Running head: WORKING MEMORY AND EMOTION IN THE PATIENT-DOCTOR
RELATIONSHIP
Working Memory and Emotion in The Patient-Doctor Relationship
Paul Naddaff
Bentley University
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INTRODUCTION
Our brain is equipped with various systems that help us absorb, encode/process, and
store/retrieve information. Our senses absorb information about the world around us. They send
that information to the brain where a series of processes turn raw information into a coherent
form. Before that information stored away, a vitally important system called working memory
helps us make sense of what our senses are telling us. At its core, we use working memory to
hold various pieces of information temporarily at the front of our mind, essentially it is a problem
solving workspace. Doing so allows us to keep relevant information easily accessible so that a
task, thought, or problem may be worked on before it is stored in long-term memory. Working
memory is a critical component of how we learn and solve problems in day-to-day life and
beyond. In fact, it has been proposed that the effectiveness of working memory is a better
predictor of intelligence than IQ, and as a result, measurement of it has been incorporated into
many intelligence tests (i.e. WAIS, WISC, SB-5, WPPSI-III, etc.). Knowing how working
memory functions can allow us to design systems that maximize that part of our mind. How can it
be used in the medical world?
If you were to ask a child, “What does a doctor do?” they would likely reply, “A doctor
helps sick people get better.” In the purest sense, they would be correct in their definition. But in
our world today, healthcare has become a business. In order for a business to survive, it needs to
stay cash positive. In order for humans to survive, we need to stay healthy. When healthcare and
business collide, the patient usually loses, especially if they aren’t able to provide the business
what it needs. Human beings are no longer patients, they have become customers. The difference
being that customers are managed as quickly as possible, while patients are cared for, as if they
were family. There must be a sense of relationship and trust between the caregiver and care
receiver. When doctors have been documented as spending 30-50% of their time on paperwork
(charting, dictation, etc.) vs. direct patient contact, something is amiss. Not to defend the status
quo of the current healthcare system in America, but the organization of the massive amount of
data generated during the 1 billion+ hospital visits each year, is a monumental task (CDC, 2011).
That data is extremely valuable in researching and developing healthcare that will help people
live healthier lives; it also helps save money through prevention. If the data must be collected, it
should be done so in a way that doesn’t compromise the quality of care provided to patients.
A wholly different breed of system,
called OpenMRS, is an open-sourced medical
records system designed to be used in the most
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challenging health care delivery environments around the world. OpenMRS, as its name would
imply, is open sourced, meaning it can be modified to serve a specific group’s needs. It is also
user-centered in that modifications can be made based on the environment in which it being used
to best serve the unique needs of various users. In this paper, we will provide a brief review of
how working memory has evolved. We will then examine OpenMRS from the perspective of
working memory subsystems while discussing the effects of load on working memory.
Building on those observations we will discuss modifications to OpenMRS that could
enhance the patient-doctor relationship. We will also discuss modifications that would
leverage knowledge of emotions, including motivational and anxiety factors pertinent to the
implementation OpenMRS in a medical environment.
WORKING MEMORY:
The concept of working memory has gone by a handful of different names over the past
100 years. Terms such as primary memory, short-term memory, and working memory refer to
general notion of human memory being broken down into multiple parts that dynamically interact
with each other. William James (1890) divided human memory into two main parts, primary
memory and secondary memory (or short-term memory and long-term memory, respectively).
Primary memory is the space where information is first gathered so that it may be manipulated,
examined, and perhaps learned. The magic of primary/working memory lies in the connection is
shares with long-term memory. For complex tasks, the two systems lend processing power from
their respective spaces that allow us to make sense of and build upon information we are
presented with.
Although James’ cognitive theories were powerful, the behaviorist school of thought (led
by Watson, 1913) dominated from 1900-1950. It wasn’t until the 1950’s that cognitive
experimental studies gained momentum with the Cognitive Revolution. George Miller’s, seminal
paper “The Magical Number Seven, Plus or Minus Two” (Miller, 1956) reintroduced the concept
of dual levels of memory, specifically short-term memory (STM) and long-term memory (LTM).
His paper discussed the capacity of our short-term memory; 7 +/-2 referred to the number of
“chunks” of information that we can hold in our short-term memory (i.e. the digits in a phone
number or license plate). Using various strategies, information can be grouped together into
chunks so that, for example, the letters D-O-G will count as one chunk (DOG) and not three.
Without chunking strategies, the magical number may be lower than seven (Cowan, 2001). Also,
information contained in short-term memory was identified as being available for a short duration
(i.e. 20 seconds) and for being highly accessible.
