Advertisement

Digital Health Research Methods and Tools: Suggestions and Selected Resources for Researchers

  • Kathleen GrayEmail author
  • Cecily Gilbert
Chapter
Part of the Intelligent Systems Reference Library book series (ISRL, volume 137)

Abstract

This chapter provides an overview of digital health research, aimed at people new to conducting investigations in this field who seek to engage seriously with patients, clients and consumers. Digital health is not a scientific discipline. This chapter argues that health and biomedical informatics offers a strong scholarly basis for research in this field, and it outlines the theoretical and conceptual frameworks, ethical considerations, research methods, and examples of tools applicable for studies of digital health interventions. Researchers from clinical, IT, engineering and similar domains who plan to undertake studies involving digital health applications will be introduced to methodologies such as using guidelines and standards, performance indicators, validated input models and outcome measures, and evaluation resources. In the specific area of consumer health informatics research, an increasing array of tools and methods exist to investigate the interaction between consumers and their health data. In addition this chapter discusses research methods with health apps, patient-generated health data, social media and wearable self-tracking devices. Practical advice is given on techniques such as critically appraising digital health research literature, primary data collection from devices and services, study reporting and publishing results.

Keywords

Biomedical informatics Consumer health informatics Digital health Health informatics Research methods 

References

  1. 1.
    Taylor, K.: Connected Health: How Digital Technology is Transforming Health and Social Care. Deloitte Centre for Health Solutions, London (2015)Google Scholar
  2. 2.
    IOM Institute of Medicine (US), Grossmann, C., Powers, B., McGinnis, J.M.: Digital Infrastructure for the Learning Health System—The Foundation for Continuous Improvement in Health and Health Care: Workshop Series Summary. National Academy of Sciences, Washington, DC (2011)Google Scholar
  3. 3.
    Frank, S.R., Williams, J.R., Veiel, E.L.: Digital health care: where health care, information technology, and the Internet converge. Manag. Care Q. 8(3), 37–47 (2000)Google Scholar
  4. 4.
    Iyawa, G.E., Herselman, M., Botha, A.: Digital health innovation ecosystems: from systematic literature review to conceptual framework. In: International Conference on ENTERprise Information Systems/International Conference on Project MANagement/International Conference on Health and Social Care Information Systems and Technologies. CENTERIS/ProjMAN/HCist, no. (100), pp. 244–252 (2016). doi: 10.1016/j.procs.2016.09.149
  5. 5.
    Hagens, S., Zelmer, J., Frazer, C., Gheorghiu, B., Leaver, C.: Valuing national effects of digital health investments: an applied method. Stud. Health Technol. Inf. 208, 165–169 (2015)Google Scholar
  6. 6.
    World Health Organisation: Atlas of eHealth Country Profiles 2015: The Use of eHealth in Support of Universal Health Coverage; Based on the Findings of the 2015 Global Survey on eHealth. WHO, Geneva (2016)Google Scholar
  7. 7.
    Australia: Public Governance, Performance and Accountability (Establishing the Australian Digital Health Agency) Rule. vol F2016L00070 (2016)Google Scholar
  8. 8.
    Accenture: Digital Health Tech Vision, 2016. (2016)Google Scholar
  9. 9.
    Agarwal, R., Gao, G., DesRoches, C., Jha, A.K.: Research commentary—the digital transformation of healthcare: current status and the road ahead. Inf. Syst. Res. 21, 796–809 (2010). doi: 10.1287/isre.1100.0327 CrossRefGoogle Scholar
  10. 10.
    Burrill, G.S.: Digital health investment opportunities abound, but standouts deliver disruptive change. J. Commerc. Biotechnol. 18(1), 495 (2012). doi: 10.5912/jcb495 CrossRefGoogle Scholar
  11. 11.
    Flores, M., Glusman, G., Brogaard, K., Price, N.D., Hood, L.: P4 medicine: how systems medicine will transform the healthcare sector and society. Per. Med. 10(6), 565–576 (2013). doi: 10.2217/PME.13.57 CrossRefGoogle Scholar
  12. 12.
    Martin-Sanchez, F., Lopez-Campos, G., Gray, K.: Biomedical informatics methods for personalized medicine and participatory health. In: Sarkar, I.N. (ed.) Methods in Biomedical Informatics, pp. 347–394. Academic Press, Oxford (2014). doi: 10.1016/B978-0-12-401678-1.00011-7 CrossRefGoogle Scholar
  13. 13.
    Demiris, G.: Consumer health informatics: past, present, and future of a rapidly evolving domain. Yearb. Med. Inf. 1, 42–47 (2016). doi: 10.15265/IYS-2016-s005
  14. 14.
    Flaherty, D., Hoffman-Goetz, L., Arocha, J.F.: What is consumer health informatics? A systematic review of published definitions. Inf. Health Soc. Care 40(2), 91–112 (2015). doi: 10.3109/17538157.2014.907804 CrossRefGoogle Scholar
  15. 15.
    Greaves, F., Millett, C., Nuki, P.: England’s experience incorporating “anecdotal” reports from consumers into their national reporting system: lessons for the United States of what to do or not to do? Med. Care Res. Rev. MCRR 71(5 Suppl), 65S–80S (2014). doi: 10.1177/1077558714535470 CrossRefGoogle Scholar
  16. 16.
    Okun, S., Caligtan, C.A.: The engaged ePatient. In: Nelson, R., Staggers, N. (eds.) Health Informatics: An Interprofessional Approach, vol. 2, pp. 204–219. Elsevier, St Louis, MO (2018)Google Scholar
  17. 17.
    Kushniruk, A.W., Turner, P.: Who’s users? Participation and empowerment in socio-technical approaches to health IT developments. Stud. Health Technol. Inf. 164, 280–285 (2011)Google Scholar
  18. 18.
    Stephanie, F.L., Sharma, R.S.: Health on a cloud: modeling digital flows in an e-health ecosystem. J. Adv. Manag. Sci. Inf. Syst. 2, 1–20 (2016)Google Scholar
  19. 19.
    Awori, J., Lee, J.M.: A maker movement for health: a new paradigm for health innovation. JAMA Pediatr. 171(2), 107–108 (2017). doi: 10.1001/jamapediatrics.2016.3747 CrossRefGoogle Scholar
  20. 20.
    Filonik, D., Bednarz, T., Rittenbruch, M., Foth, M.: Collaborative data exploration interfaces—from participatory sensing to participatory sensemaking. In: 2015 Big Data Visual Analytics (BDVA), Hobart, Tas., 22–25 Sep 2015. IEEE, pp 1–2. doi: 10.1109/BDVA.2015.7314289
  21. 21.
