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Web as Medium for Patient Access to Electronic Health Information

Explore how online platforms like PatCIS improve patient care through easy health data access. Understand the impact on patient care and the patient-provider relationship. Learn from insights on the WebCIS system usage and enrollment statistics for better healthcare management.

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Web as Medium for Patient Access to Electronic Health Information

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  1. Web as Medium for Patient Access to Electronic Health Information James J. Cimino, MD, Vimla L. Patel, PhD, Andre W. Kushniruk, PhD Columbia University and McGill University

  2. Consumer Health Information Issues • Understanding on-line health information • Access to personal health records • Regulatory requirements are coming • Commercial sites for giving patients access to their data • What will happen to the patient? • What will happen to the patient-provider relationship?

  3. The Patient Clinical Information System (PatCIS) • New York Presbyterian Hospital clinical data repository • Web-based Clinical Information System (WebCIS) • National Information Infrastructure contract from NLM: • give patients WebCIS • see what happens • Pilot study conducted

  4. 2 1 3 6 5 4 CGI PatCIS Architecture Web Server Web Browser patcis.cgi Data Entry Session Registry Vital Signs Blood Sugar Logout Data Entry Review Advice Education Usage Log Comments Help Internet

  5. PatCIS Recruitment • Mail physician consent forms to physicians • Wait for physicians to suggest subjects • Mail URL for consent form to subjects • On-line enrollment • Patient prints, signs and mails consent form • Physician provides function-specific consent • Mail user name, password and SecurID card to patients

  6. Log File Analysis sandcar!Fri Oct 27 11:32:22 2000!cim.cpmc.columbia.edu! |patcis^login sandcar!Fri Oct 27 11:32:24 2000!cim.cpmc.columbia.edu! |patcis^Data Review sandcar!Fri Oct 27 11:32:28 2000!cim.cpmc.columbia.edu! |patcis^Data Review^Laboratory Detail^lab_detail.cgi sandcar!Fri Oct 27 11:32:30 2000!cim.cpmc.columbia.edu! |patcis^Data Review^Laboratory Detail^labSum.cgi sandcar!Fri Oct 27 11:32:35 2000!cim.cpmc.columbia.edu! |patcis^logout

  7. Results • Functions • Enrollment • System usage • Function usage • Adverse events

  8. Functions • Data entry: vital signs, diabetic flow sheet • Data review: vital signs, diabetic flow sheet, laboratory, radiology, pathology, cardiology, discharge summaries, microbiology • Education: geriatrics, diabetes, Home Medical Guide, advanced directives • Advice: cholesterol, mammograms • Infobuttons: body-mass index, laboratory, microbiology organisms, microbiology sensitivities, Pap smear

  9. Enrollment • Mailing to >200 physicians • 13 physicians returned signed consent forms • 19 subjects suggested • 13 enrolled • 12 used the system over 19 months • 1 non-CPMC subject enrolled

  10. System Usage 131 log-on failures 22 wrong user name 51 wrong password 58 wrong Secure ID 33 log-ons without any activity 466 active sessions (261 logged out) ----- 630 log-ons

  11. Log-Ons Failures by User

  12. Active Log-Ons by User

  13. Average Monthly Log-Ons

  14. Average Session Time by User

  15. Minutes per Month

  16. Function Usage I • Data review: 1831 total • 1518 laboratory • 737 “Laboratory” button  1083 specific reports • 186 “Laboratory Details” button • 249 summaries • 36 vital signs • 35 diabetes flow sheets • 212 reports (81 radiology, 35 pathology) • 30 Microbiology

  17. I Function Usage I • Data entry: 73 total • 34 vital signs • 39 diabetes flow sheets • Education: 53 total • Advice: 6 total • 5 cholesterol guideline • 1 mammography guideline • Other: • 10 newsgroups • 83 infobuttons • 2 comments • 10 e-mail to physician • 17 disclaimers • 13 help • Data review: 1831 total

  18. Adverse Events • None reported

  19. Discussion • Architecture supports integration, security and tracking • Enrollment was disappointing • Population was highly selected: by MD, by self, by Web • Two patterns: monthly and daily • Log-on difficulties overcome • Laboratories are the most popular

  20. Next Directions • Diabetes mellitus patients • Data entry • Coordination with clinicians • Targeted educational materials • HIV patients

  21. Conclusion • Enthusiasm is not universal • Technical issues were not a problem for our patients • Privacy is achievable • Patient understanding of their records was good • Other features were of less interest • Patient-physician impact was positive

  22. The Three Questions • How will your results affect diffusion of telemedicine? • Increase the “comfort level” • Identify areas for focused efforts • What aspects would benefit from other study? • Security model • Evaluation methods • If you were proposing this project today, how and why would the approach differ? • Build a patient’s view of the record • Study doctor-patient-computer interactions directly

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