User Support

November 2007

Yafu Zhao, M.S. (Social & Scientific Systems), William Encinosa, Ph.D. (AHRQ), and Fred Hellinger, Ph.D (AHRQ)



Introduction

Increased access to expensive new drug therapies for persons with HIV infection has decreased the morbidity and mortality for HIV.1 Over the past decade, the proportion of HIV costs attributable to drugs has risen from 10 percent to more than 40 percent among persons with HIV infection, and the cost of drug therapy is now between $10,000 and $15,000 per year.^2,3,4 The importance of drug therapy is evidenced by the drop in the number of HIV deaths in the United States after the diffusion of drug therapies that include a protease inhibitor or a non-nucleoside reverse transcriptase inhibitors and at least one nucleoside reverse transcriptase inhibitor (referred to as highly active antiretroviral therapy or HAART).⁵ In December 1995, the first protease inhibitor was approved and several other protease inhibitors were approved in early 1996.⁶ In June 1996, the first non-nucleoside reverse transcriptase inhibitor was approved. In 1995, there were 51,117 persons in the United States who died from AIDS, and, after the diffusion of protease inhibitors and non-nucleoside reverse transcriptase inhibitors in 1996, the number of persons who died from AIDS fell to 22,245 in 1997.⁷ While this was an enormous initial decline in mortality, little is known about the longer term impact of HAART on HIV hospitalizations.

This Statistical Brief examines the long run trend in HIV hospitalizations between 1998 and 2005 after the introduction of HAART, using data from the Healthcare Cost and Utilization Project (HCUP). First, national estimates of HIV discharges and hospital costs are provided for 1998 and 2005. HIV-related hospital stays are analyzed by age, gender and payer. Second, we examined the top ten principal diagnoses for HIV hospital stays between 1998 and 2005. Third, the inpatient death rate of HIV hospitalizations and HIV-associated complications are examined. All differences between estimates in the text are statistically significant at the 0.05 level or better, unless otherwise noted.

HIV Discharges by age, sex, payer, and HIV cost
Table 1 estimates nationwide HIV-related discharges in 1998 and 2005. In 2005, there were 240,461 hospital inpatient discharges with either a principal or secondary HIV diagnosis. Compared to 1998, hospitalizations with any HIV diagnosis decreased by 11 percent. More specifically, there were 74,604 inpatient hospital stays with a principal HIV diagnosis in 2005, accounting for 31 percent of HIV-related hospitalization. Hospital stays with a principal HIV diagnosis decreased by 21 percent. However, in Figure 1, we see that hospital stays with a secondary HIV diagnosis declined between 1998 and 2001 by about 15 percent, but then increased thereafter. As a result, between 1998 and 2005, hospital stays with a secondary HIV diagnosis had declined by only 5 percent.

Findings

As shown in Table 1, in 1998, 43 percent of HIV hospital stays were among patients aged 35–44 and 28 percent were among younger adults aged 18–34. In 2005, however, 36 percent of all HIV hospitalizations were for patients aged 35–44 and young adults aged 18–34 accounted for 20 percent of all HIV hospital stays. Among the groups with decreased HIV hospitalizations, infant HIV hospital stays decreased the most, by 64 percent from 1998 to 2005. HIV hospital stays among children aged 2–17 dropped 41 percent. However, the number of hospital discharges increased among patients aged 45 and over. The largest increase was 61 percent for the near-elderly (aged 55–64). HIV hospitalizations increased by 56 percent for the elderly and by 43 percent for patients aged 45–54.

More men had HIV hospitalizations compared with women in 1998 and 2005. Men accounted for 68 percent of all HIV hospital stays in 2005. There were 162,517 hospital stays for men and 77,854 hospital stays for women in 2005. HIV discharges declined for both sexes from 1998 to 2005, with a steeper decline among females.

Medicaid and Medicare reimbursed the majority of HIV hospitalizations over the time period. In 2005, 43 percent of HIV hospitalizations were paid by Medicaid and 28 percent by Medicare. Private insurance covered 16 percent of HIV hospital stays and self-pay patients covered 10 percent. HIV hospital stays covered by Medicaid, private insurance, and self-pay declined by 18 percent, 26 percent and 2 percent respectively. However, charity care coverage of HIV hospital stays increased by 44 percent. Moreover, hospitalizations covered by Medicare increased by 16 percent.