    Swan, M.: Health 2050: the realization of personalized medicine through crowdsourcing, the quantified self, and the participatory biocitizen. J. Pers. Med. 2(3), 93–118 (2012). doi: 10.3390/jpm2030093 CrossRefGoogle Scholar
  22. 22.
    Vayena, E., Tasioulas, J.: Adapting standards: ethical oversight of participant-led health research. PLoS Med. 10(3), e1001402 (2013). doi: 10.1371/journal.pmed.1001402 CrossRefGoogle Scholar
  23. 23.
    Lane, T.S., Armin, J., Gordon, J.S.: Online recruitment methods for web-based and mobile health studies: a review of the literature. J. Med. Internet Res. 17(7), e183 (2015). doi: 10.2196/jmir.4359 CrossRefGoogle Scholar
  24. 24.
    O’Connor, S., Hanlon, P., O’Donnell, C.A., Garcia, S., Glanville, J., Mair, F.S.: Understanding factors affecting patient and public engagement and recruitment to digital health interventions: a systematic review of qualitative studies. BMC Med. Inf. Decis. Mak. 16 (1):120-016-0359-0353 (2016). doi: 10.1186/s12911-016-0359-3
  25. 25.
    Karnoe, A., Kayser, L.: How is eHealth literacy measured and what do the measurements tell us? A systematic review. Knowl. Manag. E-Learn. 7(4), 576–600 (2015)Google Scholar
  26. 26.
    Mackert, M., Champlin, S.E., Holton, A., Muñoz, I.I., Damásio, M.J.: eHealth and health literacy: a research methodology review. J. Comput.-Mediat. Commun. 19(3), 516–528 (2014). doi: 10.1111/jcc4.12044 CrossRefGoogle Scholar
  27. 27.
    Agarwal, R., Anderson, C., Crowley, K., Kannan, P.T., Westat: Improving Consumer Health IT Application Development: Lessons From Other Industries, Background Report. vol AHRQ Publication No. 11–0065-EF. Agency for Healthcare Research and Quality, Rockville, MD (2011)Google Scholar
  28. 28.
    Elwyn, G., Kreuwel, I., Durand, M.A., Sivell, S., Joseph-Williams, N., Evans, R., Edwards, A.: How to develop web-based decision support interventions for patients: a process map. Patient Educ. Couns. 82(2), 260–265 (2011). doi: 10.1016/j.pec.2010.04.034 CrossRefGoogle Scholar
  29. 29.
    Eyles, H., Jull, A., Dobson, R., Firestone, R., Whittaker, R., Te Morenga, L., Goodwin, D., Mhurchu, C.N.: Co-design of mHealth delivered interventions: a systematic review to assess key methods and processes. Curr. Nutr. Rep. 5(3), 160–167 (2016). doi: 10.1007/s13668-016-0165-7 CrossRefGoogle Scholar
  30. 30.
    Johnson, C.M., Turley, J.P.: A new approach to building web-based interfaces for healthcare consumers. e-J. Health Inf. 2(2) (2007)Google Scholar
  31. 31.
    Kayser, L., Kushniruk, A., Osborne, R.H., Norgaard, O., Turner, P.: Enhancing the effectiveness of consumer-focused health information technology systems through eHealth literacy: a framework for understanding users’ needs. JMIR Human Factors 2(1), e9 (2015). doi: 10.2196/humanfactors.3696 CrossRefGoogle Scholar
  32. 32.
    Marquard, J.L., Zayas-Caban, T.: Commercial off-the-shelf consumer health informatics interventions: recommendations for their design, evaluation and redesign. J. Am. Med. Inf. Assoc. JAMIA 19(1), 137–142 (2012). doi: 10.1136/amiajnl-2011-000338 CrossRefGoogle Scholar
  33. 33.
    Mummah, S.A., Robinson, T.N., King, A.C., Gardner, C.D., Sutton, S.: IDEAS (Integrate, Design, Assess, and Share): a framework and toolkit of strategies for the development of more effective digital interventions to change health behavior. J. Med. Internet Res. 18(12), e317 (2016). doi: 10.2196/jmir.5927 CrossRefGoogle Scholar
  34. 34.
    Valdez, R.S., Holden, R.J., Novak, L.L., Veinot, T.C.: Transforming consumer health informatics through a patient work framework: connecting patients to context. J. Am. Med. Inf. Assoc. JAMIA 22(1), 2–10 (2015). doi: 10.1136/amiajnl-2014-002826 Google Scholar
  35. 35.
    van Gemert-Pijnen, J.E., Nijland, N., van Limburg, M., Ossebaard, H.C., Kelders, S.M., Eysenbach, G., Seydel, E.R.: A holistic framework to improve the uptake and impact of eHealth technologies. J. Med. Internet Res. 13(4), e111 (2011). doi: 10.2196/jmir.1672 CrossRefGoogle Scholar
  36. 36.
    Andersen, T., Kensing, F., Kjellberg, L., Moll, J.: From research prototypes to a marketable eHealth system. Stud. Health Technol. Inf. 218, 40589 (2015)Google Scholar
  37. 37.
    Baker, T.B., Gustafson, D.H., Shah, D.: How can research keep up with eHealth? Ten strategies for increasing the timeliness and usefulness of eHealth research. J. Med. Internet Res. 16(2), e36 (2014). doi: 10.2196/jmir.2925 CrossRefGoogle Scholar
  38. 38.
    Holden, R.J., Bodke, K., Tambe, R., Comer, R.S., Clark, D.O., Boustani, M.: Rapid translational field research approach for eHealth R&D. Proc. Int. Symp. Hum. Factors Ergon. Health C 5(1), 25–27 (2016). doi: 10.1177/2327857916051003 CrossRefGoogle Scholar
  39. 39.
    Patrick, K., Hekler, E.B., Estrin, D., Mohr, D.C., Riper, H., Crane, D., Godino, J., Riley, W.T.: The pace of technologic change: implications for digital health behavior intervention research. Am. J. Prev. Med. 51(5), 816–824 (2016). doi: 10.1016/j.amepre.2016.05.001 CrossRefGoogle Scholar
  40. 40.
    Gray, K., Sockolow, P.: Conceptual models in health informatics research: a literature review and suggestions for development. JMIR Med. Inf. 4(1), e7 (2016). doi: 10.2196/medinform.5021 CrossRefGoogle Scholar
  41. 41.
    Cano, I., Lluch-Ariet, M., Gomez-Cabrero, D., Maier, D., Kalko, S., Cascante, M., Tegner, J., Miralles, F., Herrera, D., Roca, J., Synergy-COPD Consortium.: Biomedical research in a digital health framework. J. Transl. Med. 12(Suppl 2), S10–5876-5812-S5872-S5810. Epub 2014 Nov 5828 (2014). doi: 10.1186/1479-5876-12-S2-S10
  42. 42.