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Later, the Atkinson-Shiffrin model of memory explained how short-term and long-term
memory interact with each other on a basic level (Atkinson & Shiffrin, 1968). In their model,
STM acts as a gateway that information must pass through in order to access LTM. The
workspace of short-term memory allows us to encode information in a way that makes sense to us,
preparing it in way that makes it easily organized into our long-term memory. STM allows us to
enhance and apply meaning to information, which improves learning and retention. Their model
is also referred to as the “modal model” due to its two-phase construction, which views STM as
slightly more rigid and sequential than what has become known as working memory (WM).
The current concept of working memory plays up the ability of the dynamic
interconnectedness of WM (formerly STM) and LTM. STM gradually became replaced by WM
due to the fact that patients who had brain damage to areas of the brain believed to be associated
with STM were still able to store information in LTM, debunking the gateway Atkinson had put
forth (Shallice & Warrington, 1970). The strongest support for the non-rigid working memory
model came from a key study by Baddley and Hitch (1974). They argued that there were three
sub-systems of working memory, and introduced the concept of the central control system that
effectively divided memory allocation and the balance between processing and storage. The first
of the three components was called the “central executive”; it also dictates the removal of
information from WM when no we are longer actively trying to remember it (or when we are
interrupted by something). According to Baddley-Hitch, WM enables complex cognitive
activities to effectively juggle chunks of information. Two other components of WM are the
visuospatial scetchpad (for processing visual information) and the phonological loop (for
processing verbal information). Since the two are independent from each other, each can
simultaneously handle different information. This is important to designers, because through
design, we can maximize both the visual and verbal components of working memory, effectively
increasing a user’s WM potential.
Figure 1. Illustration of mental systems. Paul Naddaff, 2011
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Recently, updates to the strong working memory model have been made. Baddeley
(2000) and Tulving (2002) added a fourth component to the former trio (central executive, spatial,
phonological) called the episodic buffer. This system, as its name would imply, acts as a buffer
for the other sub systems of working memory, acting as both an overflow and a space in which
spatial and verbal information can be mixed together. While there are slightly different models of
working memory coming from such renowned experts like Cowan (2005) and Ericsson and
Kintsch (1995), the differences raise interesting points, however they are beyond the scope of this
paper.
OPENMRS: WORKING MEMORY & EMOTION
There are many pressures being applied to a doctor/medical worker when they sit with a
patient. These pressures contribute to the motivation of the caregiver. Motivation can be divided
into two categories; intrinsic and extrinsic. Intrinsic motivation applies to the internal motivations
that the caregiver will feel, for example, wanting to help alleviate a patient’s pain. Conversely,
the doctor is also faced with extrinsic motivation, for example after spending a long amount of
time with one patient, being cognizant that there are many other patients who desperately need
help. The interplay of these two different kinds of motivations (as well as all the other pressures a
doctor faces) contributes to the emotional condition of the doctor, and indirectly, the emotions of
the patient. The end result of the two motivations is a potentially overwhelming sense of anxiety.
While it has been shown that a small amount of anxiety can help improve productivity, too much
anxiety can be crippling; doctors likely do not need help being any more anxious. OpenMRS can
help manage this anxiety or at least not contribute to it by acting in such a way that does not
impede on the doctor-patient relationship.
OpenMRS is built around a
powerful “concept dictionary” that
allows users to search and add to a
database of diseases, clinical findings,
laboratory test results, etc. The main
benefit of the concept dictionary is
that it organically and collectively
grows as each user (around the world)
adds to it. The end result of this
dictionary is an extremely rich
Figure 2 OpenMRS' concept dictionary
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conglomeration of searchable data that can be used in the research and treatment of illnesses. In
essence, it is a Google for real-world medical data. In fact, Google works directly with OpenMRS
after having recently shut down Google Health.
The use of the concept dictionary is relatively effective in reducing the load imposed on
the user’s working memory. For instance, the user does not have to necessarily know exactly
what to type into the concept dictionary, as suggested/related terms will automatically be
displayed as the user types (similar to Google). As the user types, they can be thinking about their
next step as opposed to focusing directly on which term they are supposed to enter.
While the concept dictionary partially leverages knowledge of working memory, it could
do so even more. We will now discuss design enhancements that leverage working memory and
emotional concepts. The first would be to allow the doctor to rapidly enter patient notes into a
sketchpad in non-standard shorthand, without worrying about which field of a specific form it
should be entered into. Using available algorithms, this data can later be used to automatically
populate the fields and charts (with user approval to correct errors). This would allow the health
worker to collect raw data in a very low-profile
manner, so that full attention can stay on the patient.
