Journal of Medical Systems

, Volume 36, Issue 4, pp 2111–2128 | Cite as

Intelligent Personal Health Record: Experience and Open Issues



Web-based personal health records (PHRs) are under massive deployment. To improve PHR’s capability and usability, we previously proposed the concept of intelligent PHR (iPHR). By introducing and extending expert system technology and Web search technology into the PHR domain, iPHR can automatically provide users with personalized healthcare information to facilitate their daily activities of living. Our iPHR system currently provides three functions: guided search for disease information, recommendation of home nursing activities, and recommendation of home medical products. This paper discusses our experience with iPHR as well as the open issues, including both enhancements to the existing functions and potential new functions. We outline some preliminary solutions, whereas a main purpose of this paper is to stimulate future research work in the area of consumer health informatics.


Search engine Personal health record Expert system Home medical product Nursing activity 


  1. 1.
    Ackley, B. J., and Ladwig, G. B., Nursing Diagnosis Handbook: An Evidence-based Guide to Planning Care, 8th ed. Mosby, 2007.Google Scholar
  2. 2.
    Adomavicius, G., and Tuzhilin, A., Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. TKDE 17(6):734–749, 2005.Google Scholar
  3. 3.
    AllegroMedical homepage., 2010.
  4. 4.
    Amazon homepage., 2010.
  5. 5.
    Bing homepage., 2010.
  6. 6.
    Bulechek, G. M., Butcher, H. K., and Dochterman, J. M., Nursing Interventions Classification (NIC), 5th ed. Mosby, 2007.Google Scholar
  7. 7.
    Baeza-Yates, R. A., and Ribeiro-Neto, B. A., Modern Information Retrieval. ACM Press/Addison-Wesley, 1999.Google Scholar
  8. 8.
    Billings, J. A., and Stoeckle, J. D., The Clinical Encounter: A Guide to the Medical Interview & Case Presentation, 2nd ed. Mosby, 1999.Google Scholar
  9. 9.
    Chatroulette homepage., 2010.
  10. 10.
    Cimino, J. J., Use, usability, usefulness and impact of an Infobutton manager. Proceedings of AMIA’06, pp. 151–155, 2006.Google Scholar
  11. 11.
    Collins, R. D., Algorithmic Diagnosis of Symptoms and Signs: Cost-Effective Approach. Lippincott Williams & Wilkins, 2002.Google Scholar
  12. 12.
    Conditions by incidence., 2010.
  13. 13.
    Data & Statistics, Centers for Disease Control and Prevention., 2010.
  14. 14.
    Dunning, T., Nursing Care of Older People with Diabetes. Wiley-Blackwell, 2005.Google Scholar
  15. 15.
    Duyff, R. L., American Dietetic Association Complete Food and Nutrition Guide, 3rd ed. Wiley, 2006.Google Scholar
  16. 16.
    Eysenbach, G., Consumer health informatics. BMJ 320(7251):1713–1716, 2000.CrossRefGoogle Scholar
  17. 17.
    Eysenbach, G., Medicine 2.0: social networking, collaboration, participation, apomediation, and openness. J Med Internet Res 10(3):e22, 2008.CrossRefGoogle Scholar
  18. 18.
    Farfan, F., Hristidis, V., and Ranganathan, A., et al., XOntoRank: Ontology-aware search of electronic medical records. Proceedings of ICDE’09, pp. 820-831, 2009.Google Scholar
  19. 19.
    Gagliano, M. E., A literature review on the efficacy of video in patient education. J Med Educ 63(10):785–792, 1988.Google Scholar
  20. 20.
  21. 21.
    Goetz, T., The Decision Tree: Taking Control of Your Health in the New Era of Personalized Medicine. Rodale Books, 2010.Google Scholar
  22. 22.
    Google product search homepage., 2010.
  23. 23.
    Hanas, R., Type 1 Diabetes in Children, Adolescents and Young Adults: How to Become an Expert on Your Own Diabetes, 4th ed. Class Publishing, 2009.Google Scholar
  24. 24.
    Hanson, W., The Edge of Medicine: The Technology That will Change Our Lives. Palgrave Macmillan, 2008.Google Scholar
  25. 25.
    Healthline homepage., 2010.
  26. 26.
    New Healthline symptom search dramatically improves one of the most popular online health research activities., 2007.
  27. 27.
    HealthPricer homepage., 2010.
  28. 28.
    Hidola homepage., 2010.
  29. 29.
    Hood, C., Unique holiday gifts - fitness equipment., 2007.
  30. 30.
    Johnson, M., Bulechek, G. M., and Dochterman, J. M., et al., NANDA, NOC, and NIC Linkages: Nursing Diagnoses, Outcomes, and Interventions, 2nd ed. Mosby, 2005.Google Scholar
  31. 31.
    Li, X., and Croft, W. B., Time-based language models. Proceedings of CIKM’03, pp. 469–475, 2003.Google Scholar
