OBJECTIVE—To describe the extent to which hospitalizations for patients with diabetes reflect multiple stays by the same individuals and to examine how multiple hospitalizations vary by patient demographic and socioeconomic characteristics.

RESEARCH DESIGN AND METHODS—Using the Healthcare Cost and Utilization Project complete discharge data for five states (California, Missouri, New York, Tennessee, and Virginia) in 1999, we identified 648,748 nonneonatal, nonmaternal patients who had one or more hospitalizations listing diabetes. Multiple hospitalizations were measured as percent of patients with multiple stays, percent of total stays represented by multiple stays, and average number of stays per patient. Total hospital costs were also examined. Stratified analysis and regression were performed to assess differences by age, sex, race/ethnicity, payer, location, and income.

RESULTS—Among patients with diabetes who had been hospitalized, 30% had two or more stays accounting for >50% of total hospitalizations and hospital costs. Controlled for patient age, sex, and clinical characteristics, the likelihood of having multiple hospitalizations was higher for Hispanics and non-Hispanic blacks compared with non-Hispanic whites, as well as for patients covered by Medicare or Medicaid and those living in low-income areas. The prevalence of diabetes complications and multiple conditions differed by age, race/ethnicity, and payer among patients with multiple stays.

CONCLUSIONS—Multiple hospitalizations are common among patients with diabetes but vary by age, race/ethnicity, payer, and income, with those populations traditionally considered to be more vulnerable experiencing higher likelihoods of multiple stays. Significant opportunities exist to reduce the proportion of multiple hospitalizations for patients with diabetes. Clinical and policy interventions to improve the quality of care and outcomes for these patients should be designed accordingly and have the potential to pay major dividends.

Diabetes is one of the most common chronic conditions in the U.S. The prevalence of diabetes has increased 41% over the last decade, reaching 6.5% in 1999 (1), and is projected to continue to increase due to an aging population, changing racial/ethnic composition, and rising disease incidence (2). The total direct medical costs incurred by people with diabetes are estimated to be $44.1 billion, with >60% of the spending on inpatient care for treatment of diabetes complications and general medical conditions (3). People with diabetes are more likely to be hospitalized and incur nearly twofold higher total inpatient costs per capita than people without diabetes (3). Although prior studies have estimated hospital admission rates among people with diabetes using nationwide survey data (3,4), little published data on patients with multiple hospitalizations exist.

In health care, a small proportion of patients tend to account for a majority of the care and costs, often called the 80/20 principle (5). For example, Krop et al. (6) found that the top 10% of Medicare beneficiaries with diabetes in terms of expense accounted for 56% of total expenditures for individuals with diabetes. Likewise, if patients with multiple hospitalizations contribute strongly to the total inpatient care and costs for diabetes, this would have significant implications for the design of interventions such as disease management programs, referral protocols, and financial incentives within health plans. Therefore, we conducted a cross-sectional analysis using all-payer hospital discharge abstract data from five states. The purpose of our study is twofold: 1) to assess the extent to which hospitalizations for patients with diabetes reflect multiple stays by the same individuals and 2) to examine how multiple hospitalizations vary by patient demographic and socioeconomic characteristics.

We used 1999 data from the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases. Sponsored by the Agency for Healthcare Research and Quality, HCUP is a federal/state/industry partnership to build a multistate health care data system. The core of HCUP is hospital discharge abstract data obtained from state data organizations or hospital associations. The State Inpatient Databases include data on inpatient stays from virtually all community hospitals in participating states. Community hospitals are short-term, nonfederal, general, and specialty hospitals, including academic medical centers but excluding long-term care and psychiatric hospitals. We selected five states (California, Missouri, New York, Tennessee, and Virginia) that provide patient numbers (PNUMs) encrypted from the patient’s name and/or social security number. PNUMs are used to identify multiple admissions by distinct patients across hospitals within the same state. These five states also provide a relatively high representation of racial/ethnic minorities.

We identified 1,129,506 nonneonatal, nonmaternal discharges with the principal or secondary diagnosis indicating diabetes (ICD-9-CM code of 250.xx). Other researchers have used the same method to identify hospital discharges by patients with diabetes (3,4,7). We excluded discharges that had missing PNUMs, the same PNUM but inconsistent age (different by >1 year) or sex, or missing admission dates. If a patient had 2 consecutive stays in which the discharge date of the first stay overlapped with the admission date of the second by >2 days, both discharges were excluded. This left 1,076,562 discharges (95.3%) remaining in the study. To avoid the counting of transfers, if the readmission occurred on the same day of or 1 day before discharge of the previous stay, the readmission was not considered as a separate hospitalization. The final study population consisted of 648,748 patients with a total of 993,074 hospitalizations.

