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1
Information Overload and the Design and Implementation of
Computerized Decision Support
Charlene R. Weir, PhDAssociate Director Education and Evaluation, SLC GRECC
Associate Professor
Department of Biomedical Informatics
University of Utah
OBJECTIVES
Identify concepts and causes of Information Overload in terms of computerized clinical environments.
Discuss the relationship between information overload and different memory systems.
Describe how to match clinical task characteristics and implementation strategies in order to minimize information overload in the clinical setting.
OVERVIEW
Definition of Computerized Decision Support
The Goal and the Mandate
Are we meeting the goal?
Central Thesis
The Adaptive User
Memory, attention and control
Recommendations
“Providing clinicians, patients or individuals
with knowledge and person specific or
population information, intelligently filtered or
presented at appropriate times, to foster
better health processes, better individual
patient care, and better population health.” Consensus Definition of DSS by A Roadmap for
National Action on Clinical Decision Support, AMIA 2006
Types of Decision Support
Alerts
Reminders
Guidelines
Information Displays
Provider Order Entry
Electronic Text/Templates
“to ensure that optimal, usable and effective
clinical decision support is widely available to
providers, patients, and individuals where and
when they need it to make health care decisions.”
A Roadmap for National Action on Clinical Decision Support
AMIA 2006
THE GOAL
ARE WE MEETING THE GOAL?Systematic Reviews - Outcomes
Garg, et al.(2005) Effects of CDSS on Practitioner Performance and Patient Outcomes: . . . . . Sig improvements in practitioner performance in
64% of studies and improvements in patient outcomes for only 13%.
Unable to aggregate due to significant unexplained variation
Recommendations: “Important issues include CDSS user acceptance, workflow integration . . . (p. 1236)
ARE WE MEETING THE GOAL?Systematic Reviews - Outcomes
Kawamoto, et al (2005). Improving clinical practice using clinical decision support systems: a systematic review. Sig improvements in practitioner performance in
68%. Patient outcomes were not examined. Unable to aggregate effects due to significant
unexplained variation Recommendations: “The promise of evidence
based medicine will be fulfilled only when strategies for implementing best practice are rigorously evidence-based themselves.” (p. 7)
ARE WE MEETING THE GOAL?Systematic Reviews - Outcomes
Shekelle P. Costs and Benefits of Health Information Technology. AHRQ Publication. Santa Monica, CA. Unable to aggregate due to significant
unexplained variation
Also published in: Chaudhry B, Want J, Wu S, et al. Systematic review: Impact of HIT on quality, efficiency, and costs of medical care. Annals of Internal Medicine 2006;144:E12-E22
CONLUSION “In summary, we identified no study or collection
of studies, outside of those from a handful of HIT leaders, that would allow a reader to make a determination about the generalizable knowledge of the system’s reported benefit.
Even if further randomized, controlled trials are performed, the generalizability of the evidence would remain low unless additional systematic, comprehensive, and relevant descriptions and measurements are made regarding how the technology is utilized, the individuals using it, and the environment it is used in.” (Shekelle, et al, p. 4)
Types of Unintended Consequences Related to CPOE
“Great care must be taken to balance the risks of over-alerting with not alerting.
Developers should re-work clinical system interfaces to: 1) reduce collection of
redundant information; b) display relevant information in logical locations . . . “ (p.
553)
Campbell, Sittig, Ash, Guappone and Dykstra, JAMIA. 13:547-556.
Information-System Related Errors
Interface not suitable for highly interruptive context
Causes cognitive overload due to overly structured information entry and retrieval
Misrepresenting collective, interactive work as a linear, clear-cut and predictable workflow
Misrepresenting communication as information transfer.
Ash, J, Berg,M. Coiera, E. JAMIA 2004; 11:104-112
Barriers to Effective Use of VA Clinical Reminders
Patterson, et al (2004) Workload was the primary barrier Inapplicability to the situation Lack of utility and ease of use Workflow - not related to core work - duplication “Assembly line medicine” “Having physicians do clerical entry tasks”
Issues in Electronic Documentation
“overwhelmed”
“takes too much effort to sort through everything”
“I avoid reading nursing notes, they just have pages and
pages of blank fields”
“There is so much stuff put into a note, I can’t find what I
need.”
Access versus Availability
Tools to identify relevance not available
Accuracy goals are competing with efficiency goals
Weir, C and Nebeker, J (2007). Critical Issues in an Electronic Documentation System. AMIA Proceedings.
**CENTRAL THESIS** Inattention to work processes in the
implementation process is experienced as information overload to clinicians.
