A correlation study to determine the effect of diabetes self management on diabetes outcomes
A CORRELATION STUDY TO DETERMINE THE EFFECT OF
DIABETES SELF-MANAGEMENT ON DIABETES OUTCOMES
KURT EMANUEL NAUGLES, M.D., M.P.H.
TENNESSEE STATE UNIVERSITY
COLLEGE OF HEALTH SCIENCES
DEPARTMENT OF PUBLIC HEALTH
APRIL 1, 2013
A Correlation Study to Determine the Effect of
Diabetes Self-Management on Diabetes Outcomes
Self-Management in this paper refers to those activities people undertake in an effort to
promote health, prevent disease, limit illness, and restore well being. Several investigators
contend that self-management be made a major component of any patient health-care strategy
(Glasgow, et al., 2001; Wagner, et al., 2001). Currently, nearly 125 million Americans suffer
from chronic debilitating illnesses (Anderson, 2000). These national figures clearly underscore
the need to develop a multidimensional approach in regards to disease management.
Accordingly, measures that incorporate the patient’s perspective in managing his or her health
should be explored.
Diabetes mellitus is among those conditions suspected to be highly influenced by selfmanagement activities (Sprangers, et. al., 2000). If benefits do indeed exist, they need to be
fully evidenced. The investigation presented here sought to examine the role self management
plays in the health outcomes of individuals living with diabetes.
Medicine defines diabetes mellitus (DM) as a collection of disease processes all
characterized by a metabolic state known as hyperglycemia or elevated blood glucose levels. A
host of biochemical disturbances are known to cause hyperglycemia. However, in most cases of
DM, defects in insulin secretion and/or insulin action are considered the prime culprits in the
pathogenesis of diabetes (ADA, 2010).
The medical community also describes diabetes as a chronic, debilitating disease. It is an
incontestable fact that prolonged hyperglycemic states are associated with severe multisystem, end-organ damage, particularly of the nerves, kidneys, heart, eyes, and blood vessels
(ADA, 2010; Carver & Abrahamson, 2009; CDC, 2007). In addition to causing serious disruptions
in blood (serum) glucose levels, insulin deficiency also results in major disturbances in fat and
protein metabolism which too have devastating systemic consequences (Carver & Abrahamson,
The classic clinical presentation of DM is a patient who complains of polyuria (heavy
urine flow), polydipsia (increased frequency of urination), and/or unexplained weight loss
(McCance, et.al., 1997). Although these signs and symptoms are highly indicative of a case of
diabetes, one cannot simply make a medical analysis based on these manifestations alone. In
order to make a formal diagnosis of DM, certain clinical criteria must be met (McCance, et.al.,
A patient who presents with any one of the aforementioned classical symptoms
suggestive of diabetes along with a casual blood glucose level equal-to or greater-than 200
mg/dl (11.1 mmol/L) meets the first diagnostic criteria for DM. Casual blood glucose levels may
be interpreted as measurements taken any time of day without regard to time since last meal.
Again, the classic symptoms of DM include polyuria, polydipsia, and unexplained weight loss
(McCance, et.al., 1997).
The second diagnostic criteria for DM is any fasting plasma glucose (FPG) concentration
equal-to or greater-than 126 mg/dl (7.0 mmol/L). Fasting is clinically defined as no caloric
intake for at least 8 hours, which includes soft-drink beverages. In addition, fasting periods
must be coupled with complete smoking cessation and only mild-to-moderate physical exertion
(McCance, et.al., 1997).
The third diagnostic criteria for DM is finding a blood glucose level equal-to or greaterthan 200 mg/dl during a 2-hour oral glucose tolerance test (OGTT). The OGTT is a test
administered in the morning after an overnight fasting period of 8 to 16 hours. It is a timed
series of blood glucose measurements recorded after a patient consumes a sugar-load
equivalent to 75-grams of anhydrous glucose dissolved in water. The test takes approximately 2
hours to complete. To begin, a blood sample is taken at the start of the test, after which the
prepared sugar load is consumed by the subject. Additional samples are then taken at regular
time intervals up to two hours post sugar load consumption. Subjects with a normal sugar
metabolism will have a relatively modest rise in their blood glucose levels, whereas those with
DM or impaired glucose tolerance will have blood glucose levels equal-to or greater-than 200
mg/dl (McCance, et.al., 1997).
Again, diabetes is a complex disease that can be the result of several pathogenic
processes. Ironically, the categorization of DM into disease sub-types based on distinct
etiological pathways has only recently been adopted. In 1979, the National Diabetes Data
Group (NDDG) published the first set of DM guidelines to be widely accepted within the medical
community (NDDG, 1979). After receiving global praise and recognition, the NDDG system of
classification obtained noteworthy endorsement from the World Health Organization in 1985
(WHO, 1985). For the first time, an international standardization of DM nomenclature and
definitions was firmly established. Health practitioners could now assuredly differentiate
between the various forms of diabetes. Moreover, as the science of diabetes evolves, the
model is set-up to be regularly revisited and revised accordingly (NDDG, 1995).
The result of these advances is a greatly improved and modern system of diabetes
classification. A central framework can be quite advantageous considering that each form of
DM has its own epidemiological and clinical implications as well as preventive and management
strategies (McCance, et al., 1997). Stemming off the pioneering efforts of the NDDG, the
American Diabetes Association (ADA) currently categorizes DM into three main types: type-1,
type-2, and gestational. The majority of diabetes cases fall into either type-1 (5-10% of DM
cases) or type-2 (90-95% of DM cases) with the remaining covering only a very small percentage
of the remaining cases (ADA, 2010).
Type-1 diabetes mellitus (T1DM), once termed juvenile-type diabetes because of its
typically early-childhood onset, is an autoimmune disease of the pancreas. Progressive loss of
the gland’s exocrine beta-cell islets leads to an absolute deficiency of the sugar regulatory
hormone insulin. Consequently, those with T1DM tend to experience erratic fluctuations in
serum glucose levels, making them highly susceptible to life threatening, acute glycemic events,
such as diabetic-coma and keto-acidosis. T1DM is also frequently referred to as insulindependent diabetes mellitus (IDDM) because it requires lifetime exogenous insulin for survival.
To date, the treatment standard for insulin replacement therapy involves the multi-daily
administration of measured needle-injections (ADA, 2010; Carver & Abrahamson, 2009; CDC,
Type-2 diabetes mellitus (T2DM) is primarily due to a partial insulin deficiency and/or a
state of increased insulin resistance (Carver & Abrahamson, 2009). It is frequently diagnosed in
obese patients. Unlike T1DM, T2DM is usually late in onset, occurring primarily in early to late
adulthood, though it is becoming increasingly more common in teenagers and adolescents
(ADA, 2000; NHLBI, 1998). In addition, T2DM typically does not require insulin replacement
therapy like T1DM. Many T2DM patients can be successfully managed with a regiment of
physical exercise and strict diet. In certain cases where these strategies are ineffective or
impractical, oral glucose lowering drugs may be warranted. As a last measure, especially in
those difficult cases of increased-insulin deficiency, resistance, or rapid disease progression,
insulin replacement therapy is introduced (Carver & Abrahamson, 2009).
Gestational diabetes is another type of DM, which as its name suggest, only occurs
during pregnancy. This form of DM develops when a women’s body does not produce adequate
amounts of insulin to manage the increased blood sugar load experienced during pregnancy
(Berg, 2000). Generally, gestational diabetes is a temporary condition and is typically wellmanaged with a combination of proper diet and regular exercise. However, in some cases,
insulin therapy to control rising serum glucose concentrations is necessary, as oral glycemic
drugs are contra-indicated (Rosenn, 2009). Remarkably, expecting mothers diagnosed with
gestational diabetes are more likely to require delivery by cesarean section because their
infants are often too large for natural birth. In addition, nearly 60% of expecting mothers with
gestational diabetes are at a markedly increased risk of developing T2DM later in life (Berg,
2000). Other forms of DM are the result of, but not limited to: adverse conditions of the
pancreas, medication side-effects, or genetic defects (CDC, 2007; Carver & Abrahamson, 2009).
The number of patients with diabetes mellitus is increasing rapidly across America,
making it among the most challenging public health issues the nation faces. The threat DM
imposes on society in terms of its incidence and prevalence, morbidity and mortality, as well as
economic and emotional toll, is quite astounding (ADA, 2010; CDC, 2007; CDC, 2011; Fowler,
2008; NHLBI, 1998). Only after careful examination of the epidemiology of diabetes does one
truly begin to realize how menacing a public health issue it has become.
In terms of mortality, diabetes mellitus ranks as the 7th leading cause of death in the
United States (CDC, 2007). Roughly 26 million Americans, about 8.3% of the entire U.S
population, have been diagnosed with diabetes mellitus (CDC, 2011). In addition, national
figures continually demonstrate an alarming uptick in the DM incidence rate over the past few
decades. The CDC recently reported nearly three million new cases since 2009 (CDC, 2011).
Notably, it has long been recognized that obesity is associated with increased risk of T2DM.
With more U.S. teenagers and adolescents being clinically diagnosed as obese, a national rise in
diabetes cases shouldn’t seem all that surprising (NHLBI, 1998). Moreover, 79 million additional
Americans would demonstrate impaired glucose tolerance if they were tested. These
individuals are often considered “pre-diabetic” because they have a significantly increased risk
of developing overt diabetes (CDC, 2011).
As previously stated, DM is a chronic debilitating illness - a disease characterized by
long-term complications and significant morbidity. Extensive vascular injury is the major reason
for DM’s often crippling nature. Diabetic patients suffer largely from two types of lifethreatening vascular insults: micro-vascular (i.e., diabetic neuropathy, retinopathy, and
nephropathy) and macro-vascular (i.e., stroke, peripheral vascular disease, and coronary artery
disease) (ADA, 2010).
Diabetic retinopathy is the most common micro-vascular complication associated with
DM. It is also the leading cause of blindness in the U.S. (Fowler, 2008). Diabetic nephropathy is
another frequent micro-vascular related event. It is the leading cause of end stage renal disease
as well as the top reason for lifelong dialysis treatment in the U.S. (Fowler, 2008). The
occurrence of peripheral and central neuropathy is also very common among diabetics.