  32. 32.
    Luo, G., Design and evaluation of the iMed intelligent medical search engine. Proceedings of ICDE’09, pp. 1379–1390, 2009.Google Scholar
  33. 33.
    Luo, G., Intelligent output interface for intelligent medical search engine. Proceedings of AAAI’08, pp. 1201–1206, 2008.Google Scholar
  34. 34.
    Luo, G., Lessons learned from building the iMed intelligent medical search engine. Proceedings of EMBC’09, pp. 5138–5142, 2009.Google Scholar
  35. 35.
    Luo, G., On search guide phrase compilation for recommending home medical products. Proceedings of EMBC’10, pp. 2167–2171, 2010.Google Scholar
  36. 36.
    Luo, G., Navigation interface for recommending home medical products. JMS, to appear.Google Scholar
  37. 37.
    Luo, G., and Tang, C., On iterative intelligent medical search. Proceedings of SIGIR’08, pp. 3–10, 2008.Google Scholar
  38. 38.
    Luo, G., and Tang, C., Challenging issues in iterative intelligent medical search. Proceedings of ICPR’08, pp. 1–4, 2008.Google Scholar
  39. 39.
    Luo, G., and Tang, C., Automatic home nursing activity recommendation. Proceedings of AMIA’09, pp. 401–405, 2009.Google Scholar
  40. 40.
    Luo, G., Thomas, S. B., and Tang, C., Intelligent consumer-centric electronic medical record. Proceedings of MIE’09, pp. 120–124, 2009.Google Scholar
  41. 41.
    Luo, G., Thomas, S. B., and Tang, C., Automatic home medical product recommendation. JMS, to appear.Google Scholar
  42. 42.
    Metz, C., Google eyes Cleveland medical records., 2008.
  43. 43.
    Microsoft HealthVault homepage., 2010.
  44. 44.
    Meyer, M. M., and Derr, P., The Comfort of Home: a Complete Guide for Caregivers, 3rd ed. CareTrust Publications LLC, 2007.Google Scholar
  45. 45.
    PatientsLikeMe homepage., 2010.
  46. 46.
    Prevention magazine editors. The Doctors Book of Home Remedies. Bantam, 2003.Google Scholar
  47. 47.
    Ramasubramanian, V., Peterson, R., and Sirer, E. G., Corona: A high performance publish-subscribe system for the World Wide Web. Proceedings of NSDI’06, 2006.Google Scholar
  48. 48.
    Revolution Health homepage., 2010.
  49. 49.
    Radomski, M. V., and Trombly, C. A., Occupational Therapy for Physical Dysfunction, 6th ed. Lippincott Williams & Wilkins, 2007.Google Scholar
  50. 50.
    Sullivan, D., What is real time search? Definitions & players., 2009.
  51. 51.
    Tatum, M., Which sugar substitutes are safe for diabetics?, 2010.
  52. 52.
    Teevan, J., Dumais, S. T., and Liebling, D. J., To personalize or not to personalize: modeling queries with variation in user intent. Proceedings of SIGIR’08, pp. 163-170, 2008.Google Scholar
  53. 53.
    Thompson, H. J., and Thielke, S. M., How do health care providers perceive technologies for monitoring older adults? Proceedings of EMBC’09, pp. 4315–4318, 2009.Google Scholar
  54. 54.
    Vogeli, C., Shields, A. E., Lee, T. A., et al., Multiple chronic conditions: prevalence, health consequences, and implications for quality, care management, and costs. JGIM 22(Suppl 3):391–395, 2007.CrossRefGoogle Scholar
  55. 55.
    WebMD homepage., 2010.
  56. 56.
    White, R.W., and Horvitz, E., Cyberchondria: Studies of the escalation of medical concerns in Web search. ACM Trans. Inf. Syst. 27(4), 2009.Google Scholar
  57. 57.
    Wii Fit homepage., 2010.
  58. 58.
    Wikipedia homepage., 2010.
  59. 59.
    Wilkinson, R., and Smeaton, A.F., Automatic link generation. ACM Comput. Surv. 31(4), 1999.Google Scholar
  60. 60.
    YouTube homepage., 2010.
  61. 61.
    Yang, K., Evens, M. W., and Trace, D., Improving the text summaries in the intelligent medical record system. Proceedings of MAICS’06, 2006.Google Scholar
  62. 62.
    American Dietetic Association. Electronic medical records and personal health records: A call for the creation and inclusion of a nutrition dataset., 2009.
  63. 63.
    Bakken, S., Currie, L. M., Lee, N. J., et al., Integrating evidence into clinical information systems for nursing decision support. I J Med Inform 77(6):413–420, 2008.CrossRefGoogle Scholar
  64. 64.
    Barnett, G. O., Cimino, J. J., Hupp, J. A., et al., DXplain. An evolving diagnostic decision-support system. JAMA 258(1):67–74, 1987.CrossRefGoogle Scholar
  65. 65.
    Batavia, M., Contraindications in Physical Rehabilitation: Doing No Harm. Saunders, 2006.Google Scholar
  66. 66.