    Hu, Y.: Health communication research in the digital age: a systematic review. J. Commun. Healthc. 8(4), 260–288 (2015). doi: 10.1080/17538068.2015.1107308 CrossRefGoogle Scholar
  43. 43.
    Lupton, D.: Towards critical digital health studies: reflections on two decades of research in health and the way forward. Health 20(1), 49–61 (2016). doi: 10.1177/1363459315611940. (London, England: 1997)CrossRefGoogle Scholar
  44. 44.
    Sjostrom, J., von Essen, L., Gronqvist, H.: The origin and impact of ideals in eHealth research: experiences from the U-CARE research environment. JMIR Res. Protoc. 3(2), e28 (2014). doi: 10.2196/resprot.3202 CrossRefGoogle Scholar
  45. 45.
    Ammenwerth, E.: Evidence-based health informatics: how do we know what we know? Methods Inf. Med. 54(4), 298–307 (2015). doi: 10.3414/ME14-01-0119 CrossRefGoogle Scholar
  46. 46.
    Mookherji, S., Mehl, G., Kaonga, N., Mechael, P.: Unmet need: improving mHealth evaluation rigor to build the evidence base. J. Health Commun. 20(10), 1224–1229 (2015). doi: 10.1080/10810730.2015.1018624 CrossRefGoogle Scholar
  47. 47.
    Rigby, M., Ammenwerth, E., Beuscart-Zephir, M.C., Brender, J., Hypponen, H., Melia, S., Nykanen, P., Talmon, J., de Keizer, N.: Evidence based health informatics: 10 years of efforts to promote the principle. Joint contribution of IMIA WG EVAL and EFMI WG EVAL. Yearb. Med. Inf. 8, 34–46 (2013)Google Scholar
  48. 48.
    Black, A.D., Car, J., Pagliari, C., Anandan, C., Cresswell, K., Bokun, T., McKinstry, B., Procter, R., Majeed, A., Sheikh, A.: The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med. 8(1), e1000387 (2011). doi: 10.1371/journal.pmed.1000387 CrossRefGoogle Scholar
  49. 49.
    Parthasarathy, R., Steinbach, T.: Health Informatics for Healthcare Quality Improvement: A literature review of issues, challenges and findings. In: AMCIS 2015: Twenty-first Americas Conference on Information Systems, Fajardo, Puerto Rico, Citeseer, pp. 1–23 (2015)Google Scholar
  50. 50.
    Ravka, N.: Informatics and health services: the potential benefits and challenges of electronic health records and personal electronic health records in patient care, cost control, and health research—an overview. In: El Morr, C. (ed.) Research Perspectives on the Role of Informatics in Health Policy and Management, pp. 89–114. IGI Global, Hershey, PA, USA (2014). doi: 10.4018/978-1-4666-4321-5.ch007 CrossRefGoogle Scholar
  51. 51.
    Barratt, H., Campbell, M., Moore, L., Zwarenstein, M., Bower, P.: Randomised controlled trials of complex interventions and large-scale transformation of services. Health Serv. Deliv. Res. 4(16), 19–36 (2016). doi: 10.3310/hsdr04160-19 Google Scholar
  52. 52.
    Hubner, U.: What are complex eHealth innovations and how do you measure them? Position paper. Methods Inf. Med. 54(4), 319–327 (2015). doi: 10.3414/ME14-05-0001 CrossRefGoogle Scholar
  53. 53.
    Liao, P., Klasnja, P., Tewari, A., Murphy, S.A.: Sample size calculations for micro-randomized trials in mHealth. Stat. Med. 35(12), 1944–1971 (2016). doi: 10.1002/sim.6847 MathSciNetCrossRefGoogle Scholar
  54. 54.
    Washington P, Kumar M, Tibrewal A, Sabharwal A ScaleMed: A methodology for iterative mHealth clinical trials. In: 17th International Conference on E-health Networking, Application & Services, HealthCom 2015, Boston, MA, USA, October 14–17, 2015. IEEE, pp. 139-143 (2015). doi: 10.1109/HealthCom.2015.7454487
  55. 55.
    Georgiou, A., Whetton, S.: Broadening the socio-technical horizons of health informatics. Open Med. Inf. J. 4, 179–180 (2010). doi: 10.2174/1874431101004010179 Google Scholar
  56. 56.
    Scott, P.J., Briggs, J.S.: STAT-HI: a socio-technical assessment tool for health informatics implementations. Open Med. Inf. J. 4, 214–220 (2010). doi: 10.2174/1874431101004010214 CrossRefGoogle Scholar
  57. 57.
    Levati, S., Campbell, P., Frost, R., Dougall, N., Wells, M., Donaldson, C., Hagen, S.: Optimisation of complex health interventions prior to a randomised controlled trial: a scoping review of strategies used. Pilot Feasibility Stud. 2, 17 (2016). doi: 10.1186/s40814-016-0058-y CrossRefGoogle Scholar
  58. 58.
    Orsmond, G.I., Cohn, E.S.: The distinctive features of a feasibility study: objectives and guiding questions. OTJR Occup. Participation Health 35(3), 169–177 (2015)CrossRefGoogle Scholar
  59. 59.
    Bowling, A.: Research Methods in Health: Investigating Health and Health Services, 4th edn. Open University Press, Maidenhead (2014)Google Scholar
  60. 60.
    Grassel, E., Donath, C., Hollederer, A., Drexler, H., Kornhuber, J., Zobel, A., Kolominsky-Rabas, P.: Evidence-based health services research–a short review and implications. Gesundheitswesen 77(3), 193–199 (2015). doi: 10.1055/s-0034-1382042 Google Scholar
  61. 61.
    Scutchfield, F.D., Perez, D.J., Monroe, J.A., Howard, A.F.: New public health services and systems research agenda: directions for the next decade. Am. J. Prev. Med. 42(5 Suppl 1), S1–S5 (2012). doi: 10.1016/j.amepre.2012.01.027 CrossRefGoogle Scholar
  62. 62.
    Smith, P.C., Anell, A., Busse, R., Crivelli, L., Healy, J., Lindahl, A.K., Westert, G., Kene, T.: Leadership and governance in seven developed health systems. Health Policy 106(1), 37–49 (2012). doi: 10.1016/j.healthpol.2011.12.009 CrossRefGoogle Scholar
  63. 63.
    Australian Institute of Health and Welfare: National Health Reform: Performance and Accountability Framework. AIHW. http://www.aihw.gov.au/health-performance/performance-and-accountability-framework/ (2017) Accessed 15 July 2017
  64. 64.
    National Health Information Standards and Statistics Committee: Revised National Health Performance Framework, 2nd edn. Australian Institute of Health and Welfare, Canberra (2009)Google Scholar
  65. 65.
    Consumers Health Forum of Australia, George Institute for Global Health Putting the Consumer First: Creating a Consumer Centred Health System for a 21st Century Australia—A Health Policy Report. Sydney (2016)Google Scholar
  66. 66.