Multiple hospitalization

The purpose of our analysis is to examine the resource implications and opportunities for improving outcomes of multiple hospitalizations by patients with diabetes. We classified a patient as having multiple hospitalizations if the patient had two or more hospital stays during 1999, regardless of whether the readmission was planned or unplanned, preventable or unpreventable, or related or unrelated to prior stay. This definition has been used in a study by researchers of the Veterans Administration (8). We examined multiple hospitalizations using three indicators: the percent of patients with multiple hospitalizations, the percent of total stays represented by multiple hospitalizations, and the average number of stays per patient. We also examined total hospital costs that were derived from total hospital charges. We applied the cost-to-charge ratios developed from national data compiled by Centers for Medicare and Medicaid Services and tested against accounting systems from four states (9). We used hospital wage indices to adjust for geographic differences in labor cost. We calculated total hospital costs separately for patients with single hospitalization and patients with multiple stays.

Patient demographic, socioeconomic, and clinical characteristics

Patient demographic and socioeconomic characteristics include age, sex, race/ethnicity, expected payer, location of residence, and median income of the patient’s community. We used the patient’s county or zip code to determine whether the patient lived in a rural or urban area. Rural areas are defined as areas outside a Metropolitan Statistical Area. We estimated income using the median household income of the patient’s zip code and categorized income into three levels using quartiles specific to each state. Low income refers to zip codes in the lowest quartile of median income within that state, while high income refers to zip codes in the highest quartile. Medium income includes those zip codes with median incomes falling in the two middle quartiles.

We performed stratified analyses by patient demographic and socioeconomic characteristics to identify differences across patient subgroups in the extent of multiple hospitalizations and resource implications. Student’s t test and χ2 test were used to determine statistical significance of comparisons across age-groups (nonelderly adults being the reference), sex, race (non-Hispanic whites being the reference), payer (private insurance being the reference), location, and income. Differences in the likelihood of having multiple stays across racial/ethnic and socioeconomic groups were further assessed by logistic regression to control for patient age, sex, and clinical characteristics at the first stay, which include the type of diabetes complications and chronic conditions (see online appendix at http://care.diabetesjournals.org), length of stay (in log function), and disposition (e.g., transfer to nursing home or other health care facility, home health care). Admission month of the first stay was included to adjust for different follow-up period lengths. Dummy variables indicating individual states were used to control for state effects.

We also compared the presence of different clinical conditions among patients with multiple hospitalizations by age, sex, race/ethnicity, and payer. Three types of conditions were identified: 1) acute complications of diabetes (e.g., ketoacidosis, hyperosmolarity, diabetic coma), 2) chronic complications of diabetes (e.g., ophthalmic disease, lower extremity disease, renal disease, cardiovascular disease), and 3) general chronic conditions. The online appendix provides the ICD-9-CM codes used to define these conditions. Each condition was considered present if the code corresponding to the condition was listed as a principal or secondary diagnosis during any hospital stay.

Extent of multiple hospitalizations

Among patients with diabetes who had been hospitalized during 1999 in five selected states (California, Missouri, New York, Tennessee, and Virginia), 30% had two or more stays that contributed to 55% of total hospitalizations and 54% of total hospital costs. The average length of stay is slightly longer for patients with multiple stays than for patients with single hospitalization (7.4 vs. 6.8 days) (Table 1). The total hospital cost per patient is nearly three times as high for patients with multiple stays as for patients with a single stay ($23,119 vs. $8,508). For patients with multiple hospitalizations, the total hospital cost covers all patient stays.

Table 1 also shows proportions of multiple hospitalizations, average length of stay, and total hospital cost per patient by age and sex. The percent of patients with multiple hospitalizations (two or more stays) increased by age, ranging from 16.0% for patients age 1–17 years to 31.4% for patients age ≥65 years. Multiple stays accounted for 35% of total hospitalizations for pediatric patients compared with 55% for adults. There was no substantial difference in the extent of multiple hospitalizations between male and female patients except for children. Girls had higher proportions of multiple hospitalizations than boys (percent of distinct patients: 18.2 vs. 13.4%; percent of total stays: 39.2 vs. 29.6%; average number of stays per patient: 1.35 vs. 1.23).