    Brin, S., and Page, L., The anatomy of a large-scale hypertextual Web search engine. Comput Netw 30(1–7):107–117, 1998.Google Scholar
  67. 67.
    Collins, R.D., Algorithmic Approach to Treatment. Lippincott Williams & Wilkins, 1997.Google Scholar
  68. 68.
    Collins, R.D., Algorithmic Selection and Interpretation of Diagnostic Tests. Williams & Wilkins, 1998.Google Scholar
  69. 69.
    Demner-Fushman, D., Seckman, C., and Fisher, C., et al., A prototype system to support evidence-based practice. Proceedings of AMIA’08, pp. 151-155, 2008.Google Scholar
  70. 70.
    Doenges, M., Moorhouse, M., and Murr, A., Nursing Care Plans: Guidelines for Individualizing Client Care across the Life Span, 8th ed. F.A. Davis Company, 2009.Google Scholar
  71. 71.
    Elhadad, N., Kan, M., Klavans, J. L., et al., Customization in a unified framework for summarizing medical literature. Artif Intell Med 33(2):179–198, 2005.CrossRefGoogle Scholar
  72. 72.
    Google Alerts homepage., 2010.
  73. 73.
    Google Guide Quick Reference: Google Advanced Operators (Cheat Sheet)., 2010.
  74. 74.
    Google homepage., 2010.
  75. 75.
    Haugen, N., and Galura, S.J., Ulrich & Canale's Nursing Care Planning Guides: Prioritization, Delegation, and Critical Thinking, 7th ed. Saunders, 2010.Google Scholar
  76. 76.
    International Classification of Diseases (ICD-10) homepage., 2010.
  77. 77.
    Luo, G., Tang, C., and Thomas, S. B., Intelligent personal health record: experience and open issues. Proceedings of IHI’10, pp. 326-335, 2010.Google Scholar
  78. 78.
    Rodgers, S., Delmar's Medical-Surgical Nursing Care Plans. Delmar Cengage Learning, 2007.Google Scholar
  79. 79.
    Tatro, D. S., 2011 Drug Interaction Facts: The Authority on Drug Interactions. Lippincott Williams & Wilkins, 2010.Google Scholar
  80. 80.
    Wang, Y., and Liu, Z., Automatic detecting indicators for quality of health information on the Web. I J Med Inform 76(8):575–582, 2007.CrossRefGoogle Scholar
  81. 81.
    Wilson, P., How to find the good and avoid the bad or ugly: a short guide to tools for rating quality of health information on the internet. BMJ 324(7337):598–602, 2002.CrossRefGoogle Scholar
  82. 82.
  83. 83.
  84. 84.
    Comer, S. R., Delmar's Geriatric Nursing Care Plans, 3rd ed. Delmar Cengage Learning, 2004.Google Scholar
  85. 85.
    Comer, S. R., Delmar's Critical Care Nursing Care Plans, 2nd ed. Delmar Cengage Learning, 2004.Google Scholar
  86. 86.
    Luxner, K. L., Delmar's Maternal-Infant Nursing Care Plans, 2nd ed. Delmar Cengage Learning, 2004.Google Scholar
  87. 87.
    Luxner, K. L., Delmar's Pediatric Nursing Care Plans, 3rd ed. Delmar Cengage Learning, 2004.Google Scholar
  88. 88.
    Gulanick, M., and Myers, J. L., Nursing Care Plans: Diagnoses, Interventions, and Outcomes, 7th ed. Mosby, 2010.Google Scholar
  89. 89.
    Swearingen, P. L., All-in-One Care Planning Resource: Medical-Surgical, Pediatric, Maternity, and Psychiatric Nursing Care Plans, 2nd ed. Mosby, 2007.Google Scholar
  90. 90.
    Schultz, J. M., and Videbeck, S. L., Lippincott's Manual of Psychiatric Nursing Care Plans, 8th ed. Lippincott Williams & Wilkins, 2008.Google Scholar
  91. 91.
    Varcarolis, E. M., Manual of Psychiatric Nursing Care Planning: Assessment Guides, Diagnoses, Psychopharmacology, 4th ed. Saunders, 2010.Google Scholar
  92. 92.
    Cawsey, A. J., Jones, R. B., and Pearson, J., The evaluation of a personalised health information system for patients with cancer. User Model User-Adapt Interact 10(1):47–72, 2000.CrossRefGoogle Scholar
  93. 93.
    Al-Busaidi, A., Gray, A., and Fiddian, N., Personalizing web information for patients: linking patient medical data with the web via a patient personal knowledge base. Health Inform J 12(1):27–39, 2006.CrossRefGoogle Scholar
  94. 94.
    Bental, D. S., Cawsey, A., and Jones, R., Patient information systems that tailor to the individual. Patient Educ Couns 36(2):171–180, 1999.CrossRefGoogle Scholar
  95. 95.
  96. 96.
    Luo, G., Tang, C., and Yang, H., et al., MedSearch: a specialized search engine for medical information retrieval. Proceedings of CIKM’08, pp. 143-152, 2008.Google Scholar
  97. 97.
    A future doctor shortage? A growing lack of new doctors could be American's next health crisis., 2006.

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.IBM T.J. Watson Research CenterHawthorneUSA

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