Association Between Sustained Glycated Hemoglobin Control and Healthcare Costs

Diabetes is one of the most common and costly diseases, affecting 25.8 million people, or 8.3% of the US population.¹ Diabetes is also the seventhleading cause of death in the United States and can result in serious health complications including heart disease, stroke, kidney failure, blindness, and lower-extremity amputations. In 2007, the estimated cost of diabetes in the United States was $1.7 billion, with direct medical expenditures for people with diabetes averaging nearly 2.4 times that of people without the disease.¹

Glycated hemoglobin (A1C) is one of the most common measurements used in the assessment of glycemic control; it is thought to reflect the average glycemic control over several months² and predict the occurrence of diabetes-related complications.³ The most recent guidelines put forth by the American Diabetes Association recommend lowering A1C to below or around 7%.⁴ This recommendation was based on findings from multiple trials performed in both type 1 and type 2 diabetes patients demonstrating significant decreases in microvascular and neuropathic complications associated with reductions in A1C.^5-7 In addition to the microvascular benefits of intensive glycemic control, both the Diabetes Control and Complications Trial Research Group and UK Prospective Diabetes Study demonstrated the potential of intensive glucose control to lower the risk of cardiovascular events.

The percentage of diabetic patients with poor glycemic control (A1C >9.0%) fell from 21.0% in 1999 to 2000 and 17.8% in 2001 to 2002 to 12.4% in 2003 to 2004.⁸ Despite these encouraging trends, many patients still struggle to achieve and/or sustain optimal glycemic control over extended periods of time (ie, years).

Some prior evidence suggests that having an A1C level of less than 7% is associated with lower costs of medical care.^9-13 However, many of these studies examined crosssectional relationships that may be confounded by severity of disease. Although all studies required a diagnosis of diabetes, there may have been some false positives (ie, people with a diagnosis and A1C <7% who do not really have diabetes). Also, some people have diabetes of low severity and would not be expected to have high costs. To address these issues, our study started with a sample of patients with poor initial control (A1C >9%) and used propensity score matching to defi ne a comparable cohort.

The purpose of this study was to examine the relationship between sustained glycemic control and total direct healthcare costs among patients with diabetes with an initial A1C level greater than or equal to 9%. Specifically, this study sought to test the hypothesis that lowering A1C from above 9% to below 7%—and sustaining this level&mdash;reduces healthcare costs among patients with diabetes mellitus.

METHODS

We conducted a retrospective analysis of administrative data from patients with diabetes enrolled in a large health plan in Hawaii. To be included in the study, patients needed to meet the following criteria: (1) be identified as having diabetes, by having either 2 or more claims for type 2 diabetes in medical claims (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD- 9-CM] code 250.xx) or at least 1 prescription for an oral hypoglycemic agent and/or insulin; (2) be at least 18 but under 75 years old; (3) be enrolled with medical and drug coverage; and (4) have at least 1 A1C value greater than 9% in 2006. This level was chosen because the National Committee on Quality Assurance’s Healthcare Effectiveness Data and Information Set uses a level of 9% to indicate poor A1C control.

Patient information including age, sex, isle of residence, and type of coverage (health maintenance organization, preferred provider organization, Medicare cost contract) was obtained from administrative data. Patient morbidity level was determined by using ICD-9-CM codes according to the Johns Hopkins Adjusted Clinical Group methodology; levels of 4 or 5 on the 5-point scale were considered high morbidity.¹⁴ In addition, using disease management algorithms, we created dichotomous variables to identify patients with coronary artery disease and congestive heart failure because these are conditions known to be prevalent in patients with diabetes and to increase costs. Diagnoses of diabetes, coronary artery disease, and congestive heart failure were confi rmed whenever possible through contacting members and their physicians. A physician’s confirmation was required to exclude false positives.