Approximately 70% of DM patients will exhibit some form of mild to severe neural damage
manifested by impaired pain perception, tingling or burning sensation in the feet, erectile
dysfunction as well as other types of nervous system disorders (Fowler, 2008).
A leading macro-vascular related-event found among diabetics is peripheral vascular
disease. Poor circulation as a result of damaged and narrowed blood vessels (i.e., arteries,
veins, and capillaries) is commonplace. Without adequate vascular flow, cellular tissue cannot
extract oxygen and nutrients from the bloodstream. Consequently, the risk of ischemic events is
drastically heightened (Hiatt, 2001). Major organ infarctions, as in the case of a heart attack or
a brain stroke, can occur (Wingard & Barrett-Connor, 1995).
The combination of both micro-vascular and macro-vascular impairment can be quite
devastating in a DM patient. Far too often a grim clinical scenario plays out in this population
group (Gibbons, 1987). First of all, peripheral vascular disease can impede blood flow to the
point at which epidermal (skin) necrosis and ulceration develops. Secondly, peripheral
neuropathy can significantly compromise neural activity, effectively reducing cutaneous (skin)
perception of pain. As a result, diabetics who develop minor skin lesions are at increased risk of
gross tissue destruction due to a repeated damage of a primary injury. In the case of a distal
extremity, recurring skin insults can become infected and eventually gangrenous, often
necessitating a partial or complete limb amputation (Singh, et al., 2005; Gibbons, 1987). More
than 60% of all non-traumatic lower limb losses occur in patients suffering from chronic
diabetes (CDC, 2007; Fowell, 2008).
Besides the pathogenic course diabetes takes, it also exacts a massive financial toll on
society. The growing prevalence of DM in the U.S. could theoretically burden the national
budget to the point of endangering economic stability. In 2007, the total estimated dollars
spent managing diabetes and its complications (direct and indirect) were $174 billion (ADA,
2007; CDC, 2007). Treatment and hospitalizations accounted for nearly $116 billion in direct
cost. Disability/Worker’s compensation, productivity loss, and premature mortality accounted
for nearly another $58 billion in indirect cost (ADA, 2011).
Again, the epidemiology of diabetes is quite staggering in America. It is unquestionably a
disease reaching near endemic proportions, resulting in enormous morbidity and mortality,
while simultaneously inflicting severe economic wounds. Although the future outlook might
appear grim, studies do suggest that effective diabetes control can be achieved. Reaching this
goal will require a judicious national strategy (ADA, 2010; Funnell, Tang, & Anderson, 2007;
Funnell et al., 2009; Siminerio, 2009).
Current diabetes management schedules focus on keeping serum glucose
concentrations below hyperglycemic levels (>126 mg/dl or >7 mmol/l) as much as possible
(McCance, et.al., 1997). Avoiding prolonged hyperglycemic states has proven to avert
subsequent diabetic complications (Goldstein, et al., 2004). This starts with routine blood
glucose monitoring, and ends in both conventional and alternative therapeutic strategies.
Self-monitoring of blood glucose (SMBG) is a valuable tool in diabetes care. With a small
finger-prick and a minuscule amount of blood, diabetics can determine their own blood glucose
concentration at any time. This allows patients to link lifestyle and behavior to actual glycemic
numbers. Since the advent of SMBG, the task of daily diabetes management has increasingly
fallen into the hands of the patient and less on providers. This simply test has single handedly
revolutionized the practice of diabetes self-maintenance making it an invaluable DM
management tool. Although SMBG will continue to be at the forefront of the battle against DM,
other efficacious modalities have also emerged (Welschen L. et al., 2005).
Important changes in diabetes care occurred in the 1980s with arrival of a new
diagnostic technique. Based on the research findings of major diabetes investigators and the
support of organizations like the American Diabetes Association, glycosolated hemoglobin
(HbA1C) testing emerged as a new means of evaluating DM/ glycemic control over an extended
time frame (ADA, 2007; Funnell, et al., 2009; Siminerio, 2009; Carver & Abrahamson, 2009).
Since then it has been universally accepted as the gold-standard in overall DM assessment
HbA1C is the molecular by-product of the slow, irreversible reaction between glucose
and hemoglobin molecules within red blood cells (RBCs). Its percent measurement is indicative
of an individual’s average blood glucose concentration over the preceding 90 days – the natural
life-span of RBCs (Goldstein et al., 2004). The HbA1C assay therefore provides a reliable
measure of a subject’s long-term glycemic control without the need for repeated FPG testing or
routine OGTTs (Buell, et al., 2007). In addition, it correlates well with the risk of long-term
diabetes complications and mortality (Khaw, et al., 2004; UKPDS, 1998; Klein, et al., 1994).
Reduction in HbA1C values by just 1% has proven to reduce diabetic complications by as much
as 25% (UKPDS, 1998). Moreover, an increase in HbA1C levels by just 1 percentage point
reportedly doubles an individual’s risk of diabetic retinopathy (Klein, et al., 1994). Accordingly
the ADA has established national HbA1C interpretation standards. Guidelines suggest HbA1C
levels to be less than 6.5% in order to presume satisfactory glycemic control (ADA, 2007). As a
result of its accuracy and predictability, HbA1C measurements have emerged as the preferred
method for assessing disease status in diabetics (ADA, 2007).
Despite the many clinical advances in glycemic assessment, diabetes mellitus still
remains a very complicated disease process to control (Gill & Huddle, 1989; Patrick, et al.,
1994). Routine SMBG, FPG, OGGT, and HbA1C checks are just a few of the many measures
employed in the management of DM. Diabetics are now increasingly asked to take-up a more
active role in glycemic maintenance. Today’s challenge calls for a willingness of patients to set
and meet their own diabetes self-care goals. This includes persons living with diabetes making
the difficult decisions regarding lifestyle modification. Cumulatively, this is referred to as the
practice of diabetes self-management (Clement, 1995).
Diabetes self-management is a combination of patient-centered, goal-oriented activities
employed primarily by the patient to foster glycemic control. Strategies common to diabetes
self-management include rigorous medication compliance, frequent clinical visits, routine
blood-glucose self checks, proper dieting, regular exercise, scrupulous foot care, and systematic
disease monitoring (Funnell et al., 2009; Siminerio, 2009). These tasks can be quite demanding
and require hard work, perseverance, commitment, self-discipline, and above all reliance on
self in performing these duties successfully (Funnell et al., 2009).
In devising a diabetes self-management plan, the concept "one size fits all" would not
apply because each patient’s therapeutic course is uniquely different. However, although a
single “cookie cutter” approach is not recommended; basic principles can still be used to guide
the development of a distinct, yet effective, diabetes control strategy. To assist health care
providers and patients in constructing tailored strategies, experts in diabetes care have
partnered to devise a series of Diabetes Self Management Education (DSME) modules (Funnell
et al., 2009).
DSME programs map out a set of standard activities necessary to facilitate the skills,
knowledge, ability, and resolve necessary for adept diabetes self-management. Every five years,
an interdisciplinary task force of health providers (e.g., doctors, nurses, pharmacists, dieticians,)
meets to consider and make changes in these DSME guidelines. This collaborative work is
termed The National Standards of DSME (Funnell et al., 2009). No one basic theme best
describes the focus of The National Standards of DSME but an objective-emphasized, patientcentered, culturally-sensitive, group-based, age-specific, and lifestyle-behavior oriented
approach make-up the guiding principles (Funnell, Tang & Anderson, 2007; Funnell et al., 2009).
Although a patient’s DSME plan may depend primarily on his/her glycemic state, it will
also rely heavily upon individual’s socio-economic factors (Funnell et al., 2009; de Weerdt, et
al., 1989). Not only must the needs, wants, objectives, and experiences of the diabetic patient
be taken into account, the DSME strategy is also contingent on the dynamic interactions of
numerous social and economic factors. Accordingly as environmental conditions change and
evolve, a diabetic’s self-management goals will inevitably need to be adjusted to reflect life
changes. Hence, an adequate DSME program weighs such factors like health care resource,
financial status, and social support before tailoring a plan to a patient’s unique health needs
(Funnell et al., 2009).
As noted, social support is major socio-economic factor that is considered before
constructing a suitable DSME plan. Social support can influence an individual’s perceived ability
in carrying out self-care goals (van der Bijl, et al., 1999). Social networks have proven invaluable
in helping patients craft problem-solving strategies. In addition, social systems are important in
helping individuals make behavioral and lifestyle changes. Social support is therefore essential
to the efforts made by patients involved in DSME programs who are hoping to achieve diabetes
self-care (Funnell, Tang & Anderson, 2007; Funnell et al., 2009). Co-morbid conditions, like
depression, can create considerable barriers to successful diabetes self-care (McKellar,
Humphreys & Peitte; 2004; Peyrot et al., 2006). The presence of social support, however, has
been shown to improve diabetes self-care and control in patients under psychological stress
(Tang et al., 2008).
The impact DSME has on diabetes health outcome could be quite significant (van der
Bijl, et al., 1999). Based on the Social Cognitive Theory (SCT), particularly the construct of SelfEfficacy, an interdependent relationship between self-management and glycemic control is
theoretically supported. Dr. Albert Bandura, a prominent behavioral psychologist who worked
in the field of human learning and development, believed that self-efficacy was a central
construct of the SCT. His studies examined the role of self-efficacy in the development of
personality. According to Bandura, self-efficacy can be defined as "the belief in one’s capacity
to organize and execute the courses of action required to manage prospective situations"
(Bandura, 1977). Behavior, in other words, depends highly on one’s perceived ability to
perform a particular task. He also asserted that behavior was deeply rooted in observational
learning and social experience. In large, the SCT takes into account the external social and
physical structures as well as the internal cognitive processes which collectively influence
behavior (Bandura, 1977, 1986, 1997). It seems only fitting that the practice of self-efficacy and
the art of self-care be interlinked.