Table 2 shows differences in the percent of patients with multiple hospitalizations by race/ethnicity, payer, location of residence, and income of community. Among the elderly, Hispanic patients had the highest percent of multiple hospitalizations (37.2%), followed by non-Hispanic blacks (34.0%) and non-Hispanic whites (30.9%). For patients <65 years of age, the percents of multiple hospitalizations were similar for Hispanics and non-Hispanic blacks but higher for both of these groups than for non-Hispanic whites. The difference was greatest among children. The percents of multiple hospitalizations for Asian-Pacific Islanders were comparable to those of non-Hispanic whites.

Both Medicare and Medicaid patients had higher percents of multiple hospitalizations than privately insured patients. The difference was greater among the nonelderly: compared with privately insured, the percent of multiple hospitalizations for Medicaid patients was 80% higher among pediatric patients and 55% higher among nonelderly adults. The percents of multiple hospitalizations were similar between urban and rural patients except for pediatric patients. Children living in urban areas had a higher percent of multiple hospitalizations than children residing in rural areas (16.6 vs. 13.6%). Patients from low-income zip codes had higher percents of multiple hospitalizations than patients in high-income zip codes. The percent of children with multiple stays was 18.6% for the low-income group compared with 12.6% for the high-income group.

Results of the full logistic regression confirm the patterns of disparities already reported. Controlling for patient age, sex, and clinical characteristics at the first hospital stay, significantly higher odds of having multiple stays were found for Hispanics and non-Hispanic blacks relative to non-Hispanic whites (P < 0.0001), Medicare or Medicaid patients compared with privately insured (P < 0.0001), and patients in low-income areas (P < 0.05).

Table 3 presents average total hospital costs for patients with multiple stays by race/ethnicity, payer, location, and income. Among adults who had two or more hospitalizations, the average total hospital cost per patient was significantly higher for racial/ethnic minority groups, Medicare or Medicaid patients, and patients from low-income areas. Similar patterns were found for pediatric patients but not reaching statistical significance due to relatively small patient volumes.

Presence of diabetes complications and other conditions among patients with multiple hospitalizations

Over 60% of pediatric diabetes patients who had multiple hospitalizations had experienced acute complications of diabetes as a primary or coexisting condition for the stay. This compared with only 10% for nonelderly adults and <5% for the elderly. In contrast, chronic complications of diabetes were more common among adults. About 40% of adult diabetes patients with multiple hospitalizations had developed lower extremity disease. Hypertension was the most common cardiovascular disease among adult patients, followed by ischemic heart disease and congestive heart failure. (Detailed results by age/sex are available from authors.)

Table 4 shows differences in presence of diabetes complications and comorbidities by race/ethnicity and payer among patients with multiple stays. Only adult patients (age ≥18 years) were included in the analysis. The acute complication rate was much higher for non-Hispanic blacks than for other racial/ethnic groups. All three racial/ethnic minority groups had higher renal disease rates than non-Hispanic whites. Asian/Pacific Islanders had a higher rate for stroke than other racial/ethnic groups (one in four versus one in five) but lowest rates for several comorbidities, including obesity, depression, and substance abuse. Across payers, the acute complication rate was more than twice as high for the uninsured as for patients with insurance coverage. The uninsured also had the highest rate for substance abuse. Compared with privately insured patients, Medicaid patients had higher rates for a number of conditions, including renal disease, congestive heart failure, stroke, chronic obstructive pulmonary disease, depression, and substance abuse.

The results of this study indicate that multiple hospitalizations are common among patients with diabetes but vary by age, race/ethnicity, payer, and income. Although only 30% of patients were hospitalized more than once, these patients accounted for a majority of the inpatient costs for patients with diabetes, suggesting that efforts aimed at reducing the need for multiple hospitalizations could pay major dividends. Prior studies have shown that focused efforts using disease or case management can improve outcomes (10) and reduce utilization and costs (11). Future evaluation of disease management programs could include multiple hospitalizations as an outcome measure.

While we generally consider the elderly to be sicker and more likely to use inpatient care, there was no substantial difference in the percent of patients with multiple hospitalizations between nonelderly adults and the elderly (28.2 vs. 31.4%). Our data do not permit separate analysis by type 1 versus type 2 diabetes, but patients with type 1 diabetes most likely accounted for a larger proportion of the nonelderly group than the elderly group. Some of these patients may be in an advanced stage of diabetes with multiple complications that could increase their likelihood of having multiple hospitalizations.