During the baseline year (2006), we identifi ed all patients with diabetes who had a A1C level of greater than 9% (4667 out of 56,921 patients with diabetes). For each subsequent year (2007-2009), we calculated mean A1C levels for these patients. We used propensity scores¹⁵ to identify a comparable control cohort for those with A1C of less than 7% in 2007 using demographic and utilization data, including age, sex, isle of residence, type of insurance coverage, comorbid conditions, diabetes duration, number of distinct medications, and morbidity level. We conducted cross-sectional analyses, comparing the average annual direct medical costs of patients whose mean A1C level was less than 7% with the costs for those who did not meet this glycemic level in the matched sample (4093 observations for 1304 individuals).

For longitudinal analyses, we created a dichotomous variable indicating whether or not the patient had sustained A1C control at target levels (A1C <7%) for all 3 years (2007-2009). Of the 1304 individuals in the matched sample, 518 were enrolled, had A1C values for all 4 years (2006 through 2009), and were included in the longitudinal analyses of cost change.

We calculated average baseline costs of care (2006) for these patients and subsequent average annual costs in years 2007 through 2009 by using medical claims data. Costs included direct medical expenses paid by the health plan. We analyzed total costs and cost broken into cost categories: facility, physician services, and pharmaceutical. All costs in the study were adjusted to constant 2009 dollars using the medical care component of the Consumer Price Index. For samples matched using propensity scores, we compared costs (total and by category) in a given year for patients with A1C levels less than 7% with the costs for patients with higher A1C levels. We also examined differences in cost changes for patients who were able to sustain A1C levels of less than 7% for 3 years compared with patients who had A1C levels higher than 7% for at least 1 year.

Next, to account for year and baseline costs, we used generalized estimating equations with robust standard errors to compare annual average healthcare costs by cost category for patients at recommended levels (A1C <7%) with the costs for patients with A1C levels at or above 7% for the matched groups.¹⁶ Interaction terms between year and A1C level were included to account for differences in the relationship over time.

Generalized linear models with a negative binomial distribution and log link were used to examine the relationship between sustained control (A1C <7% for 3 years) and direct medical costs according to cost category (total, inpatient facility, physician services, and pharmaceutical) in 2009, adjusting for baseline costs. Inpatient costs included costs of all facilities such as hospitals and long- term care institutions. Physician services included both inpatient and outpatient physician reimbursement. Institutional review board approval was obtained from the University of Hawaii. All analyses were conducted with Stata statistical software, release 11 (StataCorp, College Station, Texas).

RESULTS

Of members with A1C levels greater than or equal to 9% in 2006 (n = 4667), the percentage of members able to achieve mean A1C levels of less than 7% were 10.0% in 2007, 12.7% in 2008, and 13.3% in 2009. Only 3.6% of members with A1C levels greater than 9% in the baseline year were able to reduce their A1C level to goal (<7%) and sustain this level for 3 years.

Although there were signifi cant differences in 2007 between those achieving an A1C level of 7% in the unmatched sample (n = 4667) in terms of age, isle of residence, type of coverage, and duration of diabetes, there were no significant differences in demographic characteristics and utilization for the groups matched using propensity scores (n = 1304,

Table 1

).

For the matched sample in 2007, the mean age of those whose A1C level was less than 7% was 54 ± 0.53 years, and the mean age for those not at recommended levels was 54 ± 0.41 years. Forty-three percent of patients in both groups were female (Table 1). Most patients were in the preferred provider organization (67% of those with A1C <7% and 66% of those with A1C >7%). The average duration of diabetes was 6.9 years for both groups, and patients in both groups were taking 9 distinct medications for a year on average. Approximately 44% of patients at target had high morbidity compared with 41% of those whose A1C level was greater than or equal to 7%. With respect to comorbid conditions, 13% of patients in both groups had congestive heart failure, and 23% of patients whose A1C level was less than 7% had a history of coronary artery disease compared with 24% of patients not at recommended A1C levels. This suggests that the propensity matching was successful in creating groups that had similar observable characteristics.

