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Behavior analysis in medicine: a clinical decision model to support patient care

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Behavior analysis in medicine: a clinical decision model to support patient care

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BEHAVIOR ANALYSIS IN MEDICINE
A CLINICAL DECISION MODEL TO SUPPORT PATIENT CARE

by

Naira Kirakosyan

A Thesis Presented to the
FACULTY OF THE USC DORNSIFE COLLEGE OF LETTERS, ARTS AND SCIENCES
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(APPLIED BEHAVIOR ANALYSIS)

December 2020

Copyright 2020 Naira Kirakosyan

TABLE OF CONTENTS

List of Tables……...…………………………………………………..………… ….…………...iii
List of Figures……......…………………………………………………………………………...iv
Abstract…………………………….…………………………………………...… ..……………v
Introduction………………………….…………………………………………………………….1
Literature Review…………………….…………………………………………………..………..2
Participants……………….………………………………………………………………………..6
Dependent Variable: Participant Answers on Knowledge Survey……………………..…………7
Independent Variable: The Decision Model………………………………………………………7
Experimental Design…………………………………………………………………………...….8
Results…………………………………..…………………………………………………………9
Discussion…...…………………………………………………………………………………….9
References…………………….……………………………………………………………….…13

ii

Table 1: Questionnaire/Confidence Scale

1 Do know where to go if you have a medical issue or
pain?
1 2 3 4 5
2 How confident are you to speak to a doctor about your
health concerns?
1 2 3 4 5
3 How well can you describe your pain? 1 2 3 4 5
4 How involved would you be when addressing a medical
concern?
1 2 3 4 5
5 Do you know what specialties there are in medicine and
what they do?
1 2 3 4 5
6 How well can you identify your own medical needs? 1 2 3 4 5
7 When given a referral, how well do you understand the
reason?
1 2 3 4 5
8 How well do you think you understand the medical
process?
1 2 3 4 5
9 Can you identify and describe your symptoms well? 1 2 3 4 5
10 How well can you outline your medical history at a
doctor’s appointment?
1 2 3 4 5
iiiiiiii

Figure 1: Graph

iv

Abstract
Within the American health care system, millions of dollars go to waste as a result of
inappropriate referrals and unnecessary doctor appointments. Meanwhile primary care physicians
have month-long waiting lists for simple visits. This is a result of certain insurance plans
insisting on primary care appointments prior to seeing a specialist. This system, although not
proven completely ineffective, has created dissatisfaction among patients as well as physicians.
However, without a proper solution, patients have no other choice but to visit primary physicians
with any and all health concerns. With the recent growth in technology, such issues have been
addressed through online appointment systems and Electronic Health Records. However, there
does not seem to be a comprehensive and effective intervention that addresses both the concerns
of patients as well as physicians. Clinical Decision Support Systems have been proven to be
effective both in the field of medicine as well as within corporate infrastructures through
organizational behavior management. The purpose of this study is to demonstrate how a Clinical
Decision Support System can be used to guide patients to access needed medical care as well as
allowing for less time spent within the referral process and unnecessary medical appointments.

v

Introduction
The potential impact of the field of behavior analysis is broad, however, the utilization of
behavioral technology outside of autism remains limited. A large percentage of Board Certified
Behavior Analysts never receive any training in other specialties, such as behavioral medicine or
organizational behavior management, and most tend to work in large part within private practice
with children diagnosed with Autism Spectrum Disorder (ASD). Although this pertains to a large
majority of Applied Behavior Analysis (ABA), there are Board Certified Behavior Analysts who
have been utilizing behavioral principles and applying them to various other fields and settings.
One such tool is the decision model. Decision models are tools that are used to guide behavior
and assist with the determination of the most effective course of action for professionals. This
model can be used in both the field of ABA as well as in a variety of other contexts such as
speech pathology, physical therapy, medicine, economics and business. Decision models are not
used as a generic structure, rather a model is used as a clinical guide that generates
recommendations and prompts the professional in useful directions. Personal clinical judgement
is then used to analyze the individual situation. Thus far, decision models have been adopted less
in the discipline of applied behavior analysis, compared with other professions.
Current deficiencies in both the fields of ABA as well as medicine include the lack of
collaboration and connection between professions as well as between the patient and
professional. Such collaboration is key, however, tools such as decision models are rarely made
available, resulting in poor communication. The use of a decision model, as stated above, could
be the link that ties together the physician and patient communication.

