The Science of Cognition and Human-Computer Interaction in Health Care Vimla L. Patel, PhD, DSc Cognitive Studies in Medicine: Centre for Medical Education McGill University Montreal, Canada

Evolution of Medical Informatics: Importance of Interface Design Technology is “good enough” User Experience Dominates Technology Matched to Increasing User Sophistication Unfilled Technology Need High Sophistication of Typical User System Complexity Masked from Lay User ? Technology Delivers Basic Need Current Trend Risk of Excess Functionality Low Low High Sophistication of Technology

What is the User Interface? Those aspects of the system with which the human user comes in contact Examples: ATM, point-and-click navigation in web browsers... Output Language Communication Protocol Input Language

Ways to Deal with User Interface Design Focus on the way the user has traditionally functioned Focus on optimizing the interface and requiring user adaptation Study Interaction to see: what aspects of the user can change what aspects of the system can change

Dimensions of Human Computer Interaction (HCI) Technological Hardware and Software Advances Cognitive Representation Knowledge Organization Reasoning and Strategies

Cognitive Aspects of Interface Design Human Processes: Comprehension Navigation Communication These Affect: Learning Performance

Comprehension and Levels of Meaning Text-based Model - Surface Syntax / Semantics Generation of Local Inferences Propositions Situation Model - Deep Representation of Events, Actions and Persons in Context Conceptual Generation of High-Level Inferences Pragmatics: Context-Bound Inferences

Comprehension Processes CLINICAL DATA Data-driven Process Representation of Clinical Information Interpretation (in Context) Comprehension NEW KNOWLEDGE Generalization PRIOR KNOWLEDGE Instantiation Conceptually Driven Process

Semantic Representation of Natural Language Analysis Semantic Network (relationships between propositions) CONCEPTUAL REPRESENTATION situational model PROPOSITIONAL REPRESENTATION text-based model Propositional Analysis (a form of representation of a semantic network in memory) NATURAL LANGUAGE expressed through THOUGHTS AND IDEAS

Structure of Medical Knowledge in Problem Solving SYSTEMS LEVEL C1 C2 DIAGNOSTIC LEVEL D1 D2 D3 INTERMEDIATE CONSTRUCT FA1 FA2 FA3 FA4 FA5 FINDING LEVEL F1 F2 F3 F4 F5 F6 F7 F8 F9 + + + O1 O2 O3 O4 O5 O6 OBSERVATION LEVEL O7 O8 O9 O10 O11 O12

Cognition and HCI Learning to use technology “Effects with” technology Learning beyond technology “Effects of” technology

Human-Machine Cognition Human experts skip steps during the reasoning process Decision-support systems go through every step methodically in the logical process This distinction can lead to cognitive dissonance between users and machines

Usability Usability Testing Testing of ease of use must be theory-driven Usability Inspection Cognitive walkthrough as a method for gaining insight into user perceptions and misconceptions

Usability Inspection Use of Medline Cognitive Walkthrough: Assess usability for specific tasks Usability analyst steps through system interface methodically Question: Can we anticipate user goals, actions and potential problems in using an information retrieval system like Medline?

Cognitive Walkthrough - Medline Search TASK: To find articles from Medline related to pregnancy and diabetes Goal 1: Find articles related to diabetes Sub-Goal: Do a keyword search on diabetes Action: enter key combination <control R> System Response: “Enter a word or phrase” Action: type in diabetes and press enter System Response: Returns 22998 entries Potential Problem: List too extensive Goal 2: Find articles on pregnancy As above (Goal 1)

Goal 3: Merge list of entries on diabetes and pregnancy Potential Problem: Subject must map term “combine” to action “merge” Sub-Goal: Combine data sets (diabetes and pregnancy) Action: Key combination <control n> System Response: Screen with 2 sets and instructions “Use spacebar to select at least two sets to combine and then press <Enter>” Action: Scroll to diabetes, press space-bar Action: Scroll to pregnancy, press space-bar Action: Press <enter> System Response: Combine sets screen: Choose Boolean connective “and” or “or” Potential Problem: Choice of connectives Action: Select “and” and press <enter> ….

Results Numerous potential problems To perform the task required: 12 sub-goals 22 actions 9 transitions between screens The goal-action analysis shows the cognitive load put on the user in doing simple tasks

Impact of a CPR System on Human Cognition Studies of transition from paper records to CPR and back to paper record Impact on knowledge organization, reasoning, and learning

Changes in Reasoning Patterns Paper Records Data driven reasoning Computer-Based Record Problem directed reasoning Return to Paper Record after CPR Problem Directed Reasoning Residual effect of CPR on learning (after CPR removed)

Changes in Information Management and CPR Use % of Record Contents

Diagnostic Reasoning Using Paper Record Multiple Hypotheses Patient Data Diagnostic Reasoning Using CPR Patient Data Hypotheses