Costs in 1998 are inflation-adjusted to 2005 dollars.⁸ The average cost per stay increased by 16 percent from $11,465 in 1998 to $13,290 in 2005. National HIV hospitalization costs in 2005 totaled $3.2 billion, an increase of only 4 percent since 1998.

Principal diagnosis for HIV hospitalizations
Table 2 presents the top ten principal diagnoses for HIV hospitalization in 1998 and 2005. These ten principal diagnoses accounted for 61 percent of all HIV hospital stays in 1998 and 54 percent in 2005. Among all HIV hospital stays, HIV as a principal diagnosis accounted for 35 percent in 1998 and 31 percent in 2005. Among hospital stays with HIV as a secondary diagnosis, pneumonia was the most common principal diagnosis, accounting for 7 percent of all HIV hospitalizations in 1998 and 5 percent in 2005. HIV hospital stays with substance-related mental disorders as a principal diagnosis dropped in ranking compared to 1998, but remained in the top 5 principal diagnoses. Skin infections and schizophrenia, however, accounted for more HIV hospital stays as a principal diagnosis in 2005 compared to 1998. Other conditions such as affective disorders, alcohol-related mental disorders, complications of device, and pancreatic disorders were among the top ten principal diagnoses in both years. In addition, there were more principal diagnoses with nonspecific chest pain in 2005 compared to 1998.

Death rate, clinical conditions and mental disorders among HIV inpatient stays
Table 3 presents outcomes of HIV hospitalizations and examines HIV-associated complications and mental health conditions among HIV inpatients.

The average length of HIV-related hospital stays declined from 7.4 days in 1998 to 6.9 days in 2005. Between 1998 and 2005, the death rate of HIV inpatients declined 22 percent from 4.9 percent to 3.8 percent. In 1998, 13,141 HIV patients died (based on all-listed diagnoses) while 9,109 patients died during HIV-related hospitalizations in 2005. Men had a higher death rate than women in both years, but the death rate among men declined more compared to women.

It is known that HIV-infected people have increased risks of infections and cancers as their immune systems are weakened by HIV. In Table 3, we reported major HIV-associated complications which usually do not occur in people who have a normal immune system. These conditions are among the 1993 AIDS surveillance case definition by the Centers for Disease Control and Prevention (CDC).⁹

Among the complications, candidiasis and pneumocystis carinii pneumonia (PCP) were the more common complications associated with HIV hospital stays. In 2005, 15 percent of HIV hospitalizations were associated with candidiasis and 6 percent with PCP. 1.7 percent of HIV patients were infected with cytomegaloviral diseases and 1.7 percent with mycobacterial diseases, while 1.5 percent had a diagnosis of Kaposi’s sarcoma.

Between 1998 and 2005, complications related to HIV infection generally declined. Cytomegaloviral diseases declined by 56 percent, pulmonary tuberculosis by 47 percent, mycobacterial diseases by 37 percent and toxoplasmosis by 37 percent. Besides theses HIV-associated complications, we also examined weight loss, which is a major symptom among seriously ill HIV patients. As shown in Table 3, weight loss occurred in less than 1 percent of HIV inpatient stays, but HIV hospital stays with weight loss increased by 91 percent between 1998 and 2005.

In 2005, 26 percent of HIV hospitalizations involved drug abuse as a co-existing condition. Alcohol abuse, psychosis and depression occurred among 13 percent, 13 percent, and 10 percent of HIV hospitalizations, respectively in 2005. Between 1998 and 2005, alcohol abuse among HIV patients declined by 16 percent and drug abuse declined by 19 percent. However, depression increased by 56 percent and psychosis increased by 12 percent.

Data Source

The estimates in this Statistical Brief are based upon data from the HCUP 1998 and 2005 Nationwide Inpatient Sample (NIS).

Definitions

Diagnoses, ICD-9-CM, and Clinical Classifications Software (CCS)
The principal diagnosis is that condition established after study to be chiefly responsible for the patient’s admission to the hospital. Secondary diagnoses are concomitant conditions that coexist at the time of admission or that develop during the stay. All-listed diagnoses include the principal diagnosis plus these additional secondary conditions.

ICD-9-CM is the International Classification of Diseases, Ninth Revision, Clinical Modification, which assigns numeric codes to diagnoses. There are about 12,000 ICD-9-CM diagnosis codes.

CCS categorizes ICD-9-CM diagnoses into 260 clinically meaningful categories.¹⁰ This "clinical grouper" makes it easier to quickly understand patterns of diagnoses and procedures.

