Loading…

Flash Player 9 (or above) is needed to view presentations.
We have detected that you do not have it on your computer. To install it, go here.

Like this presentation? Why not share!

Lecture 9 Computerized Clinical Decision Support.ppt

on

  • 1,734 views

 

Statistics

Views

Total Views
1,734
Views on SlideShare
1,734
Embed Views
0

Actions

Likes
0
Downloads
33
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Lecture 9 Computerized Clinical Decision Support.ppt Lecture 9 Computerized Clinical Decision Support.ppt Presentation Transcript

  • eHealth: Innovations and Issues Lecture 9 Computerized Clinical Decision Support Norm Archer
  • Agenda
    • Definitions
    • Medical procedure for patients
    • History of medical DSS
    • Consumer DSS
    • Clinical DSS
    • Treatments for diseases & conditions
    • Example use of DSS
    • Excerpts from Andre Kushniruk presentation on usability testing of DSS
  • Definitions
    • Decision support system
      • A computer system designed to assist users in decision-making activities.
    • Decision support systems in healthcare
      • Management DSS - Computer technologies which allow providers to collect and analyze data in more sophisticated and complex ways. Activities supported include case mix, budgeting, cost accounting, clinical protocols and pathways, outcomes, and actuarial analysis.
      • Clinical (CDSS) - form a significant part of the field of clinical knowledge management technologies through their capacity to support the clinical process and use of knowledge, from diagnosis and investigation through treatment and long-term care.
      • Consumer DSS - help consumers become more aware and responsible for their own healthcare through a patient-centred approach, while cooperating with medical professionals who make informed treatment decisions.
  • Definitions…
    • Disease
      • A disease is an abnormal condition of the body or mind that causes discomfort, dysfunction, or distress to the person afflicted or those in contact with the person. Sometimes the term is used broadly to include injuries, disabilities, syndromes, symptoms, deviant behaviours, and atypical variations of structure and function, while in other contexts these may be considered distinguishable categories.
    • Differential diagnosis
      • Determination of which one of two or more diseases or conditions with similar symptoms is the one from which the patient is suffering.
      • Correct diagnosis leads to the choice of the most effective treatments that will alleviate the disease or condition
  • Medical Procedure for Patients
    • 1. Ill patient has appointment with physician, or visit to emergency room or clinic
    • 2. Physician takes patient history, symptoms, examines patient
    • 3. Physician
      • Makes preliminary determination of disease
        • Writes prescription for medication to combat the illness, or
        • Refers patient to specialist, or
        • Orders medical tests
      • If patient sent to specialist - orders additional tests and either reports back to physician or takes patient under care for treatment or surgery
      • If further tests ordered or specialist reports back, physician makes determination of illness and writes prescription for treatment
    • Best practice information very helpful for physician or specialist in treating disease after it has been identified
  • History of Medical DSS
    • See http://www.openclinical.org/dss.html
    • Early history
    • 1970s and 80s, development of rule-based expert systems – INTERNIST, MYCIN, PIP, ONCOCIN
    • Some were commercialized as DSS
      • E.g. DXPlain and QMR
      • Demo of DXPlain at http://www.openclinical.org/dm_dxplain.html
  • Consumer DSS (Eysenbach 2000)
    • Using self-analysis decision support tools, patients may be able to attain a healthy balance between self reliance and seeking professional help, by balancing of the need for face to face interaction with provision of virtual interaction.
    • Focus group evaluations of HouseCall (for example) have shown that the program is easy to use and that consumers like using technology at home to investigate health issues and like participating in solving their medical problems.
    • Obviously, such systems “do not and cannot replace visits with physicians; they can, however, make such encounters more productive, for both doctor and patient.” They may also help to triage patients. For consumers, the aim of such support systems would not be to make definitive diagnoses or to propose treatment but to answer simple questions such as “do I need to see a doctor?” or to alert patients to potential drug interactions or other health risks.