Diabetes self-management is a demanding and multifaceted task. To optimize diabetes
outcomes, the individual must possess the ability to acquire knowledge, demonstrate cognition,
and perform specific tasks (ADA, 2010; Toobert, Glasgow, & Hampson, 1996). These are the
key requirements needed for information acquisition, self assessment, problem solving,
informed decision making, and appropriate psychomotor action (Orem, 1995). In addition,
based on the Bandura’s principle of self-efficacy, belief in one’s ability to perform a prescribed
set of tasks would also be fundamental (Bandura, 1977, 1986, 1997). Furthermore, it might also
be said as one’s knowledge, cognition, and skill set increases, so does one’s self efficacy, and
vice versa – a type of reciprocal determinism (Bandura, 1997). Ultimately, if the framework
holds true, as diabetes self-care improves, the prospect of glycemic control becomes more
realistic and the threat of diabetes complications less pronounced (DCCTRG, 1993; UKPDS,
Accordingly, certain features of Bandura’s work can theoretically be applied to the
advancement of DSME. It is one thing for a diabetic to create reasonable goals, but quite
another to actually see them through. For many this could be a virtual feat in and of itself.
Putting plans into action definitely would require a significant challenge of “self.” Accordingly,
widespread adoption of the self-efficacy model could play a revolutionary role in how diabetes
control and management strategies are approached.
Generally, the majority of DM investigational studies have remained unchanged over
the past few decades; being predominantly descriptive, correlational, or predictive in nature.
Some mainly focused on the profile of the DM patient in terms of the diabetic complications
(Fowler, 2008; Singh, et al., 2005; Gibbons, 1987). Others have centered on highlighting the
unique relationship between diabetes and obesity (Resnick, et al., 2000). And then there are
those that sought to further underscore the correlation between cardiac disease and diabetes
(Wingard & Barrett-Connor, 1995; Laing, et al., 2003). Conversely, studies which seek to assess
correlations between the social determinants and diabetes are seemingly less common. In
particular those that examine health education and its impact on glycemic outcomes are
lacking. These types of studies must be conducted if a broad diabetes control agenda is to be
successful. It is the responsibility of health-care advocates to ensure that a comprehensive
approach to diabetes management is pursued. (ADA, 2010; Funnell et al., 2009; Siminerio,
2009). Clinical sites, like Watts Primary Care (WPC), are among the many that are actively
seeking to explore this connection in an effort to improve diabetes health outcomes.
Watts Primary Care (WPC) is a for-profit, private medical practice established in 2005
specializing in Primary Care Medicine. The practice is located at 2001 Charlotte Avenue, Suite
101, Nashville, Tennessee 37203. Situated in the West End district, it is just minutes away from
downtown Nashville. It is also very close to two of the largest hospital systems in the city,
Baptist Hospital and Centennial Medical Center. The office is open Monday through Friday
from 8:00 a.m. to 5:00 p.m. Patients are mainly seen by appointment unless there is a medical
emergency. It has a modern office set-up and centralized billing system.
WPC is committed to providing high-quality health care in the most professional, timely,
and effective manner. Besides having tremendous appreciation for the science of medicine, the
clinic also strives to incorporate human care and compassion into its clinical practice, offering a
holistic approach to patient management. Wellness and prevention make up the cornerstone
of the Watts Primary Care mission. As stated in their published materials:
“Our primary mission is to provide excellent health care to the residents of the Greater
Nashville community. We believe health first begins by empowering patients with the
knowledge, skills, and support needed to live healthy lifestyles. For this, we are committed to
providing quality services for the timely assessment of both acute and chronic illnesses with the
primary goal of early prevention and effective treatment. Above all, we take pride in
considering the whole patient in determining health needs.”
Accordingly, care at WPC begins with communication, allowing sufficient time
for satisfactory provider-patient interaction. The practice is guided by the core principle that
care must be both effective and efficient, so that early detection and management of medical
problems is possible. A balanced and comprehensive approach is emphasized with the primary
goal of prevention. Averting the debilitating complications of diseases like diabetes, heart
disease, stroke, and cancer is paramount to the practice.
Watts Primary Care has two medical doctors on staff, Dr. Eli Watts and Dr. Kenneth
Williams. They are American Board-Certified in Internal Medicine and Family Medicine,
respectively. Each is licensed by the state of Tennessee to practice medicine. Most major office
decisions are made with the mutual approval of both practicing physicians. In addition, the
medical practice has on staff six additional employees. Although certain mandatory duties are
required by all staff members to execute, like the practice of infection control and
environmental safety, each staff member is charged with separate and unique responsibilities.
Below is a brief summarization of each employee’s job description.
WPC has on staff both a medical receptionist (MR) and a medical clerk (MC). These are
the only two non-licensed positions held in the office. The MR primarily provides front desk
secretarial support. Responsibilities include: answering telephone calls, managing patient
check-ins and outs, monitoring patient flow, scheduling follow-up appointments and
procedures, sorting incoming mail, and ordering office supplies. When needed, the MC is also
there to provide assistance to the MR. Other duties of the MC include record filing, copying and
scanning documents, maintaining and retrieving patient records, preparing patient files, and
forwarding information to other sites (via email, fax, and/or post).
Three licensed medical assistants (MAs) make up the core of the WPC health-care
support team. All MAs hold professional certification in the state of Tennessee. In addition,
MAs work under the supervision of Dr. Watts and Dr. Williams. Their role is to assist the two
physicians in meeting the health needs of the patients under WPC care. Some of the typical
duties of the MAs include: escorting patients to and from exam rooms, checking vital signs,
performing basic physical examinations, drawing blood samples, assisting in drug injections and
immunizations, administering medications, and preparing charts. The MAs also assist in
specialized procedures, such as Diabetic Wound Debridement, as well as provide ancillary
services, like educating diabetic patients on proper insulin injection.
The primary hospital affiliations WPC maintains are with Baptist Hospital, TriStar
Centennial Medical Center, and TriStar Skyline Medical Center. These are three of the major
health-care facilities located in the city of Nashville. Affiliations with these hospitals are
essential to WPC. Patients requiring more complex medical services are referred to these
facilities. A summary profile of each hospital is provided here.
Baptist Hospital is the largest non-profit community hospital in Middle Tennessee,
licensed for 683 acute and rehab care beds. The hospital has serviced the health care needs of
metropolitan Nashville and Middle Tennessee for over 90 years. The primary address is 2000
Church Street Nashville, Tennessee 37236. The main campus covers nearly 2 million square feet
and spans more than six city blocks, or 38 acres. Founded as a faith-based health ministry,
Baptist Hospital operates with the commitment of “serving all persons with special attention to
those who are poor and vulnerable.” In 2002, Baptist Hospital joined the Saint Thomas Health’s
regional health system which consists of five hospitals – Baptist and Saint Thomas Hospitals and
The Hospital for Spinal Surgery in Nashville, Middle Tennessee Medical Center in Murfreesboro
and Hickman Community Hospital in Centerville. Baptist hospital provides a full range of
specialized health-care services – i.e., cardiology and cardiac surgery, neurology, oncology,
ophthalmology, orthopedics, and organ transplantation (Baptist Hospital, 2012).
Centennial Medical Center also serves the metropolitan Nashville community. It is the
largest for-profit hospital in Middle Tennessee. The hospital is the flagship health-care facility of
Hospital Corporation of America (HCA) and is part of the TriStar Health-Care System. Centennial
Medical Center has provided quality health-care services to the residents of Nashville and the
Middle Tennessee region for 44 years. The main campus can be found at 2300 Patterson Street,
Nashville, TN 37203. The facility houses 657 hospital beds, and offers a wide range of medical,
surgical, and behavioral health programs. Along with 24-hour emergency room services, the
campus provides heart and vascular, imaging, neurosciences, oncology, orthopedics, pediatrics,
rehabilitation, sleep disorder, and women’s services. An affiliate of TriStar Health, Centennial
Medical Center is home to some of the most advanced health care facilities in the region. These
include the TriStar Sarah Cannon Cancer Center, TriStar Centennial Women’s & Children’s,
TriStar Centennial Heart & Vascular Center and TriStar Centennial Parthenon Pavilion (TriStar
Skyline Medical Center, also a member of TriStar Health, is recognized as the premier
regional medical center serving patients throughout northern middle Tennessee and southern
Kentucky. Located at 3441 Dickerson Pike, Nashville, TN 37207, Skyline houses a total of 467
beds. Skyline’s primary mission is to “provide patients with the highest quality and most
technologically advanced care” medicine has to offer. Although Skyline Medical Center is
considered a general medical and surgical facility, it has earned numerous honors and
distinctions since its founding. Skyline was named in “the top 10% of HCA hospitals nationwide
for best overall patient satisfaction,” and received the “Best Acute Care Hospital” award. In
addition, it is has acquired accreditation by several health-care organizations - the Commission
on Accreditation of Rehabilitation Facilities, the American College of Surgeon's Commission on
Cancer, and the Society for Chest Pain Physicians and Providers just to name a few.
Furthermore, Centennial was the first Tennessee hospital to earn "Primary Stroke Center
Certification" (TriStar Skyline, 2012).
Dr. Eli Watts, the founder and proprietor of WPC, received his medical degree from
Meharry Medical College in Nashville, Tennessee in 1999. Following medical school, he
completed a three year residency program in Internal Medicine at the UCLA- Charles R. Drew
University of Medicine and Science in Los Angeles, California. Upon completion of his residency
training, Dr. Watts accepted a specialty fellowship at Vanderbilt Medical Center. After careful
consideration of his next career move, he decided to stay in the Nashville area and start Watts
Primary Care. Along with serving the patients in his medical practice, Dr. Watts serves as a
medical consultant and academic advisor to his alma mater, Meharry Medical College. In
addition, Dr. Watts regularly gives back to the Nashville community, taking time to make on-site
visits to local health centers where he consults on difficult cases.