The proportions of multiple hospitalizations were higher for some groups that are considered vulnerable, including racial/ethnic minorities, those covered under Medicare or Medicaid, and those living in lower-income communities. Compared with non-Hispanic whites, Hispanics and non-Hispanic blacks had higher likelihoods of having multiple hospitalizations. Among patients with multiple stays, Hispanics and non-Hispanic blacks had higher total hospital costs per patient and higher prevalence rates for acute complications and end-stage renal disease. These results are consistent with other studies that found Hispanics and non-Hispanic blacks were less likely to receive HbA1c test and eye exam (12), less likely to do self-monitoring of blood glucose level, and more likely to have poor glycemic control (13). Better glycemic control can help reduce hospitalization (14) and achieve significant cost savings (15). Of note, lack of insurance was not associated with higher rates of multiple hospitalizations. While they did not have a higher proportion of multiple stays, the uninsured adults had a clinically distinct pattern compared with other groups: higher rates of acute complications, lower rates of chronic complications, and higher rates of substance abuse. This lack of a consistent association between the socioeconomic vulnerable subgroups and multiple hospitalizations suggests that the latter may be determined by an interplay of factors, including eligibility for insurance, access to primary and specialty care, demographics such as age, prevalence of complications, and patient preferences and bias (16).

It is worth noting that compared with adults, greater differences were found for pediatric patients in multiple hospitalizations by race, payer, and income of community. This may be related to the higher prevalence of acute diabetes complications among pediatric patients, shown by our data, many of which are preventable for the more vulnerable subgroups. A relatively higher admission rate for acute complications has been reported by other studies for Medicaid patients (17) and patients living in low-income areas (18).

Our study relies on hospital discharge data that have several limitations. First, we were unable to distinguish betweein type 1 and type 2 diabetes because the fifth digit in the ICD-9-CM codes that specify whether the patient was insulin dependent is inaccurate in identifying the type of diabetes. Patients with different types of diabetes could have different patterns of hospital utilization and outcomes. Second, the data do not provide information on duration of diabetes. The likelihood of developing complications and being hospitalized could increase by how long the patient has had diabetes. Related to this, the data do not provide a measure of disease severity beyond that captured by complications and comorbidities. Third, the data capture only inpatient stays that would underreport those conditions, such as eye disorders, and that are more likely to be treated in the outpatient setting. Fourth, this study examines a 1-year period of time. It is likely that some patients who had only one hospitalization during 1999 were also hospitalized within 1 year of their inpatient stay, either in 1998 or 2000. However, the approach we used provides an annual picture of utilization patterns similar to time frames in many national surveys of health care utilization, such as the National Health Interview Survey or the Medical Expenditure Panel Survey. Fifth, we only captured hospital stays with diabetes listed as one of the discharge diagnoses. It is possible that some diabetic patients may not have diabetes reported in their discharge records. Thus, the study likely underestimates the percentage of diabetic patients with multiple hospitalizations and the associated costs.

In summary, the results of this study reveal multiple hospitalizations to be an important contributor to hospital utilization and costs for patients with diabetes. Among patients with multiple stays, >60% of children had experienced acute complications; ∼90% of adults had cardiovascular disease, 25% renal disease, and 40% lower extremity disease. Some of the multiple hospitalizations that resulted from these complications, as well as some of the complications themselves, are preventable with quality outpatient care, including patient self-management of the condition. Future research should explore what type of patients would have a higher probability of preventable readmissions and identify cost-effective interventions to target this specific group of patients.

Table 1—

Number of hospitalizations, average length of stay, and total hospital cost for patients with diabetes, by age and sex, for five states combined (CA, NY, MO, TN, and VA) in 1999