1

Literature Review
How do decision models connect with the basic principles of ABA? We know that
behaviors must be observable and measurable to be included within the realm of ABA. However,
we may also refer to non-observable behaviors as what Skinner called “private events”. Private
events fill in the gap of behaviors that occur however are not observable by others, this includes
thoughts, feelings as well as problem solving and decision making. By focusing on the latter, it is
possible to measure behavior change or the outcomes of a behavior without observing the
occurrence of the behavior itself. This is the prime principle we will be applying in decision
modeling within ABA. Essentially, this means we cannot observe the exact behavior, the inner
workings of the mind, however we can monitor and measure the overt behavior change that those
private events lead to. Skinner defines this behavior of thinking and deciding as not the execution
of the act decided upon but the preliminary behavior responsible for it (Skinner 1953. P 243).
Hence, the use of a decision model may be thought of as an antecedent strategy for promoting
more advanced self-care behaviors. Such a behavioral repertoire is often overlooked due to the
minute deficiencies by adults. Such deficiencies may include escaping a visit to the doctor even
when needs are clearly present, this could lead to the worsening of the issue, or in some cases to
the advancement of a life-threatening illness, such as cancer. As Skinner puts it “The individual
manipulates relevant variables in making a decision because the behavior of doing so has certain
reinforcing consequences. One of these is simply escape from indecision. Conflicting
alternatives lead to an oscillation between incomplete forms of response which, by occupying a
good deal of the individual's time, may be strongly aversive” (Skinner 1953 p 251). This goes
back to one of the primary principles of applied behavior analysis, negative reinforcement.
Negative reinforcement is when the removal of a stimulus results in the increase of a behavior.
This means that aversive activities may be removed temporarily, and this will lead to an increase
2

of the avoidant behaviors associated with self-advocacy. Within this paradigm, we can conclude
that self-care may be heavily compromised when decisions are either difficult to be made or an
aversiveness is tied into make decisions. This can be particularly essential when the decisions to
be made are related to one’s health. Avoiding the decision-making process may lead to often dire
consequences when it comes to healthcare. For example, proper diagnosis and treatment may not
occur for a long period of time, leading to the advancement of any possible disorder, infection or
illness. Hence, by assisting in the decision-making process, decision models may play a role in
antecedent interventions for better self-care of individuals. In addition, an article by Alden et al.
suggests the positive outcomes of increased patient involvement when it comes to medical
treatment. Throughout history and “beginning with the Hippocratic tradition and lasting for the
next 2,400 years the physician-patient relationship remained relatively unchanged under the
beneficence model, a paternalistic framework characterized by the authoritative physician being
afforded maximum discretion by the trusting, obedient patient” (Will, 2011) suggesting that
patient involvement within the field of medicine has been scarce and limited, yet “increasing
clinical evidence indicates that patient involvement in medical decision making improves health
care outcomes” (Alden, 2014). The transition between the models of medical care have been
varied in the recent years. Most of the time a state of fear, lack of knowledge or lack of
information has prevented patients from participating in the medical process. This involvement is
of the utmost importance as self-advocacy is crucial to the treatment of any disorder or disease.
Hence, any type of assistance is necessary and “…several studies report that use of decision aids
improves patient confidence and openness to participating in the consultation process” (Bekker,
2003). Essentially, decision aids provide the tools for patients to advocate for themselves no
matter the situation. This tool would not only provide assistance with decision making, it would
also provide a more organized report on their own signs and symptoms.
3

Although medicine is one of the oldest and most established fields of human care, there
still remain some inefficiencies that could be easily addressed. One of these inefficiencies
include access to professionals by patients. Although seemingly simple, it may take a patient
three appointments within a span of three months to see a specialized doctor for immediate care.
This system is due to various insurance policies requiring referrals from primary care physicians
for specialists. Within this model, when a patient has a new health issue, they have to go through
a series of steps to receive care. First, they would have to make an appointment with a primary
care doctor. This could take up to one month depending on the caseload of the doctor. During
this appointment, the patient would express their concerns. Then, following that appointment, the
physician would bill for a referral to the insurer. The insurer would then process the referral and
mail the acceptance to the patient. After that, the patient would need to locate the nearest
specialist needed and make another appointment. Again, this might take a while dependent on
the caseload of the specialist. One way we can streamline this process is through the use of a
medical decision model. Through this model, a patient may be able to input their symptoms and
past significant medical history and receive a recommendation, all without leaving the comfort of
their own home. This would not only save time for the patients; it would save physicians time by
not having appointments where they simply write referrals. According to recent data,
“Approximately 40% of patients are referred each year” (Franks 2000). This means that 40% of
appointments for primary care physicians are simply occurring for this reason only. That is
almost half of all appointments, lowering this statistic would in large part reduce wait times for
those seeking care from their primary care physicians. In addition, this would save the insurance
company money by not paying for those additional visits to a primary care physician. Evidently,
the current system and “the role of primary physicians as gatekeepers in managed care has been
controversial. Largely on the basis of evidence that specialist care is more expensive, managed
4