Dr. Watts works predominantly out of WPC, seeing approximately 130 patients per
week in his practice. His clinic focuses primarily on providing primary care - Family Medicine,
General Internal Medicine, Geriatric, Environmental, Occupational, and Preventative Medicine,
and Gynecology with the exception of Obstetrics. On occasion Dr. Watts will see patients in the
hospital setting. Patients are usually admitted or transferred to one of WPC’s affiliates, namely
Baptist, Centennial, or Skyline. He generally has 2-3 patients in hospital admission solely under
his care and another 2-3 patients under referred care per week. He makes 4-5 house-calls per
week - mostly at nursing home sites and hospices. Dr. Watt’s schedule varies considerably from
week to week. His schedule is contingent on the time of year as well as the medical needs of
The patients Dr. Watts encounters in the clinical setting, admits into hospital care, or
provides medical consultation for present with a variety of medical conditions. Trained in
primary care, many of Dr. Watts’ patients are diabetic. As a result of his training and frequency
of contact with diabetic patients, Dr. Watts is very knowledgeable of diabetic care and
management. Besides in-patient and out-patient care, Dr. Watts is also committed to an
emergency call schedule at the hospitals he has privileges with. While “on call” Dr. Watts is
required to serve patients in hospitals when paged by medical services. Dr. Watts’ evening call
schedule is one in every five week nights and one in five weekends.
While working at WPC, I was specifically charged with the task of assisting the physician
and nurses in performing their regular medical duties. When assigned to a case, I would
regularly take the patient’s history of present illness or chief complaint, and conduct basic
physical examinations. Accordingly, I was responsible for completing a detailed SOAP note for
each encounter and based on my clinical findings, share that information with the appropriate
medical staff. A SOAP note is a medical report employed by physicians and other medical
providers (nurse, psychologist) in the health care field to record a general synopsis of the
patient’s current presentation and subsequent medical management. SOAP is an acronym for
subjective, objective, assessment, and plan.
S = Subjective data; Statements patient makes about medical problem or course of
treatment (history). Could also be information gathered from family or friend.
O= Objective data; Gathered by observation of patients clinical presentation (physical
examination). This also includes laboratory data.
A = Analysis (or assessment); Based on the information obtained from Subjective &
Objective inquiry. This can indicate progression, regression, or no change in patient’s
condition related to medical issue.
P = Plan or Treatment; Based on the Assessment. New treatment plan is either
initialized or old plan is maintained as is, updated, or suspended.
While interning at WPC, I had access to medical instrumentation used to perform
physical examinations; otoscope, opthlamoscope, stethoscope, blood pressure cuffs, etc... I also
was privy to confidential information which included laboratory data like serum HbA1C values.
Based on my clinical findings, I was allowed the opportunity to make recommendations to the
two physicians I shadowed, which they would possibly incorporate in their medical decision
making process. Periodic evaluations, both verbal and written, were used to assess my degree
of progress pertaining to my job performance.
WPC is deeply committed to quality improvement. Along with staying current on major
advances in the field of Medical Technology, WPC constantly seeks improvement in the
burgeoning field of Medical Information Technology (MIT). As WPC continues to expand it
patient roster, regular MIT upgrades have become a necessary asset to ensure high quality
patient care. WPC just recently began transitioning to full use of Electronic Medical Records
(EMRs). They have invested in an EMR program called eClinicalWorks (ECW). Besides the
potential financial benefits, increased productivity and reduced medical errors were also major
driving forces behind the shift. Most notably, the system is Health Insurance Portability and
Accountability Act of 1996 compliant (Health Information & Privacy, 2012).
In addition to being web-enabled, ECW is readily compatible with a host of electronic
devices ranging from laptops, smart-phones, personal digital assistants (PDAs), handhelds
tablets, and desktop computers. Medical staff can access patient records from any clinical or
office room, and providers can securely review files from distant-sites with internet service. Key
attributes that the system possesses include real-time alerts for adverse drug-drug interactions
and known drug allergies, as well as other notifications based on the patient’s EMRs.
The ability to capture information electronically is also a central feature of the ECW
system WPC is using. The recording of clinical encounters in digital format is now possible, such
as History of Present Illness, Review of Systems, Physical Exams, and SOAP notes (Subjective,
Objective, Assessment, and Plan). Furthermore, the system allows for the sharing of encrypted
information as well as secure EMR integration with other affiliates (other practices, pharmacies,
insurance companies, and hospital systems.
Watts Primary Care can now generate and maintain entire patient’s medical records in
house. Medical billing can be tracked electronically, as well as insurance claims processed
instantaneously. Web-based portals hosted by ECW allow patients to register on-line, view and
update their information as needed, reschedule and check appointments, request prescription
refills, and view laboratory reports. Using ECW, staff members can determine exactly how many
phone calls, emails, prescription refills and lab reports were handled on any given day or time
Besides general reports, EMRs are also used in disease management strategies. WPC
has already employed EMRs as a tool in evaluating the relationship between disease outcome
and demographic/socioeconomic variables. For example, EMRs can follow HbA1C values over
time and provide a realistic assessment of a patient’s diabetic status. Correlation tests can then
be performed to determine if glycemic status has a significant relationship with variety of
factors believed to influence health.
In addition to the improvements in MIT, Watts Primary Care provides a full range of
medical care services. WPC is a primary care practice, so it prefers its patients contact the office
first before seeking Emergency Room care or self-referring to a medical specialist. Encouraging
patients to contact WPC first ensures greater continuity of care. Along with general medical
services like routine physical examinations and pap smears, WPC offers specialized services
such as on-site Diabetes Self Management Education consultations.
Diabetes self-management accounts for a major part of WPC’s diabetes control strategy.
WPC believes that the diabetic patient is largely responsible for much of the day-to-day
activities impacting glycemic control. Undoubtedly WPC health care providers play a major
preventative role, but in the end, the bulk of the responsibility falls on the WPC patients living
A major goal of WPC is to provide the information and training DM patients need to
successfully control their diabetes. DSME programs conducted in-house could provide an
excellent means of promoting these skills. Such educational activities possess the potential to
effectively avert diabetic complications. In this environment, a patient-centered,
multidisciplinary team approach can be pursued.
For most WPC patients with diabetes the clinical setting is where they receive the bulk
of their diabetes care. Based on office records nearly 90% of all WPC patients receive
professional diabetes care strictly from WPC and DM cases account for nearly 10% of all WPC
patient visits in a typical day. One might ask, “Can a routine doctor’s appointment fit in a
comprehensive and effective diabetes control effort?” Overall most patient-encounters at WPC
last 10-15 minutes, while on average, the time a diabetic patient spends with a WPC primary
care provider is around 16 minutes. In general, most clinical visits will consist of a basic history
of the present illness, physical examination, review of systems, clinical assessment, and
treatment plan. A diabetic case, however, might also include diet or nutritional counseling,
physical exercise advisement, as well as weight-reduction recommendations.
When faced with a DM case, WPC primary care physicians typically focus on the
identification of any acute and chronic hyperglycemic complications. The promotion of specific
DM self-care strategies is usually not possible, a direct consequence of the inherent time
limitations occurring in the primary care setting. Considering the numerous health demands
that burden the average diabetic, it seems plausible that many diabetic patients may not be
receiving adequate DM education and training. Acquiring the skill set needed for effective
diabetes self-care is a complex and lengthy process, involving the development of both
problem-solving skills (e.g., maintaining a nutritional, well-balanced diet on a tight budget) and
technical skills (e.g., performing accurate blood glucose testing or proper medication
administration). Clearly addressing these issues would present the average clinic with major
challenges. Under such circumstances, any health-care organization would undoubtedly benefit
from a well staffed DSME program.
Hosting a DSME program was seen as a means of improving quality of care at the WPC
practice. The DSME initiative began first by recruiting a Certified Diabetes Educator (CDE). A
CDE is a health professional certified by the American Association of Diabetes Educators (AADE)
who teaches self-management techniques to patients diagnosed with diabetes (AADE, 2000). In
the summer of 2012, a decision was made by the two primary care physicians, along with the
recommendations of supporting office personnel, to hire a CDE. During these meetings the
frequency of the CDE’s attendance, which patients would be seen, how visits would be
scheduled, and where the CDE would provide education services and store supplies were
WPC conducts the DSME program once every 2 weeks on Friday. The program lasts the
entire work day (i.e., 8-hours). Many of the related activities occur on-site, but off-site sessions
are also held. As part of the WPC internship, I was charged with the duty of informing patients
diagnosed with DM about the DSME program. The conversation typically began by first
describing what DSME entailed and then outlining the general goals of the DSME program,
which included helping diabetics acquire the knowledge, information, self-management
practices, coping skills, and attitudes required for effective diabetes self-management. These
discussions were then followed by informing the patient that a CDE was now a part of the WPC
team and that it may be to their benefit to make an appointment see the specialist in the office
for diabetes-related education and counseling services.
In addition to the initial clinical work-up, I was sometimes granted permission by the
patient to observe and assist the CDE in consultation. A typical first visit started with an
introduction and description of the role of the CDE. Patients were then asked “What they
expected or hoped to gain from the encounter?” An overview of the patient’s past medical
history was performed, along with a general assessment of their health knowledge. DM related
lifestyle and behavioral information was also recorded by the CDE. Patients' use of a blood
glucose meter, insulin preparation, injection technique, and other skills were also determined
as part of the initial evaluation. Individual assessments of each patient’s nutritional and physical
needs were also performed.
Research demonstrates that diabetes patients can benefit from dietary education.
Before beginning nutritional education, the patient’s perception of diabetes and diet was
assessed. Dietary status is typically measured by the CDE using the Mini Nutritional Assessment
survey (Guigoz, et al., 1994), but other modalities were also employed. In addition, an account
of each patient’s food preferences, resources, and meal preparation techniques was taken.
Potential barriers to adequate nutrition were also noted, including feeding difficulties like poor
dentition & gastrointestinal disorders, as well as socio-economic issues, like food accessibility
and availability. A nutritional plan was later fashioned based on each patient’s needs, concerns,
and resources. The overall intent of the diet plan was to improve diabetes outcomes and
enhance quality of life.
