HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Appendix Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Jiang, H. J. Articles by Andrews, R. Search for Related Content PubMed PubMed Citation Articles by Jiang, H. J. Articles by Andrews, R. Social Bookmarking                What's this?

Multiple Hospitalizations for Patients With Diabetes

¹ Center for Organization and Delivery Studies, Agency for Healthcare Research and Quality, Rockville, Maryland
² Center for Quality Improvement and Patient Safety, Agency for Healthcare Research and Quality, Rockville, Maryland

	ABSTRACT

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

 
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.

Abbreviations: HCUP, Healthcare Cost and Utilization Project • PNUM, patient number

	INTRODUCTION

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

 
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.

	RESEARCH DESIGN AND METHODS

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

 
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 ² 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.

	RESULTS

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

 
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 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.

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.

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.

View this table: [in this window] [in a new window]   Table 4— Presence of diabetes complications and chronic conditions among adult patients with multiple hospital stays, by race and payer

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

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 HbA_1c 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.

	Acknowledgments

 
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.

	Footnotes

 
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: jjiang{at}ahrq.gov.

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.

	References

TOP ABSTRACT INTRODUCTION RESEARCH DESIGN AND METHODS RESULTS CONCLUSIONS References

 

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[Free Full Text]
   
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[Abstract/Free Full Text]
   
3. American Diabetes Association: Economic consequences of diabetes mellitus in the U.S. in 1997. Diabetes Care 21:296–309, 1998[Abstract]
   
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[Abstract]
   
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[Medline]
   
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[Medline]
   
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[Abstract/Free Full Text]
    
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[Abstract/Free Full Text]
    
14. Moss SE, Klein R, Klein BEK: Risk factors for hospitalization in people with diabetes. Arch Intern Med 159:2053–2057, 1999[Abstract/Free Full Text]
    
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[Abstract/Free Full Text]
    
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[Abstract]
    
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[Abstract]
    

CiteULike

Del.icio.us

Digg

Reddit

Technorati

This article has been cited by other articles:

				R. L. Rothman, S. Mulvaney, T. A. Elasy, A. VanderWoude, T. Gebretsadik, A. Shintani, A. Potter, W. E. Russell, and D. Schlundt Self-Management Behaviors, Racial Disparities, and Glycemic Control Among Adolescents With Type 2 Diabetes Pediatrics, April 1, 2008; 121(4): e912 - e919. [Abstract] [Full Text] [PDF]

				R. H. Glazier, J. Bajcar, N. R. Kennie, and K. Willson A Systematic Review of Interventions to Improve Diabetes Care in Socially Disadvantaged Populations Diabetes Care, July 1, 2006; 29(7): 1675 - 1688. [Abstract] [Full Text] [PDF]

				B. Friedman, H. J. Jiang, A. Elixhauser, and A. Segal Hospital Inpatient Costs for Adults with Multiple Chronic Conditions. Med Care Res Rev, June 1, 2006; 63(3): 327 - 346. [Abstract] [PDF]

				C. B. Cook, M. E. Boyle, N. S. Cisar, V. Miller-Cage, P. Bourgeois, L. R. Roust, S. A. Smith, and R. S. Zimmerman Use of Continuous Subcutaneous Insulin Infusion (Insulin Pump) Therapy in the Hospital Setting: Proposed Guidelines and Outcome Measures The Diabetes Educator, November 1, 2005; 31(6): 849 - 857. [Abstract] [Full Text] [PDF]

				H. J. Jiang, R. Andrews, D. Stryer, and B. Friedman Racial/Ethnic Disparities in Potentially Preventable Readmissions: The Case of Diabetes Am J Public Health, September 1, 2005; 95(9): 1561 - 1567. [Abstract] [Full Text] [PDF]

				T. Bodenheimer and A. Fernandez High and Rising Health Care Costs. Part 4: Can Costs Be Controlled While Preserving Quality? Ann Intern Med, July 5, 2005; 143(1): 26 - 31. [Abstract] [Full Text] [PDF]

				B. Friedman and J. Basu The Rate and Cost of Hospital Readmissions for Preventable Conditions Med Care Res Rev, June 1, 2004; 61(2): 225 - 240. [Abstract] [PDF]

				M. L. Maciejewski and C. Maynard Diabetes-Related Utilization and Costs for Inpatient and Outpatient Services in the Veterans Administration Diabetes Care, May 1, 2004; 27(suppl_2): B69 - B73. [Abstract] [Full Text] [PDF]

				S. Clement, S. S. Braithwaite, M. F. Magee, A. Ahmann, E. P. Smith, R. G. Schafer, and I. B. Hirsch Management of Diabetes and Hyperglycemia in Hospitals Diabetes Care, February 1, 2004; 27(2): 553 - 591. [Full Text] [PDF]

This Article Abstract Full Text (PDF) Appendix Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Request Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Jiang, H. J. Articles by Andrews, R. Search for Related Content PubMed PubMed Citation Articles by Jiang, H. J. Articles by Andrews, R. Social Bookmarking                What's this?