Because: Deviations in work-flow are perceived as
interruptions
Changes in information location and timing increases cognitive effort
The process of adaptation results in the creation of innovative strategies to decrease cognitive burden
Information Overload is really a “mismatch” between available cognitive resources and the task
TASK ANALYSISInformation Management Strategies
Systematic selection of 13 / 133 VA sites Random selection of a primary care clinic Procedures
Site visit, observations and interviews Goal-based interviews (“in order to . .”; “by . .”)
88 participants (14 nurses, 53 ordering providers, 8 pharmacists, 2 dieticians)
About 60 hours of observation Qualitative Analysis ( tasks, common components,
and goals)
Weir, CR, et al (2007). A cognitive task analysis of information management strategies in a computerized provider order entry environment. JAMIA 14(1):65-75
Information Management Goals
Relevance Screening
Ensuring Accuracy
Minimizing Memory Load
Negotiating Responsibility
COPING STRATEGIES FOR INFORMATION INPUT OVERLOAD
Omission
Reduced Precision
Queuing
Filtering
Cutting Categories
De-centralization
Escape
Hollnagel, E and Woods, D (2005) Joint Cognitive Systems. CRC Press (p. 80)
CONCEPTS of “INFORMATION OVERLOAD”
Mismatch between us and context
Disorientation/ lost
Inability to determine relevance
Distracting/forget goal
High Effort
Lack of situational awareness
Inability to “think” or analyze
ASSOCIATIVE MEMORY PROCESSING
Associative Learning: Gradual accretion of knowledge through progressive associations; expert performance is an example.
Thinking: fast, pattern-completion, effortless Awareness: Not required for performance Errors: common heuristics or “rules of thumb” Change: change is slow,hard; like “breaking
bad habits.”
VERY RESISTANT TO IMPACT OF COGNITIVE LOAD
SYMBOLIC MEMORY PROCESSING
Symbolic Learning: Fast increase in
knowledge through rules/symbols/language.
Thinking: slow, effortful, requires attention
Awareness: Required for performance
Errors: miss-identifed task, not understanding
CHANGE: change may be fast
HIGHLY SENSITIVE TO COGNITIVE LOAD
IMPLICATIONS Both types of cognition are “working”
simultaneously.
Humans prefer to minimize cognitive load, hence their behavior will likely be under the control of what they know as much as possible.
Adaptive strategies or “work-arounds” are geared to “think less.”
Experts do much more with less attention and effort.
MOTIVATION
As cognitive load increases (work, distractions), then the work will be taken care of by the associative system (less thinking, more automatic, pattern-recognition processing).
As motivation to be accurate increases, more of the work will be done by the symbolic system (new material, high patient acuity, social pressure)
RECOMMENDATIONSTask-Person-Technology Fit
Decision support for easy tasks should not require attention (they will be seen as interruptions). Increase Control Order sets and protocols Standing Orders Administrative Control (e.g. formulary) Documentation / Order Combinations Embedded tracking of behavior “just in time” heuristic
RECOMMENDATIONSTask-Person-Technology Fit
Decision support for hard/complex tasks should assist the human in active problem-solving - not replace him/her. Provide information early in the planning phase Display information by tasks (e.g.problems) Slow down the process in order to facilitate
“deeper processing” Info buttons, access to other experts/consults;
and/or scientific authoritative sources Enhance team communication
RECOMMENDATIONSTask-Person-Technology Fit
Humans vary in expertise, current conditions of cognitive load and need for choice and flexibility. User expertise and role identification - based
views.
Search, query and custom views
Tailor views to situations - busy settings may have different views
EXAMPLES Antibiotic prescribing
support Assessing decision-
making capacity Patient Education Diagnoses Identification of
Adverse Drug Events Management of HPT
Flu vaccine Depression Screening DVT prevention
protocols Prevention of
constipation resulting from narcotics
Fall Screening
High Task Complexity/DifficultyLow Task Complexity/Difficulty
Embed Interventions and Increase Control
Increase Information/High Flexibility
Minimizing Harm from ADEs by Improving Nurse-Patient Communication - Weir (PI)
VA funded research project
Medication Management is a complex, multi-
disciplinary activity
Analyze Medication Management
Communication Patterns
Design an Intervention that enhances
information exchange between providers on
medication management issues
“VA Integrated Medication Manager” Nebeker (PI)
VA-based development project
Improves information display for management of hypertension
Includes symptoms, medication history changes and relevant lab data.
Uses human factor methods to identify task characteristics.