An exercise plan was also developed for each DM patient. Based on clinical experience
and close observation during this internship, diabetes patients tended to present with
significant physical de-conditioning or deterioration in motor skills. This could very well have
been the product of diabetes co-morbidities like obesity, acute infections, debilitating illnesses,
chronic pain, and physical injuries. Before proceeding further, these factors were identified and
properly addressed. After a thorough evaluation of the patient’s current functional status, a
tentative exercise schedule was drawn-up. This plan was tailored to each patient’s needs and
environmental constraints. Routine physical activity has been shown to reduce serum glucose
and cholesterol, improve blood pressure, as well as increase muscle strength and coordination,
cardiovascular function, pulmonary capacity, and overall quality of life (Beard, et al., 1996;
Clanton, et al., 1987; Hiatt, 1990; Pescatello, 2004; Tyni-Lenne, 1998). Providing patients with
an exercise schedule was therefore a major part of the CDE’s plan to improve patient quality of
A discussion regarding patient preferences with respect to diabetes self-care was also
normally included as part of the CDE consultation session. DSME plans that included individual
preferences offered the benefit of increased patient compliance and satisfaction, as well as
improved diabetes outcomes. In addition, some patients needed further adjustment to their
DSME plans due to physical, mental, psychological, social, and financial challenges that may
have been overlooked while the initial plan was developed.
After a complete DSME profile was developed, the CDE’s recommendations were then
discussed with each patient. Patients were given time to consider what the CDE had suggested.
While deliberating, it was customary for patients to think about those skills, behaviors,
problems, and/or goals that they wanted most to focus on. Customarily patients would relay
their wishes and desires to the CDE and revisions would be made. Only after an acceptable
course of action had been agreed upon by both the patient and CDE, did a final plan emerge.
Before ending consultation sessions, each patient was asked to complete a goal worksheet that
would later be used to assess their progress during the next visit.
At WPC, visits with the CDE usually lasted 45 minutes. Follow-up visits took 15-30
minutes. Attempts were made to stay within the recommended time frames. This was done
mainly to ensure that diabetic patients maintained their strict activity schedules. Many diabetic
patients must maintain a rigorous activity schedule to avoid acute glycemic events associated
with delayed meal, insulin administration, and oral-drug intake times. At the end of each
encounter with the CDE, the patient and CDE would plan follow-up visits, if warranted. Most
patients chose to return for counseling 2–4 times per year. A few patients insisted on returning
monthly or according to some other regularly scheduled time for additional support.
In addition, the CDE sometimes chose to conduct peer group sessions during non-office
hours at pre-arranged locations, such as community centers, senior living homes, and churches.
Patients who participated in these group meetings were afforded the opportunity to exchange
diabetes-related information, share coping strategies, and set up social support networks. The
sessions were usually peer-directed, but professionally moderated by the CDE, giving patients
the freedom to interact with one another in a safe, supportive environment. Group members
were strongly encouraged to highlight both their successes and failures with their day-to-day
DM self-care activities as both surmount to lessons learned.
Based on my observations, the primary care clinic appears to be an ideal setting for a
DSME program. Working within the primary care office allows the CDE to access patient
medical records, which can help tailor education to patient's medical needs. Diagnostic tests
such as serial HbA1C results can be translated into real-time data for illustration and analysis
during DSME sessions. In addition, there are other potential advantages to providing DSME
programs at primary care sites. Patients' diabetes education charts can be kept at the office for
safe guarding of confidential information, as well as for instant access and review by medical
staff. Moreover, patient education needs and concerns can be directly communicated to other
DSME team members.
Living and coping with diabetes can be difficult. DSME gives patients the skills and
confidence needed to manage their diabetes. DSME programs are an excellent means of
promoting diabetes knowledge and awareness. They can also be helpful in providing diabetes
social support which can in turn enhance diabetes self-management behaviors thereby
influencing diabetes outcomes. Social support presumably acts by imparting psychological,
social, and physical protection (WHO, 1998). Providers, the health-care system, the community,
friends, and family all contribute to a patient’s social support structure. A CDE, in particular,
acts as an educator, motivator, and manager, just to name a few. This type of support can
definitely help patients in meeting health goals and objectives.
Although each DM clinical picture is unique, generally speaking, a DSME encounter aims
to promote key aspects of the diabetes self-management strategy; dieting, physical activity,
blood glucose monitoring, medication compliance, lifestyle change, healthy behavior, and
problem solving skills. Ultimately, the goal is to optimize glycemic control and quality of life and
to prevent acute and chronic DM complications. A case study presentation would provide
valuable insight into how a specific DSME clinical encounter might play out.
The case study presents one of the most attractive ways of illustrating the process of
observation, data collection, assessment, and planning. They are an effective means of problem
solving and as a result are regularly employed in the field of health-care (Gephart, 2004). In this
arena, these studies provide information about specific cases with the aim of sharing lessons
learned with the wider health community (Mariano, 2000). Disease prevention and
maintenance models frequently undergo case study investigation. Every case presents its own
set of challenges for which no single approach is either right or wrong. The purpose is to learn
through trial and error and build upon previous successes and failures. In an effort to recount
the practice of devising an individual DSME plan at WPC, a typical case study of that process is
A 68-year-old white female (Patient X) checked in at the WPC clinic for a regularly
scheduled appointment. She had been advised to seek DSME counseling after her last two
random blood glucose checks were recorded in the hyperglycemic range (i.e., 172 & 198
mmol/L, respectively). Her family history indicated risk for type 2 diabetes, which had been
diagnosed in a younger brother. Besides these two readings, Patient X had had well-controlled
type 2 diabetes for the last 20 years. Her most current HbA1C test was 10.1% – normal <6.5%;
random blood glucose 156 mg/dl – normal 85-125 mg/dL; Low density lipoprotein (LDL; bad
cholesterol) 161 mg/dL – normal 70-130 mg/dL (lower numbers are better); High density
lipoprotein (HDL; good cholesterol) 32 mg/dL – normal 40-60 mg/dL (high numbers are better);
BP 165/70 – normal <120/80; ophthalmologic (eye) examination shows early signs of
proliferative retinopathy; Current medications: glibenclamide 10 mg twice a day (INN
Sulfonylurea - oral DM medication), gemfibrozil 150 mg daily (Lopid - cholesterol lowering
drug), irbesartan 150 mg daily (Avapro - hypertension medication used specifically in DM
cases), furosemide increased to 40 mg twice a day (Lasix - loop diuretic). At this presentation,
Patient X met the clinical diagnosis of T2DM (not controlled), currently obese, hyperglycemic,
hyper-lipidemic, and hypertensive with signs of proliferative diabetic retinopathy. Upon
physician’s advice, NPH insulin (Humulin N) 24 units AM, 20 units PM, was also added to the
patient’s pharmaceutical regimen to control diabetes progression.
Patient X is an obese (BMI=31), stay-at-home wife for the past 42 years who complains
of being very tired and not getting enough sleep as of late. She also states that her husband is
very ill and has been recently placed in a nursing home. Patient X contends that she sees him
three to five times a week but would visit more often if she just had the energy. She confesses
that she does not always adhere to her drug treatment plan stating her husband use to
constantly remind her about taking her meds. She also admits to poor eating habits, consisting
primarily of fast-food meals. She simply states “my life is in disarray.”
Patient X’s case presentation highlights the importance of placing all of an individual’s
life circumstances and priorities in perspective when planning DSME. It also underscores the
crucial role family plays in the management of DM and the need to strengthen social support in
this group. Poor sleeping and eating habits is almost certainly a sign of being overloaded and
stressed. These along with the absence of her husband are perhaps early signs of depression as
well. This is probably the primary cause of her hyperglycemia since she reports these new
circumstances have caused her to waver from her normal activities. Based on the recent rise in
her HbA1C values, the hyperglycemia is probably an acute medical phenomenon. Her oral DM
meds have proven inadequate to deal with her hyperglycemia. NPH insulin (Humulin N - 24
units AM, 20 units PM) was warranted. Along with the addition of insulin into her schedule, the
patient could also benefit tremendously from DSME services. This involved an evaluation of the
following variables: socioeconomic status like social support, health indicators like obesity, as
well as specific treatment strategies like drug therapy and dietary practices.
Along with the basic clinical examination, the history of present illness, and the most
recent blood chemistries, Patient X’s diabetes self-management resources and skill sets were
evaluated. The accuracy of her blood glucose meter was assessed with a control strip. A check
of her blood glucose strips to ensure they were in date was also done. An assessment of her
testing technique was also performed. A review of previous blood glucose checks stored in her
test meter was conducted with attention to frequency particularly noted. These assessments
are performed to help find and eliminate user error, which is often unintended. All test proved
to be satisfactory.
Based on Patient X’s major life changes, a mental health analysis was also conducted.
Performing this test helped to determine if Patient X was suffering from any mental health
disorder like depression. After careful assessment, Patients X’s mental status was reportedly
normal. The patient, however, did reveal an overwhelming desire to maintain her autonomy.
Unsurprisingly, independency is often prized over dependency even when times of need are
great. Patient X’s self-help desires in this regard would definitely influence but not totally
dictate her DSME plan. Considering her significant health risks, all current forms of support
system were first examined. Since she has already expressed a diminished social network,
particular in regards to her husband’s absence from home, other potential sources would have
to be identified. This ancillary support can be derived from family and friends, community
members, as well as the primary care team itself. Let us be reminded of the important role
physicians, nurses, and other providers can play in her management. WPC can provide
elements of teaching, counseling, and education. In addition, the clinic provided her with
information regarding community based programs established within the Nashville
Metropolitan area that cater to the needs of DM patients. The importance of social support
cannot be overstated.
An additional assessment performed by WPC was an evaluation of Patient X’s poor
sleeping patterns. Obesity is associated with a condition known as obstructive sleep apnea
(OSA). If left diagnosed and untreated, OSA results in diminished sleep at night and excessive
daytime sleepiness (Reichmuth, et al., 2005). This is especially dangerous if OSA sufferers are
operating motor vehicles or heavy equipment. Elderly patients can also sustain major injury
from serious falls. With the threat of these potential hazards, the decision was made to
recommend diagnostic testing for OSA. The patient was referred to a licensed
A review of Patient X’s diet was the next in the evaluation process. In addition to the
patient overlooking her drug schedules, she might be neglecting her diet as well. Often when a
spouse is ill, the partner neglects his or her own health needs. This could pose a significant risk
of malnutrition, a dangerous condition for a diabetic. The Mid-Cumberland Human Resource
Agency (MCHRA) conducts a service called Meals on Wheels in the Middle Tennessee region.