    Australian Commission on Safety and Quality in Health Care Practice-Level Indicators of Safety and Quality for Primary Health Care Specification. Version 1.0 edn. ACSQHC, Sydney (2012)Google Scholar
  67. 67.
    ACHS Australian Council on Healthcare Standards (n.d.) EQUiP National Table. http://www.achs.org.au/media/38984/table_equipnational_standards.pdf
  68. 68.
    Australian College of Rural and Remote Medicine: ACRRM Telehealth Advisory Committee Standards Framework. 05/16 edn. Australian College of Rural and Remote Medicine, Brisbane (2016)Google Scholar
  69. 69.
    Mora, M., Steenkamp, A.L., Gelman, O., Raisinghani, : On IT and SwE research methodologies and paradigms: a systemic landscape review. In: Manuel, M., Ovsei, G., Annette, L.S., Mahesh, R. (eds.) Research Methodologies, Innovations and Philosophies in Software Systems Engineering and Information Systems, pp. 149–164. IGI Global, Hershey, PA (2012). doi: 10.4018/978-1-4666-0179-6.ch008 CrossRefGoogle Scholar
  70. 70.
    Riedl, R., Rueckel, D.: Americas Conference on Information S Historical Development of Research Methods in the Information Systems Discipline. In: AMCIS 2011 Proceedings—All Submissions, Detroit, MI, (2011). AIS Electronic Library, p. 28Google Scholar
  71. 71.
    Venkatesh, V., Brown, S.A., Bala, H.: Bridging the qualitative-quantitative divide: guidelines for conducting mixed methods research in information systems. MIS Q. 37(1), 21–54 (2013)CrossRefGoogle Scholar
  72. 72.
    Coiera, E.: Guide to Health Informatics, 3rd edn. CRC Press, Taylor & Francis Group, Boca Raton, FL (2015)Google Scholar
  73. 73.
    Shortliffe, E.H., Cimino, J.J.: Biomedical Informatics: Computer Applications in Health Care and Biomedicine, 4th edn. Springer, London (2014). doi: 10.1007/978-1-4471-4474-8 CrossRefGoogle Scholar
  74. 74.
    Venot, A., Burgun, A., Quantin, C.: Medical Informatics, e-Health: Fundamentals and Applications. Springer, Paris (2014). doi: 10.1007/978-2-8178-0478-1 CrossRefGoogle Scholar
  75. 75.
    Weaver, C.A., Ball, M.J., Kim, G.R., Kiel, J.M.: Healthcare Information Management Aystems: Cases, Strategies and Solutions, 4th edn. Springer International Publishing, Geneva (2016). doi: 10.1007/978-3-319-20765-0 CrossRefGoogle Scholar
  76. 76.
    Li, F., Li, M., Guan, P., Ma, S., Cui, L.: Mapping publication trends and identifying hot spots of research on Internet health information seeking behavior: a quantitative and co-word biclustering analysis. J. Med. Internet Res. 17(3), e81 (2015). doi: 10.2196/jmir.3326 CrossRefGoogle Scholar
  77. 77.
    Zuccon, G., Palotti, J., Goeuriot, L., Kelly, L., Lupu, M., Pecina, P., Mueller, H., Budaher, J., Deacon, A.: The IR task at the CLEF eHealth evaluation lab 2016: user-centred health information retrieval. In: CLEF 2016-Conference and Labs of the Evaluation Forum, Evora, Portugal, 5–8 Sep 2016. CEUR Workshop Proceedings. CEUR, pp. 15–27Google Scholar
  78. 78.
    Arora, S., Yttri, J., Nilse, W.: Privacy and security in mobile health (mHealth) research. Alcohol Res. Curr. Rev. 36(1), 143–151 (2014)Google Scholar
  79. 79.
    Kotz, D., Gunter, C.A., Kumar, S., Weiner, J.P.: Privacy and security in mobile health: a research agenda. Computer 49(6), 22–30 (2016). doi: 10.1109/MC.2016.185 CrossRefGoogle Scholar
  80. 80.
    Lennon, M., Baillie, L., Hoonhout, J., Robertson, J., Fitzpatrick, G.: Crossing HCI and health: advancing health and wellness technology research in home and community settings. In: CHI EA ‘15 Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, pp. 2353–2356. ACM, Seoul (2015). doi: 10.1145/2702613.2702652
  81. 81.
    Wilson, V., Djamasbi, S.: Human-computer interaction in health and wellness: research and publication opportunities. AIS Trans. Hum.-Comput. Interact 7(3), 97–108 (2015)Google Scholar
  82. 82.
    Gallivan, M., Tao, Y.: Value of co-Citation analysis for understanding a field’s intellectual structure: an application to Healthcare Information Technology (HIT) Research. In: AMCIS 2014: Twentieth Americas Conference on Information Systems, p. 3. Savannah, Georgia, USA (2014)Google Scholar
  83. 83.
    Guise, J.M., Chang, C., Viswanathan, M., Glick, S., Treadwell, J., Umscheid, C.A., Whitlock, E., Fu, R., Berliner, E., Paynter, R., Anderson, J.: Systematic Reviews of Complex Multicomponent Health Care Interventions, vol. 14-EHC003-EF. Agency for Healthcare Research and Quality, Rockville, MD (2014)Google Scholar
  84. 84.
    Deshazo, J.P., Lavallie, D.L., Wolf, F.M.: Publication trends in the medical informatics literature: 20 years of “Medical Informatics” in MeSH. BMC Med. Inform. Decis. Mak. 9, 7 (2009). doi: 10.1186/1472-6947-9-7 CrossRefGoogle Scholar
  85. 85.
    Weigel, F.K., Rainer, R.K., Hazen, B.T., Cegielski, C.G., Ford, F.N.: Uncovering research opportunities in the medical informatics field: a quantitative content analysis. Commun. Assoc. Inf. Syst. 33, 15–32 (2013)Google Scholar
  86. 86.
    Urquhart, C., Currell, R.: Systematic reviews and meta-analyses of health IT. In: Ammenwerth, E., Rigby, M. (eds.) Evidence-Based Health Informatics. Studies in Health Technology and Informatics, pp. 262–274. IOS Press, Amsterdam (2016). doi: 10.3233/978-1-61499-635-4-262 Google Scholar
  87. 87.
    Pfadenhauer, L., Rohwer, A., Burns, J., Booth, A., Lysdahl, K.B., Hofmann, B., Gerhardus, A., Mozygemba, K., Tummers, M., Wahlster, P., Rehfuess, E.: Guidance for the Assessment of Context and Implementation in Health Technology Assessments (HTA) and Systematic Reviews of Complex Interventions: The Context and Implementation of Complex Interventions (CICI) Framework Project report. Integrate-HTA (2016)Google Scholar
  88. 88.
