A Lazy User Perspective to Patient Adoption and Use of Personal Health Records

  • K. Niki KuneneEmail author
Part of the Healthcare Delivery in the Information Age book series (Healthcare Delivery Inform. Age)


Personal health records (PHRs) are seen as the bedrock of patient engagement. They have the potential to improve health outcomes for individual healthcare consumers, providers, and the broader healthcare system. With Meaningful Use Stage 2 now mandating the implementation of tethered PHRs (as patient portals), will healthcare consumers actually use PHRs and realize the contributions to patient safety, quality care, efficiencies, and reduced health disparities through engagement? Or will PHR actual use remain low? In this interpretive qualitative study, using grounded theory, we asked healthcare consumers users they currently manage their personal health information (PHI) and why. Evidence from our study iterates to the lazy user theory, we found that letting physicians manage healthcare consumers PHI is the least effort-based solution and thus the predominant and preferred solution by healthcare consumers. Providers as guardians of patient PHI suggest that the low use rates may yet persist. The implicit equating of personal health information as provider-generated health information by both healthcare consumers and the designers of PHR tools they use blurs the value proposition for consumers.


Patient engagement Personal health records Patient portal 


  1. Abramson, E. L., Patel, V., Edwards, A., & Kaushal, R. (2014). Consumer perspectives on personal health records: A 4-community study. American Journal of Managed Care, 20, 287–a298.Google Scholar
  2. Agency for Healthcare Research and Quality. (2017). About the national quality strategy. Agency for Healthcare Research and Quality. Accessed 22 Sept 2018.
  3. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (pp. 11–39). Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
  4. Ajzen, I., & Fishbein, M. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading: Addison-Wesley.Google Scholar
  5. Alter, S. (2010). Designing and engineering for emergence: A challenge for HCI practice and research. AIS Transactions on Human-Computer Interaction, 2(4), 127–140.CrossRefGoogle Scholar
  6. Ancker, J. S., Osorio, S. N., Cheriff, A., Cole, C. L., Silver, M., & Kaushal, R. (2015). Patient activation and use of an electronic patient portal. Informatics for Health & Social Care, 40, 254–266.CrossRefGoogle Scholar
  7. Archer, N., Fevrier-Thomas, U., Lokker, C., McKibbon, K. A., & Straus, S. E. (2011). Personal health records: A scoping review. Journal of the American Medical Informatics Association, 18, 515–522.PubMedPubMedCentralCrossRefGoogle Scholar
  8. Association, A. H. (2018). Expanding electronic patient engagement. Annual Survey, IT Supplement Brief March.Google Scholar
  9. Bagozzi, R. P., Davis, F. D., & Warshaw, P. R. (1992). Development and test of a theory of technological learning and usage. Human Relations, 45, 659–686.CrossRefGoogle Scholar
  10. Bhaumik, S. K., & Piesse, J. (2008). Does lending behaviour of banks in emerging economies vary by ownership? Evidence from the Indian banking sector. Economic Systems, 32, 177–196.CrossRefGoogle Scholar
  11. Borfitz, D. (2018). Blockchain-secured, patient-controlled health records. healthcare.aspx.
  12. Bouri, N., & Ravi, S. (2014). Going mobile: How mobile personal health records can improve health care during emergencies. JMIR mHealth and uHealth, 2, e8.PubMedPubMedCentralCrossRefGoogle Scholar
  13. Carrión, I., Alemán, J. L. F., & Toval, A. (2011). Assessing the HIPAA standard in practice: PHR privacy policies. In: Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, 2011. IEEE, pp 2380–2383.Google Scholar
  14. Collan, M., & Tétard, F. (2011). Lazy user model: Solution selection and discussion about switching costs. In Scandinavian conference on information systems (pp. 56–68). Berlin, Heidelberg: Springer.Google Scholar
  15. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 12, 319–340.Google Scholar
  16. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35, 982–1003.CrossRefGoogle Scholar