The program offers home-delivered meals to eligible residents (mostly senior and disabled
citizens) of Nashville who are homebound and cannot shop or cook for themselves (MCHRA,
2012). The patient was advised to consider registering for this service. The necessary
paperwork and contact information was provided to Patient X. In addition, the patient was
taught the basics on counting carbohydrates. This training was conducted by the CDE.
Monitoring the portion of carbohydrates consumed is a key strategy for optimal glycemic
In addition, since Patient X would be starting insulin therapy for the first time, Patient X
needed a thorough explanation about the progressive nature of DM and the serious need for
insulin therapy. This issue must be approached with immense sensitivity. A patient who has
maintained good glycemic status for nearly a lifetime may be hard to convince to undertake
another therapeutic modality. Instead of debating over experience, a continuation of the
subject’s past personal success was emphasized. In addition, the choice of which insulin
delivery device was discussed. Since her last ophthalmologic exam showed signs of proliferative
retinopathy, her visual acuity could become progressively compromised. Difficulty in setting the
correct dial-up dosage on certain injection devices may become a potential problem. NPH
insulin (Humulin N) can be dispensed in a variety of devices. After being presented with the
available options the patient decided on the InnoLet doser (InnoLet, 2012). This device has
large number dials which the manufacturer markets to be much easier for people with poor
eyesight. In addition, triggering the injector to administer the insulin does not generally require
as much strength or dexterity as the other dosers.
Based on the overall analysis, Patient X should have close follow-ups. She was therefore
scheduled for a physician appointed every 3 months. The appropriate lab work-up will be
included at each visit. Patient X was also referred to receive dilated ophthalmic (eye)
examination to monitor her retinopathy. DSME follow-up counseling was also set up to
INTERNSHIP GOALS AND OBJECTIVES
The primary aim of this internship was to afford me the opportunity to gain clinical
experience in the field of primary care medicine. Specifically, I made it a goal to advance my
communication skills. Public health-care providers who aspire to work predominantly in the
hospital or clinical setting must possess the ability to communicate effectively with patient
populations of diverse backgrounds. This is essential if providers intend on establishing a robust
rapport. Moreover, they must be capable of successfully translating technical jargon into
everyday language that the average patient can understand. Although I have a background in
the medical field, it has been quite some time since I have had regular encounters with
patients. Working at WPC definitely granted me the opportunity to strengthen my
communication skills while simultaneously increasing my appreciation of cultural competency.
Along with enhancing my communication skills and broadening my cultural sensitivity and
awareness, my other objectives were to demonstrate clinical proficiency in each of the
following domains: patient care, medical knowledge, interpersonal skills, and professionalism.
These are the fundamentals of medical-care that all health providers strive to acquire and
maintain throughout their professional lives. Achieving proficiency in these domains required
that I made a consistent effort on enhancing the skills sets that I had already possessed. These
activities included medical history taking, physical examination, clinical findings presentation,
and differential diagnosis development. I also worked extensively on successfully composing
more detailed SOAP notes. Improving upon this particular task assisted me in making a more
complete and systematic clinical presentation. I am quite confident that I was able to
successfully meet these additional objectives as well. The regular feedback I received from Dr.
Watts helps to support this assumption.
In hindsight, I was able to take full advantage of the many learning opportunities
afforded me during this field experience. Although my capstone project focused primarily on
diabetics, WPC still serves a broad spectrum of patients. This clinical experience will be of
enormous benefit when I re-enter the medical profession.
On another note, I have seen, first hand, the state of our health care system up-close
and frankly it leaves me somewhat disappointed. Our current system has too many inequities
and barriers to care, most being payment-based processes that I find counter-productive. This
is one area of primary care that I find troubling, yet amendable to changes in policy.
CAPSTONE PROJECT GOALS AND OBJECTIVES
The main purpose of the research conducted for this Capstone Project was to determine
whether diabetes self-management demonstrated any correlation with diabetes outcome.
There are two research questions which guided this investigational study.
1. Is there a correlation between self care (DSMA) and DM control (HbA1C levels) in an
adult population group currently receiving medical care?
2. Are any co-variables (demographic characteristics: age, race, gender, education,
income; or physiologic characteristics: weight, BMI, duration of diabetes, treatmenttype, and diabetic complications) related to DM control?
1. There will be a statistically significant correlation between self-care and DM control.
2. A particular set of demographic characteristics are related to DM control.
In order to test the hypotheses given here, it is first necessary to provide operational
definitions to two key constructs presented thus far; Diabetes Self-Management and Diabetes
Outcome. An operational definition gives a concept meaning and validation by outlining the
processes or procedures that must be executed in order to empirically measure that concept
(Ary, et al., 1985).
Diabetes Self-Management can be defined as the performance of a variety of DM selfcare activities and skill sets (Toobert & Glasgow, 2000). If executed properly, studies have
shown these strategies to be quite effective in controlling diabetes and preventing
complications (Toobert & Glasgow, 2000). The practice of Diabetes Self-Management primarily
involves eating healthy, being active, self-monitoring, reducing risk, and developing problemsolving and coping strategies. In this investigation it will be operationally measured by the
Diabetes Self-Management Activities (DSMA) survey (Toobert & Glasgow, 2000).
The DSMA is a 12-item questionnaire frequently used to assess the degree of diabetes
self-management in the seven days preceding the questionnaire. To begin the survey is divided
into five individual sections. Each section poses a set of questions that evaluate the five major
aspects of the diabetes self-management strategy. These include the patient’s foot-care
practice, dietary habits, exercise routine, self-monitoring of blood glucose (SMBG), and
medication compliance (Toobert & Glasgow, 2000).
The four questions pertaining to diet can be divided into two sets. The first set measures
subject’s adherence to a healthy eating plan and begins by asking, “How many of the last SEVEN
DAYS have you followed a healthy eating plan?” followed by “On average, over the past month,
how many DAYS PER WEEK have you followed your eating plan?” The second set then measures
the nutritional content of the patient’s diet over that same week. It begins with “On how many
of the last SEVEN DAYS did you eat five or more servings of fruits and vegetables?” followed by
“On how many of the last SEVEN DAYS did you eat high fat foods such as red meat or full-fat
The two questions addressing exercise evaluate the amount and degree of physical
activity performed in a week by the subject. The first question asks, “On how many of the last
SEVEN DAYS did you participate in at least 30 minutes of physical activity?” The second then
inquires, “On how many of the last SEVEN DAYS did you participate in a specific exercise session
(such as swimming, walking, biking) other than what you do around the house or as part of your
The two questions pertaining to SMBG measure the subject’s frequency of both
voluntary and recommended serum-tests over the past week. The two questions are as follows.
“On how many of the last SEVEN DAYS did you test your blood sugar? – “On how many of the
last SEVEN DAYS did you test your blood sugar the number of times recommended by your
health care provider?”
The two questions regarding foot-care assess the frequency of podiatric inspections as
well as the depth of examination by the subject over a week’s time. The patient is first asks,
“On how many of the last SEVEN DAYS did you check your feet?” The follow-up question would
then be, “On how many of the SEVEN DAYS did you inspect the inside of your shoes?”
The two questions pertaining to diabetes medication measure patient compliance to
either physician prescribed oral-drug intake or insulin administration in the previous week. Only
one of the two questions will be recorded as subjects will only be scored for either their insulin
or oral-drug adherence. The two questions are as follows: “On how many of the last SEVEN
DAYS did you take your recommended insulin injections? – “On how many of the last SEVEN
DAYS, did you take your recommended diabetes oral medication?” As such, only 11 of the 12
question-items are used.
Five summary scores are generated from the DSMA survey. Each score represents the
fraction of days the subject performs the recommended task related to diet, exercise, blood
sugar testing, foot care, and diabetes medication. A tallied score can range from 0 to 77; the
higher the score the better the diabetes self-care (Toobert & Glasgow, 2000). Toobert &
Glasgow reported internal consistency and reliability through inter-item reliability testing. They
were able to demonstrate an inter-item correlation greater than 0.5 (0.74 to 0.78 for physical
activity, 0.59 to 0.74 for diet, and 0.38 to 0.76 for self-monitoring of blood glucose (Toobert &
Glasgow, 2000). A complete copy of the DSMA survey can be found in Appendix 2.
Diabetes Outcome can be defined as a clinical interpretation of one’s glycemic status,
and particularly a reflection of one’s risk for diabetic complications (Goldstein et al., 2004). The
operational definition of ‘Diabetes Outcome” will be the most recent measurement of a
patient’s HbA1C within the past 3 months (Goldstein et al., 2004). The ADA considers HbA1C
testing as the gold standard in the assessment of one’s glycemic state. Moreover, serial HbA1C
tests have immense prognostic value in terms of predicting diabetes outcome (ADA, 2010).
Maintaining HbA1C values less than 6.5% has shown to significantly reduce the risk of severe
micro-vascular and macro-vascular complications due to diabetes (ADA, 2010). In addition,
reduction in HbA1C values by just 1% has proven to reduce diabetic complications by as much
as 25% (UKPDS, 1998).
A descriptive correlation (observational) study was employed to address and test the
questions and hypotheses proposed here. Employment of this study design was considered
appropriate in describing the relationship between Self-Management and DM control. For
reference, the independent variables will be self-reported Self-Management as interpreted by
DSMA, as well as the following demographic characteristics (age, gender, marital status, level of
education, health coverage, employment status, and income) and physiological characteristics
(BMI, patient history, family history, oral-drug treatment, insulin therapy, smoking habits,
DSME history, and DM complications). The dependent variable will be DM control as
interpreted by HbA1C levels.
Adult patients diagnosed with diabetes mellitus (DM) were recruited from WPC to
participate in the study entitled, “A correlation Study to Determine the Effect of Diabetes SelfManagement on Diabetes Outcomes.” The study group consisted of patients, 18 years or older,
with either Type 1 or Type 2 DM, diagnosed within the past year. The study sought to recruit
between 125-150 diabetic patients for participation. Race, ethnicity, gender, class, or most
other social demographic factors did not preclude or exclude individuals diagnosed with DM
from participating. All pregnant women, however, were ineligible for participation. In addition,
patients who did not speak English proficiently were also excluded. Finally, individuals who
were either anemic, had a mental illness (e.g., dementia, psychosis, or mental retardation),
were on steroid or chemo-therapy, diagnosed with alcoholism, or post-operative within the
past three months were not able to participate in this study.
