User Support

May 2020

Pamela L. Owens, Ph.D., Audrey J. Weiss, Ph.D., and Marguerite L. Barrett, M.S.


Introduction

Reflective of the national opioid crisis, the rate of opioid-related hospitalizations has increased substantially in the United States, from 164.2 per 100,000 population in 2006 to 296.9 per 100,000 population in 2016.¹ The escalation in opioid-related inpatient stays has been accompanied by a disproportionately large increase in the costs associated with these types of hospitalizations. One study estimated that charges for hospital stays involving opioid abuse or dependence nearly quadrupled between 2002 and 2012, reaching almost $15 billion.²

The dramatic rise in hospitalizations related to taking opioids (defined as abuse, dependence, or use) and associated conditions place an increased burden on hospitals to be able to manage, treat, and potentially help minimize opioid-related problems for their patients. In October 2017, the American Hospital Association published a toolkit to assist hospitals in their efforts to address the opioid crisis, covering areas such as appropriate prescribing practices, identification and treatment of opioid use disorder, and nonopioid pain management.³ In order to help better focus hospital resources, it is important to understand which hospitals are facing the most substantial burden of opioid-related cases.

This Healthcare Cost and Utilization Project (HCUP) Statistical Brief focuses on the hospital burden of opioid-related hospitalizations by hospital urban-rural location. The Statistical Brief presents hospital statistics on opioid-related inpatient stays using the 2016 State Inpatient Databases (SID) from 46 States and the District of Columbia. The hospital rate of opioid-related stays per 1,000 inpatient stays is examined for a total of 4,207 community hospitals (excluding rehabilitation and long-term acute care hospitals) classified based on the urban-rural location of the hospital: metropolitan (metro), rural and adjacent to a metropolitan area (rural-adjacent), and rural and not adjacent to a metropolitan area (rural-remote). The hospital rate of opioid-related stays is presented by hospital urban-rural location for each U.S. census division. The distribution of the rate is provided across all metropolitan and rural hospitals. Finally, the rate is presented by hospital urban-rural location for hospitals with different bed sizes and occupancy levels. All differences between estimates noted in the text are statistically significant at the .05 level or better.

Findings

Burden of opioid-related stays in community hospitals by hospital urban-rural location, 2016
Figure 1 provides the average number and average hospital rate of opioid-related stays per 1,000 inpatient stays by hospital urban-rural location (metro, rural-adjacent to metro, and rural-remote) in 2016.

• Metropolitan hospitals had more opioid-related stays and had a higher average rate of opioid-related inpatient stays compared with rural hospitals.
  
  Of the 4,207 community hospitals examined, 60.9 percent (2,564 hospitals) were located in metropolitan areas, 21.3 percent (896 hospitals) were in rural-adjacent areas, and 17.8 percent (747 hospitals) were in rural-remote areas. In 2016, metropolitan hospitals treated 7 to 9 times as many opioid-related cases on average as did rural-adjacent or rural-remote hospitals (312.2 vs. 43.8 and 33.3, respectively). Moreover, the average hospital rate of opioid-related stays at metropolitan hospitals also was higher than the rate at rural-adjacent and rural-remote hospitals (30.8 per 1,000 stays vs. 20.1 and 16.2, respectively).

Figure 2 presents the average hospital rate of opioid-related stays per 1,000 inpatient stays by hospital urban-rural location and U.S. census division in 2016. The number of hospitals in each hospital urban-rural location in each census division category is provided to the right of the figure, for reference.

• The opioid burden based on hospital urban-rural location varied substantially across U.S. census divisions.
  
  Across U.S. census divisions, the average hospital rate of opioid-related inpatient stays ranged from 9.4 per 1,000 stays among rural-remote hospitals in the West South Central division to 40.7 per 1,000 stays among metropolitan hospitals in the New England division. Within U.S. census divisions, hospitals in the New England division had the smallest variation in the average hospital rate of opioid-related stays by hospital urban-rural location, ranging from 32.7 for rural-adjacent hospitals to 40.7 for metropolitan hospitals. Hospitals in the West North Central division had the largest variation, with the average hospital rate of opioid-related stays for metropolitan hospitals more than double the rate for rural-remote hospitals (22.1 vs. 9.9 per 1,000 stays).



• For most divisions, metropolitan hospitals had a larger opioid burden than did rural hospitals.
  
  For eight of the nine divisions, metropolitan hospitals had average hospital rates of opioid-related inpatient stays that were higher than the rates for rural-adjacent and/or rural-remote hospitals. Only in the New England division were the rates of opioid-related stays similar for all three urban-rural hospital locations.

Distribution of hospital rates of opioid-related inpatient stays by hospital urban-rural location, 2016
Figure 3 displays the distribution of hospital rates of opioid-related inpatient stays among metropolitan hospitals compared with rural hospitals (rural-adjacent and rural-remote hospitals were combined for this analysis). In addition to the average hospital rate, the rate threshold for the 10 percent of hospitals with the highest rates also is noted.

• The hospital rate of opioid-related stays was higher on average among metropolitan than among rural hospitals.
  
  In 2016, the average hospital rate of opioid-related stays among metropolitan hospitals was 30.8 per 1,000 inpatient stays, and 10 percent of metropolitan hospitals had a rate above 57.7. The average hospital rate of opioid-related stays was lower among rural hospitals—18.3 per 1,000 inpatient stays—and 10 percent of rural hospitals had a rate above 39.0.
  
  A larger percentage of metropolitan hospitals than rural hospitals had the highest rates of opioid-related inpatient stays (defined as 64 per 1,000 stays or higher): 7.9 percent or 202 metropolitan hospitals versus 3.2 percent or 53 rural hospitals, respectively.
  
  A smaller percentage of metropolitan hospitals than rural hospitals had no opioid-related stays (rate of zero) during the year: 4.3 percent or 109 metropolitan hospitals versus 15.1 percent or 248 rural hospitals, respectively.

Figure 4 displays the distribution in hospital rates of opioid-related inpatient stays among rural hospitals adjacent to metropolitan areas compared with rural hospitals in remote areas. In addition to the average hospital rate, the rate threshold for the 10 percent of hospitals with the highest rates also is noted.

• The hospital rate of opioid-related stays was slightly higher on average among rural-adjacent than among rural-remote hospitals.
  
  In 2016, the average hospital rate of opioid-related stays among rural-adjacent hospitals was 20.1 per 1,000 inpatient stays, and 10 percent of these hospitals had a rate above 41.9. The average hospital rate of opioid-related stays was slightly lower among rural-remote hospitals—16.2 per 1,000 inpatient stays—and 10 percent of rural-remote hospitals had a rate above 36.3.
  
  Compared with rural-remote hospitals, a slightly larger percentage of rural-adjacent hospitals had the highest rates of opioid-related inpatient stays (defined as 64 per 1,000 stays or higher): 3.9 percent or 35 rural-adjacent hospitals versus 2.4 percent or 18 rural-remote hospitals, respectively.
  
  A smaller percentage of rural-adjacent hospitals than rural-remote hospitals had no opioid-related stays (rate of zero) during the year: 11.6 percent or 104 rural-adjacent hospitals versus 19.3 percent or 144 rural-remote hospitals, respectively.

Differences in the average hospital rates of opioid-related inpatient stays by hospital urban-rural location, bed size, and occupancy level, 2016
Figure 5 presents the average hospital rate of opioid-related inpatient stays by hospital urban-rural location and bed size in 2016. The number of hospitals by urban-rural location and bed size is provided below the figure, for reference.

• Small hospitals had the lowest opioid burden across all hospital bed sizes and locations.
  
  Regardless of urban-rural location of the hospital, the average hospital rate of opioid-related stays was lowest among the smallest hospitals, those with 25 or fewer beds (range: 11.7 per 1,000 stays for rural-remote hospitals to 14.9 per 1,000 stays for rural-adjacent hospitals), compared with larger hospitals in each location.

Figure 6 presents the average hospital rate of opioid-related inpatient stays by hospital urban-rural location and occupancy level in 2016. The number of hospitals by urban-rural location and occupancy level is provided below the figure, for reference.

• Metropolitan hospitals with high occupancy levels had the greatest opioid burden across all hospital urban-rural locations and occupancy levels.
  
  Overall, metropolitan hospitals with 75 percent or greater occupancy and those between 50 and 75 percent occupancy had the highest average hospital rates of opioid-related inpatient stays (34.6 and 33.5 per 1,000 stays, respectively).

About Statistical Briefs

Healthcare Cost and Utilization Project (HCUP) Statistical Briefs provide basic descriptive statistics on a variety of topics using HCUP administrative healthcare data. Topics include hospital inpatient, ambulatory surgery, and emergency department use and costs, quality of care, access to care, medical conditions, procedures, and patient populations, among other topics. The reports are intended to generate hypotheses that can be further explored in other research; the reports are not designed to answer in-depth research questions using multivariate methods.

Data Source

The estimates in this Statistical Brief are based upon data from the HCUP 2016 State Inpatient Databases (SID) from 46 States and the District of Columbia: Alaska, Arkansas, Arizona, California, Connecticut, Colorado, Delaware, District of Columbia, Florida, Hawaii, Iowa, Illinois, Indiana, Kansas, Kentucky, Louisiana, Maryland, Maine, Massachusetts, Michigan, Minnesota, Missouri, Mississippi, Montana, North Carolina, North Dakota, Nebraska, Nevada, New Jersey, New Mexico, New York, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, Wisconsin, West Virginia, and Wyoming.

Table 1 presents a summary of the number of hospitals for which HCUP 2016 inpatient data were available for analysis by U.S. census region and division.

Definitions

Diagnoses and ICD-10-CM
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 develop during the stay. All-listed diagnoses include the principal diagnosis plus these additional secondary conditions.

ICD-10-CM is the International Classification of Diseases, Tenth Revision, Clinical Modification. In October 2015, ICD-10-CM replaced the ICD-9-CM diagnosis with the ICD-10-CM diagnosis coding system for most inpatient and outpatient medical encounters. There are over 70,000 ICD-10-CM diagnosis codes.

Case definition
Opioid-related inpatient stays were defined using the all-listed ICD-10-CM diagnosis codes shown in Table 2.

Types of hospitals included in HCUP State Inpatient Databases
This analysis used State Inpatient Databases (SID) limited to data from community hospitals, which are defined as short-term, non-Federal, general, and other hospitals, excluding hospital units of other institutions (e.g., prisons). Community hospitals include obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded for this analysis are long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals. However, if a patient received long-term care, rehabilitation, or treatment for a psychiatric or chemical dependency condition in a community hospital, the discharge record for that stay was included in the analysis.

Unit of analysis
The unit of analysis in this Statistical Brief is the hospital. Hospital counts of opioid-related inpatient stays are based on the 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 1 year will be counted each time as a separate discharge from the hospital.

Urban-rural location of hospital
Hospital urban-rural location is based on the rural-urban continuum codes (RUCC) for U.S. counties developed by the United States Department of Agriculture (USDA).⁴ For this Statistical Brief, we collapsed the RUCC codes into the following three categories:

Metropolitan (metro) area:

• Counties in metro areas of 1 million population or more
• Counties in metro areas of 250,000 to 1 million population
• Counties in metro areas of fewer than 250,000 population

Rural-adjacent to metro area:

• Urban population of 20,000 or more, adjacent to a metro area
• Urban population of 2,500 to 19,999, adjacent to a metro area
• Completely rural or less than 2,500 urban population, adjacent to a metro area

Rural-remote area:

• Urban population of 20,000 or more, not adjacent to a metro area
• Urban population of 2,500 to 19,999, not adjacent to a metro area
• Completely rural or less than 2,500 urban population, not adjacent to a metro area

Region and division
Region is one of the four regions defined by the U.S. Census Bureau. Division corresponds to the location of the hospital and is one of the nine divisions defined by the U.S. Census Bureau.

• Northeast:
  • New England: Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut
  • Middle Atlantic: New York, New Jersey, Pennsylvania
• Midwest:
  • East North Central: Ohio, Indiana, Illinois, Michigan, Wisconsin
  • West North Central: Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, Kansas
• South:
  • South Atlantic: Delaware, Maryland, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida
  • East South Central: Kentucky, Tennessee, Alabama, Mississippi
  • West South Central: Arkansas, Louisiana, Oklahoma, Texas
• West:
  • Mountain: Montana, Idaho, Wyoming, Colorado, New Mexico, Arizona, Utah, Nevada
  • Pacific: Washington, Oregon, California, Alaska, Hawaii

About HCUP

The Healthcare Cost and Utilization Project (HCUP, pronounced "H-Cup") is a family of healthcare databases and related software tools and products developed through a Federal-State-Industry partnership and sponsored by the Agency for Healthcare Research and Quality (AHRQ). HCUP databases bring together the data collection efforts of State data organizations, hospital associations, and private data organizations (HCUP Partners) and the Federal government to create a national information resource of encounter-level healthcare data. HCUP includes the largest collection of longitudinal hospital care data in the United States, with all-payer, encounter-level information beginning in 1988. These databases enable research on a broad range of health policy issues, including cost and quality of health services, medical practice patterns, access to healthcare programs, and outcomes of treatments at the national, State, and local market levels.

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

Alaska Department of Health and Social Services
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
Delaware Division of Public Health
District of Columbia Hospital Association
Florida Agency for Health Care Administration
Georgia Hospital Association
Hawaii Laulima Data Alliance, a subsidiary of the Healthcare Association of Hawaii
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
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 State Department of Health
Missouri Hospital Industry Data Institute
Montana Hospital Association
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
North Dakota (data provided by the Minnesota Hospital Association)
Ohio Hospital Association
Oklahoma State Department of Health
Oregon Association of Hospitals and Health Systems
Oregon Office of Health Analytics
Pennsylvania Health Care Cost Containment Council
Rhode Island Department of Health
South Carolina Revenue and Fiscal Affairs Office
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 Department of Health and Human Resources, West Virginia Health Care Authority
Wisconsin Department of Health Services
Wyoming Hospital Association

About the SID

The HCUP State Inpatient Databases (SID) are hospital inpatient databases from data organizations participating in HCUP. The SID contain the universe of the inpatient discharge abstracts in the participating HCUP States, translated into a uniform format to facilitate multistate comparisons and analyses. Together, the SID encompass more than 95 percent of all U.S. community hospital discharges. The SID can be used to investigate questions unique to one State, to compare data from two or more States, to conduct market-area variation analyses, and to identify State-specific trends in inpatient care utilization, access, charges, and outcomes.

For More Information

For other information on mental and substance use disorders, refer to the HCUP Statistical Briefs located at www.hcup-us.ahrq.gov/reports/statbriefs/sb_mhsa.jsp.

For additional HCUP statistics, visit:

• HCUP Fast Stats at https://datatools.ahrq.gov/hcup-fast-stats for easy access to the latest HCUP-based statistics for healthcare information topics
• HCUPnet, HCUP's interactive query system, at datatools.ahrq.gov/hcupnet

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

For a detailed description of HCUP and more information on the design of the State Inpatient Databases (SID), please refer to the following database documentation:

Agency for Healthcare Research and Quality. Overview of the State Inpatient Databases (SID). Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality. Updated November 2019. www.hcup-us.ahrq.gov/sidoverview.jsp. Accessed February 3, 2020.

Suggested Citation

Owens PL (AHRQ), Weiss AJ (IBM Watson Health), Barrett ML (M.L. Barrett, Inc.). Hospital Burden of Opioid-Related Inpatient Stays: Metropolitan and Rural Hospitals, 2016. HCUP Statistical Brief #258. May 2020. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb258-Opioid-Hospitalizations-Rural-Metro-Hospitals-2016.pdf.

Acknowledgments

The authors would like to acknowledge the contributions of Minya Sheng of IBM Watson Health.

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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:

Joel W. Cohen, Ph.D., Director
Center for Financing, Access and Cost Trends
Agency for Healthcare Research and Quality
5600 Fishers Lane
Rockville, MD 20857


This Statistical Brief was posted online on May 26, 2020.


¹ Healthcare Cost and Utilization Project. HCUP Fast Stats, Opioid-Related Hospital Use. www.hcup-us.ahrq.gov/faststats/OpioidUseServlet?setting1=IP&location=US. Accessed January 26, 2020.
² Ronan MV, Herzig SJ. Hospitalizations related to opioid abuse/dependence and associated serious infections increased sharply, 2002-12. Health Affairs. 2016;35(5):832-7.
³ American Hospital Association. Stem the Tide: Addressing the Opioid Epidemic. 2017. Chicago: IL. www.aha.org/opioidtoolkit. Accessed October 9, 2019.
⁴ United States Department of Agriculture. Rural-Urban Continuum Codes. www.ers.usda.gov/data-products/rural-urban-continuum-codes/. Accessed June 26, 2019.