  17. Department of Health and Human Services CfMaMS. (2010). 42 CFR parts 412, 413, 422 et al. Medicare and medicaid programs: Electronic health record incentive program; Final Rule.Google Scholar
  18. DiCicco-Bloom, B., & Crabtree, B. F. (2006). The qualitative research interview. Medical Education, 40, 314–321.PubMedCrossRefGoogle Scholar
  19. Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading: Addison-Wesley.Google Scholar
  20. Goodhue, D. L. (1995). Understanding user evaluations of information systems. Management Science, 41, 1827–1844.CrossRefGoogle Scholar
  21. Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 7, 213–236.Google Scholar
  22. Houston, T. K., & Ehrenberger, H. E. (2001). The potential of consumer health informatics. Seminars in Oncology Nursing, 17, 41–47. Scholar
  23. Jones, D. A., Shipman, J. P., Plaut, D. A., & Selden, C. R. (2010). Characteristics of personal health records: Findings of the medical library association/national library of medicine joint electronic personal health record task force. Journal of the Medical Library Association: JMLA, 98, 243.PubMedCrossRefGoogle Scholar
  24. Kaelber, D. C., Jha, A. K., Johnston, D., Middleton, B., & Bates, D. W. (2008). A research agenda for personal health records (PHRs). Journal of the American Medical Informatics Association, 15, 729–736.PubMedPubMedCentralCrossRefGoogle Scholar
  25. Kavoussi, S., Huang, J., Tsai, J., & Kempton, J. (2014). HIPAA for physicians in the information age. Connecticut Medicine, 78, 425–427.PubMedGoogle Scholar
  26. Kim, J., Jung, H., & Bates, D. W. (2011). History and trends of “personal health record” research in PubMed. Healthcare Informatics Research, 17, 3–17. Scholar
  27. Kunene, K. N., Zysk, K., & Diop, M. -F. (2016). Healthcare consumers’ voluntary adoption and non- adoption of electronic personal health records. In: The 27th Australasian Conference on Information Systems, Wollongong, NSW, Australia, 2016. University of Wollongong, Faculty of Business.Google Scholar
  28. Lafky, D. B., & Horan, T. A. (2011). Personal health records: Consumer attitudes toward privacy and security of their personal health information. Health Informatics Journal, 17, 63–71.PubMedCrossRefGoogle Scholar
  29. Lee, A. S., & Baskerville, R. L. (2003). Generalizing generalizability in information systems research. Information Systems Research, 14, 221–243.CrossRefGoogle Scholar
  30. Lehnbom, E., Douglas, H., & Makeham, M. (2016). Positive beliefs and privacy concerns shape the future for the personally controlled electronic health record. Internal Medicine Journal, 46, 108–111.PubMedCrossRefGoogle Scholar
  31. Lester, M., Boateng, S., Studeny, J., & Coustasse, A. (2016). Personal health records: Beneficial or burdensome for patients and healthcare providers? Perspectives in Health Information Management, 13, 115–118.Google Scholar
  32. Mitchell, B., & Begoray, D. (2010). Electronic personal health records that promote self-management in chronic illness. OJIN: The Online Journal of Issues in Nursing, 15, 1B–10B.Google Scholar
  33. Patel, V., & Johnson, C. (2018). Individuals’ use of online medical records and technology for health needs (Vol. 40). Washington, DC: Office of the National Coordinator.Google Scholar
  34. Patel, V. N., et al. (2011). Low-income, ethnically diverse consumers’ perspective on health information exchange and personal health records. Informatics for Health & Social Care, 36, 233–252.CrossRefGoogle Scholar
  35. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.Google Scholar
  36. Saparova, D. (2012). Motivating, influencing, and persuading patients through personal health records: A scoping review. Perspectives in Health Information Management, 1 243–249.Google Scholar
  37. Schutz, A. (1962). Concept and theory formation in the social sciences. In Collected papers I (pp. 48–66). Dordrecht: Springer.CrossRefGoogle Scholar
  38. Señor, I. C., Fernández-Alemán, J. L., & Toval, A. (2012). Are personal health records safe? A review of free web-accessible personal health record privacy policies. Journal of Medical Internet Research, 14, e114.CrossRefGoogle Scholar
  39. Services CfMaM. (2018). Promoting interoperability. Centers for Medicare and Medicaid Services. Accessed 22 Sept 2018.