We identified HIV-related hospitalizations with CCS diagnosis category 5 (HIV infection). We used the following ICD-9-CM diagnosis codes for HIV-associated complications and weight loss:

We used the following ICD-9-CM diagnosis codes for mental disorders:

–alcohol-related mental disorders:
291.0, 291.1, 291.2, 291.3, 291.5, 291.8, 291.81, 291.89, 291.9, 303.00, 303.01, 303.02, 303.03, 303.90, 303.91, 303.92, 303.93, 305.00, 305.01, 305.02, and 305.03

–drug-related mental disorders:
292.0, 292.82, 292.83, 292.84, 292.89, 292.9, 304.00, 304.01, 304.02, 304.03, 304.10, 304.11, 304.12, 304.13, 304.20, 304.21, 304.22, 304.23, 304.30, 304.31, 304.32, 304.33, 304.40, 304.41, 304.42, 304.43, 304.50, 304.51, 304.52, 304.53, 304.60, 304.61, 304.62, 304.63 304.70, 304.71, 304.72, 304.73, 304.80, 304.81, 304.82, 304.83, 304.90, 304.91, 304.92, 304.93, 305.20, 305.21, 305.22, 305.23, 305.30, 305.31, 305.32, 305.33, 305.40, 305.41, 305.42, 305.43, 305.50, 305.51, 305.52, 305.53, 305.60, 305.61, 305.62, 305.63, 305.70, 305.71, 305.72, 305.73, 305.80, 305.81, 305.82, 305.83, 305.90, 305.91, 305.92, 305.93, 648.30, 648.31, 648.32, 648.33, and 648.34

–psychosis:
295.00, 295.01, 295.02, 295.03, 295.04, 295.05, 295.10, 295.11, 295.12, 295.13, 295.14, 295.15, 295.20, 295.21, 295.22, 295.23, 295.24, 295.25, 295.30, 295.31, 295.32, 295.33, 295.34, 295.35, 295.40, 295.41, 295.42, 295.43, 295.44, 295.45, 295.50, 295.51, 295.52, 295.53, 295.54, 295.55, 295.60, 295.61, 295.62, 295.63, 295.64, 295.65, 295.70, 295.71, 295.72, 295.73, 295.74, 295.75, 295.80, 295.81, 295.82, 295.83, 295.84, 295.85, 295.90, 295.91, 295.92, 295.93, 295.94, 295.95, 296.00, 296.01, 296.02, 296.03, 296.04, 296.05, 296.06, 296.10, 296.11, 296.12, 296.13, 296.14, 296.15, 296.16, 296.20, 296.21, 296.22, 296.23, 296.24, 296.25, 296.26, 296.30, 296.31, 296.32, 296.33, 296.34, 296.35, 296.36, 296.40, 296.41, 296.42, 296.43, 296.44, 296.45, 296.46, 296.50, 296.51, 296.52, 296.53, 296.54, 296.55, 296.56, 296.60, 296.61, 296.62, 296.63, 296.64, 296.65, 296.66, 296.7, 296.80, 296.81, 296.82, 296.89, 296.90, 296.99, 297.0, 297.1, 297.2, 29 7.3, 297.8, 297.9, 298.0, 298.1, 298.2, 298.3, 298.4, 298.8, 298.9, 299.10, and 299.11

–depression:
300.4, 301.12, 309.0, 309.1, 311, 290.13, and E950.

Types of hospitals included in HCUP
HCUP is based on data from community hospitals, defined as short-term, non-Federal, general and other hospitals, excluding hospital units of other institutions (e.g., prisons). HCUP data include OB-GYN, ENT, orthopedic, cancer, pediatric, public, and academic medical hospitals. They exclude long-term care, rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals, but these types of discharges are included if they are from community hospitals.

Unit of analysis
The unit of analysis is the hospital discharge (i.e., the hospital stay), not a person or patient. This means that a person who is admitted to the hospital multiple times in one year will be counted each time as a separate "discharge" from the hospital.

Costs and charges
Total hospital charges were converted to costs using HCUP cost-to-charge ratios based on hospital accounting reports from the Centers for Medicare and Medicaid Services (CMS).¹¹ Costs will tend to reflect the actual costs of production, while charges represent what the hospital billed for the case. For each hospital, a hospital-wide cost-to-charge ratio is used because detailed charges are not available across all HCUP states. Hospital charges reflect the amount the hospital charged for the entire hospital stay and does not include professional (physician) fees. For the purposes of this Statistical Brief, costs are reported to the nearest hundred.

