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Quality of Diabetes Care in U.S. Academic Medical Centers: Low Rates of Medical Regimen Change

Quality of Diabetes Care in U.S. Academic Medical Centers: Low Rates of Medical Regimen Change -- Posted by Gumbo on 02-16-05 05:28

Quality of Diabetes Care in U.S. Academic Medical Centers: Low Rates of
Medical Regimen Change

Originally Published:20050201.

Results from clinical trials over the past decade have led to national
guidelines that advocate aggressive management of hyperglycemia,
hypertension, and hyperlipidemia for patients with diabetes (1-7). Other
research has established the evidence base for specific screening and
prophylactic recommendations, including retinal and foot examinations and
daily aspirin (8-10). Despite this scientific progress, patients with
diabetes continue to suffer from high rates of cardiovascular and
microvascular complications and can expect a lifespan reduction of 10-15
years (11,12). This inability to effectively and widely translate clinical
evidence into usual practice represents a major barrier to reducing the
burden of diabetes ancl its complications.

With the continued increase in the worldwide epidemic of diabetes (13), the
quality of care for patients with diabetes has come under increasing
scrutiny. In 2001, the Diabetes Quality Improvement Project (DQIP) was
initiated to define a comprehensive set of national measures for
population-level evaluation of the quality of diabetes care (14). DQIP
measures included rates of annual testing (e.g., for HbA1c), screening
(e.g., for foot problems and retinal disease), and levels of
diabetes-related risk factor control (such as HbA1c and cholesterol).
Subsequent studies using both national and local data have found significant
shortcomings in most DQIP quality measures (15-17). Indeed, recently
published data from the National Health and Nutrition Examination Survey
(NHANES) have demonstrated little improvement in risk factor control from
the 1988-1994 to 1999-2000 surveys, particularly with regard to HbA1c and
blood pressure (18).

Academic medical centers represent a key health delivery system in the U.S.
whose mission includes training new health professionals and advancing
clinical research while caring for a diverse population of patients. We
report here the results of a clinical benchmarking project to assess both
established and novel quality measures of ambulatory diabetes care among 30
U.S. academic medical centers. The goals of this analysis are to describe
the current state of care provided by our nation's academic health centers
and to assess medication changes in this setting among the subset of
patients not meeting evidence-based goals of care.

RESEARCH DESIGN AND METHODS- A total of 30 U.S. academic medical centers
located in 20 different states from every region of the county contributed
patients to this study. Within each participating institution, individual
clinics with a minimum of 500 annual diabetes patient visits were eligible
for inclusion. Clinics included both primary care practices (family
practice, internal medicine, and general medicine) and specialty practices
(diabetes/ endocrinology). Overall, 44 separate clinical practices were
selected for further data collection and analysis.

Patients were eligible for inclusion if they were aged ?18 years, had type 1
or type 2 diabetes according to their medical records, and had at least two
visits to the study clinic in the 24 months before 10 January 2002, with the
most recent visit occurring in the 6 months before 10 January 2002. For each
clinic, patients were systematically identified in reverse chronologic order
from the most recent visit date, and the first 40 patients with an even
medical record number were selected for analysis. Each practice contributed
unique patients with no overlap between practices within a single academic
medical center.

For each patient, data for the prior year and for the most recent clinic
visit were collected using standardized chart review forms. Data abstraction
personnel each received 1 h of individual training in use of the form. A
clinic visit was defined as a visit with a physical assessment by either a
physician or nurse practitioner. The following variables were assessed:
testing in the prior year and the last measured value for HbA1c and
cholesterol before the most recent clinic visit (or during the visit for
point-of-care testing); recorded blood pressure measurement during the most
recent visit; documentation of foot examination, retinal examination,
smoking cessation counseling, urine microalbumin screening, self-glucose
monitoring, and antiplatelet therapy; and medical regimen changes during the
most recent visit.

Medication changes at the most recent visit

We recorded medical regimens for patients at the time of the most recent
clinic visit and assessed whether changes in therapy were made during this
visit among the subset of patients with corresponding risk factor elevation.
We used the most recent HbA1c and cholesterol results available to the
attending physician at the time of the visit and the blood pressure values
obtained during the visit.