    Rosenbloom, S.T.: Person-generated health and wellness data for health care. J. Am. Med. Inf. Assoc. JAMIA 23(3), 438–439 (2016). doi: 10.1093/jamia/ocw059 CrossRefGoogle Scholar
  89. 89.
    Clark, K., Duckham, M., Guillemin, M., Hunter, A., McVernon, J., O’Keefe, C., Pitkin, C., Prawer, S., Sinnott, R., Warr, D., Waycott, J.: Guidelines for the Ethical use of Digital Data in Human Research. University of Melbourne, Parkville (2015)Google Scholar
  90. 90.
    Gray, K.: Like, comment, share: should you share your genetic data online? Australas. Sci. 37(6), 24 (2016)Google Scholar
  91. 91.
    Lupton, D.: Digital health technologies and digital data: new ways of monitoring, measuring and commodifying human bodies. In: Olleros, F.X., Zhegu, M. (eds) Research Handbook on Digital Transformations, pp. 85–102. Edward Elgar Publishing (2016) doi: 10.4337/9781784717766.00011
  92. 92.
    Taylor, P.L., Mandl, K.D.: Leaping the data chasm: structuring donation of clinical data for healthcare innovation and modeling. Harvard Health Policy Rev. Stud. Publ. Harvard Interfaculty Initiative Health Policy 14(2), 18–21 (2015)Google Scholar
  93. 93.
    Winickoff, D.E., Jamal, L., Anderson, N.R.: New modes of engagement for big data research. J. Res. Innov. 3(2), 169–177 (2016). doi: 10.1080/23299460.2016.1190443 Google Scholar
  94. 94.
    Ajorlou, S., Shams, I., Yang, K.: An analytics approach to designing patient centered medical homes. Health Care Manag. Sci. 18(1), 3–18 (2015). doi: 10.1007/s10729-014-9287-x CrossRefGoogle Scholar
  95. 95.
    Gachet Páez, D., Morales Botello, M.L., Puertas, E., de Buenaga, M.: Health sensors information processing and analytics using big data approaches. In: Mandler B (ed) Internet of Things. IoT Infrastructures: Second International Summit, IoT 360° 2015, Rome, Italy, October 27–29, 2015. Revised Selected Papers, Part I. pp 481–486. Springer International Publishing (2016) Cham. doi: 10.1007/978-3-319-47063-4_52
  96. 96.
    Khan, W.A., Idris, M., Ali, T., Ali, R., Hussain, S., Hussain, M., Amin, M.B., Khattak, A.M., Weiwei, Y., Afzal, M., Lee, S., Kang, B.H.: Correlating health and wellness analytics for personalized decision making. In: 2015 17th International Conference on E-health Networking, Application & Services (HealthCom), pp. 256–261. (2015) doi: 10.1109/HealthCom.2015.7454508
  97. 97.
    Cohen, I.G., Amarasingham, R., Shah, A., Xie, B., Lo, B.: The legal and ethical concerns that arise from using complex predictive analytics in health care. Health Aff. (Project Hope) 33(7), 1139–1147 (2014). doi: 10.1377/hlthaff.2014.0048 CrossRefGoogle Scholar
  98. 98.
    Koster, J., Stewart, E., Kolker, E.: Health care transformation: a strategy rooted in data and analytics. Acad. Med. J. Assoc. Am. Med. Coll. 91(2), 165–167 (2016). doi: 10.1097/ACM.0000000000001047 CrossRefGoogle Scholar
  99. 99.
    Weiser, P., Ellis, A.: The Information Revolution Meets Health: The Transformative Power and Implementation Challenges of Health Analytics. Silicon Flatirons Center, Boulder, CO (2015). doi: 10.2139/ssrn.2593879 Google Scholar
  100. 100.
    Tailor, K.: The Patient Revolution: How Big Data and Analytics are Transforming the Health Care Experience. Wiley, Hoboken, NJ (2015)CrossRefGoogle Scholar
  101. 101.
    Bergmo, T.S.: How to measure costs and benefits of eHealth interventions: an overview of methods and frameworks. J. Med. Internet Res. 17(11), e254 (2015). doi: 10.2196/jmir.4521 CrossRefGoogle Scholar
  102. 102.
    Eslami Andargoli, A., Scheepers, H., Rajendran, D., Sohal, A.: Health information systems evaluation frameworks: a systematic review. Int. J. Med. Inf. 97, 195–209 (2017). doi: 10.1016/j.ijmedinf.2016.10.008 CrossRefGoogle Scholar
  103. 103.
    Jacobs, M.A., Graham, A.L.: Iterative development and evaluation methods of mHealth behavior change interventions. Curr. Opin. Psychol. 9, 33–37 (2016). doi: 10.1016/j.copsyc.2015.09.001 CrossRefGoogle Scholar
  104. 104.
    Kumar, S., Nilsen, W.J., Abernethy, A., Atienza, A., Patrick, K., Pavel, M., Riley, W.T., Shar, A., Spring, B., Spruijt-Metz, D., Hedeker, D., Honavar, V., Kravitz, R., Lefebvre, R.C., Mohr, D.C., Murphy, S.A., Quinn, C., Shusterman, V., Swendeman, D.: Mobile health technology evaluation: the mHealth evidence workshop. Am. J. Prev. Med. 45(2), 228–236 (2013). doi: 10.1016/j.amepre.2013.03.017 CrossRefGoogle Scholar
  105. 105.
    McGee-Lennon, M., Bouamrane, M., Grieve, E., O’Donnell, C.A., O’Connor, S., Agbakoba, R., Devlin, A.A.: Flexible toolkit for evaluating person-centred digital health and eellness at scale. In: Duffy, V.G., Lightner, N. (eds) Advances in Human Factors and Ergonomics in Healthcare: Proceedings of the AHFE 2016 International Conference on Human Factors and Ergonomics in Healthcare. pp. 105–118. Springer International Publishing, Walt Disney World, Florida, USA, Cham (2017) doi: 10.1007/978-3-319-41652-6_11
  106. 106.
    Murray, E., Hekler, E.B., Andersson, G., Collins, L.M., Doherty, A., Hollis, C., Rivera, D.E., West, R., Wyatt, J.C.: Evaluating digital health interventions: key questions and approaches. Am. J. Prev. Med. 51(5), 843–851 (2016). doi: 10.1016/j.amepre.2016.06.008 CrossRefGoogle Scholar
  107. 107.
    World Health Organisation: Monitoring and Evaluating Digital Health Interventions: A Practical Guide to Conducting Research and Assessment. WHO, Geneva (2016)Google Scholar
  108. 108.
