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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
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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?
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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
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Data Entry Review Advice Education Comments Help Logout Vital SignsBlood Sugar Data Entry patcis.cgi Web Server Web Browser Session Registry Usage Log Internet 2 3 6 PatCIS Architecture 1 CGI 4 5
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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
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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
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Results Functions Enrollment System usage Function usage Adverse events
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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
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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
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System Usage 131log-on failures 22wrong user name 51wrong password 58wrong Secure ID 33log-ons without any activity 466active sessions (261 logged out) ----- 630log-ons
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Log-Ons Failures by User
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Active Log-Ons by User
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Average Monthly Log-Ons
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Average Session Time by User
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Minutes per Month
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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
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Function Usage I Data review: 1831 total 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
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Adverse Events None reported
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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
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Next Directions Diabetes mellitus patients –Data entry –Coordination with clinicians –Targeted educational materials HIV patients
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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
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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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