nPercent of distinct patients with
Multiple stays as a percent of total staysAverage number of stays per distinct patientAverage length of each stay (days)
Average total hospital cost ($) per distinct patient
One stayTwo staysThree or more staysSingle stayMultiple staysSingle stayMultiple stays
All 648,748 70.0 18.1 11.9 54.3 1.53 6.8 7.4 8,508 23,119 
Pediatric (age 1–17 years) 4,698 84.0 10.0 6.0 35.0 1.29 4.0 4.5 4,029 13,745 
 Male 2,186 86.6 8.6 4.8 29.6 1.23 3.9 4.6 3,912 13,978 
 Female 2,511 81.8 11.2 7.0 39.2 1.35 4.1 4.4 4,137 13,595 
Nonelderly (age 18–64 years) 265,778 71.8 16.4 11.8 53.2 1.53 5.7 6.7 7,859 23,689 
 Male 135,076 72.6 16.2 11.2 52.0 1.51 5.8 6.7 8,407 23,962 
 Female 130,673 71.0 16.5 12.4 54.4 1.56 5.6 6.8 7,282 23,423 
Elderly (age ≥65 years) 378,226 68.6 19.3 12.1 55.2 1.53 7.6 7.9 9,049 22,822 
 Male 164,895 68.8 19.4 11.8 54.8 1.52 7.4 7.7 9,547 23,202 
 Female 213,288 68.4 19.2 12.4 55.6 1.54 7.8 8.0 8,666 22,534 
nPercent of distinct patients with
Multiple stays as a percent of total staysAverage number of stays per distinct patientAverage length of each stay (days)
Average total hospital cost ($) per distinct patient
One stayTwo staysThree or more staysSingle stayMultiple staysSingle stayMultiple stays
All 648,748 70.0 18.1 11.9 54.3 1.53 6.8 7.4 8,508 23,119 
Pediatric (age 1–17 years) 4,698 84.0 10.0 6.0 35.0 1.29 4.0 4.5 4,029 13,745 
 Male 2,186 86.6 8.6 4.8 29.6 1.23 3.9 4.6 3,912 13,978 
 Female 2,511 81.8 11.2 7.0 39.2 1.35 4.1 4.4 4,137 13,595 
Nonelderly (age 18–64 years) 265,778 71.8 16.4 11.8 53.2 1.53 5.7 6.7 7,859 23,689 
 Male 135,076 72.6 16.2 11.2 52.0 1.51 5.8 6.7 8,407 23,962 
 Female 130,673 71.0 16.5 12.4 54.4 1.56 5.6 6.8 7,282 23,423 
Elderly (age ≥65 years) 378,226 68.6 19.3 12.1 55.2 1.53 7.6 7.9 9,049 22,822 
 Male 164,895 68.8 19.4 11.8 54.8 1.52 7.4 7.7 9,547 23,202 
 Female 213,288 68.4 19.2 12.4 55.6 1.54 7.8 8.0 8,666 22,534 

Statistical significance was tested for across age-group comparisons, with nonelderly adults being the reference, and for male-female comparison in each age-group. All comparisons were significant at P < 0.001 except for: 1) male-female difference in percent of patients with multiple stays among the elderly (P < 0.05), 2) male-female differences in average length of stay and total hospital cost among pediatric patients (P > 0.2), and 3) the difference in overall average number of stays per patient between the nonelderly and the elderly (P > 0.2).

Table 2—

Percentage of distinct patients with multiple hospitalizations by race/ethnicity, payer, location, and income for five states combined (CA, NY, MO, TN, and VA) in 1999

nDistinct patients with multiple stays (%)
Odds ratio for having multiple stays§
Pediatric (age 1–17 years)Nonelderly (age 18–64 years)Elderly (age ≥65 years)
Race/ethnicity      
 White, Non-Hispanic 408,194 14.3 27.8 30.9 1.00 
 Black, Non-Hispanic 102,389 21.4* 30.8* 34.0* 1.15 (1.13–1.17)* 
 Hispanic 74,425 20.8* 31.2* 37.2* 1.20 (1.18–1.23)* 
 Asian/Pacific Islander 22,900 — 24.8* 31.3 0.98 (0.95–1.01) 
 Other# 18,260 10.6 19.5* 23.1* 0.71 (0.68–0.74)* 
Expected payer      
 Private 147,854 12.3 22.4 28.6 1.00 
 Medicare 345,092 — 38.8* 31.5* 1.48 (1.45–1.50)* 
 Medicaid 116,293 22.3* 34.7* 33.9* 1.63 (1.60–1.66)* 
 Uninsured** 25,919 8.2 20.5* 23.4* 0.95 (0.91–0.98) 
 Other 11,200 20.6 22.4 29.1 1.08 (1.03–1.14) 
Patient residence      
 Rural 96,721 13.6 28.1 31.6 1.00 
 Urban 543,427 16.6 28.4 31.6 1.01 (0.99–1.03) 
Median family income at patient zip code††      
 High 160,816 12.6 26.0 30.1 1.00 
 Medium 322,734 16.6 28.3* 31.5* 1.03 (1.01–1.04) 
 Low 162,371 18.6* 29.9* 32.8* 1.03 (1.01–1.05) 
nDistinct patients with multiple stays (%)
Odds ratio for having multiple stays§
Pediatric (age 1–17 years)Nonelderly (age 18–64 years)Elderly (age ≥65 years)
Race/ethnicity      
 White, Non-Hispanic 408,194 14.3 27.8 30.9 1.00 
 Black, Non-Hispanic 102,389 21.4* 30.8* 34.0* 1.15 (1.13–1.17)* 
 Hispanic 74,425 20.8* 31.2* 37.2* 1.20 (1.18–1.23)* 
 Asian/Pacific Islander 22,900 — 24.8* 31.3 0.98 (0.95–1.01) 
 Other# 18,260 10.6 19.5* 23.1* 0.71 (0.68–0.74)* 
Expected payer      
 Private 147,854 12.3 22.4 28.6 1.00 
 Medicare 345,092 — 38.8* 31.5* 1.48 (1.45–1.50)* 
 Medicaid 116,293 22.3* 34.7* 33.9* 1.63 (1.60–1.66)* 
 Uninsured** 25,919 8.2 20.5* 23.4* 0.95 (0.91–0.98) 
 Other 11,200 20.6 22.4 29.1 1.08 (1.03–1.14) 
Patient residence      
 Rural 96,721 13.6 28.1 31.6 1.00 
 Urban 543,427 16.6 28.4 31.6 1.01 (0.99–1.03) 
Median family income at patient zip code††      
 High 160,816 12.6 26.0 30.1 1.00 
 Medium 322,734 16.6 28.3* 31.5* 1.03 (1.01–1.04) 
 Low 162,371 18.6* 29.9* 32.8* 1.03 (1.01–1.05) 
§

