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January 2013

Anne Pfuntner, Lauren M. Wier, M.P.H., and Carol Stocks, R.N., M.H.S.A.



Introduction

A patient can be admitted to the hospital with multiple conditions or diagnoses. The principal diagnosis is the condition that is primarily responsible for a patient's hospitalization. This condition can affect other components of the patient's hospital stay, including the length of stay, healthcare costs, and procedures performed.

This Statistical Brief presents data from the Healthcare Cost and Utilization Project (HCUP) on the most common principal diagnoses in 2010 for all hospital stays in the United States, as well as for stays by age and primary payer. Changes in the overall number of stays and the rate of hospitalization in the population are presented for the most common conditions in 1997 and 2010. All differences between estimates noted in the text are statistically significant at the .001 level or better.

Findings

Most frequent principal diagnoses during hospital stays, 2010
Table 1 shows the most frequent principal diagnoses during hospital stays in 2010. In 2010, there were 39 million hospital stays in the U.S.—1,261 stays per 10,000 population. The 10 most frequent principal diagnoses accounted for 30 percent of all stays in 2010.

Liveborn (newborn infant) was the most common reason for hospitalization, accounting for more than 3.9 million stays in 2010 (10 percent of all stays).

Two respiratory illnesses—pneumonia and chronic obstructive pulmonary disease (COPD)—were among the 10 most frequent principal diagnoses in 2010. Pneumonia was the second most common reason for hospitalization in 2010 (2.8 percent of all stays).

Two circulatory conditions—congestive heart failure (CHF) and cardiac dysrhythmias—were also among the 10 most common principal diagnoses in 2010.

Principal diagnoses with the most rapid growth, 1997-2010
Although the rate of hospitalization overall remained stable between 1997 and 2010, the hospitalization rate for some principal diagnoses experienced rapid growth (table 2). Acute renal failure was the most rapidly growing condition between 1997 and 2010, with an increase of 264 percent in the hospitalization rate (from 3.6 to 13.1 stays per 10,000 population). The hospitalization rate for 5 conditions—prolonged pregnancy, pulmonary heart disease, osteoarthritis, anemia, and septicemia—also doubled during this time period.

Most frequent principal diagnoses by age during hospital stays, 2010
Table 3 highlights the 5 most frequent reasons for hospitalization for each age group in 2010 as well as the change in the rate of hospitalization for these diagnoses since 1997. Overall, the hospitalization rate increased with age—with the exception of infants, who had a high hospitalization rate (11,438 per 10,000 population) primarily because of newborn births, which accounted for 86 percent of stays for children younger than 1 year.

For children ages 1-17, the top 3 principal diagnoses in 2010—mood disorders, pneumonia, and asthma—each occurred in 17 stays per 10,000 population. The rate of hospitalization for asthma fell by 30 percent and doubled for skin and subcutaneous tissue infections between 1997 and 2010.

Among adults ages 18-44, 4 of the top 5 conditions were related to pregnancy and childbirth: trauma to the perineum and vulva due to childbirth, maternal stay with a previous Cesarean section, prolonged pregnancy, and hypertension complicating pregnancy and childbirth. The rate of hospitalization for delivery following a Cesarean section increased 82 percent; however, the rate of hospitalization for normal pregnancy and/or delivery fell 56 percent between 1997 and 2010 (data not shown).

In 2010, osteoarthritis was the most common principal diagnosis among adults ages 45-64 and 65-84. The rate of hospitalization for this condition increased 164 percent and 60 percent, respectively, among these age groups between 1997 and 2010. Cardiovascular conditions were also common among adults age 45 and older. The rate of hospitalization for nonspecific chest pain and coronary atherosclerosis for adults ages 45-64 decreased 16 percent and 64 percent, respectively, between 1997 and 2010.

Congestive heart failure (CHF), pneumonia, septicemia, and cardiac dysrhythmias accounted for 4 of the top 5 conditions among adults ages 65-84 and age 85 and older. Hospitalization rates for CHF, pneumonia, and septicemia were higher by a factor of 2 or more for adults age 85 and older, compared to rates among adults ages 65-84. From 1997 to 2010, the hospitalization rate for CHF and pneumonia decreased among adults age 65 and older. In contrast, hospitalization rates for septicemia increased by 80 percent among adults ages 65-84 and by 56 percent among adults age 85 and older.