    • The main challenge in developing comprehensive systems for consumers is that little is known about how patients interact with computer based informatics tools and how they digest and act on information.
  • Online Consumer DSS
    • General
      • YourDiagnosis (U.S. $12.50 to $15.00) http://www.yourdiagnosis.com/start.htm
      • The Analyst (U.S. $25.00 to $77.00) http://www.diagnose-me.com/?page=main
      • MyElectronicMD (free) http://myelectronicmd.com/step1.php
      • EasyDiagnosis (Subscription cost) http://easydiagnosis.com/
    • Cancer
      • NexProfiler (free, operated by NexCura) http://www.cancerfacts.com/DefaultSecure.asp
    • Cardiology
      • NexProfiler (free, operated by NexCura) http://health.discovery.com/jump/nexcura/heart_profiler.html
    • Other diseases
      • HealthCommunities (free, operated by NexCura) http://www.healthcommunities.com/
  • Clinical DSS for Physicians
    • Medexpert/WWW is a medical knowledge base server – links to many online DSS http://medexpert.imc.akh-wien.ac.at/start.html
    • Example: MedTechUSA (annual $1050 U.S. subscription) medical reference tools for a variety of diseases and conditions (includes handheld device versions) http://www.medicalamazon.com/
  • Treatments for Diseases and Conditions
    • List of diseases and treatments
      • http://www.surgerydoor.co.uk/medical_conditions/
    • Information on diseases and treatments
      • http://www.mayoclinic.com/
    • And many others
  • Example 1
    • Symptoms
      • Tingling in upper right arm
        • At irregular intervals, when walking, computer work, driving, etc.
        • Especially when looking upwards (e.g. changing a light bulb in the ceiling)
        • Tingling stops when right hand is placed at back of neck in stretching motion
        • Problem began August 2005 while swimming
        • No or little loss of strength and use of right arm
    • Patient chart and history
      • Gender
      • Age
      • Pre-existing health problems – episode of carpal tunnel syndrome about 1990 (cleared up over a one year period after ergonomic adjustment of computer work environment)
      • Current medications
      • Life style (exercise, diet)
      • Psychological and physical (work, home)
      • Medical test results from EMG (electromyography) compared right & left arms.
  • Example 2
    • Symptoms
      • Episodes or sudden onsets for 10 to 30 minutes of:
        • Dizziness
        • Sweating
        • Blurred vision
        • Excessive saliva
        • Déjà vu
        • Episodes have been occurring irregularly for several years
    • Patient chart and history
      • Gender
      • Age
      • Parental health histories
      • Pre-existing health problems
      • Mental condition
      • Current medications
      • Life style (exercise, diet)
      • Psychological and physical (work, home)
      • Recent visits to foreign countries
      • Medical test results
  • Excerpts from “From Laboratory Usability Testing to ‘Televaluation’ of Web-based Information Systems” 2003 Presentation by André W. Kushniruk, Ph.D. Director, Information Technology Program, Faculty of Arts York University, Toronto, Ontario, Canada
  • Needs-satisfaction curve of information technology High Technology Human-Computer Interaction Unfilled Technology Need Technology is “good enough” User Experience Dominates Excess Functionality Transition Point : Technology delivers basic need Performance Required by Typical User
  • Motivation – HCI Issues in Health Informatics
    • Problems with information systems in health care
      • Lack of acceptance of systems
      • Poor usability
      • Failure to support work practices
      • Introduction of errors
      • Inadvertent changes in workflow
    • Issues related to human-computer interaction (individual and group/social level) may be single-most important barrier to successful implementation of systems in health care
  • Evaluation in Health Informatics
    • Summative Evaluation - need for assessment of whether systems meet the needs of users, are safe and effective
    • Formative Evaluation – need for assessment of systems throughout their development
      • Traditional development approach – classic waterfall development cycle
      • Newer approach – rapid prototyping involving continued user input and testing
  • From Laboratory to Real-world Analysis and Evaluation (Kushniruk,2001)
    • LABORATORY
    • Fixed usability lab
    • Experimental tasks
    • - “think aloud”
    • - cognitive task
    • analysis
    • Simulations
    • E.g. “simulated”