    Chaudoir, S.R., Dugan, A.G., Barr, C.H.: Measuring factors affecting implementation of health innovations: a systematic review of structural, organizational, provider, patient, and innovation level measures. Implementation Sci. IS 8:22–5908-5908-5922. (2013) doi: 10.1186/1748-5908-8-22
  109. 109.
    Ross, J., Stevenson, F., Lau, R., Murray, E.: Factors that influence the implementation of e-health: a systematic review of systematic reviews (an update). Implementation Sci. IS 11(1), 146 (2016). doi: 10.1186/s13012-016-0510-7 CrossRefGoogle Scholar
  110. 110.
    Grob, R., Schlesinger, M., Parker, A.M., Shaller, D., Barre, L.R., Martino, S.C., Finucane, M.L., Rybowski, L., Cerully, J.L.: Breaking narrative ground: innovative methods for rigorously eliciting and assessing patient narratives. Health Serv. Res. 51(Suppl 2), 1248–1272 (2016). doi: 10.1111/1475-6773.12503 CrossRefGoogle Scholar
  111. 111.
    Hibbard, J.H., Stockard, J., Mahoney, E.R., Tusler, M.: Development of the Patient Activation Measure (PAM): conceptualizing and measuring activation in patients and consumers. Health Serv. Res. 39(4 Pt 1), 1005–1026 (2004). doi: 10.1111/j.1475-6773.2004.00269.x CrossRefGoogle Scholar
  112. 112.
    Barello, S., Triberti, S., Graffigna, G., Libreri, C., Serino, S., Hibbard, J., Riva, G.: eHealth for patient engagement: a systematic review. Front Psychol. 6, 2013 (2016). doi: 10.3389/fpsyg.2015.02013 CrossRefGoogle Scholar
  113. 113.
    Sawesi, S., Rashrash, M., Phalakornkule, K., Carpenter, J.S., Jones, J.F.: The impact of information technology on patient engagement and health behavior change: a systematic review of the literature. JMIR Med. Inf. 4(1), e1 (2016). doi: 10.2196/medinform.4514 CrossRefGoogle Scholar
  114. 114.
    Albert, W., Tullis, T.: Measuring the User Experience: Collecting, Analyzing and Presenting Usability Metrics, 2nd edn. Morgan Kaufmann, Burlington, MA (2013)Google Scholar
  115. 115.
    Klein, L.: UX for Lean Start-ups: Faster, Smarter User Experience Research and Design. O’Reilly Media, Sebastopol, CA (2013)Google Scholar
  116. 116.
    Sauro, J.: The challenges and opportunities of measuring the user experience. J. Usability Stud. 12(1), 1–7 (2016)Google Scholar
  117. 117.
    Petersen, C., DeMuro, P.: Legal and regulatory considerations associated with use of patient-generated health data from social media and mobile health (mHealth) devices. Appl. Clin. Inf. 6(1), 16–26 (2015). doi: 10.4338/ACI-2014-09-R-0082 CrossRefGoogle Scholar
  118. 118.
    Agarwal, S., LeFevre, A.E., Lee, J., L’Engle, K., Mehl, G., Sinha, C., Labrique, A., W. H. O. mHealth Technical Evidence Review Group: Guidelines for reporting of health interventions using mobile phones: mobile health (mHealth) evidence reporting and assessment (mERA) checklist. BMJ (Clin. Res. Ed.) 352, i1174 (2016). doi: 10.1136/bmj.i1174
  119. 119.
    Ammenwerth, E., de Keizer, N.F.: Publishing health IT evaluation studies. In: Ammenwerth, E., Rigby, M. (eds.) Evidence-Based Health Informatics: Promoting Safety and Efficiency Through Scientific Methods and Ethical Policy. Studies in Health Technology and Informatics, pp. 304–311. IOS Press, Amsterdam (2016). doi: 10.3233/978-1-61499-635-4-304 Google Scholar
  120. 120.
    Brender, J., Talmon, J., de Keizer, N., Nykanen, P., Rigby, M., Ammenwerth, E.: STARE-HI - statement on reporting of evaluation studies in health informatics: explanation and elaboration. Appl. Clin. Inf. 4(3), 331–358 (2013). doi: 10.4338/ACI-2013-04-RA-0024 CrossRefGoogle Scholar
  121. 121.
    Eysenbach, G.: Improving the quality of Web surveys: the Checklist for Reporting Results of Internet E-Surveys (CHERRIES). J. Med. Internet Res. 6(3), e34 (2004). doi: 10.2196/jmir.6.3.e34 CrossRefGoogle Scholar
  122. 122.
    Eysenbach G, Group C-E: CONSORT-EHEALTH: improving and standardizing evaluation reports of Web-based and mobile health interventions. J. Med. Internet Res. 13(4), e126 (2011). doi: 10.2196/jmir.1923 CrossRefGoogle Scholar
  123. 123.
    Khanal, S., Burgon, J., Leonard, S., Griffiths, M., Eddowes, L.A.: Recommendations for the improved effectiveness and reporting of telemedicine programs in developing countries: results of a systematic literature review. Telemed. J. E-health Official J. Am. Telemed. Assoc. 21(11), 903–915 (2015). doi: 10.1089/tmj.2014.0194 Google Scholar
  124. 124.
    Niederstadt, C., Droste, S.: Reporting and presenting information retrieval processes: the need for optimizing common practice in health technology assessment. Int. J. Technol. Assess. Health Care 26(4), 450–457 (2010). doi: 10.1017/S0266462310001066 CrossRefGoogle Scholar
  125. 125.
    SMART—An App platform for healthcare. Boston Children’s Hospital Computational Health Informatics Program; Harvard Medical School Department for Biomedical Informatics. http://smarthealthit.org/an-app-platform-for-healthcare/about/. Accessed 15 July 2017
  126. 126.
    Apple Inc. Apple HealthKit. https://developer.apple.com/healthkit/
  127. 127.
    Armstrong, S.: What happens to data gathered by health and wellness apps? BMJ 353, i3406 (2016). doi: 10.1136/bmj.i3406 CrossRefGoogle Scholar
  128. 128.
    Australia. Therapeutic Goods Administration: Regulation of Medical Software and Mobile Medical ‘Apps’. https://www.tga.gov.au/node/4316 (2013)
  129. 129.
    BinDhim, N.F., Trevena, L.: Health-related smartphone apps: regulations, safety, privacy and quality. BMJ Innov. 1(2), 43–45 (2015). doi: 10.1136/bmjinnov-2014-000019 CrossRefGoogle Scholar
  130. 130.
    Boulos, M.N., Brewer, A.C., Karimkhani, C., Buller, D.B., Dellavalle, R.P.: Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online J. Public Health Inf. 5(3), 229 (2014). doi: 10.5210/ojphi.v5i3.4814 Google Scholar
  131. 131.
  132. 132.
    Chindalo, P., Karim, A., Brahmbhatt, R., 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). doi: 10.4018/IJHCR.2016040103 CrossRefGoogle Scholar
  133. 133.