Difference in Average Costs and Cost Change

In cross-sectional comparisons, the average annual costs for patients whose A1C level was less than 7% was $14,821 compared with $12,108 for the matched sample of patients whose A1C level was greater than or equal to 7%, for a difference of $2713 (95% confi dence interval [CI], $285-$5140) (

Table 2

). In contrast, when we examined the change in cost from 2006 to 2009 for patients who had sustained levels of A1C at less than 7% for all 3 years, we found that total cost of care for patients with sustained control decreased by $2207 compared with a $3006 increase for patients without sustained control, for a difference of —$5214 (95% CI, –$10,163 to –$264).

Negative Binomial Regression Results

Our negative binomial results (

Table 3A

and

Table 3B

) are consistent with fi ndings in Table 2. In the panel data analyses, costs were higher for patients whose mean A1C level was less than 7% compared with patients who had higher mean A1C values. For total costs, the incidence rate ratio (IRR) was estimated at 1.35 (95% CI, 1.28-1.44). These results were consistent across all cost categories (Table 3).

In contrast, when examining the impact of duration of A1C control on cost, we found that patients who had 3 years of sustained A1C control (A1C <7%) had smaller cost increases than patients without sustained control (IRR = 0.71; 95% CI, 0.59-0.86; Table 3). Cost ratios of patients with sustained control were signifi cantly less than 1 for all cost categories except for pharmaceutical costs, which did not differ between groups.

DISCUSSION

Fewer than 4% of the study population who had poor glycemic control in 2006 (A1C >9%) were able to reduce their A1C level to less than 7% and sustain this level for 3 years (2007-2009); however, achievement and maintenance of glycemic control were associated with lower total healthcare costs in 2009. To our knowledge, our study is the first to examine the impact of sustained A1C control on costs and to use propensity score matching to minimize potential confounding.

Although cost increases in pharmaceutical treatment were similar in both groups, cost reductions for both physician and inpatient services were found for the group with sustained A1C control. Prior evidence has shown that complications are key drivers of the direct medical costs in patients with diabetes.¹⁷ Hence, some of the cost reductions seen in our study with sustained glycemic control may be due to a reduced incidence of diabetes complications and morbidity.

Our analyses of panel data reveal, however, that these cost savings are not immediate. In our study, during any given year that patients achieved A1C levels of less than 7%, their costs were signifi cantly higher than those for patients whose A1C levels were greater than or equal to 7%. We acknowledge that even though the group that sustained good glycemic control had cost savings of more than $5000 from 2009 to 2006, some of these savings could be counterbalanced by cost increases in the intervening years, as additional physician visits and medications might be needed to achieve this control. The costs are immediate, but the benefits may take years to be realized. Even so, it is likely that costs will continue to be lower in subsequent years if patients maintain glycemic control.

These findings contrast with those of several prior studies that have found short-term cost savings. Shetty and colleagues11 divided a cohort of patients with diabetes in a managed care setting into 2 groups, those at the target A1C level (<7%) and those above the target A1C level (>7%), and examined cost savings after 1 year of follow-up. They found substantial cost savings of 32% for patients at target A1C level. In another study, grouping patients with type 2 diabetes by glycemic control (good [A1C <7%], fair [>7% to <9%], and poor [>9%]), Oglesby and colleagues¹² found diabetes-related costs to be 16% lower for patients with good control than for patients with fair control and 20% lower than for patients with poor control.¹² Similarly, Gilmer and colleagues¹³ examined medical charges related to A1C and found that after controlling for demographics and cardiovascular disease, costs increased by 30% as A1C increased from 6% to 10%.

Our findings of increased costs for the patients whose A1C level was less than 7% within a year differed from the results of these prior studies. We believe the main difference was that we required patients to have elevated A1C levels (>9%) at baseline, while these other studies did not. Hence, those researchers may have had in their at target group patients with fairly “normal” A1C levels even without treatment. It may also be that initial interventions for patients with poor control that drive up immediate costs were not evaluated in these cross-sectional cohort studies.