plans have sought to limit access to specialists” (Franks 2000). However, often times the reversal
occurs and lower access to specialists may be associated with increased costs. This was
demonstrated in a study by Stein et al who found that “cardiologists were much less likely than
generalists [PCPs] to order inappropriate tests for coronary artery disease, so that referral to
cardiologists before tests are ordered would result in significant cost savings” (Franks 2000).
In addition, other studies have also shown that “patients referred early in the course of
their orthopedic or endocrine problems had lower costs than those referred later” (Neyman
1998). This would mean that cutting out primary care physician visits not only extrinsically
reduces costs due to actual appointments, but intrinsically reduces costs by not having extra and
unnecessary tests ordered. Although little research supports this notion, it is also plausible that
“patient health status outcomes are affected by referral behavior; appropriate referral may lead to
prompt diagnosis and treatment of conditions that were beyond the immediate expertise of the
[primary physician], delayed referrals or needed referrals that do not occur (under referral) may
result in adverse outcomes or require interventions that are ultimately more expensive” (Franks
2000). Such effects are often not measured and hence go unnoticed in the vastness of the current
healthcare system. However, unofficial methods may show us that such inefficiencies do occur,
and a solution is available. Currently, data does not exist on referral rates, specific numbers and
statistics on the amount of money spent by funding sources on unnecessary referrals is simply
not tracked or followed. Hence, the issue may not even be apparent to many in the field. The sole
method of measurement would be to change the behavior of the consumer and analyze the
effects.
Decision theory is the distinguishing of behaviors which allows an individual to make
decisions and consider the variable outcomes dependent on the decisions guided by current
standards of practice and research. Decision theory may be categorized into two major forms that
5

contribute to decision modeling. These include normative decision modeling and descriptive
decision modeling. Normative decision modeling prioritizes on how decisions should be made
regarding the rationality of the situation, meanwhile, descriptive decision modeling prioritizes
how decisions can be made with consideration to real-world events. Normative decision
modeling is informed by current literature and standards of practice however does not address
practical and clinical factors that may arise. In opposition, descriptive decision modeling focuses
on how decisions are made specifically with the consideration of real-life events, hence does not
consider the rationality or literature-based research. Both types of decision theory are necessary
to create decision models which are effective at guiding the decision of professionals (Hansson,
1994). In addition to decision theory, decision analysis has been used in large part by other
disciplines. Decision analysis is derived from the fields of operations research, economics, and
applied mathematics; it has been used in many different areas, including medical research.
Although some aspects of decision analysis may apply to clinical practice, the largest use has
been in clinical research to disseminate problems and assess expected outcomes for complex
issues that concern public policy and patient populations. In this respect, decision analysis
models are often developed to assess the economic outcomes and cost-effectiveness of various
health care programs and health care interventions (Chalfin 2000). Hence, we may conclude that
decision modeling and theory has been backed by literature in multiple domains and disciples, all
having used the theory to further advancement in the field.
Participants
For the current study, a variety of participants will be recruited. Recruitment will be
conducted on the campus of USC via posters and online postings. Participants will be included if
they are between the ages of 18 and 80 and are able to use a computer program. Participants are
also required to speak, read, and write in English. The participants identities will be kept private
6

and even study staff will not need to know the names of the participants. Identifying information
needed will be age and gender. A total of 3 participants will be tested in the trial and will need to
be present for one session which could last up to an hour.
Dependent Variable: Participant Answers on Knowledge Survey
After participants have been recruited, a medical vignette will be provided that outlines a
common medical issue typically faced by individuals. The vignette will include all the
information needed such as sample age, gender, health history and current issues. A
questionnaire will be provided that will attempt to take baseline measures of the participant’s
knowledge of healthcare. Participants will be asked which type of doctor they would typically go
see for the health concerns outlines in the vignette. For example, if flu like symptoms are
identified, they would go to a primary care physician. The questionnaire will also measure the
verbal behavior of the participant by asking about their confidence level in attending a medical
appointment as well as how much they feel they are involved in the medical process. Answers
will be recorded on a one to five confidence scale; one would be the least agreement with the
statement or question and five would be the most confidence or agreement they have in the
question. Scores will be calculated out of the maximum amount of confidence in answers, a five
for all ten questions, will result in a total score of 50.
Independent Variable: The Decision Model
Once they have completed the questionnaire, participants will have access to a decision
model that will ask a series of questions and provide a referral suggestion. The decision model
itself is a computer software that includes a series of questions that can be answered through
selecting checkboxes, filling in dialogue boxes as well as selecting answers that apply. The use
of the decision model will be dependent of the participant only, research staff will not ask
additional questions or assist by providing any answers. This will ensure that all the answers
7

