient health record. Telemed E-Health J. 2013; 19(6):497–500. https://doi.org/10.1089/tmj.2012.0116.CrossRef

16.

Arif MJ, Emary IMME, Koutsouris D-D. A review on the technologies and services used in the self-management of health and independent living of elderly. Technol Health Care. 2014; 22(5):677–87. https://doi.org/10.3233/THC-140851.

17.

Boulos MK, Brewer A, Karimkhani C, Buller D, Dellavalle R. Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online J Public Health Inform. 2014; 5(3):229. https://doi.org/10.5210/ojphi.v5i3.4814.

18.

Meiling J, Jeongeun K. Development and evaluation of an evaluation tool for healthcare smartphone application. Telemed E-Health J. 2015; 21(10):831–7. https://doi.org/10.1089/tmj.2014.0151.CrossRef

19.

Cook VE, Ellis AK, Hildebrand KJ. Mobile health applications in clinical practice: pearls, pitfalls, and key considerations. Ann Allergy Asthma Immunol. 2016; 117(2):143–9. https://doi.org/10.1016/j.anai.2016.01.012.CrossRef

20.

Peek STM, Wouters EJM, van Hoof J, Luijkx KG, Boeije HR, Vrijhoef HJM. Factors influencing acceptance of technology for aging in place: A systematic review. Int J Med Infor. 2014; 83(4):235–48. https://doi.org/10.1016/j.ijmedinf.2014.01.004.CrossRef

21.

Yusif S, Soar J, Hafeez-Baig A. Older people, assistive technologies, and the barriers to adoption: A systematic review. Int J Med Inform. 2016; 94(Supplement C):112–6. https://doi.org/10.1016/j.ijmedinf.2016.07.004.CrossRef

22.

Rajan JV, Moura J, Gourley G, Kiso K, Sizilio A, Cortez AM, Riley LW, Veras MA, Sarkar U. Understanding the barriers to successful adoption and use of a mobile health information system in a community health center in são paulo, brazil: a cohort study. BMC Med Inform Decision Making. 2016; 16(1):146. https://doi.org/10.1186/s12911-016-0385-1.

23.

Khosravi P, Ghapanchi AH. Investigating the effectiveness of technologies applied to assist seniors: A systematic literature review. Int J Med Inform. 2016; 85(1):17–26. https://doi.org/10.1016/j.ijmedinf.2015.05.014.CrossRef

24.

Nicholas D, Huntington P, Jamali H. Digital Health Information for the Consumer: Evidence and Policy Implications. London: Ashgate Publishing, Ltd.; 2007.

25.

Lee J-A, Choi M, Lee SA, Jiang N. Effective behavioral intervention strategies using mobile health applications for chronic disease management: a systematic review. BMC Med Inf Decision Making. 2018; 18(1):12. https://doi.org/10.1186/s12911-018-0591-0.

26.

Liu L, Stroulia E, Nikolaidis I, Miguel-Cruz A, Rincon AR. Smart homes and home health monitoring technologies for older adults: A systematic review. Int J Med Inf. 2016; 91(Supplement C):44–59. https://doi.org/10.1016/j.ijmedinf.2016.04.007.CrossRef

27.

Cafazzo AJ, Casselman M, Hamming N, Katzman KD, Palmert RM. Design of an mhealth app for the self-management of adolescent type 1 diabetes: A pilot study. J Med Internet Res. 2012; 14(3):70. https://doi.org/10.2196/jmir.2058.CrossRef

28.

Stutzel MC, Fillipo M, Sztajnberg A, Brittes A, da Motta LB. SMAI - Mobile System for Elderly Monitoring. In: 2016 IEEE International Conference on Serious Games and Applications for Health (SeGAH). Orlando: IEEE: 2016. p. 1–8. http://ieeecomputersociety.org/10.1109/SeGAH.2016.7586274.

29.

Michie S, Yardley L, West R, Patrick K, Greaves F. Developing and evaluating digital interventions to promote behavior change in health and health care: Recommendations resulting from an international workshop. J Med Internet Res. 2017; 19(6):232. https://doi.org/10.2196/jmir.7126.CrossRef

30.

Messick SJ. Metric properties of the semantic differential. Educ Psychol Meas. 1957; 17(2):200–6. https://doi.org/10.1177/001316445701700203.CrossRef

31.

Yen P-Y, Walker DM, Smith JMG, Zhou MP, Menser TL, McAlearney AS. Usability evaluation of a commercial inpatient portal. Int J Med Inf. 2018; 110:10–18. https://doi.org/10.1016/j.ijmedinf.2017.11.007.CrossRef

32.