    • doctor-patient
    • interviews
    • NATURALISTIC
    • ” Virtual”
    • usability lab
    • Analysis of Web-
    • based systems
    • - Data mining
    A Continuum of Studies
  • A Continuum of Approaches to Evaluation Along the SDLC 1. Planning (needs analysis) -workflow analysis -job analysis -analysis of decision making -interviews 2. Analysis (requirements) -interviews -questionnaires -focus groups -video analysis -cognitive task analysis 3. Design 4. Implementation (programming) 5. Support (maintenance) Figure 1. The systems development life cycle (SDLC) in relation to evaluation methodologies.
    • usability testing
    • -usability
    • inspection
    • -design walk-
    • throughs
    -usability testing -code inspections -software unit testing -outcome-based evaluations -randomized clinical trials -summative evaluations
    • Study 2: Study of use in diabetes clinic over six month period – naturalistic approach
      • Interviews (pre and post) – 16 clinic staff
      • Usability testing with subset of subjects
      • Training recorded as well
      • Logging of all system use
      • Study of contents of paper and computer records
      • More irrelevant information in paper records
      • Overall less information recorded in computer based records
        • For corresponding records, CPR version contained 25% less information.
      • Fewer diagnoses recorded in CPR for matched records - typically only single primary diagnosis
      • Change in reasoning -- from “hypothesis driven” to “screen driven”
    Study 2 Results…
  • Changes in Reasoning
      • Data-directed (paper records)
      • Problem-directed (CPR)
      • Problem-directed (paper records)
      • Lasting change in reasoning patterns, even when CPR removed (“effects of” and “effects with”)
  • Patient Data Multiple Hypotheses Diagnostic Reasoning Using CPR Patient Data Hypotheses Diagnostic Reasoning Using Paper Record
  • Residual Effects of CPR Use % of Record Contents
  • 10 fold decrease in usability problems
    • Use of same method as above for improving prototype CPR system
      • 9 subjects video recorded using the system
      • Number of problems and type of problems identified from coding scheme
      • System refined based on the testing
      • 9 new subjects run
      • Found:
        • Dramatic decrease in number of errors:
          • From 19 per session on average in first testing to 1.9 in second testing!
  • Usability and the WWW (Kushniruk et al., 2001)
    • Objective to adapt usability testing to the WWW
      • how are people using health care sites?
      • Do they get information they want from particular sites?
      • what problems do they have?
      • How are Web-based guidelines used?
    • Remote tracking of Web users
    • Remote video-based usability testing
  • Evaluation of Usability of Web-Based Health Care Information Systems
    • Varied users who interact from various locations
      • Less able to conduct controlled evaluative studies
    • Current state-of-the-art
      • track user actions (e.g. clicks) - tells what they do, but not why
      • on-line questionnaires/feedback forms - often not filled in, limited questions
      • interviews - problem that users often do not know what they do
  • Questions in the Evaluation of e-Health Information Systems
    • What type of information do e-Health consumers want?
    • Is the information provided useful, helpful?
    • How to collect useful data from large number of subjects remotely?
    • How to integrate data from multiple sources?
    • How to analyze such data from varied data sources to discover usage patterns?
  • Objectives
    • To collect psychologically rich and useful data on a large scale
      • Methods for automatically collecting usability data at point of system use
        • identify patterns of usage of interest to automatically collect data about
      • Analysis tools and discovery tools
        • Automatically identify patterns of usage from merge of data collected
    • Integration of multi-method data collection and analysis
      • To answer both specific and generic questions regarding use and usability of Web-based health systems
  • 1. Video Based Usability Testing - from laboratory to remote 2. Interviews - from phone to electronic User Interact via WWW 3. E-mail (to evaluators) Consumer Information System 4. Tracking User Actions - System Usage Database (log files) 5. On-line Questionnaire Data (triggered forms) Remote evaluation of System Usage Kushniruk, Patel, Patel, & Cimino, 2001
  • Example: Evaluation of a Patient Clinical Information System (PatCIS)