Eligible subjects were first identified as diabetics before arriving at WPC using the office
EMRs. Patients were approached during sign-in at the reception desk of WPC. After a brief
introduction, patients were informed that he/she was eligible to participant in a diabetes
research study. Exceptional care was taken in relaying to the patient that he/she was under no
obligation to participate.
If the patient expressed verbal interest in learning more about the investigation, a more
detailed description of the project was presented to the patient. The subject was then given a
research packet. Materials in the packet were presented in the following order. To begin an
informational form (Appendix 3) outlining the study’s goals and objectives, as well as risks and
benefits was provided. After review of this form, a written consent form (Appendix 4) was then
presented. If the patient agreed to participation, signing and dating this form acted as written
consent. At this time patients were provided a demographic survey (Appendix 1) and a research
questionnaire (Appendix 2). Once completed all materials were collected.
After these forms were retrieved, the participant would then wait to be taken to an
exam room for their regular scheduled appointed. At that time the patient’s most recent HbA1C
value was added to his/her demographic survey (Appendix 1). Recruitment of participants
concluded when sufficient numbers of patients to yield statistically significant results was
Adult participants, as part of the study design, were asked to complete a Demographic
Survey (DS; Appendix 1) and a Diabetes Self-Management Activities (DSMA; Appendix 2)
questionnaire. These forms served as the investigation’s data collection tools. The DSMA
questionnaire has previously been described in the section on operational definitions.
The DS form was an in-house survey that collected data on demographic and physiologic
characteristics. Demographic traits included gender, age, income, education, employment
status, marital status, medical coverage, and past diabetes self management education.
Physiologic attributes included BMI, patient and family DM history, treatment regimen, DM
complications, and smoking habits.
The purpose of the survey and questionnaire was thoroughly explained during the
introductory interview with each prospective participant. After written informed consent was
obtained, patient participation in the study was granted. All completed research packets were
gathered by office personnel. A note of the patient’s most recent HbA1C reading was also
recorded at this time (< 3 months old). It is presumed that research participants responded
honestly and objectively on the two self-reported questionnaires (the DSMA and DS).
Protection of Human Subjects
Loss of time was identified as a potential inconvenience for study participants. Invasion
of privacy was also recognized as a potential risk to subjects. Questions regarding income,
health habits and practices, and/or substance/pharmaceutical might have been considered
invasive to some participants. Other minor risks identified for research participants included:
boredom, mental fatigue, and frustration. Besides these, no other identifiable risks,
discomforts, or inconveniences associated with the study’s research activities were determined
beyond those which diabetic patients typically encounter during a normal medical visit.
To address concerns regarding loss of time, an estimated time range was identified in
the consent form as well as the oral introductory presentation provided to the prospective
participants. The time estimate was based on a pilot test of individuals that completed the
research activities. To address the potential risk regarding loss of privacy and confidentiality,
the surveys refrained from obtaining information that could potentially link subjects to
questionnaires, such as name, birth date, and Social Security Number. In addition, the consent
form provided clear explanations and rationales regarding the appropriateness of personal and
private questions pertaining to behavior, lifestyle, and socioeconomic status. All participants
maintained the right to skip questions that made them uncomfortable or even terminate the
study altogether at any time. In addition, it was made very clear that all data collection
instruments would not be shared with any outside individual or group. During the investigation,
all completed surveys were stored in a locked file cabinet with other patient medical records at
WPC. All forms were destroyed after study completion. Most concerns held by research
subjects were appropriately addressed during patient encounters. Future concerns will be
For added protection of human rights, a research application was submitted to the
Institutional Review Board (IRB) at Tennessee State University for approval prior to initiating
the recruitment of subjects and collection of data. Approval of the research application was
granted by the TSU IRB committee in the month of November, year 2012. A complete copy of
the IRB Approval form can be found in Appendix 5.
In summation, given the nature of the population from which the study group was
recruited (diabetic patients from a primary care clinical), participants were regularly reassured
that withdrawal from the study would never affect the quality of healthcare services rendered
by WPC. Confidentiality of data collected from the participants was maintained throughout the
process of data collection, data analysis, analysis, interpretation and dissemination. As
previously noted, no identifying information was recorded at anytime (e.g., first/last name,
social security number, patient number). WPC personnel were expected to honor the universal
health professional privacy code and maintain strict patient confidentiality. Upon completion of
the final report, all data forms were appropriately discarded.
All questionnaires were checked for completeness. Unfinished forms were considered
unusable and the entire patient research packet was properly discarded. IBM Statistical
Package for the Social Sciences (SPSS) version 21.0 was employed in this investigation for data
analysis. SPSS was specifically chosen because of its ease of use as well as its high availability on
the Tennessee State University campus. In addition, the software is considered an effective tool
in performing a descriptive correlation analysis. For all analysis, statistical significance was
based on an alpha of < 0.05.
Descriptive statistics were used to illustrate the demographic and physiological
attributes of the study participants. Nominal variables were summarized as frequencies and
percentages. For continuous variables, minimum and maximum values were given along with
the corresponding means and standard deviations (SD).
A Mixed-Effects Model (MEM) was also employed for the purpose of correlation
analysis. A MEM includes a combination of both fixed and random factors. In a MEM, each
factor in a study has levels. The effects associated with each factor are the effects that the
levels of the factor have on the dependent variable of interest. Fixed effects are those variables
for which the only levels considered are kept in coding of those effects. Random effects are
those variables for which the only levels considered are kept in coding of those factors that are
a random sample of the total number of levels in the population for that factor. Random and
fixed effects are presented as both unadjusted and adjusted univariate methods (Baayen,
The unadjusted univariate method assessed the correlation between the independent
variables (DSMA, demographic characteristics, and physiological characteristics) and the
dependent variable (HbA1C) with random effect. The adjusted univariate method assessed the
correlation between the independent variable (DSMA) and the dependent variable (HbA1C)
with covariates that turned statistically significant in the unadjusted univariate method, namely
demographic and physiologic characteristics and random effect. Random effect was assigned to
choice of primary care provider. PCP1 was coded for Dr. Eli Watts and PCP2 was coded for Dr.
Kenneth Williams, thus taking into account for correlation of observations for each provider.
The integration of covariates was used for predicting the statistically significant variables in the
variance of HbA1C levels. Employing this methodology would theoretically provide accurate
standard errors for random or fixed effects.
Using the WPC clinical database, 490 patients were formally identified as potential
participants in the research study. Of these, 159 were deemed ineligible for the following
reasons; 38 were no longer considered WPC patients; 33 had a past history of mental illness; 25
had recent history of alcoholism; 18 were post-op (<3months); 28 were presently on steroid or
chemo-therapy; 17 had lab reported anemia. Of the 331 remaining eligible patients, 129 did not
make a clinical visit during the enrollment period. A total of 202 patients were approached the
day of their primary-care appointment. Of these, 23 patients opted out of study participation,
10 turned-in partially finished surveys, and another 17 were too ill to engage in study activities.
Overall, 152 patients submitted completed research packets. A final review of EMRs revealed
148 of the 152 patients had at least one HbA1C measurement performed within the last 3
months. This final group of 148 subjects constituted the entire study sample.
Age Range: Participants were asked to group themselves in one of the following age
ranges; “18-29,” “30-39,” “40-49,” “50-59,” “60-69,” and “70+.” Around 32% of the study’s
respondents were between the ages of 50-59 years (n= 48). Exactly 27% were between the ages
of 60-69 (n=40). Nearly 22% were 70 years or older (n=32). Another 4.7% were aged 30 to 39
(n=7). Only 3.4% of the respondents were aged of 18-29(n=5). Table 1, Section 1a summarizes
the age distribution of the study participants.
Gender: The gender of the participants was defined as either “male” or “female.” Of the
148 participants, 58% were females (n=86). Another 42% of the participants were males (n=62).
Table 1, Section 1b summarizes the gender distribution of the study participants.
Marital Status: To describe marital status, participants were asked to select from the
following categories; “Single,” “Married,” “Divorced/Separated,” “Widowed.” Around 54% of
participants were married (n= 80). Widowed and single subjects each represented 16.2% of
respondents (n=24, 24). Another 13.5% were either divorced or separated (n=20). Table 1,
Section 1c summarizes the marital status distribution of the study participants.
Level of Education: To assess the highest level of education achieved, participants were
ask to select from the following choices: “10-12 years of education or high school diploma”,
“13-14 years of education or technical degree”, “13-14 years of education or associates
degree”, “15-16 years of education or college degree” and “16+ years of education or graduate
degree”. The majority of the participants, approximately 35% had only a high school education
(n= 52). Respondents who possessed the equivalence of either a technical or associates degree
represented a combined 33% of the study group (17.6%, n= 26; and 14.9%, n= 22; respectively).
Exactly 23% of participants indicated having a college degree or equivalent level education
(n=34). Another 9.5% reportedly had pursued or possessed a graduate degree (n=14). Table 1,
Section 1d summarizes the educational distribution of the study participants.
Employment Status: To assess employment status, participants were to select one of the
following; “Full-time,” “Part time,” “Unemployed (physically able),” “Unemployed (physically
unable),” “Homemaker/Housewife,” and “Retired.” Nearly 43% of all participants indicated fulltime (n=63). Around 15% reported part-time employment only (n=22). Another 13.5% of
respondents were reportedly unemployed (n=20). Exactly 23% of the participants specified
being either homemakers or housewives (n=33). Another 7% were reportedly retired (n=10).
Table 1, Section 1e summarizes the employment distribution of the study participants.