A subsequent study by Gilmer and colleagues¹⁸ reported that in a large Minnesota health plan, higher A1C in patients with either type 1 or type 2 diabetes predicted higher 3-year total healthcare costs for patients with A1C greater than 7.5%. This study differed from ours in that it did not examine the impact of changes in A1C levels. Both studies by Gilmer and colleagues emphasized that cardiovascular disease was a stronger predictor of costs than glycemic control. We did not examine the association between cardiovascular disease and costs in our study.

In a recent study, Menzin and colleagues¹⁹ examined a cohort of patients with diabetes in a managed care setting. The investigators found the odds of having at least 1 diabetesrelated hospitalization were not significantly associated with higher mean A1C levels except for patients with a mean A1C level of at least 10%. They did find that for hospitalized patients, mean costs were higher among patients with higher mean A1C levels. However, because they did not examine total costs of care or changes in costs related to changes in A1C levels, we cannot directly compare their findings with ours.

A study by Wagner and colleagues²⁰ was the most similar to ours in that it focused on changes in cost related to changes in A1C levels. They examined data for diabetic patients enrolled in a staff model health maintenance organization in the mid-1990s. The investigators defined improvement as having at least a 1% decrease in A1C levels. They found costs for the improved group were lower each subsequent year. but differences were statistically significant only for those with baseline A1C levels of greater than or equal to 10%. Our study design differed from theirs in that we examined costs for patients who dropped their A1C levels from greater than 9% to less than 7%. Hence, we required a higher level of improvement (2 percentage point reduction) as well as sustained control, and found that patients whose initial A1C levels were greater than 9% experienced significant cost reductions.

Our study may underestimate potential savings from A1C reduction to target levels. Tissue damage from inadequate glycemic control may not be promptly overcome or mitigated. Clinical trials have demonstrated that approximately 8 years are needed to realize fully all of the microvascular benefi ts of glycemic control.²¹ The UK Prospective Diabetes Study demonstrated that maintaining a lower A1C (7%) over 10 years is associated with a substantially reduced risk of microvascular complications.7 Hence, further risk reduction and cost savings may be observed within an extended study period (8-10 years).

This study had several limitations. First, it was conducted with enrollees of a single health plan in Hawaii. The percentage of patients in poor control (A1C >9%) in 2006 (8%) was lower than the national average, so our results may not be generalizable to other areas or uninsured populations. Second, we only estimated direct medical costs covered by the health plan. Free drug samples distributed by physicians, use of aspirin, and other noncovered costs would not be included in our analyses. Adding indirect measures such as productivity gains and decreased absenteeism would most likely have increased the cost savings for the group with sustained glucose control.²² We were also not able to separate out diabetes-specific costs.

Third, we relied on administrative data from a health plan to identify patients with diabetes and to estimate costs. The possibility of false positives arising from identifi cation based on claims data was diminished in our study as we required a diagnosis of diabetes and an A1C value greater than 9% at baseline. Fourth, this study also did not examine the quality-of-life implications, which could be substantial. Fifth, only 3% of patients were able to achieve target level A1C for 3 years. This group may have been different in other ways. For instance, they may have eaten healthier diets, smoked less, and exercised more than those not able to sustain control. These factors may have been as important to sustained glycemic control as medical interventions, but the costs would have primarily been absorbed by the patients and they were unmeasured in this study. Future research is needed that takes a more comprehensive approach to measuring factors that might contribute to cost changes.

CONCLUSIONS

In our study of 1304 managed care enrollees with poor initial A1C control, we found that patients who were able to achieve target goals had lower costs after 3 years compared with patients not able to sustain these target levels.

Quality indicators for health plans and physicians often include A1C screening and reaching target levels. Our study suggests that while achieving these target goals may not immediately result in cost reductions, sustained A1C control is associated with lower costs in a 3-year time frame, suggesting that efforts to support and reward physicians and health plans for achieving these target goals may be a good investment in the intermediate term.