Detailed dose information and dose adjustments were collected for all
glycemia-related medicines (sulfonylureas, metformin hydrochloride,
thiazolidinediones, ?-glucoside inhibitors, and insulin). However, because
of the large number of possible antihypertensive and lipid-lowering agents,
we did not collect detailed dose data for these medicines. Therefore, for
hypertension and hyperlipidemia, we report the proportion of currently
untreated patients above various risk factor thresholds who were initiated
on corresponding therapy during the target clinical visit.

Statistical methods

Continuous variables were compared by Student's t tests if normally
distributed or Wilcoxon's rank-sum test if nonnormal, and proportions were
compared using ?2 tests. In an exploratory analysis, we identified
univariate predictors of change in therapy (for HbA1c >7.0%) or initiation
of therapy if untreated (for systolic blood pressure > 130/80 mmHg or LDL
cholesterol >100 mg/dl) using patient demographics (age, sex, insurance
status, race, and English language skills), specialty versus general
medicine practices, and clinical factors (type 1 versus type 2 diabetes,
treatment modalities, comorbid diagnoses, and risk factor levels). Variables
that were significantly associated with change or initiation in therapy in
univariate analysis (P < 0.05) were then entered into logistic models to
determine adjusted odds ratios for independent predictors of medication
change (SAS statistical software, version 9.0; SAS Institute, Cary, NC).
Separate models were constructed for each risk factor (HbA1c, blood
pressure, and LDL cholesterol).

RESULTS - A total of 30 academic medical centers contributed 44 clinics and
1,765 patients to this analysis. Patients received care from diabetes/
endocrinology (33.6% of patient cohort), internal medicine (30.9%), and
family practice (19.8%) clinics (Table 1). The remaining 15.7% of patients
were cared for in other primary care or indigent care clinics. Overall,
patients were middle aged and racially/ethnically diverse, and a little more
than half were women. Most patients had type 2 diabetes, and both coronary
artery disease (CAD) and obesity were highly prevalent. Patients attending
diabetes/endocrinology clinics were significantly younger, more often white,
better insured, and less obese. Prevalence of type 1 diabetes and use of
insulin was also greater in the diabetes/ endocrinology practices.

Measurement and control of diabetes-related risk factors

Diabetes risk factor management was of high quality in terms of risk factor
testing rates, but quality was lower in terms of proportions of patients
meeting goals for risk factor levels (Table 2). Overall, only 11.8% of
patients were simultaneously below goal for HbA1c, blood pressure, and total
cholesterol. This proportion was 10.0% when the LDL cholesterol goal was
used instead of the total cholesterol goal.

Table 2 also shows rates of other recommended screening and care practices.
Approximately two-thirds of patients were self-monitoring glucose or had
undergone urine albumin screening, but fewer than half had a documented
retinal or foot examination in the prior year. Less than half of patients
with diagnosed CAD had prescription of prophylactic aspirin or other
antiplatelet agents documented in the medical record (477 of 1,430 patients,
33.4%).

Medical regimen changes among patients with risk factors above goal

At the time of the target clinical visit, 92.6% of patients were taking
medication for hyperglycemia, 73.4% were taking medication for hypertension,
and 42.4% were taking medication for hyperlipidemia.

Fewer than half of patients with elevated HbA1c levels had changes in
hypoglycemic therapy during their clinic visit (Table 3). The farther the
patient was from goal, the more likely that therapy was adjusted: The
proportion of patients with glycemic regimen adjustment increased from 40.4%
(HbA1c >7%) to 45.6% (HbA1c >8%) to 48.5% (HbA1c >9.0%, P for trend =
0.002). Overall, the mean HbA1c for above-goal patients whose regimens were
adjusted was 9.4 ą 1.9 vs. 8.6 ą 1.7% for patients without medication
changes (P < 0.001). Of 47 patients above HbA1c goal and not on therapy at
the time of the target visit (2.7% of cohort), therapy was initiated in 11
(23.4%) patients during the visit.

A total of 449 patients were not on antihypertensive therapy at the time of
the most recent clinic visit. Of the 208 patients (46.3% of 449) with blood
pressures > 130/80 mmHg, only 21 patients (10.1%) were started on
antihypertensive therapy (Table 3). Patients started on therapy had higher
systolic (147.4 ą 14.8 vs. 140.0 ą 15.4 mmHg, P = 0.04) but similar
diastolic (82.0 ą 10.3 vs. 79.0 ą 10.8 mmHg, P = 0.2) blood pressure levels
compared with patients in whom treatment was not initiated.

Most patients with LDL > 100 mg/dl were untreated (55.9%, 427 of 763
patients) and of these patients, only 24 (5.6%) were initiated on therapy
during the clinic visit (Table 3). As with hyperglycemia and hypertension,
the likelihood that a patient was initiated on lipid-lowering therapy
increased with increasing LDL level (P for trend = 0.005) but remained low
in absolute terms. Above-goal patients who were started on therapy had a
mean LDL level of 152.7 ą 34.7 mg/dl, compared with 132.0 ą 29.6 mg/dl for
patients in whom therapy was not initiated (P = 0.001).

We also analyzed therapy intensification according to type of diabetes. A
total of 216 patients (12.2% of cohort) had type 1 diabetes. These patients
were younger (42.8 vs. 58.5 years, P < 0.001), more likely to be white (63
vs. 33%, P < 0.001), and less likely to be diagnosed with hypertension (35
vs. 73%, P < 0.001). Overall levels of risk factor control were similar for
type 1 versus type 2 diabetes (HbA1c 8.2 ą 1.9 vs. 8.0 ą 2.1%, respectively,
P = 0.3; LDL 103.1 ą 38.4 vs. 107.1 ą 38.8 mg/dl, P = 0.2) and among
patients with hypertension (blood pressure 134.4/71.7 ą 20.1/11.7 vs.
138.4/76.1 ą 19.9/12.1 mmHg, P = 0.07/0.004). For the primary outcome of
medication change among patients above goal, we found that patients with
type 1 diabetes were somewhat more likely to have a regimen change if HbA1c
>7.0% (51.1 vs. 38.9% among patients with type 2 diabetes, P = 0.01) but not
for HbA1c >8.0 or >9.0%. There were no statistically significant differences
in medication initiation at any level of elevated blood pressure or LDL
(data not shown).

We constructed multivariate logistic regression models to identity
independent predictors of change in therapy among patients above goal at the
target visit. Factors associated with glycemic therapy intensification
included attendance at a diabetes/endocrinology clinic (adjusted odds ratio
[aOR] 2.5, 95% CI 2.0-3.2), current use of insulin (1.3, 1.01-1.7),
decreasing age (1.09/decade, 1.01-1.2), and increasing HbA1c level
(1.3/unit, 1.2-1.3). For control of blood pressure and cholesterol, only
higher risk factor levels at baseline significantly predicted initiation of
corresponding therapy at the target visit: the aOR for antihypertensive
medication initiation was 4.3 (95% CI 3.0-8.1) for every 10-mmHg increase in
systolic and 2.9 (1.8-6.5) for every 10-mmHg increase in diastolic blood
pressure, whereas the aOR for initiating lipid-lowering agents was 10.2
(6.1-30.5) for every 10-mg/l increase in LDL cholesterol. In this
exploratory multivariate analysis, demographic factors such as age,
race/ethnicity, type of diabetes, and overall cardiovascular risk (as
represented by diagnosed CAD and by concurrent elevations of other risk
factors such as blood pressure in the analysis of lipid therapy change and
vice versa) were not significantly associated with corresponding changes in
therapy at the target visit.

CONCLUSIONS- A very high proportion of patients cared for in this sample of
academic medical center ambulatory clinics received annual HbA1c, blood
pressure, and cholesterol measurement. However, the proportion of patients
meeting corresponding goals of risk factor control was considerably lower.
Moreover, rates of medication initiation and dose adjustment for patients
with elevated risk factor levels seemed to be low. Because appropriate
medication adjustment is a critical intermediate step between measurement
and effective control, our findings suggest that future efforts to improve
the quality of diabetes care should focus on rates of, and barriers to,
medical regimen changes.

The proportion of academic medical center patients reaching recommended
goals for all three diabetes-related risk factors, although low in absolute
terms, was higher than the national average (11.8 vs. 7.3%) estimated by the
NHANES 1999-2000 (n = 441) (18). In addition, there was a high prevalence of
diabetes education and other recommended practices, particularly in
diabetes/endocrinology practices.

Despite these generally favorable levels of commonly applied quality
measures, significant proportions of patients above their risk factor goal
remained untreated, and there were low rates of medication initiation and
dose adjustment during the target clinic visit in these above-goal patients.
Our finding of infrequent hypertensive therapy adjustment is consistent with
results from prior studies of patients with diabetes cared for in Veterans
Association hospitals (19). These data add to the literature demonstrating
that excellent performance on diabetes care process measures does not
necessarily translate into adequate metabolic control (15,18), the key
mechanism leading to reduced risk of diabetes complications.

Although patient education and lifestyle counseling are fundamental to
effective diabetes management, titration of medical therapy represents the
major strategy by which levels of glucose, blood pressure, and lipids are
lowered to improve patient outcomes. Lack of medication adjustment in
patients not meeting therapeutic goals of therapy has been termed "clinical
inertia" and has been associated with poor risk factor control (20-22).

The decision to initiate or increase medical therapy can be complex, is
poorly understood, and requires collaboration between physicians and
patients. Patients with complex chronic diseases such as diabetes can expect
to see a physician for perhaps 20 min approximately every 3 months (23).
Prior research has implicated time limitations and competing demands
(24,25), medication costs and burden of comorbid illness (26,27), and clinic
organization as potential barriers to evidence-based care (28,29). Current
elforts to overcome barriers to therapy intensification have included
"academic detailing" of physicians and use of treatment protocols by
midlevel providers (30) and informatics-based decision support (31). In one
innovative study, physicians received content-rich E-mail messages linked to
the electronic medical record that allowed them to view timely test result
information and make corresponding prescription changes with "one-click"
order writing (32). More research is needed to better understand the
clinical process of medication initiation and adjustment for diabetes
control and to identify effective strategies for overcoming barriers to
making these changes.

Several limitations of our study must be considered. Our analysis of the
actions at a single visit does not account for the series of changes that
may occur over consecutive visits or for the acute problems that can
dominate a single visit to the exclusion of other problems. However, other
studies suggest that inaction at one visit is likely to reflect inaction
over a series of visits, at least for hypertension management (33). In
addition, although we did identify low rates of initiation among untreated
patients with elevated blood pressure and cholesterol levels, we did not
collect sufficiently detailed medication adjustment data for the subset of
patients already on therapy. Further research is needed to confirm the
reasonable assumption that rates of medication change are also low in this
patient subset. Finally, our patient sampling method may have preferentially
selected patients more engaged in regular care. To the extent that this is
true, our finding of low rates of medication initiation and adjustment in
our study cohort is even more striking. Although more clinical detail is
required to fully understand the management decision for an individual
patient at a single clinic visit, our population-based assessment of
medication change patterns per clinic visit represents an important and
innovative approach to measuring quality of diabetes care.

Initial efforts to standardize and improve the quality of diabetes care
focused on easily assessed parameters such as screening rates and measured
risk factor levels (23). Despite high risk factor testing rates, a minority
of visits in our analyses resulted in medication adjustment. This marked
discrepancy between very high levels of risk factor testing and relatively
low levels of actual risk factor control points to the need for novel
measures of clinical quality in diabetes and other chronic disease care. A
new paradigm for quality measurement focused on facilitating the process of
initiating and advancing effective medical therapies in chronic,
medication-intensive diseases like type 2 diabetes may be needed. Our
findings suggest that attention must now be turned to the next critical step
in the management pathway leading to reduced risk factor levels: overcoming
barriers to effective medical regimen changes.

(C) 2005 Diabetes Care. via ProQuest Information and Learning Company; All
Rights Reserved

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