    Dialogue Consulting: Guidelines for Developing Healthy Living Apps. VicHealth. https://www.vichealth.vic.gov.au/media-and-resources/app-developers (2015)
  134. 134.
    Heffernan, K.J., Chang, S., Maclean, S.T., Callegari, E.T., Garland, S.M., Reavley, N.J., Varigos, G.A., Wark, J.D.: Guidelines and recommendations for developing interactive eHealth apps for complex messaging in health promotion. JMIR Mhealth Uhealth 4(1), e14 (2016). doi: 10.2196/mhealth.4423 CrossRefGoogle Scholar
  135. 135.
    Hillebrand, U., von Jan, U., Albrecht, U.V.: Concepts for quality assurance of health related apps. Stud. Health Technol. Inf. 226, 209–212 (2016). doi: 10.2196/mhealth.4423 Google Scholar
  136. 136.
    Martinez-Perez, B., de la Torre-Diez, I., Lopez-Coronado, M.: Privacy and security in mobile health apps: a review and recommendations. J. Med. Syst. 39(1):181-014-0181-0183. Epub 2014 Dec 0187 (2015). doi: 10.1007/s10916-014-0181-3
  137. 137.
    Research2Guidance (2016) mHealth App Developer Economics: The Current Status and Trends of the mHealth App Market. http://research2guidance.com/r2g/r2g-mHealth-App-Developer-Economics-2016.pdf (2016)
  138. 138.
    Schnall, R., Rojas, M., Bakken, S., Brown, W., Carballo-Dieguez, A., Carry, M., Gelaude, D., Mosley, J.P., Travers, J.: A user-centered model for designing consumer mobile health (mHealth) applications (apps). J. Biomed. Inf. 60, 243–251 (2016). doi: 10.1016/j.jbi.2016.02.002 CrossRefGoogle Scholar
  139. 139.
    Stoyanov, S.R., Hides, L., Kavanagh, D.J., Zelenko, O., Tjondronegoro, D., Mani, M.: Mobile app rating scale: a new tool for assessing the quality of health mobile apps. JMIR mHealth uHealth 3(1), e27 (2015). doi: 10.2196/mhealth.3422 CrossRefGoogle Scholar
  140. 140.
    UK. National Health Service App Development: An NHS guide to developing mobile healthcare applications. NHS Innov. South East, [n.p.] (2014)Google Scholar
  141. 141.
    Abbasi, A., Adjeroh, D., Dredze, M., Paul, M.J., Zahedi, F.M., Zhao, H., Walia, N., Jain, H., Sanvanson, P., Shaker, R., Huesch, M.D., Beal, R., Zheng, W., Abate, M., Ross, A.: Social media analytics for smart health. IEEE Intell. Syst. 29(2), 60 (2014). doi: 10.1109/MIS.2014.29 CrossRefGoogle Scholar
  142. 142.
    Ben-Harush, O., Carroll, J.-A., Marsh, B.: Using mobile social media and GIS in health and place research. Continuum 26(5), 715–730 (2012). doi: 10.1080/10304312.2012.706460 CrossRefGoogle Scholar
  143. 143.
    Bond, C.S., Ahmed, O.H., Hind, M.: Implications for research methods when conducting studies with the users of online health communities. Comput. Inf. Nurs. CIN 32(3), 101–104 (2014). doi: 10.1097/CIN.0000000000000049 CrossRefGoogle Scholar
  144. 144.
    Bradley, M., Braverman, J., Harrington, M., Wicks, P.: Patients’ motivations and interest in research: characteristics of volunteers for patient-led projects on PatientsLikeMe. Res. Involvement Engagem. 2(1), 33 (2016). doi: 10.1186/s40900-016-0047-6 CrossRefGoogle Scholar
  145. 145.
    Capurro, D., Cole, K., Echavarria, M.I., Joe, J., Neogi, T., Turner, A.M.: The use of social networking sites for public health practice and research: a systematic review. J. Med. Internet Res. 16(3), e79 (2014). doi: 10.2196/jmir.2679 CrossRefGoogle Scholar
  146. 146.
    Cyrus, J.W.: A review of recent research on internet access, use, and online health information seeking. J. Hosp. Librariansh 14(2), 149–157 (2014). doi: 10.1080/15323269.2014.888630 CrossRefGoogle Scholar
  147. 147.
    Ekberg, J., Gursky, E.A., Timpka, T.: Pre-launch evaluation checklist for online health-promoting communities. J. Biomed. Inform. 47, 11–17 (2014). doi: 10.1016/j.jbi.2013.10.004 CrossRefGoogle Scholar
  148. 148.
    Heidelberger, C.A., El-Gayar, O., Sarnikar, S.: Online health social networks and patient Health decision behavior: a research agenda. In: 2011 44th Hawaii International Conference on System Sciences, New York, 2011. IEEE, pp. 1–7. doi: 10.1109/HICSS.2011.328
  149. 149.
    Ho, K., Workshop, Peter Wall: Harnessing the social web for health and wellness: issues for research and knowledge translation. J. Med. Internet Res. 16(2), e34 (2014). doi: 10.2196/jmir.2969 CrossRefGoogle Scholar
  150. 150.
    Ji, X., Chun, S.A., Cappellari, P., Geller, J.: Linking and using social media data for enhancing public health analytics. J. Inf. Sci. (Online First):1–25. (2016) doi: 10.1177/0165551515625029
  151. 151.
    Kim, Y., Huang, J., Emery, S.: Garbage in, garbage out: data collection, quality assessment and reporting standards for social media data use in health research, infodemiology and digital disease detection. J. Med. Internet Res. 18(2), e41 (2016). doi: 10.2196/jmir.4738 CrossRefGoogle Scholar
  152. 152.
    Martínez, P., Martínez, J.L., Segura-Bedmar, I., Moreno-Schneider, J., Luna, A., Revert, R.: Turning user generated health-related content into actionable knowledge through text analytics services. Nat. Lang. Process. Text Analytics Ind. 78, 43–56 (2016). doi: 10.1016/j.compind.2015.10.006 Google Scholar
  153. 153.
    McKee, R.: Ethical issues in using social media for health and health care research. Health Policy (Amsterdam, Netherlands) 110 (2–3):298-301. (2013) doi: 10.1016/j.healthpol.2013.02.006
  154. 154.
    Merolli, M., Martin-Sanchez, F.J., Gray, K.: Social media and online survey: tools for knowledge management in health research. In: HIKM’14 Proceedings of the Seventh Australasian Workshop on Health Informatics and Knowledge Management, Auckland, New Zealand, 2014. Australian Computer Society, Inc, pp. 21–29Google Scholar
  155. 155.