provided come directly from the participant and not staff. They will enter in all information
needed until the model notifies them of completion. The decision model will provide a rationale
for the given choice, however, will be used simply as a guiding tool. It will be noted that all
actual medical decisions will need the approval of an MD. After completing the model,
participants will be provided the same questionnaire they filled out prior to the model. It will be
made clear that the referral provided by the model is simply a suggestion and not a basis for
medical treatment. At the conclusion of the model use and in addition to providing a referral, the
model will provide a report of all questions asked in an easy to read format. This report will act
as a tool for the patient upon visiting the MD of choice. By outlining the symptoms, past medical
history and a more objective explanation of concerns, the model will assist in the verbal behavior
of the patient. This is primarily important for self-advocacy and a provides a more accurate
communication between the patient and physician. After a referral has been provided, the
participant will then be asked again what steps they would take and which doctor they would go
to, given the issues outlined. Baseline measures will be examined along with post-intervention
data to identify the changes and efficacy of the model.
Experimental Design
The experimental design used will be a delayed multiple baseline design and will include
a total of 3 participants. Each participant’s results will be graphed within the multiple baseline
graph and include 3 data points, one for each vignette in the baseline phase and 3 data points, one
for each vignette post-decision model as part of the intervention phase. Due to the nature of the
experiment, more data points will not be needed. The delayed multiple baseline design is used
due to the fact that all three participants will not be tested at the same time and will be accessing
the decision model as different times.

8

Results
The expected results are to guide the verbal behavior and choice making of patients
exposed to a decision model. This will be demonstrated through a change in scores on the
confidence scale pre and post usage of the decision model. In addition to the overt behavior
changes, the outcome of the health report is to strengthen the verbal repertoire of the patient and
influence self-advocacy within their own healthcare. Projected results include an increase in
scores from the tens to the forties on the graph equaling a total answer of 10-20 points up to a
total answer of 40-50 points on the confidence scale. This means the individual would increase
their knowledge when it comes to physician choice as well as adding to their verbal repertoire of
self-advocacy.
Discussion
Through the model, patients will learn to identify and properly disclose information
relating to the pain they experience along with other symptoms. As a report will be generated
upon completion, this report may be used as a guide for the physician or specialist to have a
better understanding of the current state of the patients. Often times, patients may forget to
mention certain symptoms, changes in their diet or environment or other factors. The report
provided will allow patients to have concrete data when attending an appointment with the
specialist. The report will include all the answers provided by the patient and create a guideline
for both patient and physician. This will provide the physician with an accurate description of
patient needs which will ultimately lead to better patient care overall.
Other implications of the use of the model include better systems management for
healthcare companies. This will occur inadvertently through less wait times for primary care
physicians, which means faster access to a physician when needed. In addition, due to the cut of
primary care physician appointments that simply lead to referrals, healthcare funders will benefit
9

financially as funds will not be exhausted on unnecessary appointments. This is particularly true
for HMO health plans. However, PPO health plans may also benefit as proper referrals will cut
costs of incorrect specialist visits.
Essentially, the use of such a decision model will be beneficial for all parties involved
when used appropriately and consistently. It is important to note that a disclaimer will be
provided prior to exposure to the model. This disclaimer would include the legal mandates for
health care referrals, stating that the information provided in the model should not be accepted in
the place of recommendations from a medical professional. In addition, if the user has a life-
threatening emergency, or urgent care is needed, the user will be instructed to call 911, go to the
nearest emergency room or urgent care center. For the purposes of this experiment, the medical
vignettes will surpass the necessary medical disclaimers as true medical information of the
participants will not be needed or disclosed.
The goal is to measure current knowledge and attempt to produce a software technology
that could be beneficial to the healthcare process. The software in the form of a decision model
would not only benefit the patient but would benefit the physician as well as the funding sources.
In essence a domino effect of positive outcomes could be seen through the use of a universal
healthcare tool. Within the decision model created, sections will include a full body analysis of
pain location, pain identification in the form of adjectives as well as dialogue boxes for any
additional information not already included within the model. This will ensure that all necessary
information is recorded and stored. This information will then be generated into a report
document that can be accessed and used by both the patient and physician. Although it may seem
like systems management, this tool will not be used as a crutch, but will be used to build
independence and self-advocacy.
10