Annual Income: Regarding income, participants were asked to select from the following
salary ranges; “< $24,999”, “$25,000- $44,999”, “$45,000-$64,999”, and “> $65,000”. Almost
37% of the participants reported an annual income of less than $25,000 (n=54). One third
indicated an annual income between $25,000- $45,000 (n= 50). Another 15.5% reportedly
earned between $45,000 and $65,000 annually (n=23). Around 14% specified an annual
income of more than $65,000 (n=21). Table 1, Section 1f summarizes the income distribution of
the study participants.
Health Coverage: Participants were simply asked whether they had health care coverage
or not. A very large majority, around 89%, of the participants reported having a health coverage
(n=331). Only 11.5% (n=21) reported having no health-care coverage. Table 1, Section 1g
summarizes the health coverage distribution of the study participants.
Primary Care Provider: Patients were either being followed by one of two WPC
physicians, Dr. Watts or Dr. Williams. As such, participants were categorized by their choice of
primary care provider (PPC); PPC1 = Dr. Watts and PPC2 = Dr. Williams. Two-thirds of the
participants were assigned to PPC1 (n=99), and one-third to PPC2 (n=49). This classification was
included in order to fulfill the requirements for MEM testing with random effect for PCP. Table
1, Section 1h summarizes the choice of PPC of the study participants.
Patient’s History of Diabetes: The length of time since being diagnosed with DM (in
years) was used as a marker for “patient’s history of diabetes.” Participants chose from the
following categories; “<5 years”, “5-10 years,” “11-16 years,” and “> 17 years.” About 30.4%
reportedly have had diabetes for less than 5 years (n=45). Another 26.4% reported a 5-10 year
history of diabetes (n=39). Exactly 23% report an 11-16 year history of DM (n=34). Slightly more
than 20% have reportedly been suffering from DM for over 17 years (n=30). For the purpose of
correlation analysis the participants were further dichotomized into two categories (>10years:
56.8%, n=84; and <10years: 43.2%, n=64). Table 2, Section 2a summarizes the patient history of
the study participants.
Family History of Diabetes: Family history of diabetes was answered with a simple “Yes”
or “No.” A large majority of the participants surveyed report having a positive family history of
DM (91.2%, n= 135). The small remainder reportedly had no family history of DM (8.8%, n=13).
Table 2, Section 2b summarizes the family history of the study participants.
DM medication: Participants were asked whether or not they were currently on any
type of DM medication. Nearly 95% reported being placed on some form of pharmaceutical
therapy (n=140). Only 5.4% were reportedly receiving no DM medication of any kind (n=8).
Table 2, Section 2c summarizes the treatment status of the study participants.
Therapy Type: As a follow-up to the preceding question item, the participants were
asked “if they were receiving treatment,” what exactly constituted that therapy; the choices
included, “insulin alone,”“oral medication alone,” “both,” and “no medication”. Roughly 65.5%
of the respondents were prescribed oral drugs (n=97). Exactly23% reported being on both oral
drugs and insulin (n=34). Another 6.1% were prescribed insulin only (n=9), and 5.4% were not
on any form of medication (n=8). Table 2, Section 2d summarizes the therapy type of the study
Diabetes Education: The question of whether or not participants received formal
diabetes education was also raised. Nearly 90% reported receiving diabetes education (n=131).
A little over 11% reportedly had no formal DM education (n=17). Table 2, Section 2e
summarizes the diabetes education of the study participants.
Diabetes Complications: A review of complications associated with diabetes mellitus
was also included. Respondents could chose from the following categories, “Low blood glucose
- hypogycemia (<80mg/dl),” “High blood glucose - hyperglycemia (>300mg dl),” “Heart/Cardiac
problems,” “Neuropathy/Nerve damage,” “Sexual problems,” “Kidney/Renal problems,”
“Retinopathy/Visual problems” and “None of the above.” Of the respondents, 11.5% reported
neuropathy (n=17), 10.1% indicated hypoglycemia (n=15), 14.2% had hyperglycemia (n=21),
1.4% reported retinopathy (n=2), 2.0% indicated sexual difficulties (n=3), 3.4% had cardiac
problems (n=5), and 0.7% had nephropathy (n=1). Almost 43%, indicated having two or more
DM complications (n=63). Around 14% of all respondents reported no complications associated
with DM (n= 21). Table 2, Section 2f summarizes the diabetes complications of the study
Smoking Habits: An assessment of the respondents smoking habits was also performed.
Around 47% indicated no history smoking (n=69). Roughly 19% were current smokers (n=28).
About one third reportedly quit but did have a past history of smoking (n=51). Table 2, Section
2g summarizes the smoking habits of the study participants.
Body Mass Index: BMI is a figure calculated using an individual’s weight and height; BMI
= [mass (kg)]/ [height (in) 2]. It provides a reliable indicator of body fatness and is used to screen
for weight categories (e.g., overweight, obese) that may lead to health problems. The mean
(average) BMI of the study group in this investigation was 32.42 (SD= 7.53) ranging between
18.12 and 61.02. Table 3, Section 3a summarizes the BMI results of the study participants.
Hemoglobin HBA1C: HbA1C is the molecular by-product of the slow, irreversible
reaction between glucose and hemoglobin molecules within red blood cells. Its percent
measurement is indicative of an individual’s average blood glucose concentration over the
preceding 90 days (Goldstein et al., 2004). The HbA1C assay therefore provides a reliable
measure of a subject’s long-term glycemic control without the need for repeated FPG testing or
routine OGTTs (Buell, et al., 2007). The mean (average) HbA1C of the study participants was
7.91% (SD= 1.38), ranging between 5.65% and 14.12%. Only the HbA1C levels obtained within
the past 3 months were used. Results were retrieved from the patients’ EMRs. Table 3, Section
3b summarizes the HbA1C results of the study participants.
Diabetes Self-Management Activities (DSMA) Statistics
The DSMA survey can be divided into six subscales, each measuring a specific diabetes
self-care activity. The average (mean) of each subscale as well as its respective standard
deviation (SD) was calculated for both descriptive and correlation analysis. Scores could range
from 0-7, such that “0” equated to no days of activity and “7” equated to a seven days of
activity. The mean (average) score of the general diet subscale was 4.88 (SD= 2.43). The average
score of the specific diet subscale was 4.06 (SD= 2.11). The mean score of the physical exercise
subscale was 2.33 (SD=1.98). The average score of blood sugar testing subscale was 3.12 (SD=
2.13). The average score of the foot care subscale was 3.86 (SD= 1.87). The mean score of the
medication subscale was 6.81 (SD= 1.24). Table 4 summarizes the DSMA statistical results of the
MEM analysis was employed to answer the 1st research question, “Is there a correlation
between self care (DSMA) and DM control (HbA1C levels) in an adult population group currently
receiving medical care?” Based on the MEM results, there was no statistically significant
correlation between any of the DSMA subscales and HbA1C (p<0.05). Table 5 summarizes the
“DSMA x HbA1C” correlation results of the study participants.
In addition, MEM correlation analysis was employed to answer the 2nd research
question, “Are any co-variables (demographic characteristics: age, gender, marital status,
education, employment, income, and health coverage; or physiologic characteristics: DM
history, DM family history, DM medication, DM therapy type, DM education, DM complications,
smoking history, and BMI) related to DM control (HbA1C levels)?” Of these co-variables, age,
gender, DM complications, DM history, DM therapy type, and BMI demonstrated a statistically
significant relationship with HbA1C levels (p<0.05). Patients who were 49 years of age or
younger had HbA1C scores 1.13 % higher than those who were 50 years or older (beta= 1.13,
SE=0.22, p= 0.026). Male patients presented HbA1C levels 0.94% higher than female patients
(beta= 0.94, SE= 0.19, p= 0.041). Patients who indicated no diabetes complications possessed
HbA1C scores 2.03% less than those who reported at least one DM complication (beta= -2.3,
SE= 0.41, p= 0.037). Patients with a history of DM less than 10 years had HbA1C values 0.01%
higher than those with a history greater than 10 years (beta= 0.01, SE= 0.25, P= 0.049). Patients
on insulin therapy had HbA1C values 1.53% higher than those who were not (beta= 1.53, SE=
0.63, P= 0.0037). BMI proved to be statistically significant as well. Results demonstrated that
with every point increase in BMI, HbA1C values increased by 2.06% (beta=2.06, SE= 0.37, p=
0.009). Table 6 summarizes the “Co-variables x HbA1C” correlation results of the study
In summary, DSMA subscales did not demonstrate any statistically significant correlation
with HbA1C scores. This study therefore did not support the hypothesis that diabetic patients
who practice DM self-care activities present with improved glycemic numbers compared to
patients who do not practice such measures. However, the co-variables, age, gender, DM
therapy type, DM history, DM complications, and BMI did demonstrated a statistically
significant relationship with HbA1C levels when integrated as covariates in the adjusted and
unadjusted univariate Mixed-Effect Model (MEM) with random effect for primary care provider.
This finding does support the hypothesis that certain demographic/physiologic characteristics
do indeed influence diabetes outcome.
Although not evidenced here, from both a medical and public health standpoint,
diabetes control activities based on DSME standards still might play an important role in the
promotion of healthy behaviors and lifestyles among DM patients. Indeed, the expansion of
DSME services across America could greatly diminish the high incidence of DM complications,
including blindness, end-stage kidney failure, and limb amputations. One of the many diabetesrelated aims of Healthy People 2020 (HP 2020) is to increase the proportion of individuals
receiving formal diabetes health education (USDHHS, 2012). The current national average is
56.8% of diabetic patients receive diabetes health education and the HP 2020 target is 62.5 %
by the year 2020 (USDHHS, 2012). Although a convincible moral argument can be made for
making diabetes education part of a large national health agenda, the benefits of such a broadbased initiative still should be empirically sound. With conventional medicine’s push for
evidence-based care and practice standards, diabetes investigators are charged with the task of
gathering the proof needed to support such a push. This research investigation clearly aimed to
take up that charge.
This investigation involved diabetics currently receiving health-care, therefore
establishing the degree to which DM control was a consequence of events or circumstances
occurring before or after clinical presentation was difficult to discern. Moreover, subjects were
generally study volunteers thus not randomly selected. This self-selected group may be so
significantly different from the general population to the degree that data interpretation would
be difficult. Furthermore, this study did not seek to measure the capacity of patients to perform