    Merolli, M.A.: Participatory Health Through Social Media in Chronic Disease: a Framework for Research and Practice [PhD thesis]. University of Melbourne, Parkville (2015)Google Scholar
  156. 156.
    Mitra, S., Padman, R., Yang, H., Lee, E.K.: Understanding the role of social media in healthcare via analytics: a health plan perspective. In: Yang, H., Lee, E.K. (eds.) Healthcare Analytics: From Data to Knowledge to Healthcare Improvement, pp. 555–587. John Wiley & Sons, Inc, Hoboken, NJ (2016). doi: 10.1002/9781118919408.ch19 Google Scholar
  157. 157.
    Murray, P.J., Wright, G.: Towards a research agenda for Web 2.0 and social media in health and informatics. In: Proceedings of the 4th WSU—International Research Conference, East London, South Africa, 2014. Walter Sisulu University, pp. 89–98Google Scholar
  158. 158.
    Myneni, S., Iyengar, S.: Socially influencing technologies for health promotion: translating social media analytics into consumer-facing health solutions. In: 49th Hawaii International Conference on System Sciences (HICSS), pp. 3084–3093. EEE, New York (2016). doi: 10.1109/HICSS.2016.388
  159. 159.
    Neighbors, C., Lewis, M.A.: Editorial overview: Status update: current research on social media and health. Soc. Media Appl. Health Behav. 9, iv–vi. (2016) doi: 10.1016/j.copsyc.2016.04.021
  160. 160.
    Smith, B.G., Smith, S.B.: Engaging Health: Health Research and Policymaking in the Social Media Sphere. AcademyHealth, Washington, DC (2015)Google Scholar
  161. 161.
    Straton, N., Hansen, K., Mukkamala, R., Hussain, A., Grønli, T., Langberg, H., Vatrapu, R.: Big social data analytics for public health: Facebook engagement and performance. In: HealthCom ‘16: 18th IEEE International Conference on e-Health Networking, Applications and Services, Munich, Germany (2016). doi: 10.1109/HealthCom.2016.7749497
  162. 162.
    Taylor, H.A., Kuwana, E., Wilfond, B.S.: Ethical implications of social media in health care research. Am. J. Bioeth. AJOB 14(10), 58–59 (2014). doi: 10.1080/15265161.2014.947820 CrossRefGoogle Scholar
  163. 163.
    Thirumalai, M., Ramaprasad, A.: Ontological analysis of the research on the use of social media for health behavior change. In: 2015 48th Hawaii International Conference on System Sciences, pp. 814–823.(2015). doi: 10.1109/HICSS.2015.103
  164. 164.
    Almalki, M., Gray, K., Martin-Sanchez, F.: Activity theory as a theoretical framework for health self-quantification: a systematic review of empirical studies. J. Med. Internet Res. 18(5), e131 (2016). doi: 10.2196/jmir.5000 CrossRefGoogle Scholar
  165. 165.
    Almalki, M., Gray, K., Martin-Sanchez, F.J.: Refining the concepts of self-quantification needed for health self-management. A thematic literature review. Methods Inf. Med. 56(1), 46–54 (2017). doi: 10.3414/ME15-02-0007 CrossRefGoogle Scholar
  166. 166.
    Banaee, H., Ahmed, M.U., Loutfi, A.: Data mining for wearable sensors in health monitoring systems: a review of recent trends and challenges. Sensors (Basel, Switzerland) 13(12):17472–17500. (2013) doi: 10.3390/s131217472
  167. 167.
    Casper, G.R., McDaniel, A.: Introduction to theme issue on technologies for patient-defined and patient-generated data. Pers. Ubiquit. Comput. 19(1), 1–2 (2015). doi: 10.1007/s00779-014-0803-2 CrossRefGoogle Scholar
  168. 168.
    Chiauzzi, E., Rodarte, C., DasMahapatra, P.: Patient-centered activity monitoring in the self-management of chronic health conditions. BMC Med. 13, 77-015-0319-0312. (2015) doi: 10.1186/s12916-015-0319-2
  169. 169.
    Choe, E.K., Lee, N.B., Lee, B., Pratt, W., Kientz, J.A.: Understanding quantified-selfers’ practices in collecting and exploring personal data. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 1143–1152. ACM, Toronto, Ontario, Apr 26–May 1 (2014). doi: 10.1145/2556288.2557372
  170. 170.
    Custodio, V., Herrera, F.J., Lopez, G., Moreno, J.I.: A review on architectures and communications technologies for wearable health-monitoring systems. Sensors (Basel, Switzerland) 12(10),13907–13946. (2012) doi: 10.3390/s121013907
  171. 171.
    De Mooy, M., Yuen, S.: Towards privacy-aware research and development in wearable health. In: Proceedings of the 50th Hawaii International Conference on System Sciences (HICSS), pp. 3658–3667 (2017)Google Scholar
  172. 172.
    Deering, M.J.: ONC Issue Brief: Patient-Generated Health Data and Health IT. Office of the National Coordinator for Health Information Technology, Washington, DC (2013)Google Scholar
  173. 173.
    Gray, K., Martin-Sanchez, F.J., Lopez-Campos, G.H., Almalki, M., Merolli, M.: Person-generated data in self-quantification. A health informatics research program. Methods Inf. Med. 56(1), 40–45 (2017). doi: 10.3414/ME15-02-0006 CrossRefGoogle Scholar
  174. 174.
    Kumara, S., Cui, L., Zhang, J.: Sensors, networks and internet of things: research challenges in health care. In: IIWeb ‘11: Proceedings of the 8th International Workshop on Information Integration on the Web: in conjunction with WWW 2011, pp. 1–4. ACM, Hyderabad, India, March 28 (2011) doi: 10.1145/1982624.1982626
  175. 175.
    Piras, E.M., Ellingsen, G.: International workshop on Infrastructures for health care: patient-centered care and patient generated data. J. Particip. Med. 8, e4 (2016)Google Scholar
  176. 176.
    Rich, E., Miah, A.: Mobile, wearable and ingestible health technologies: towards a critical research agenda. Health Soc. Rev. 26(1), 84–97 (2017). doi: 10.1080/14461242.2016.1211486 CrossRefGoogle Scholar
  177. 177.
    Shapiro, M., Johnston, D., Wald, J., Mon, D.: Patient-Generated Health Data: White Paper. RTI International, Research Triangle Park, NC (2012)Google Scholar
  178. 178.
    Woods, S.S., Evans, N.C., Frisbee, K.L.: Integrating patient voices into health information for self-care and patient-clinician partnerships: veterans affairs design recommendations for patient-generated data applications. J. Am. Med. Inf. Assoc. JAMIA 23(3), 491–495 (2016). doi: 10.1093/jamia/ocv199 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Health and Biomedical Informatics CentreThe University of MelbourneParkvilleAustralia

Personalised recommendations