    • Over the WWW patients can
      • Review their own medical data (e.g. laboratory results
      • Enter their data (e.g. blood glucose levels)
      • Receive advice
      • Receive educational information
    • Subjects recruited from private practices in New York state
    • Followed over one year
    • Thousands of accesses
  • Screen of a patient clinical information system (PatCIS) showing data review function
  • Evaluation Questions
    • What features of such systems are most used by patients, Why?
    • What features are least used and why?
    • Are there usability issues that need to be resolved?
    • How does use of such systems affect the doctor-patient interaction?
    • Can patients comprehend information presented?
    • Does use of these types of systems affect decision making and disease management?
  • Results
    • Function Usage
      • Most frequently accessed function was “Review of Laboratory Data”
          • Accessed by patients at least once in the majority of the sessions
      • “ Review of Reports” was second most frequently accessed function
      • Other functions (advice, education and data entry) were used sparingly
  • Analysis of User-System Interactions
    • Function Usage (number & percent of accesses)
    • ADVICE DATA ENTRY DATA REVIEW EDUCATION TOTAL
    • .3% 4% 93% 3% 100%
    • Majority of accesses by patients for Data Review
      • Laboratory details
      • Reports – admit/discharge, cardiology, radiology
    • Discovery of patterns of usage related to both
    • demographic and medical data
      • Most used and useful for patients with specific illnesses – chronic illness (e.g. diabetes)
      • Patients liked the system since they felt greater ownership
      • Physicians liked the system as it streamlined their limited face-to-face visits with patients (patients had often reviewed their data prior to the interview)
  • Excerpts from interviews with Patients “ Communication is less in the way of getting information now, and more in the way of discussing treatment options and agreeing on a course of action, so to me its more efficient than the old way” “ I look for trends in my medical data and if I see something I can contact the doctor to see what’s going on, what we can do, change meds or whatever”
  • Excerpts from Interviews with Physicians “ Right now most of the communication takes place during the ten or fifteen minute visit and if I throw a lot of information at the patient about their condition or what I want them to do, its very hard for them to absorb all that. It (PatCIS) gives them a chance to go back and look at things about their health record that they can then ask better questions about in the limited time that we have during the visit. Its another channel of communication”
  • Figure 5a. Resource page showing links to clinical guidelines available from within a computer-based patient record system.
  • Figure 5b. Form to assess clinician’s reason for accessing a guideline (which appears when the user selects a guideline from the resource page).
  •  
  • Implications
    • Analysis of results led to guideline designers to modify
      • the format and amount of information contained in guidelines
    • Now includes text OR easy to read graphical representations (maps)
    • Studying impact of changes
  • Summary
    • Need for range of approaches for assessing HCI / usability
    • Usability is critical to success of health care information systems
    • Usability will be recognized as a major success and marketing factor
    • Consumer expectations for usability will increase
  • Future Directions
    • Extension of methods for qualitative coding of data
    • Development of newer portable and “virtual” approaches
    • Usability engineering methods applied throughout system development
      • User needs analysis (before system development)
      • During requirements gathering, design, implementation
      • In general, the earlier the better
  • References
    • Eysenbach, G. (2000). Recent advances: Consumer health informatics. British Medical Journal, 320 , 1713-1716.
    • Kushniruk, A. W. (2003). Human-computer interaction in health informatics: From laboratory usability testing to "televaluation" of Web-based information systems (pp. 57 - Powerpoint Presentation). Toronto, ON: York University.
    • Schwitzer, G. (2002). A review of features in Internet consumer health decision-support tools. Journal of Medical Internet Research, 4 (2), e11.
  • eHealth: Innovations and Issues E nd Lecture 9 Computerized Clinical Decision Support Norm Archer, Ph.D. [email_address] Ext. 23944