Work Domain Analysis Applied to Medical Diagnosis

Work Domain Analysis Applied to Medical Diagnosis *Daniel Nystrom, M.S., **Mark Graber, M.D., *Linda Williams, R.N., M.S.I., and *Douglas E. Paull, M.D.
*VA National Center for Patient Safety, Ann Arbor, MI
**Society to Improve Diagnosis in Medicine

Patient Safety Fellowship 2013-­‐2014 - ABSTRACT Little effort has been spent
describing the cognitive
components that characterize the
diagnostic process . This research
describes the use of work domain
analysis to create a functional
depiction of diagnosis. The
resulting abstraction-decomposition
space (ADS) depicting the medical
diagnostician’s work domain
provides a look into the
fundamental features of diagnosis.
To portray how a diagnosis emerges
according to this ADS, a case
example was taken from relevant
training literature and superimposed
onto this model. The example
offers a general look into how the
sources of information medical
diagnostician’s query inform their
diagnostic decision process.
Suggestions for future work towards
the reduction of diagnostic error
based on this ADS are provided.
Generalized concept of diagnosis Transla3on into abstrac3on-­‐decomposi3on space - RESULTS -
- CONCLUSION -
•  The resulting representation of the work domain analysis performed on medical
diagnosticians’ work domain is the abstraction-decomposition space (ADS) provided below.
Key features to the diagnostic process were attached ad hoc to the ADS to more thoroughly
describe the diagnostic process (see below, red dashed lines).
•  Naikar, Hopcroft, and Moylan (2005)
identify the abstraction-decomposition
space (ADS) as a bridge between the topdown processes and bottom-up processes
of a work system. Considering the ADS
•  A case example taken from diagnosis training literature was applied to the ADS model
depicting the diagnostician’s work
to further describe the cognitive processes of diagnosis (see right). The example
displays a simplified version of the processes employed in diagnosing Stage 1 Hodgkin’s domain, system influences on the
diagnostic
process
would
be
most
disease. Starting from the top ADS (1) and finishing with the bottom ADS (5), each
associated
with
the
technical
functions
numbered representation contains yellow boxes that are juxtaposed to ADS nodes.
and physical resources of the ADS, while
These yellow boxes contain text borrowed from “An Example of the Diagnostic
higher levels of the ADS hierarchy are
Process” found in Degowin’s Diagnostic Examination (LeBlond, DeGowin, & Brown,
more closely related to the cognitive
2009, p. 13) and should be read in numeric order.
elements of the diagnostic process.
•  The ADS sets a foundation for future
research to determine which sources of
information and techniques for collecting
information are important for correctly
diagnosing various diseases.
•  The ADS also provides an important
“blueprint” to aid in the development of
simulation scenarios to further study
diagnosis.
- INTRODUCTION •  Little effort has been spent on
describing the cognitive
components that characterize the
diagnostic process (Trowbridge,
Dhaliwal, & Cosby, 2013).
•  The interplay of cognitive
processes and system-related
issues makes diagnosis research
difficult, and leaves researchers
confused about how to approach
and integrate these two concepts
(Henrickson & Brady, 2013).
•  Work domain analysis is a
cognitive engineering technique
that creates a hierarchal model to
provide a context independent
representation of the work
domain, which can be used to
evaluate how information from
the physical resources of a
domain achieve the purpose of
that domain (Vicente, 1999;
Lintern, 2011).
- METHOD •  Work domain analysis (WDA) utilizes training documents, design specifications, and interviews with subject matter experts to identify the purpose of a work domain, the values and priorities held by entities within
the domain, the type of work being completed in the domain, and the technical functions fulfilled by the physical resources to satisfy the purpose of the domain (Lintern, 2009; Lintern, 2011).
•  A WDA was conducted on the medical diagnostician’s work domain. The domain purpose, values and priorities, and work functions were primarily extracted from training documents (LeBlond, DeGowin, & Brown,
2009), while case reports (Saint, Drazen, & Solomon, 2006) were referenced to identify the technical functions and physical resources within the domain. After creating an abstraction-decomposition space representing
the diagnostician’s work domain, interviews with 3 board certified clinicians were conducted to supplement the representation.
- REFERENCES •  Henriksen, K., & Brady, J. (2013). The pursuit
of better diagnostic performance: A human
factors perspective. British Medical Journal of
Quality and Safety, 00. Retrieved from doi:
10.1136/bmjqs-2013-001827
•  LeBlond, R. F., DeGowin, R. L., & Brown, D.
D. (2009). DeGowin’s Diagnostic Examination
(9th ed.). New York, NY: The McGraw-Hill
Companies, Inc.
•  Lintern, G. (2009). The foundations and
pragmatics of cognitive work analysis: A
systematic approach to design of large-scale
information systems. Retrieved from http://
www.cognitivesys-temsdesign.net/
•  Lintern, G. (2011). Tutorial: Work Domain
Analysis. Retrieved from http://www.cognitivesystemsdesign.net/
•  Naikar, N., Hopcroft, R., & Moylan, A. (2005).
Work domain analysis: Theoretical concepts
and methodology (Tech. Rep. No. DSTOTR-1665). Victoria, Australia: Australian
Government Air Operations Division, Defence
Science and Technology Organisation.
•  Saint, S., Drazen, J. M., & Solomon, C. G.
(2006). New England journal of medicine:
Clinical problem-solving. New York: McGrawHill Professional.
•  Trowbridge, R. L., Dhaliwal, G., & Cosby, K.
S. (2013). Educational agenda for diagnostic
error reduction. British Medical Journal of
Quality & Safety, 22, ii28-ii32.
•  Vicente, K. J. (1999). Cognitive work analysis:
Toward safe, productive, and healthy
computer-based work. Mahwah, NJ: Lawrence
Erlbaum Associates.