Derived from a multiple logistic regression model that included all the patient demographic and socioeconomic variables, as well as clinical characteristics presented during the first hospital stay.

Reference group for comparison and testing of statistical significance.

Statistics for the pediatric group are not presented for Asian/Pacific Islander and Medicare due to the small patient volume (n < 100).

#

Other race includes those not listed here, of which <10% are Native Americans. Missing is excluded.

**

Uninsured included self-pay, no charge, and charity or indigent programs.

††

The income level is defined by quartiles specific to each state. Low income refers to those communities in the lowest quartile, while high income refers to those in the highest quartile.

*

P < 0.0001;

P < 0.01;

P < 0.05.

Table 3—

Average total hospital cost for patients with multiple hospitalizations by race/ethnicity, payer, location, and income for five states combined (CA, NY, MO, TN, and VA) in 1999

Average total hospital cost ($) per distinct patient
Pediatric (age 1–17 years)Nonelderly (age 18–64 years)Elderly (age ≥65 years)
Race/ethnicity    
 White, Non-Hispanic§ 13,095 23,304 21,937 
 Black, Non-Hispanic 13,280 24,228* 24,935 
 Hispanic 15,777 24,028 24,580 
 Asian/Pacific Islander — 24,767 24,701 
 Other 21,470 25,405* 26,392 
Expected Payer    
 Private§ 12,513 21,725 21,428 
 Medicare — 26,556 22,662 
 Medicaid 14,390 24,688 24,581 
 Uninsured# 16,103 19,911 22,264 
 Other 16,881 20,418 20,957 
Patient residence    
 Rural§ 13,136 22,759 22,234 
 Urban 13,855 23,856* 22,932* 
Median family income at patient zip code**    
 High§ 13,144 22,597 21,641 
 Medium 13,152 23,454* 22,562 
 Low 15,287 24,929 24,553 
Average total hospital cost ($) per distinct patient
Pediatric (age 1–17 years)Nonelderly (age 18–64 years)Elderly (age ≥65 years)
Race/ethnicity    
 White, Non-Hispanic§ 13,095 23,304 21,937 
 Black, Non-Hispanic 13,280 24,228* 24,935 
 Hispanic 15,777 24,028 24,580 
 Asian/Pacific Islander — 24,767 24,701 
 Other 21,470 25,405* 26,392 
Expected Payer    
 Private§ 12,513 21,725 21,428 
 Medicare — 26,556 22,662 
 Medicaid 14,390 24,688 24,581 
 Uninsured# 16,103 19,911 22,264 
 Other 16,881 20,418 20,957 
Patient residence    
 Rural§ 13,136 22,759 22,234 
 Urban 13,855 23,856* 22,932* 
Median family income at patient zip code**    
 High§ 13,144 22,597 21,641 
 Medium 13,152 23,454* 22,562 
 Low 15,287 24,929 24,553 

The method of estimating comparable hospital costs is provided in the text.

§

Reference group for comparison and testing of statistical significance.

Statistics for the pediatric group are not presented for Asian/Pacific Islander and Medicare due to the small patient volume (n < 100).

Other race includes those not listed here, of which <10% are Native Americans. Missing is excluded.

#

Uninsured included self-pay, no charge, and charity or indigent programs.

**

The income level is defined by quartiles specific to each state. Low income refers to those communities in the lowest quartile, while high income refers to those in the highest quartile.

*

P < 0.01;

P < 0.0001;

P < 0.05.