Payer
Payer is the expected payer for the hospital stay. To make coding uniform across all HCUP data sources, payer combines detailed categories into more general groups:
–Medicare includes fee-for-service and managed care Medicare patients.
–Medicaid includes fee-for-service and managed care Medicaid patients. Patients covered by the State Children's Health Insurance Program (SCHIP) may be included here. Because most state data do not identify SCHIP patients specifically, it is not possible to present this information separately.
–Private insurance includes Blue Cross, commercial carriers, and private HMOs and PPOs.
–Other includes Worker's Compensation, TRICARE/CHAMPUS, CHAMPVA, Title V, and other government and non-government programs.
–Self-pay indicates the patient was responsible for the hospital bill with no third-party coverage.
–No charge is assumed to be charity care.
When more than one payer is listed for a hospital discharge, the first-listed payer is used.

About HCUP

HCUP is a family of powerful healthcare databases, software tools, and products for advancing research. Sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP includes the largest all-payer encounter-level collection of longitudinal healthcare data (inpatient, ambulatory surgery, and emergency department) in the United States, beginning in 1988. HCUP is a Federal-State-Industry Partnership that brings together the data collection efforts of many organizations—such as State data organizations, hospital associations, private data organizations, and the Federal government—to create a national information resource.

HCUP would not be possible without the contributions of the following data collection Partners from across the United States:

Arizona Department of Health Services
Arkansas Department of Health & Human Services
California Office of Statewide Health Planning & Development
Colorado Health & Hospital Association
Connecticut Integrated Health Information (Chime, Inc.)
Florida Agency for Health Care Administration
Georgia GHA: An Association of Hospitals & Health Systems
Hawaii Health Information Corporation
Illinois Health Care Cost Containment Council and Department of Public Health
Indiana Hospital&Health Association
Iowa Hospital Association
Kansas Hospital Association
Kentucky Cabinet for Health and Family Services
Maryland Health Services Cost Review Commission
Massachusetts Division of Health Care Finance and Policy
Michigan Health & Hospital Association
Minnesota Hospital Association
Missouri Hospital Industry Data Institute
Nebraska Hospital Association
Nevada Division of Health Care Financing and Policy, Department of Human Resources
New Hampshire Department of Health & Human Services
New Jersey Department of Health and Senior Services
New York State Department of Health
North Carolina Department of Health and Human Services
Ohio Hospital Association
Oklahoma Health Care Information Center for Health Statistics
Oregon Association of Hospitals and Health Systems
Rhode Island Department of Health
South Carolina State Budget & Control Board
South Dakota Association of Healthcare Organizations
Tennessee Hospital Association
Texas Department of State Health Services
Utah Department of Health
Vermont Association of Hospitals and Health Systems
Virginia Health Information
Washington State Department of Health
West Virginia Health Care Authority
Wisconsin Department of Health & Family Services

About the NIS

The HCUP Nationwide Inpatient Sample (NIS) is a nationwide database of hospital inpatient stays. The NIS is nationally representative of all community hospitals (i.e., short-term, non-Federal, non-rehabilitation hospitals). The NIS is a sample of hospitals and includes all patients from each hospital, regardless of payer. It is drawn from a sampling frame that contains hospitals comprising about 90 percent of all discharges in the United States. The vast size of the NIS allows the study of topics at both the national and regional levels for specific subgroups of patients. In addition, NIS data are standardized across years to facilitate ease of use.

About HCUPnet

HCUPnet is an online query system that offers instant access to the largest set of all-payer healthcare databases that are publicly available. HCUPnet has an easy step-by-step query system, allowing for tables and graphs to be generated on national and regional statistics, as well as trends for community hospitals in the U.S. HCUPnet generates statistics using data from HCUP's Nationwide Inpatient Sample (NIS), the Kids' Inpatient Database (KID), the State Inpatient Databases (SID) and the State Emergency Department Databases (SEDD).

For More Information

For more information about HCUP, visit www.hcup-us.ahrq.gov.

For additional HCUP statistics, visit HCUPnet, our interactive query system at https://datatools.ahrq.gov/hcupnet.

For information on other hospitalizations in the U.S., download HCUP Facts and Figures: Statistics on Hospital-based Care in the United States in 2005, located at http://www.hcup-us.ahrq.gov/reports.jsp.