Nielsen J, Molic R. Ergonomic requirements for office work with visual display terminals (vdts)–part 11: Guidance on usability. ISO 9241–11:1998.

33.

Nielsen J. Usability Engineering. San Francisco: Morgan Kaufmann Publishers Inc.; 1993.CrossRef

34.

Brooke J. SUS - A Quick and Dirty Usability Scale. London: Taylor & Francis; 1996, pp. 189–94.

35.

Nielsen J. Why You Only Need to Test with 5 Users. Nielsen Norman Group. Articles: Topics: User Testing. 2012. https://www.nngroup.com/articles/why-you-only-need-to-test-with-5-users/. Accessed Jun 2017.

36.

Hecorat. AZ Screen Recorder. 2017. https://play.google.com/store/apps/details?id=com.hecorat.screenrecorder.free. Accessed Oct 2017.

37.

Davis FD. A technology acceptance model for empirically testing new end-user information systems : theory and results Thesis (Ph. D.)–Massachusetts Institute of Technology, Sloan School of Management. 1986;:233–250. Massachusetts Institute of Technology, http://hdl.handle.net/1721.1/15192.

38.

Marchewka JT, Kostiwa K. An application of the UTAUT model for understanding student perceptions using course management software. Commun IIMA. 2007; 7(2):10. http://www.un.org/esa/population/publications/worldageing19502050/. Accessed Feb 2018.

39.

Bawack RE, Kamdjoug JRK. Adequacy of UTAUT in clinician adoption of health information systems in developing countries: The case of Cameroon. Int J Med Inform. 2018; 109:15–22. https://doi.org/10.1016/j.ijmedinf.2017.10.016.CrossRef

40.

Kortum P, Peres SC. The relationship between system effectiveness and subjective usability scores using the System Usability Scale. Int J Hum-Comput Interact. 2014; 30(7):575–84. https://doi.org/10.1080/10447318.2014.904177.CrossRef

41.

Kortum P, Sorber M. Measuring the usability of mobile applications for phones and tablets. Int J Hum-Comput Interact. 2015; 31(8):518–29. https://doi.org/10.1080/10447318.2015.1064658.CrossRef

42.

Venson JE, Bevilacqua F, Berni J, Onuki F, Maciel A. Diagnostic concordance between mobile interfaces and conventional workstations for emergency imaging assessment. Int J Med Inform. 2018; 113:1–8. https://doi.org/10.1016/j.ijmedinf.2018.01.019.CrossRef

43.

Bangor A, Kortum P, Miller J. Determining What Individual SUS Scores Mean: Adding an Adjective Rating Scale. J Usability Stud. 2009; 4(3):114–23. http://dl.acm.org/citation.cfm?id=2835587.2835589. Accessed Nov 2017.

44.

Kitzinger J. Focus groups In: Pope C, Mays N, editors. Qualitative Research in Health Care vol. 1, 3rd edn. Massachusetts: Blackwell Publishing Ltd: 2007. p. 21–31.

45.

Likert R. A technique for the measurement of attitudes. Arch Psychol. 1932; 22(2):5–55. http://psycnet.apa.org/record/1933-01885-001. Accessed Oct 2017.

46.

Wasilewski MB, Stinson JN, Cameron JI. Web-based health interventions for family caregivers of elderly individuals: A scoping review. Int J Med Inf. 2017; 103(Supplement C):109–38. https://doi.org/10.1016/j.ijmedinf.2017.04.009.CrossRef

47.

Mechael P, Batavia H, Kaonga N, Searle S, Kwan A, Goldberger A, Fu L, Ossman J. Barriers and Gaps Affecting mHealth in Low and Middle Income Countries: Policy White Paper. New York: Columbia university. Center for Global Health and Economic Development Earth Institute; 2010, p. 79.

Title: Multi-part quality evaluation of a customized mobile application for monitoring elderly patients with functional loss and helping caregivers
Authors: Matheus Costa Stutzel
Michel Pedro Filippo
Alexandre Sztajnberg
Rosa Maria E.M. da Costa
André da Silva Brites
Luciana Branco da Motta
Célia Pereira Caldas
Publication date: 01-12-2019
Publisher: BioMed Central
Published in: BMC Medical Informatics and Decision Making / Issue 1/2019
Electronic ISSN: 1472-6947
DOI: https://doi.org/10.1186/s12911-019-0839-3

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Multi-part quality evaluation of a customized mobile application for monitoring elderly patients with functional loss and helping caregivers

Abstract

Background

Method

Results

Conclusions

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Abstract

Background

Method

Results

Conclusions

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