Information in CPR and Hand-Written Records Category of Information Hand-Written Patient Record Computer-Based 1. Chief Complaint 10 28 2. Past Medical History 13 3. Life Style 33 19 4. Psychological Profile 11 5. Family History 7 14 6. History of Present Illness 55 27 7. Review of Systems 52 8 8. Physical Examination 60 9. Diagnosis 9 10. Investigation 29 17 11. Treatment 21 24 Total Entries 304 225

Collaboration and Distributed Cognition Investigate communication between humans, between machines, and between humans and machines Understand How people think analog processing, imprecise How machines think digital processing, precise Capitalize on individual and group expertise

Sociometric Analysis of Email Communication Patterns B E Stanford Columbia F C D G InterMed Central H K J DSG MGH I L M

Email Communication Patterns Episode 1: Vocabulary Server and Guidelines (Jan-Feb 95) Stanford A Columbia B E F C D INTERMED CENTRAL K MGH L M

Email Communication Patterns Episode 2: Guidelines Representation (Feb-Mar 96) Stanford A Columbia B E F C D G INTERMED CENTRAL H K J MGH DSG I

5. On-line Questionnaire Data Evaluation of PatCIS 1. Video Based Usability Testing (“think aloud”) 2. Telephone Interviews (audiotape) Patient PatCIS 4. Log File - System Usage Database (e.g. infobutton) 5. On-line Questionnaire Data (from pilot study) Interact via Internet 3. E-mail (to evaluators & designers)

Patient-System Interaction Lay people’s conceptual model of: Normal health and illness How people reason about health How technology works Study activities of people as they interact with systems

Reasoning Patterns, Data Entry Organization of knowledge differs among lay and professionals Reasoning patterns of professionals and patients are also different

Patients’ Use of Concepts in Explanations of their Decisions about Diabetes Reliance on lay knowledge No use of biomedical knowledge Influence of impact of decision on daily activities, effect of regimen, and fear are major contributing factors to decision making related to illness Information from health care team is reported only 8% of the time, but has become incorporated into patients’ knowledge base and is used in that way. Cytryn & Patel (1998)

Data Entered into the System Accurately by Patients and Physicians 100 Patients Physicians 75 Mean Percent Frequency 50 Errors occur throughout Patients and physicians both about equally accurate in entering glucose level and diet, activity, and stress levels Physicians more accurate in entering Insulin Dose and Hypoglycemic Reaction Different emphasis 25 Blood Glucose Diet, Activity, Insulin Hypoglycemic Level Stress Reaction Cytryn & Patel (1998) Type of Information

Reasoning Pattern: Patient Instruction: Explain decision Response: “Well let’s say if I’ll eat a pound of candies my sugar will go sky high and it might even cause a stroke!” Complications Increased Carbohydrate Intake Increased Blood Glucose Level COND (lead to) Relates symptoms (data) to intermediate factors to underlying pathophysiology Decision - will impact on weight Cytryn & Patel (1998)

Reasoning Pattern: Physician Instruction: Interpret Scenario Response: “A fasting blood sugar of 160 pretty much says she’s diabetic. The postprandial is 200 also tells us she’s diabetic. She’s overweight, that’s already got me thinking that if she’s insulin resistant, then I might be able to improve that by having her lose weight.” Overweight Fasting Blood Glucose Postprandial Blood Glucose Insulin Resistant Diabetes COND Relates symptoms (data) to intermediate factors to underlying pathophysiology Decision - will impact on weight Cytryn & Patel (1998)

Reprise: Reasoning Patterns Patient Increased Carbohydrate Intake COND Increased Blood Glucose Level COND (lead to) Complications Physician COND Fasting Blood Glucose COND Diabetes Relates symptoms (data) to intermediate factors to underlying pathophysiology Decision - will impact on weight COND Postprandial Blood Glucose Insulin Resistant COND Overweight Cytryn & Patel (1998)

Lay Reasoning about Childhood Nutrition COND: Photograph of Child INDIGESTION CAU: Throwing up of food Marasmus Malnourishment X CAU: Food sits in the stomach No food for arms and legs Enlarged stomach, thin arms and legs Kwashiorkar Sivaramakrishnan & Patel (1993)

Summing Up: What’s Next? Cognitive and social sciences are mandatory for design and implementation of UI’s Must have deep understanding of what people do and how they reason about it before developing systems that support those activities Must have better understanding of how people think about the systems they use (acknowledging different expert and lay models) Recognize the movement towards distributed systems, with human beings as heuristically-driven, analogue thinkers partnering with precise digital systems.

More Future Challenges We will move to greater complexity in systems, but need to consider smaller, manageable tasks and thus less complex systems as experienced by users Recognize relation between education and training Training is not enough Must educate to support training

Education to Support Training Linked to other Information Systems Easily & Quickly Accessible User Interface Decision Making Typical (Certain) Guidelines Action Training (Action) Update Ambiguous (incomplete, inconsistent) Discussion/Dialogue Seminars, Community-based groups Education (Knowledge)

The Key Role of Theory in Generating Design Recommendations Interpretation Analysis and Results Theory Guides Data Generalize X Recommendations Customization to Case