Bipolar disorders and depressive disorders among children ages 1-17, 1997 and 2010
One age-related finding of particular interest warranted further analysis—mood disorders, the fourth-ranked principal diagnosis among children ages 1-17 in 1997, was the most frequent principal diagnosis in 2010. Table 4 shows the number of stays and rate of hospitalization for the two specific diagnoses that constitute mood disorders—bipolar disorders and depressive disorders—by age within the 1-17 age group.

Overall, depressive disorders comprised the largest share of mood disorders, with the rate of hospitalization highest among children ages 15-17 (29 stays per 10,000 population in 2010). The rate of hospitalization for depressive disorders among children remained relatively stable between 1997 and 2010. In contrast, there was more than a four-fold increase in the rate of hospitalization for bipolar disorders among children ages 1-17 between 1997 and 2010. This increase occurred for all ages (where data were available), with the highest rates among children ages 10-14 and 15-17 (11 and 21 stays per 10,000 population, respectively, in 2010). Bipolar disorders accounted for an increasing share of hospital stays for mood disorders among children ages 1-17 in 2010 (48 percent) versus 1997 (16 percent).

Most frequent principal diagnoses by payer during hospital stays, 2010
Table 5 shows the top 5 principal diagnoses for hospital stays by primary payer. The principal diagnoses for hospitalizations by primary payer generally varied, although some conditions were common across all payer types.

There were 14.5 million stays with Medicare as the primary payer in 2010. CHF was the most common principal diagnosis, accounting for 5 percent of all Medicare stays. The number of stays for pneumonia decreased slightly between 1997 and 2010 (12 percent), but there was an increase in the number of stays billed to Medicare for septicemia (122 percent), osteoarthritis (87 percent), and cardiac dysrhythmias (32 percent).

Medicaid was the primary payer for 8.3 million stays in 2010—an increase of 47 percent from 1997. Three pregnancy- and childbirth-related conditions accounted for nearly 30 percent of all Medicaid stays in 2010: newborn birth, trauma to the perineum and vulva caused by childbirth, and previous Cesarean section. The number of stays for newborn birth and previous Cesarean section both grew from 1997 to 2010 (48 percent and 169 percent, respectively). Mood disorders was the third most common condition with Medicaid as the primary payer, increasing 78 percent from 1997 to 2010.

Private insurance was the primary payer for 12.5 million stays in 2010. Newborn birth was the most common reason for stays billed to private insurance, accounting for 15 percent of stays. Osteoarthritis was the second most common principal diagnosis among private insurance stays and more than tripled between 1997 and 2010.

The uninsured accounted for 2.3 million stays in 2010—a 40-percent increase since 1997. Newborn births accounted for 7 percent of all uninsured stays in 2010. Four of the most common conditions for uninsured hospital stays increased by more than 50 percent from 1997 to 2010: alcohol-related disorders and nonspecific chest pain grew by 52 percent and 68 percent, respectively; stays for mood disorders nearly doubled; and skin and subcutaneous tissue infections nearly tripled.

Data Source

The estimates in this Statistical Brief are based upon data from the HCUP 2010 NIS. Historical data were drawn from the 1997 NIS. Supplemental sources included data on national population estimates from "Intercensal Estimates of the Resident Population by Single Year of Age, Sex, Race, and Hispanic Origin for the United States: April 1, 2000 to July 1, 2010," Population Division, U.S. Census Bureau, Release date: September 2011. Available at (https://www.census.gov/data/datasets/time-series/demo/popest/intercensal-2000-2010-national.html). (Accessed January 7, 2013).

Supplemental sources also included data on national population estimates from "Intercensal Estimates of the United States Resident Population by Age and Sex, 1990-2000: Selected Months," Population Division, U.S. Census Bureau, Release date: August 2004. Available at (https://www.census.gov/data/datasets/time-series/demo/popest/intercensal-1990-2000-national.html). (Accessed November 8, 2017).

Many hypothesis tests were conducted for this Statistical Brief. Thus, to decrease the number of false-positive results, we reduced the significance level to .001 for individual tests.

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.

ICD-9-CM is the International Classification of Diseases, Ninth Revision, Clinical Modification, which assigns numeric codes to diagnoses. There are about 14,000 ICD-9-CM diagnosis codes.

CCS categorizes ICD-9-CM diagnoses into a manageable number of clinically meaningful categories.¹ This "clinical grouper" makes it easier to quickly understand patterns of diagnoses. CCS categories identified as "Other" are typically not reported; these categories include miscellaneous, otherwise unclassifiable diagnoses that may be difficult to interpret as a group.

The single-level diagnosis CCS aggregates illnesses and conditions into 285 mutually exclusive categories. The multi-level CCS groups single-level CCS categories into broader categories (e.g., "Diseases of the Circulatory System", "Mental Disorders", and "Injury") and also splits single-level CCS categories to provide more detail about particular groupings of codes.

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 obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are long-term care, rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals. However, if a patient received long-term care, rehabilitation, or treatment for psychiatric or chemical dependency conditions in a community hospital, the discharge record for that stay will be included in the NIS.

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.

Payer
Payer is the expected primary 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 programs
• Uninsured: includes an insurance status of "self-pay" and "no charge."

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:

Alaska State Hospital and Nursing Home Association
Arizona Department of Health Services
Arkansas Department of Health
California Office of Statewide Health Planning and Development
Colorado Hospital Association
Connecticut Hospital Association
Florida Agency for Health Care Administration
Georgia Hospital Association
Hawaii Health Information Corporation
Illinois Department of Public Health
Indiana Hospital Association
Iowa Hospital Association
Kansas Hospital Association
Kentucky Cabinet for Health and Family Services
Louisiana Department of Health and Hospitals
Maine Health Data Organization
Maryland Health Services Cost Review Commission
Massachusetts Center for Health Information and Analysis
Michigan Health & Hospital Association
Minnesota Hospital Association
Mississippi Department of Health
Missouri Hospital Industry Data Institute
Montana MHA - An Association of Montana Health Care Providers
Nebraska Hospital Association
Nevada Department of Health and Human Services
New Hampshire Department of Health & Human Services
New Jersey Department of Health
New Mexico Department of Health
New York State Department of Health
North Carolina Department of Health and Human Services
Ohio Hospital Association
Oklahoma State Department of Health
Oregon Association of Hospitals and Health Systems
Oregon Health Policy and Research
Pennsylvania Health Care Cost Containment Council
Rhode Island Department of Health
South Carolina 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 Services
Wyoming Hospital Association

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, nonrehabilitation 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 more than 95 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 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 United States. HCUPnet generates statistics using data from HCUP's Nationwide Inpatient Sample (NIS), the Kids' Inpatient Database (KID), the Nationwide Emergency Department Sample (NEDS), the State Inpatient Databases (SID), and the State Emergency Department Databases (SEDD).

For More Information

For more information about HCUP, visit http://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 United States, download HCUP Facts and Figures: Statistics on Hospital-Based Care in the United States in 2009, 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:

Introduction to the HCUP Nationwide Inpatient Sample, 2010. Online. May 2012. U.S. Agency for Healthcare Research and Quality. Available at http://www.hcup-us.ahrq.gov/db/nation/nis/NISIntroduction2010.pdf. (Accessed January 7, 2013).

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. Available at http://www.hcup-us.ahrq.gov/reports/methods/2003_02.pdf. (Accessed January 7, 2013).

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. Available at https://www.hcup-us.ahrq.gov/reports/methods/2006_05_NISTrendsReport_1988-2004A.pdf. (Accessed January 7, 2013).

Suggested Citation

Pfuntner, A (Truven Health Analytics), Wier, LM (Truven Health Analytics), Stocks, C (AHRQ). Most Frequent Conditions in U.S. Hospitals, 2010. HCUP Statistical Brief #148. January 2013. Agency for Healthcare Research and Quality, Rockville, MD. Available at http://www.hcup-us.ahrq.gov/reports/statbriefs/sb148.pdf.

Acknowledgments

The authors would like to acknowledge the contributions of Eva Witt of Truven Health Analytics.

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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



¹ HCUP Clinical Classifications Software (CCS). Healthcare Cost and Utilization Project (HCUP). U.S. Agency for Healthcare Research and Quality, Rockville, MD. Available at http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Updated March 2012. (Accessed January 7, 2013).