This would also allow users to apply information to
patient charts without disruption, which is critical to
not disrupting the user’s flow, thus enhancing their
working memory. Additionally, in the sketchpad, it
would be beneficial to have auto-detection of key
bits of inputted data that generally go together, this
feature would help create a chunking effect, further
improving the efficiency of working memory.
Figure 3 OpenMRS correcting input, not ideal.
Another way the OpenMRS could be enhanced to foster working memory would be to
allow notes relating to physical observations to be captured with quick photographs, while notes
from verbal data, could be entered with both words and audio recordings (for backup). Doing this
takes advantage of the working memory by dividing workload between the verbal and
phonological systems.
Because OpenMRS is used by both doctors and community health workers (and many
other types of users in between), the system can be modified to serve both expert and novice users.
For expert users, it would be acceptable to increase the necessary memory load and information
density slightly; however other users may need to be guided more strongly, and have a more
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simple display. For the novice users, congruent instructions (do a, then b, then c) would be
extremely beneficial. Since each user does not need to see the same information, creating
different user experiences based on the desired user will modulate workload, greatly benefitting
the user.
The role of emotions in the doctor-patient relationship is critical. Feelings and emotions
take root very quickly, especially when we are feeling particularly vulnerable (LeDoux, 1996,
Bornstein, 1992, Zajonc, 1980). A patient will pick up on a caregiver’s emotions rapidly, and
react to them- this can have multiple consequences, both positive and negative. Emotions can be
triggered in milliseconds due to a small bundle of neurons that has been identified that lead
directly from the thalamus to the amygdala across a single synapse. This allows the amygdala to
receive direct inputs from the sensory organs and initiate a response before the stimuli have been
interpreted by the neocortex- essentially, external emotionally charged stimuli don’t have to go
through much mental processing to come to fruition (LeDoux, 1996). A caregiver should be as
aware as possible of the patient’s potential feelings from the start of a visit, first impressions are
vital in the design of a system or in person-to-person interactions (Lindgaard, 2006).
To this point, every
patient has a story, likely
riddled with successes and
failures, ups and down; stories
are about emotions. Often in
medical environments, charts,
data, text, etc. fail to tell the
whole story, especially when
Figure 4 OpenMRS with emotional icon.
a patient has been passed
through multiple doctors. An OpenMRS module could be developed to assist the caregiver by
infusing emotional patient data into charts with simple visuo-emotional cues. For instance, if a
patient has had a history of repeated failures, a cue could be given to the doctor in a dedicated
section of the patient chart that indicates that this patient is likely to be feeling
upset/unmotivated/frustrated/scared- this could be visually represented with a simple icon that
calls the caregiver’s attention to the patients likely emotional state before seeing the patient.
Conversely, if positive progress is being made, a more uplifting cue could be given to remind the
caregiver, and the patient (indirectly), that their hard work is paying off. This would be extremely
helpful in cases where a new community health worker who has not yet had to deal with the
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delicate range emotions that patients will be experiencing. Making the caregiver aware of subtle
emotional states of patients could help the doctor metacognitively adjust their mindset to be more
sensitive. Caregivers and patients could truly benefit from a feature like this.
This feature would also increase the level of trust between the doctor and the patient by
making the patient feel more comfortable with the doctor, strengthening the relationship. Trust is
an extremely important component of the doctor-patient relationship, especially when the patient
is facing extremely serious conditions that require them to strictly adhere to a regimen- they’ll be
more likely to follow their doctor’s instructions if there is a strong sense of trust. A first
impression has a long-term effect that is sometimes referred to as a ‘halo effect’. This halo effect
will carry over into future evaluations the patient makes of their caregiver (Lindgaard, 2006). By
making an emotionally salient connection to the patient, the doctor will also likely encode more
details of their visit due to the increased emotional content. This has been proven to enhance
successful long-term memory storage (Baddeley, 1983).
CONCLUSION
As we have shown, systems can be designed to take advantage of what we know about
how our mind works. Working memory is especially susceptible to these considerations, the
results of which can be directly tangible in the user’s (both direct and indirect) experience.
OpenMRS is a wonderful tool used by people who care all around the world- we should strive to
make the tool more emotionally aware so that the overall interaction between patient and doctor
is more efficient, authentic, and humane.
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