  40. Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15, 325–343.CrossRefGoogle Scholar
  41. Showell, C. (2017). Barriers to the use of personal health records by patients: A structured review. PeerJ, 5, e3268.PubMedPubMedCentralCrossRefGoogle Scholar
  42. Spil, T., & Klein, R. (2014). Personal health records success: why Google health failed and what does that mean for Microsoft HealthVault? In: 2014 47th Hawaii International Conference on System Sciences (HICSS), 2014. IEEE, pp 2818–2827.Google Scholar
  43. Strauss, A., & Corbin, J. (1990). Basics of qualitative research (Vol. 15). Newbury Park: Sage.Google Scholar
  44. Strauss, A., & Corbin, J. (1994). Grounded theory methodology. Handbook of Qualitative Research, 17, 273–285.Google Scholar
  45. Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory. Second edn. Thousand Oaks: Sage Publications.Google Scholar
  46. Taha, J., Czaja, S. J., Sharit, J., & Morrow, D. G. (2013). Factors affecting usage of a personal health record (PHR) to manage health. Psychology and Aging, 28, 1124.PubMedPubMedCentralCrossRefGoogle Scholar
  47. Tang, P. C., Ash, J. S., Bates, D. W., Overhage, J. M., & Sands, D. Z. (2006). Personal health records: Definitions, benefits, and strategies for overcoming barriers to adoption. Journal of the American Medical Informatics Association, 13, 121–126.PubMedPubMedCentralCrossRefGoogle Scholar
  48. Tétard, F., & Collan, M. (2009). Lazy user theory: A dynamic model to understand user selection of products and services. In: System Sciences, 2009. HICSS’09. 42nd Hawaii International Conference on, 2009. IEEE, pp 1–9.Google Scholar
  49. Van Maanen, J. (1983). Reclaiming qualitative methods for organizational research: A preface. In J. Van Maanen (Ed.), Qualitative methodology. Beverly Hills: Sage.Google Scholar
  50. Vance, B., Tomblin, B., Studeny, J., & Coustasse, A. (2014). Personal health records: Benefits and barriers for its adoption. Insights to a Changing World Journal, 2014, 48–67.Google Scholar
  51. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 12, 425–478.Google Scholar
  52. Vessey, I. (1991). Cognitive fit: A theory-based analysis of the graphs versus tables literature. Decision Sciences, 22, 219–240.CrossRefGoogle Scholar
  53. Vessey, I., & Galletta, D. (1991). Cognitive fit: An empirical study of information acquisition. Information Systems Research, 2, 63–84.CrossRefGoogle Scholar
  54. Vydra, T. P., Cuaresma, E., Kretovics, M., & Bose-Brill, S. (2015). Diffusion and use of tethered personal health records in primary care. Perspectives in Health Information Management, 12, 109–114.Google Scholar
  55. Wagner, P. J., Dias, J., Howard, S., Kintziger, K. W., Hudson, M. F., Seol, Y.-H., & Sodomka, P. (2012). Personal health records and hypertension control: A randomized trial. Journal of the American Medical Informatics Association, 19, 626–634.PubMedPubMedCentralCrossRefGoogle Scholar
  56. Wunsch, G. (1982). Maternal and child health in the third world: Problems of data collection. Popul Famille, 53, 19–33.PubMedGoogle Scholar
  57. Wynia, M., & Dunn, K. (2010). Dreams and nightmares: Practical and ethical issues for patients and physicians using personal health records. The Journal of Law, Medicine & Ethics, 38, 64–73.CrossRefGoogle Scholar
  58. Yamin, C. K., Emani, S., Williams, D. H., Lipsitz, S. R., Karson, A. S., Wald, J. S., & Bates, D. W. (2011). The digital divide in adoption and use of a personal health record. Archives of Internal Medicine, 171, 568–574.PubMedCrossRefGoogle Scholar
  59. Young, R., Willis, E., Cameron, G., & Geana, M. (2014). “Willing but unwilling”: Attitudinal barriers to adoption of home-based health information technology among older adults. Health Informatics Journal, 20, 127–135. Scholar
  60. Zapata, B. C., Niñirola, A. H., Idri, A., Fernández-Alemán, J. L., & Toval, A. (2014). Mobile PHRs compliance with android and iOS usability guidelines. Journal of Medical Systems, 38, 81.CrossRefGoogle Scholar
  61. Zipf, G. (1949). Human behavior and the principle of least effort. Reading: Addison-Wesley.Google Scholar

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Eastern Connecticut State UniversityWillimanticUSA

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