Table 4—

Presence of diabetes complications and chronic conditions among adult patients with multiple hospital stays, by race and payer

Complications and chronic conditions§Race/ethnicity
Payer
White, Non-HispanicBlack, Non-HispanicHispanicAsian/Pacific IslanderPrivateMedicareMedicaidUninsured
Acute diabetes complications 5.3 9.0 6.9 5.2* 7.4 4.3 8.5 17.7 
Chronic diabetes complications and cardiovascular comorbidities         
 Ophthalmic disease 13.2 15.4 17.2 14.5 14.1 14.6 13.3 11.3 
 Lower extremity disease 41.5 40.4 41.8* 31.3 37.6 42.7 39.3 32.9 
 Renal disease         
 End-stage renal disease 9.7 14.3 15.6 16.2 8.7 12.6 12.1 5.7 
 Total 21.8 30.8 32.5 34.5 21.5 26.7 25.5 17.8 
Major cardiovascular diseases         
 Ischemic heart disease 57.6 41.4 48.4 52.9 47.5 58.9 45.5 32.9 
 Hypertension 73.8 84.9 78.8 82.6 73.1 78.8 76.2 63.8 
 Congestive heart failure 44.3 39.7 39.0 40.9 29.9 48.6 39.0 24.3 
 Cardiac arrhythmia 36.1 23.9 26.8 34.8 24.2 38.9 23.8* 15.6 
 Cerebrovascular disease 20.3 20.5* 19.3 25.8 14.4 23.7 17.6 10.4 
 Total 92.1 91.9 89.1 92.9 86.7 95.3 88.2 74.9 
Other chronic conditions         
 Chronic obstructive pulmonary disease 32.1 25.4 23.8 23.5 21.7 31.1 32.6 18.2 
 Cancer 11.8 10.2 8.7 12.6* 11.9 12.1* 8.3 6.2 
 Hypothyroidism 14.2 6.7 9.9 7.1 9.9 13.6 9.6* 5.6 
 Obesity 13.3 12.6 12.1 4.5 17.5 10.5 14.2 11.7 
 Depression 16.3 11.0 12.8 8.0 13.6 13.9* 17.0 13.0* 
 Substance abuse 12.4 14.6 13.3 6.4 15.3 9.1 17.3 28.2 
 Chronic liver disease 3.5 3.1 6.9 5.0 4.4 3.2 5.3 5.7 
Complications and chronic conditions§Race/ethnicity
Payer
White, Non-HispanicBlack, Non-HispanicHispanicAsian/Pacific IslanderPrivateMedicareMedicaidUninsured
Acute diabetes complications 5.3 9.0 6.9 5.2* 7.4 4.3 8.5 17.7 
Chronic diabetes complications and cardiovascular comorbidities         
 Ophthalmic disease 13.2 15.4 17.2 14.5 14.1 14.6 13.3 11.3 
 Lower extremity disease 41.5 40.4 41.8* 31.3 37.6 42.7 39.3 32.9 
 Renal disease         
 End-stage renal disease 9.7 14.3 15.6 16.2 8.7 12.6 12.1 5.7 
 Total 21.8 30.8 32.5 34.5 21.5 26.7 25.5 17.8 
Major cardiovascular diseases         
 Ischemic heart disease 57.6 41.4 48.4 52.9 47.5 58.9 45.5 32.9 
 Hypertension 73.8 84.9 78.8 82.6 73.1 78.8 76.2 63.8 
 Congestive heart failure 44.3 39.7 39.0 40.9 29.9 48.6 39.0 24.3 
 Cardiac arrhythmia 36.1 23.9 26.8 34.8 24.2 38.9 23.8* 15.6 
 Cerebrovascular disease 20.3 20.5* 19.3 25.8 14.4 23.7 17.6 10.4 
 Total 92.1 91.9 89.1 92.9 86.7 95.3 88.2 74.9 
Other chronic conditions         
 Chronic obstructive pulmonary disease 32.1 25.4 23.8 23.5 21.7 31.1 32.6 18.2 
 Cancer 11.8 10.2 8.7 12.6* 11.9 12.1* 8.3 6.2 
 Hypothyroidism 14.2 6.7 9.9 7.1 9.9 13.6 9.6* 5.6 
 Obesity 13.3 12.6 12.1 4.5 17.5 10.5 14.2 11.7 
 Depression 16.3 11.0 12.8 8.0 13.6 13.9* 17.0 13.0* 
 Substance abuse 12.4 14.6 13.3 6.4 15.3 9.1 17.3 28.2 
 Chronic liver disease 3.5 3.1 6.9 5.0 4.4 3.2 5.3 5.7 

Data are percent of distinct adult patients.

Adults include patients age ≥18 years.

§

See the online appendix for ICD-9-CM codes used to define each condition.

Reference group for comparison and testing of statistical significance.

Total also includes those conditions not listed but belonging to the same body system.

*

P > 0.05, not significant;

P < 0.05; P < 0.001 for all other comparisons.

The authors express special thanks to Zhengyi Fang at Social and Scientific Systems for his super programming skills and to Eva Weinstein, an intern at Agency for Healthcare Research and Quality, for assistance in literature search.

1.
Mokdad AH, Ford ES, Bowman BA, Nelson DE, Engelgau MM, Vinicor F, Marks JS: The continuing increase of diabetes in the U.S. (Letter).
Diabetes Care
24
:
412
,
2001
2.
Boyle JP, Honeycutt AA, Narayan KM, Hoerger TJ, Geiss LS, Chen H, Thompson TJ: Projection of diabetes burden through 2050: impact of changing demography and disease prevalence in the U.S.
Diabetes Care
24
:
1936
–1940,
2001
3.
American Diabetes Association: Economic consequences of diabetes mellitus in the U.S. in 1997.
Diabetes Care
21
:
296
–309,
1998
4.
Aubert RE, Geiss LS, Ballard DJ, Cocanougher B, Herman WH: Diabetes-related hospitalization and hospital utilization.
In Diabetes in America.
2nd ed. Bethesda, MD, National Institutes of Health,
1995
, p.
553
–570 (NIH publ. no. 95-1468)
5.
Institute of Medicine:
Crossing the Quality Chasm: A New Health System for the 21st Century.
Washington, DC, National Academy Press,
2002
6.
Krop JS, Powe NR, Weller WE, Shaffer TJ, Saudek CD, Anderson GF: Patterns of expenditures and use of services among older adults with diabetes: implications for the transition to capitated managed care.
Diabetes Care
21
:
747
–752,
1998
7.
CDC Diabetes in Managed Care Work Group: Diabetes mellitus in managed care: complications and resource utilization.
Am J Manag Care
7
:
501
–508,
2001
8.
Wray NP, Petersen NJ, Souchek J, Ashton CM, Hollingsworth JC, Geraci JM: The hospital multistay rate as an indicator of quality of care.
Health Serv Res
34
:
777
–790,
1999
9.
Friedman B, De La Mare J, Andrews R, McKenzie DH: Estimating hospital cost for discharged patients: practical options in an era of data restrictions.
J Health Care Finance
29
:
1
–13,
2002
10.
Aubert RE, Herman WH, Waters J, Moore W, Sutton D, Peterson BL, Bailey CM, Koplan JP: Nurse case management to improve glycemic control in diabetic patients in a health maintenance organization: a randomized, controlled trial.
Ann Intern Med
129
:
605
–612,
1998
11.
Lob SH, Kohatsu ND: Case management: a controlled evaluation of persons with diabetes.
Clin Perform Qual Health Care
8
:
191
,
2000
12.
Stagnitti MN:
Medical Care and Treatment for Chronic Conditions, 2000
. Rockville, MD, Agency for Healthcare Research and Quality,
2002
(MEPS Statistical Brief no. 5)
13.
Harris MI: Racial and ethnic differences in health care access and health outcomes for adults with type 2 diabetes.
Diabetes Care
24
:
454
–459,
2001
14.
Moss SE, Klein R, Klein BEK: Risk factors for hospitalization in people with diabetes.
Arch Intern Med
159
:
2053
–2057,
1999
15.
Wagner EH, Sandhu N, Newton KM, McCulloch DK, Ramsey SD, Grothaus LC: Effect of improved glycemic control on health care costs and utilization.
JAMA
285
:
182
–189,
2001
16.
Institute of Medicine:
Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care
. Washington, DC, National Academy Press,
2002
17.
Weissman JS, Gatsonis C, Epstein AM: Rates of avoidable hospitalization by insurance status in Massachusetts and Maryland.
JAMA
268
:
2388
–2394,
1992
18.
Billings J, Zeitel L, Lukomnik J, Carey TS, Blank AE, Newman L: Impact of socioeconomic status on hospital use in New York City.
Health Aff (Millwood)
12
:
162
–173,
1993

Address correspondence and reprint requests to Dr. H. Joanna Jiang, Agency for Healthcare Research and Quality, 2101 East Jefferson St., Suite 605, Rockville, MD 20852. E-mail: [email protected].

Received for publication 7 October 2002 and accepted in revised form 10 February 2003.

The views expressed in this article are those of the authors and do not necessarily reflect those of the Agency for Healthcare Research and Quality or the U.S. Department of Health and Human Services.

Additional information for this article can be found in an online appendix at http://care.diabetesjournals.org.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.