As we had discussed earlier, the involvement of a patient in the treatment process is not
only helpful but it can be critical to the efficacy of said treatment. However, barriers such as a
lack of information can hinder the patient from participating fully and will hence affect the
treatment of that individual. Currently, in the beneficence model of physician say, patient do, the
connection and collaboration of the patient physician relationship is few and far in between. Yet
the very essence of the medical field is to benefit the patient, to cure or treat the patient, hence
not including the patient in that process not only leaves them out but may even affect the
diagnosis and effective treatment. If proper tools are not provided to the patient, they may often
forget to include symptoms or not be able to accurately pinpoint what they are experiencing, and
the physician may not be able to identify the root cause of the issue. It has become the norm of
physicians to simply prescribe and analyze blood samples and test results, yet the contact and
conversation with the patient has been grossly decreased. As shocking as it may seem, the
physician’s view of the patient has become the view of a human body, of the anatomical parts in
unison and not the individual they are helping. Most doctors go into the field of medicine with
the intension of helping people yet become so removed and desensitized that the person in exam
room 1 is just that: a case that needs to be handled. Yet we know from the field of psychology
and behavioral medicine that physical symptoms may appear due to emotional states. That the
mind and body are not as separate as they may seem, that in fact the two are interconnected and
interwoven in many ways. An example of this would be the physical responses one experiences
as a result of anxiety. Heart rate may increase and sweat may be produced, these symptoms could
go as far as a perfectly healthy individual fainting and losing consciousness, all due to an
emotional state. Despite this, the medical field has become a field of lab data and red blood cell
counts. So how can we change this? How can the patient become more than just a client? The
answer is simple, through more involvement. Involvement with the diagnosis, treatment plans
11

and the follow through of all prescribed. There may be many ways in which such involvement
may occur, we can ask for longer appointments and more face time with doctors, yet we know
that change is a big one and often times not manageable. Hence, the use of an antecedent strategy
can set up the patient for success. Through the thorough questioning and concrete organization of
signs and symptoms, decision models would equip patients with the tools needed to walk into a
doctor’s appointment with confidence. Walk in knowing they are a part of the solution. This not
only assists the physician but may lead to better outcomes overall. “Kanfer suggests that the
long-term effectiveness of environment– behavior relationships in modifying individual behavior
will depend on the degree to which the individual senses control over his/her behavior-change
process” (Elder 1999). This means that when the individual feels like a part of the procedure or
has a certain control over what will happen, they are more likely to be adherent to the treatment,
this means more likely to take medications on time and more likely to attend follow up
appointments prescribed. Hence, creating a more collaborative effort when addressing any given
issue and creating a better cohesion between the physician and patient and lead to better
outcomes.

12

References

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Chalfin, D. Decision Analysis Models and Simulations in Critical Care Medicine. Current
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Dennis J. Mazur. (2015). Social Pressure on Patient Decision Making through Shifting Mental
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Elwyn, G. “Developing a Quality Criteria Framework for Patient Decision Aids: Online
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Felder, S., & Mayrhofer, T. (2017). Medical Decision Making A Health Economic Primer (2nd
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Total systems engineering evaluation of invasive pediatric medical therapies conducted in non-clinical environments

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Essays in health economics and provider behavior

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A preliminary evaluation of a telehealth approach to acceptance and commitment training (ACT) for enhancing behavioral parent training (BPT) for Chinese parents

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Primary care physicians' experiences working within the patient-portal to improve the quality of patient care

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Integration of behavioral health outcomes into electric health records to improve patient care

Asset Metadata

Creator Kirakosyan, Naira (author)

Core Title Behavior analysis in medicine: a clinical decision model to support patient care

School College of Letters, Arts and Sciences

Degree Master of Science

Degree Program Applied Behavior Analysis

Publication Date 12/13/2020

Defense Date 06/19/2020

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Applied Behavior Analysis,behavior analysis,behavioral medicine,clinical decision support systems,decision models,OAI-PMH Harvest,patient referral systems,patient referrals

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Cameron, Michael (committee chair), Meyerowitz, Beth (committee member), Tarbox, Jonathan (committee member)

Creator Email nairakirakosyan95@gmail.com,nkirakos@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-404065

Unique identifier UC11667849

Identifier etd-Kirakosyan-9212.pdf (filename),usctheses-c89-404065 (legacy record id)

Legacy Identifier etd-Kirakosyan-9212.pdf

Dmrecord 404065

Document Type Thesis

Rights Kirakosyan, Naira

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA