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Health Care Use of Individuals With Diabetes in an Employer-Based Insurance Population
Sarah B. Laditka, PhD;
Melanie P. Mastanduno, RN, MPH;
James N. Laditka, DA, MPA
Arch Intern Med. 2001;161:1301-1308.
ABSTRACT
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Background Individuals with diabetes use more health care resources than those
without the disease. Much less is known about such differences associated
with different forms of diabetes.
Methods People with types 1 and 2 diabetes were identified from claims of a
commercial insurer with an enrollment of 828 208. Age- and sex-adjusted
rates and observed-to-expected ratios for health care services use, costs,
and relative value units were compared for individuals with diabetes and the
total plan population.
Results We identified 13 563 individuals with diabetes (including 4349
with type 1 and 8810 with type 2 diabetes). The diabetic population was 1.6%
of the total population, but had 9.4% of costs. Individuals with both types
of diabetes had higher rates for use of inpatient, outpatient, and professional
services. Compared with the total population, inpatient rates for the total
diabetic population (for those with type 1 diabetes), were 4.9 (8.3) times
higher for established complications of diabetes such as acute myocardial
infarction, 9.8 (22.1) times higher for heart failure, 5.6 (8.3) times higher
for coronary artery bypass, and 5.1 (8.9) times higher for cardiac catheterization
(P < .001 for all). The following relative value
unit ratios for physician services were substantially higher for the total
diabetic population (for those with type 1 diabetes): 13.2 (27.9) times higher
for endocrinologists, 6.3 (12.9) for ophthalmologists, and 9.4 (27.8) for
nephrologists.
Conclusions Use, costs, and intensity of resources used were substantially higher
for individuals with diabetes, and markedly higher for the population with
type 1 diabetes. Our findings show that people with type 1 diabetes are at
substantially higher risk for serious complications than those with type 2
diabetes.
INTRODUCTION
DIABETES ranks among the most serious chronic diseases, with high risks
for multisystem complications.1-2
Its incidence and prevalence in the United States have increased notably during
the past several decades.3-5
Population aging brings projections of substantial further prevalence increases
during the next several decades.1, 4
Thus, clinicians, insurers, and health care policy makers should better understand
patterns of use of health care resources and costs for individuals with diabetes.
Chronic complications for people with diabetes have been well documented.
They include coronary artery disease,2, 6-7
peripheral vascular disease,8 cerebrovascular
disease,6 nephropathy,8
neuropathy,2 and retinopathy.2
People with diabetes are hospitalized more frequently than those without the
disease9 and use physician services at a higher
rate than nondiabetic individuals.6, 10
Costs associated with diabetes are substantial; in 1997, direct health care
costs were estimated at $44.1 billion in the United States, whereas indirect
costs such as lost productivity summed to an estimated $54.1 billion.11 Studies have found substantially greater costs for
individuals with diabetes than for those without the disease.8, 10, 12-14
There is also evidence of considerably reduced quality of life and shorter
life expectancies for people with diabetes.15-16
Much less is known about differences in resource use and cost patterns
between people with different forms of the disease.17
Consistent with recent guidelines of the American Diabetes Association (ADA),
we distinguish between people with type 1 and type 2 diabetes.18-19
Before the ADA established the type 1 and type 2 classifications, diabetic
individuals were distinguished as having insulin- or non–insulin-dependent
diabetes mellitus. This classification was largely determined by insulin use.
The new ADA guidelines classify individuals as having type 1 diabetes when
their pancreatic islet ß-cells do not produce insulin.19
Individuals are classified as having type 2 diabetes when they have a relative,
instead of absolute, insulin deficiency.19
Those with type 2 diabetes may or may not require insulin therapy.19 Although the causes of type 1 and type 2 diabetes
differ, both carry risks for serious long-term health problems.18-19
A few studies distinguishing between type 1 and type 2 diabetes have found
that individuals with type 1 diabetes are at higher risk for long-term complications,20-22 use more physician
services,23 and have higher costs than those
with type 2 diabetes.24
Most previous epidemiological studies of diabetes have examined use
of health care resources by using a major health event, such as acute myocardial
infarction, and focusing on end-point complications.20-21
This approach may overstate the incidence of serious complications associated
with the disease. Furthermore, this approach gives inadequate attention to
the long interval between the onset of diabetes and the development of serious
chronic complications. It may therefore underestimate the impact of the disease
on more routine use of health care resources and costs. Since many of the
more serious long-term complications of diabetes emerge at later ages, epidemiological
analyses contingent on major health events are likely to especially underestimate
use and costs for younger populations, such as those covered by employer-based
health insurance. Thus, a greater understanding of differential effects of
type 1 and type 2 diabetes among people of working age would be useful, particularly
if the analysis captures the experience of a representative sample of individuals
by avoiding major health event eligibility criteria.
We used administrative data to estimate use of health care resources
and costs, distinguishing between people with type 1 and type 2 diabetes.
We also compared the health care use and costs of the diabetic population
with those of a large comparison population. Administrative data provide ready
access to timely information about trends in use and costs. The size of the
administrative data set used in this study allowed us to examine the health
care experience of a large number of individuals. This permitted analyses
of more clinical categories than data from more in-depth surveys, where costs
of collecting information constrain sample size.25-28
The approach used in this analysis complements traditional epidemiological
methods. The most notable advantage of the approach used in this study is
that it overcomes the limitation of many epidemiological methods used to examine
morbidity associated with diabetes, ie, our approach is not contingent on
a major health event.
SUBJECTS AND METHODS
The sample for this study was the entire enrolled population of a commercial
insurer located in Ohio (828 208 individuals). Almost all members resided
within the state. This analysis included all claims information from January
1 through December 31, 1996. No single industry dominated the enrollment.
Individuals in our analysis represent a racial mix consistent with the racial
mix of the working-aged population of Ohio. Once employed by a participating
business, no individuals were excluded from enrollment based on health history.
The data did not include individuals eligible for benefits under Medicaid
or Medicare. All individuals in this analysis were younger than 65 years.
Claims information was provided by the insurer to the Codman Research
Group, Andover, Mass, a health care decision support company. The protocol
for submitting claims to the insurer was uniform among participating providers.
Extensive quality checks were performed on the raw data to verify the information
before constructing the data set used for this analysis. All claims were validated
(eg, for use of legal codes). Duplicate claims were eliminated. Claims were
then assigned into groups of clinically homogeneous service types using the International Classification of Diseases, Ninth Revision, Clinical
Modification (ICD-9-CM) diagnosis and procedure
codes29 and procedure codes from Current Procedural Terminology (CPT-4).30 Inpatient conditions and procedures in our analysis
were based on diagnosis-related groups, which were created using a hierarchical
clinical grouping algorithm with all ICD-9-CM diagnosis
and procedure codes from inpatient discharge records.
For each claim submitted, the insurer recorded an allowed dollar amount,
in addition to charges, that incorporated subscriber cost-sharing information
(eg, deductibles and co-payments). All costs in this analysis were based on
allowed dollars paid per claim. To provide a comprehensive picture of resource
consumption, all unique claims submitted by providers for payment were included
in the data set. If the insurer paid the claim, or a portion of the claim,
the claim diagnosis and procedure categories were included for the individual,
along with the allowed dollar amount. Diagnoses and procedures for denied
claims were also included in the data. The allowed dollar amount for denied
claims was recorded as 0. Proprietary software (Pandora Managed Care Information
System31) was used to compile, organize, and
analyze the data. All claims for each enrollee were aggregated under a unique
member identifier. Next, the data were organized in the following 3 ways:
(1) by total diabetic, type 1 diabetic, type 2 diabetic, and total populations
for all services and costs; (2) by medical event (all claims for a defined
type of service or procedure); and (3) by demographic category (age and sex
cohorts).
In addition to ICD-9-CM and CPT-4 codes, our analysis included information about total relative
value units (RVUs) for physician services. The RVUs were based on the Resource-Based
Relative Value Scale, which was implemented in 1992 as a payment system for
physician services provided to Medicare beneficiaries.32-34
Commercial insurers are increasingly using the scale to develop fee schedules.
Relative value units, like rates of use of services and dollars, can be used
to compare medical care resource consumption among populations. They provide
a useful supplement to use and cost comparisons. They take into account factors
such as amount of work and effort, technical training, and practice expense
required to perform a given service, regardless of physician specialty. A
service provided by a specialist may be billed at a higher rate than the equivalent
service provided by a primary care physician; regardless of these charge differences,
however, the RVU for the given service is the same. Thus, RVUs allow comparisons
of resource use that are independent of market rate mechanisms, reimbursement
controls, and differential access to specialists across various forms of managed
care.
We used ICD-9-CM diagnosis codes (250.00-250.93)
to classify individuals as having diabetes. The following criteria for classification
were used: at least 1 inpatient admission for which the principal diagnosis
was recorded as diabetes, or at least 2 inpatient admissions or 2 outpatient
facility or physician office visit claims for which any diagnosis was recorded
as diabetes. Claims for laboratory, pathology, or radiology services were
not used to identify individuals with diabetes, since their use could incorrectly
identify individuals as having diabetes based on the reason for testing (eg,
screening) rather than test results. However, to ensure a complete representation
of resource consumption, these claims were included in the analyses of use
of resources and cost, with individuals grouped by population using the other
criteria. The selection criteria were designed to minimize the percentage
of nondiabetic individuals included in the diabetic population, ie, to minimize
the amount of false-positive data. When individuals were identified as having
diabetes, ICD-9-CM diagnosis codes were again used
to classify them into the type 1 or type 2 category. The type 1 category includes
all individuals with any ICD-9-CM diagnosis code
from 250.0x through 250.9x,
where x is the fifth digit, with a value of 1 or
3. The type 2 category includes all people with ICD-9-CM diagnosis codes from 250.0x through 250.9x, where x is the fifth digit
with a value of 0 or 2. Individuals identified as having diabetes, but with
all recorded diabetes ICD-9-CM diagnosis codes absent
the fifth digit, were assigned to the category "diabetes, type not specified."
Of the 828 208 plan enrollees, 13 563 individuals were identified
as having diabetes. Of the total diabetic population, 4349 were classified
as having type 1 diabetes, 8810 were classified as having type 2 diabetes,
and 404 were assigned to the nonspecified category.
For all individuals in the data set, we identified all ICD-9-CM diagnoses and all CPT-4 procedures.
When a procedure was repeated 2 or more times, procedures and associated costs
were summed. Thus, we treated each procedure as a separate event of health
care resource use. Once a given diagnosis was identified, the individual with
the diagnosis was assigned to a group of individuals with the same diagnosis.
Each individual could be assigned only once to a given diagnosis, but multiple
treatments related to that diagnosis could be recorded and analyzed.
We grouped ICD-9-CM diagnoses and CPT-4 procedures into standard categories and compared use and costs
for selected ICD-9-CM and CPT-4 codes among the diabetic (total, type 1, and type 2) populations and
the total study population. We used the indirect method to calculate age-
and sex-adjusted observed-to-expected ratios for use, costs, and RVUs35 based on ICD-9-CM diagnoses
and CPT-4 procedures for the diabetic (total, type
1, and type 2) populations, comparing each age- and sex-adjusted ratio with
that of the total enrolled population (the benchmark rate). To calculate expected
values, rates for the standard population were determined separately for men
and women in each of 12 age categories. These rates were applied to corresponding
age/sex categories of the target population (eg, total diabetic population)
to identify the expected number of occurrences in the target population. These
expected values for the age/sex categories of the target population were then
summed to yield the total number of expected occurrences. The target population's
observed value was then compared with its expected value, producing the observed-to-expected
ratio. Following an established practice of epidemiological research,36-38 the total plan population
was used as the comparison (standard) group for the diabetic populations in
all comparisons of use of health care resources in this study. Since our results
were derived using the total rather than the nondiabetic population as the
comparison population, it is likely that they understate cost and use differences
between these groups. The diabetic population constitutes only 1.6% of the
total population, however, so the degree of understatement is likely to be
slight. The  2 test was used to determine whether rates of
use were statistically significantly higher (or lower) than the benchmark
rate. Tests of statistical significance were not applied to costs or RVUs.
RESULTS
Table 1 shows the age and
sex distributions of the nondiabetic and the total diabetic populations. Notably
larger percentages of individuals in the diabetic population were concentrated
in the older age groups, compared with people in the nondiabetic population.
This is an expected finding, since adult-onset diabetes is more common in
people 40 years and older. In results not shown, the type 2 diabetic population
was older than the type 1 diabetic population (mean ages, 50.8 and 45.7 years,
respectively).
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Table 1. Age and Sex Distributions of Nondiabetic and Diabetic Insured
Populations*
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Although the total diabetic population constituted only 1.6% of the
total population, it accounted for 9.4% of overall costs. The analogous figures
were 0.1% and 4.8% for the type 1 population, and 1.1% and 4.5% for the type
2 population. Total annual per capita costs for the nondiabetic population
were $909, compared with $5659 for the diabetic population. Thus costs were
more than 6 times higher for individuals with diabetes than for those without
the disease. A larger percentage of people in the diabetic population were
older, and older individuals typically consume more health care resources
than younger ones. However, the older age of the diabetic population did not
account for the higher costs (Figure 1).
For each age group, the proportion of total costs attributable to individuals
with diabetes was substantially higher than the proportion of individuals
in that age group with diabetes.
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Figure 1. Diabetic individuals as a percentage
of total health care plan population and expenditures. No tests of statistical
significance were applied.
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To investigate more specific sources of the diabetic population's higher
health care resource consumption, age- and sex-adjusted observed-to-expected
ratios were used to compare resource use and costs of the diabetic and total
populations. These comparisons were made for inpatient facility and outpatient
care and for all professional service categories (Figure 2). Compared with the total population, rates of use of inpatient
services were more than 4 times higher for the total diabetic population,
more than 7 times higher for those with type 1 diabetes, and 3 times higher
for those with type 2 (P < .001 for all comparisons).
For hospital outpatient services, again compared with the total population,
rates of use were more than 2 times greater for the total diabetic population,
3.7 times greater for those with type 1 diabetes, and almost 2 times greater
for those with type 2 (P < .001 for all comparisons).
The professional services category includes physician visits for ambulatory-based
care, anesthesia, preventive care, and physician-billed, hospital-based care;
for laboratory and radiology services; and for services by professional providers
such as psychologists, nurse practitioners, and physician assistants. Compared
with the total population, rates for use of professional services were 2.6
times more for the total diabetic population, about 3.5 times more for those
with type 1 diabetes, and more than 2 times more for those with type 2 (P < .001 for all comparisons). Significantly higher
use rates in these categories for diabetic populations were reflected in substantially
higher age- and sex-adjusted observed-to-expected costs. For inpatient services,
compared with the total population, costs were more than 4.8 times greater
for the total diabetic population, about 8.7 times greater for those with
type 1 diabetes, and more than 3 times greater for those with type 2. For
outpatient services, costs were 2.8 times more for the total diabetic population,
5 times more for those with type 1 diabetes, and 2 times more for those with
type 2. Again, compared with the total population, costs for professional
services were nearly 3 times greater for the total diabetic population, more
than 4 times greater for those with type 1 diabetes, and more than 2 times
greater for those with type 2. Rates of use and their differences among the
various populations for each of these service categories are roughly comparable
to the corresponding cost rates and their differences. This suggests that
the primary determinant of higher costs for diabetic individuals is their
greater use of services, rather than higher cost per service.
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Figure 2. Observed-to-expected ratios for
use and expenditures for inpatient, outpatient, and professional services
for total, type 1, and type 2 diabetic populations. Categories indicated are
inpatient services and procedures, outpatient facility services and procedures,
and professional services. Use ratios were all statistically significant at P < .001. No tests of statistical significance were applied for
expenditures.
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We also examined use of outpatient facilities, physician services, and
ancillary services, such as laboratory and radiology tests. Here we compared
use among the total diabetic, type 1 diabetic, type 2 diabetic, and total
populations for selected high-volume ambulatory categories (Figure 3). All rates were adjusted for age and sex. The category
of outpatient facility encounters includes services such as a single visit
to a hospital outpatient department or to a free-standing ambulatory surgery
facility, where multiple procedures were performed in the same visit (as in
the case where a single visit might include a physician examination, sedation,
and diagnostic colonoscopy). Such instances were counted as single encounters.
For outpatient facility encounters, the rate was 2.5 times higher for the
total diabetic population, 3.8 times higher for those with type 1 diabetes,
and nearly 2 times higher for those with type 2 than for the total population
(P < .001 in all cases). For emergency department
visits, the rate was more than 2 times higher for the total diabetic population,
more than 3 times higher for those with type 1 diabetes, and 1.7 times higher
for those with type 2 than for the total population (P
< .001 in all instances). For physician office visits, the rate was about
2.4 times higher for the total diabetic population, 2.7 times higher for those
with type 1 diabetes, and about 2.2 times higher for those with type 2 than
for the total population (P < .001 in all cases).
In the physician consultation category, rates were more than 3 times higher
for the total diabetic population, more than 5 times higher for those with
type 1 diabetes, and about 2.3 times higher for those with type 2 compared
with the total population (P < .001 in all instances).
Diabetic individuals were also more likely to use ancillary services, such
as laboratory and radiology tests; the rate was 2.8 times higher for the total
diabetic population, 3.3 times higher for those with type 1 diabetes, and
2.5 times higher for those with type 2 (P < .001
in all cases). Collectively, these findings indicate that individuals with
diabetes used significantly more physician and ancillary services, and that
the highest rate was in the type 1 diabetic population.
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Figure 3. Observed-to-expected ratios for
facility and physician encounters for total, type 1, and type 2 diabetic populations.
Observed-to-expected ratios in all categories were statistically significant
at P < .001.
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To identify differences in the volume and intensity of resources used
by physicians to provide care to diabetic populations, we calculated the age-
and sex-adjusted observed-to-expected ratio of total RVUs for primary care
physicians and selected physician specialists (Figure 4). The observed-to-expected RVU ratios generated for physician
services provide a combined measure of the volume of services used and the
intensity of those services. In all instances, observed-to-expected RVUs for
physician services to diabetic populations were notably higher than those
for the total population. This was especially the case for physicians who
commonly treat long-term complications of the disease, such as ophthalmologists,
endocrinologists, and nephrologists. For primary care physicians, the RVU
observed-to-expected ratio was 2.8 times higher for the total diabetic population
than for the total population, 3.5 times higher for those with type 1 diabetes,
and 2.5 times higher for those with type 2. Endocrinologists specialize in
the care of individuals with diabetes. In this category, again compared with
the total population, the RVU measure was 13.2 times higher for the total
diabetic population, 27.9 times higher for those with type 1 diabetes, and
7 times higher for those with type 2. In the ophthalmology specialist category,
compared with the total population, the RVU measure was 6.3 times higher for
the total diabetic population, almost 13 times higher for those with type
1 diabetes, and 3.7 times higher for those with type 2. In the nephrology
specialist category, compared with the total population, the RVU measure was
9.4 times higher for the total diabetic population, almost 28 times higher
for those with type 1 diabetes, and 2.1 times higher for those with type 2.
These results reinforce our finding of greater use of physicians among diabetic
populations. They indicate that the intensity level of care provided to diabetic
individuals by physicians, particularly for the type 1 diabetic population,
is markedly higher than the corresponding level for individuals without the
disease. This is true for primary care physicians and for a broad spectrum
of physician specialists.
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Figure 4. Observed-to-expected ratios of
relative value units (RVUs) for primary care and referral specialists for
total, type 1, and type 2 diabetic populations. No tests of statistical significance
were applied.
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To further explore the markedly higher use of inpatient services by
the diabetic population, selected inpatient conditions and procedures were
examined (using ICD-9-CM and CPT-4 codes), comparing inpatient use among the diabetic populations and
the total population (Table 2).
All rates were adjusted for age and sex. The diabetic populations had significantly
higher rates for conditions and procedures commonly associated with long-term
complications of diabetes. Rates of cardiac-related conditions and procedures
were significantly higher in the diabetic populations; the total diabetic
population had a stroke rate nearly 6 times higher and an acute myocardial
infarction rate about 5 times higher (P < .001
in both instances). Rates of cardiac catheterization, coronary artery bypass,
and coronary angioplasty were all about 5 times higher than those of the total
population (P < .001 in all cases). Rates were
also elevated for other conditions and procedures related to long-term complications
of diabetes; compared with the total population, the total diabetic population
had a rate of cellulitis more than 8 times higher, of kidney and urinary infections
more than 6 times higher, of heart failure nearly 10 times higher, of carotid
endarterectomy about 7 times higher, and of peripheral vascular disease 4
times higher (P < .001 in all instances). The
renal dialysis rate for the total diabetic population was more than 11 times
higher than that of the total population, and the skin graft rate was more
than 10 times higher. In these instances, the 2 test could
not be applied because of the small number of expected events for the total
diabetic population. As for eye procedures, participating physicians moved
substantially in the early 1990s from performing eye procedures on an inpatient
to an outpatient basis. Compared with the total plan population, the rate
of outpatient eye procedures (results not shown) was 5 times higher for the
total diabetic population, 11 times higher for those with type 1 diabetes,
and 2.6 times higher for those with type 2 (P <
.001 in all instances).
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Table 2. Observed-to-Expected Ratios for Inpatient Admission Categories
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We also found that age- and sex-adjusted inpatient rates for the diabetic
populations were greater than those for the total population for conditions
and procedures not commonly associated with the disease. Compared with that
of the total population, the rate of the total diabetic population was 2.8
times higher for gastrointestinal tract hemorrhage, 2.7 times higher for gastrointestinal
tract obstruction, 2.6 times higher for appendicitis and appendectomy, 2.4
times higher for major joint procedures, and more than 2 times higher for
major large- and small-bowel procedures and back and neck procedures (P < .001 in all cases). These results indicate that
diabetic individuals receive treatment for a broad spectrum of conditions
at significantly higher rates than people without the disease. This includes
conditions and procedures commonly associated with diabetes and those not
generally associated with the disease. In almost all instances, rates of use
were substantially higher for the type 1 than for the type 2 diabetic population.
COMMENT
Using a large sample of individuals covered by employer-based health
insurance, we examined the use of health care resources and economic costs
of a defined population of people younger than 65 years with diabetes. We
distinguished between individuals with type 1 and type 2 diabetes, and compared
their use of health care resources and health care costs, with benchmark rates
established by the total enrolled population. The approach used in our study
relies on analysis of administrative data provided by a large commercial insurer.
Our findings for the use of health care resources by the diabetic population
are consistent with morbidity patterns generally associated with diabetes,
patterns identified in studies that use more conventional epidemiological
approaches. Individuals in the diabetic populations were significantly more
likely to be treated for conditions and procedures related to complications
of the disease such as cardiovascular, ophthalmologic, renal, and peripheral
vascular disease, than were individuals in the total plan population. We found
that in the diabetic population, use of resouces, costs, and intensity of
resource use (RVUs) were markedly higher for individuals with type 1 diabetes
than for those with type 2 diabetes. Direct tests of statistical significance
were not applied to comparisons of the type 1 and type 2 diabetic populations.
Nonetheless, differences in resource use between these 2 groups were substantively
large in most instances. Our findings reinforce the importance of distinguishing
between type 1 and type 2 diabetes.
In a related result, the RVU findings indicate that physician services
provided to individuals with diabetes are notably more resource intensive
than those provided to people in the total plan population. In addition, again
measured by RVUs, individuals with type 1 diabetes used substantially more
resources than those with type 2. Those with type 1 diabetes also visited
primary care physicians at a higher rate those with type 2. This suggests
that these individuals have access to preventive and routine follow-up care,
but that their medical management by primary care physicians may not prevent
referral to and treatment by specialists. The chronic nature of many complications
of diabetes may simply require more resource-intensive interventions.
Although the data and methods used for our analysis complement more
traditional epidemiological approaches, several limitations of this study
should be acknowledged. Our data are not representative of the entire US population.
Given our reliance on commercial insurer claims information, these data are
unlikely to be representative of uninsured populations or Medicaid populations.
Because our analysis excludes people 65 years and older, it is also not representative
of older populations. Furthermore, our data are restricted to the enrolled
population of a single populous state.
Ohio's 1996 diabetes prevalence for all ages ranked it in a middle range
of prevalence, along with most states.5 The
prevalence of diabetes among working-aged individuals in our sample is 2.2%,
considerably less than the 3.3% prevalence for Ohio's working-aged population
in 1996.39-41
Much of this difference is likely due to the prevalence of diabetes among
working-aged individuals not included in our study, ie, the uninsured, disabled
individuals covered by Medicare, those who receive coverage through the military,
and those served by Medicaid. A portion of the difference may also result
from our inability to identify separately the use of health care resources
by individuals who may have received a diagnosis of diabetes before the study,
but whose resource use during the study period did not fulfill our selection
criteria. Using the Medical Expenditure Panel Survey, we estimated a 1996
national diabetes prevalence for the working-aged population of 3.1%; for
those of working age covered by private group health insurance, the prevalence
was 2.7%. Including enrollees' children, the prevalence was 2.4%.42
Another potential limitation is that individuals covered by this commercial
insurer could select from as many as 5 benefit plan options, ranging from
a traditional indemnity plan to a capitated managed care plan. Our data did
not allow us to control at the level of the individual for self-selection
into particular plans. Across the 5 benefit plans, the proportion of each
plan constituted by individuals with diabetes was reasonably consistent. Moreover,
this insurer provided generous benefits and comprehensive hospital coverage
in all of its plans. The primary differences between the benefit plans were
the degree of cost sharing, differing deductible and co-payment levels, and
the form of medical management. Most research has shown that the degree of
medical management does not play an important role in health care provided
by physicians to diabetic individuals; physicians usually use similar treatment
protocols, regardless of insurance type.43-44
In addition, research has demonstrated that the demand for short-term health
care resources such as those examined in this study is highly inelastic.45-46 These findings imply that differences
in medical management and cost sharing are not likely to account for differences
in resource consumption between the diabetic and total populations in our
analysis. The facts that billing standards were uniform across all plans and
that all claims were to be submitted by providers even when the patient was
part of a managed health care plan further reduce the potential influence
of this limitation. Further, the insurer had designed the plans to encourage
optimal service levels, with incentives for providers to avoid excessively
large and small claim volumes. It therefore seems unlikely that enrollee self-selection
accounts in large measure for our findings.
The most important limitation is that, given the high prevalence of
type 1 diabetes relative to type 2 diabetes in our data, it is likely that
a number of people with type 2 diabetes who required insulin were misclassified
as having type 1 diabetes. In the population at large, individuals with type
2 diabetes constitute about 90% of all diabetics.47
Since the prevalence of type 2 diabetes increases dramatically with age, and
our analysis was restricted to people younger than 65 years, it is reasonable
to expect that our sample's prevalence ratio of type 1 to type 2 diabetes
would be higher than that of the general population. However, one factor is
likely to contribute to misclassification of those with type 1 and type 2
diabetes in our data. The new ADA guidelines, switching from the insulin-
and non–insulin-dependent diabetes mellitus to the types 1 and 2 classifications,
became effective in October 1993.48 It takes
time before changes of this sort become widely adopted in the medical community,
and before practitioners incorporate them in daily practice. Many practitioners
may have continued to rely on the familiar older classification standard despite
the new guidelines. In our data, it seems most likely that people classified
by physicians as having type 1 diabetes had type 1 diabetes or type 2 diabetes
requiring insulin.
Regardless of any classification problems in the period after the ADA's
1993 policy change, it remains clear from our findings that people in the
type 1 diabetic group used resources more intensively than those not requiring
insulin. Thus, regardless of the classification limitation, our results highlight
the importance of glycemic control. The diagnosis limitation in this study
applies to any research based on administrative data. This limitation also
affects clinical practice studies in medical centers, hospitals, and group
practice settings. Our findings, therefore, highlight the need for communicating
to the medical community the new diagnosis standards and the need for accurate
diagnoses in claims.
Our results provide a better understanding of morbidity differences
between individuals with type 1 and type 2 diabetes. Both forms of the disease
carry substantial risks for serious long-term complications, although type
2 diabetes is much more prevalent and is often complicated by hypertension,
dyslipidemia, and obesity.18-19
However, our findings confirm that type 1 diabetes is associated with substantially
greater per capita use of health care resources and costs. Insurers can use
these results to inform risk adjustments for people in these populations,
or calculations of the consumption of health care resources and financial
effects of including type 1 and type 2 diabetic individuals in employer-based
health insurance plans.49-50 From
the perspective of the clinician, our findings provide insight into medical
problems that are more common among diabetic individuals and highlight the
fact that individuals with type 1 diabetes are at substantially higher risk
for serious complications than those with type 2. Our findings suggest an
opportunity to focus improved medical management on diabetic individuals with
the greatest risk for complications.51-52
Individuals with diabetes also need to play a greater role in managing the
disease.23, 53 Many studies indicate
an opportunity for enhanced management of diabetes, such as intensive preventive
care and screening23, 53-55
and intensive pharmacological therapy.56-57
Our results suggest the advisability of creating a special focus on patients
with type 1 diabetes.
AUTHOR INFORMATION
Accepted for publication December 4, 2000.
We thank the Codman Group Inc, whose Pandora Managed Care Information
System supported this analysis.
Presented in part at the Association for Health Services Research Conference,
Los Angeles, Calif, June 26, 2000.
We are grateful to Elizabeth Blackmer, PhD; Richard Comi, MD; Manon
Spitzer Rubin, MA; Mary Wood, MS; and 3 anonymous reviewers for useful comments
on earlier versions of this article.
Corresponding author and reprints: Sarah B. Laditka, PhD, Center
for Health and Aging, State University of New York Institute of Technology
at Utica/Rome, PO Box 3050, Utica, NY 13504-3050 (e-mail: laditks{at}sunyit.edu).
From the Center for Health and Aging, State University of New York
Institute of Technology at Utica/Rome (Dr S. Laditka); Dartmouth Hitchcock
Medical Center, Lebanon, NH (Ms Mastanduno); and the Center for Policy Research,
Syracuse University, Syracuse, NY (Dr J. Laditka).
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