For a detailed description of HCUP, more information on the design of the NIS, and methods to calculate estimates, please refer to the following publications:

Steiner, C., Elixhauser, A., Schnaier, J. The Healthcare Cost and Utilization Project: An Overview. Effective Clinical Practice 5(3):143–51, 2002.

Design of the HCUP Nationwide Inpatient Sample, 2005. Online. June 13, 2007. U.S. Agency for Healthcare Research and Quality.http://www.hcup-us.ahrq.gov/db/nation/nis/reports/NIS_2005_Design_Report.pdf

Houchens, R., Elixhauser, A. Final Report on Calculating Nationwide Inpatient Sample (NIS) Variances, 2001. HCUP Methods Series Report #2003-2. Online. June 2005 (revised June 6, 2005). U.S. Agency for Healthcare Research and Quality. http://www.hcup-us.ahrq.gov/reports/methods/2003_02.pdf

Houchens RL, Elixhauser A. Using the HCUP Nationwide Inpatient Sample to Estimate Trends. (Updated for 1988-2004). HCUP Methods Series Report #2006-05 Online. August 18, 2006. U.S. Agency for Healthcare Research and Quality. http://www.hcup-us.ahrq.gov/reports/methods/2006_05_NISTrendsReport_1988-2004.pdf

Suggested Citation

Zhao, Y., Encinosa, W. and Hellinger, F. HIV Hospitalizations in 1998 and 2005. HCUP Statistical Brief #41. November 2007. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb41.pdf

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AHRQ welcomes questions and comments from readers of this publication who are interested in obtaining more information about access, cost, use, financing, and quality of healthcare in the United States. We also invite you to tell us how you are using this Statistical Brief and other HCUP data and tools, and to share suggestions on how HCUP products might be enhanced to further meet your needs. Please e-mail us at hcup@ahrq.gov or send a letter to the address below:

Irene Fraser, Ph.D., Director
Center for Delivery, Organization, and Markets
Agency for Healthcare Research and Quality
540 Gaither Road
Rockville, MD 20850



¹Palella, F. J., Delaney K.M, Moorman A.C., Loveless M. O, Fuhrer J. F., Satten G. A, Aschman D. J., and S. D. Holmerg, and the HIV Outpatient Study Investigators. Declining Morbidity and Mortality Among Patients with Advanced Human Immunodeficiency Virus Infection The New England Journal of Medicine, vol. 338, no. 13, March 26, 1998, pp. 853-860.
²Hellinger, F. J. "The Lifetime Cost of Treating a Person with HIV" JAMA, vol. 270, no. 4, July 28, 1993, pp. 474-478.
³Bozzette, S. A., Berry S. H., Duan N., Frankel M. R., Leibowitz A. A., Lefkowitz D., Emmons C., Senterfitt J. W., Berk M. L., Morton S. C., and M. F. Shapiro. "The Care of HIV-Infected Adults in the United States" NEJM, vol. 339, no. 26, Dec. 24, 1998, pp. 1897-1904.
⁴Bozzette S., Geoffrey J., McCaffrey D. F. et al. "Expenditures for the Care of HIV-Infected Patients in the Era of Highly Active Antiretroviral Therapy" The New England Journal of Medicine, vol. 344, no. 11, March 15, 2001, pp. 817-823.
⁵Aldridge, C., Davis, D., and A. Doyle, National ADAP Monitoring Project: Interim Technical Report, supported by a grant from The Henry J. Kaiser Family Foundation, Menlo Park, California, April 2002.
⁶Moore R.D. and R.E. Chaisson, "Costs to Medicaid of Advancing Immunosuppression in an Urban HIV-Infected Patient Population in Maryland", Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology, vol. 14, no. 3, 1997, pp. 223-231.
⁷US Centers for Disease Control and Prevention, HIV/AIDS Surveillance Report: US HIV and AIDS Cases Reported through June 2001, vol. 13 no. 1, 2001.
⁸Costs are adjusted for economy-wide inflation using the U.S. Bureau of Economic Analysis Gross Domestic Product Price Index.
⁹http://www.cdc.gov/MMWR/preview/MMWRhtml/00018871.htm.
¹⁰HCUP CCS. Healthcare Cost and Utilization Project (HCUP). August 2006. U.S. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp.
¹¹HCUP Cost-to-Charge Ratio Files (CCR). Healthcare Cost and Utilization Project (HCUP). 2001–2003. U.S. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/db/state/costtocharge.jsp.