HEALTHCARE COST & UTILIZATION PROJECT

User Support

Do Your own analysis
Explore Expert Research & Limited Datasets

Changes in Hospitalizations and In-Hospital Deaths in the Initial Period of the COVID-19 Pandemic (April-December 2020), 29 States

STATISTICAL BRIEF #290
April 2022

Lawrence D. Reid, Ph.D., M.P.H., and Zhengyi Fang, M.S.


Introduction

Annually, there are approximately 35.5 million hospitalizations in the United States, including for medical conditions (48 percent), surgeries (20 percent), maternal conditions (11 percent), births and neonatal conditions (11 percent), mental health and substance use conditions (5 percent), and injuriesa (5 percent).1 With the COVID-19 pandemic beginning in early 2020, hospital utilization changed considerably, as areas of the country saw spikes in COVID-19 cases and subsequent hospitalizations. Hospitalizations related to COVID-19 varied by State and across time.2 In addition to changes in the need for hospital care, there were concerns about hospital capacity, as seen by the Centers for Medicare & Medicaid Services (CMS) recommendation that hospitals limit all nonessential planned surgeries and procedures.3 Little is known, however, about the impact of the initial period of the pandemic on hospitalizations and in-hospital deaths overall.

This Healthcare Cost and Utilization Project (HCUP) Statistical Brief presents data from 29 States on the number of hospitalizations and in-hospital deaths across time periods and States with a focus on the initial impact of the COVID-19 pandemic. The counts are presented overall and by patient characteristics across 29 States from April to December 2020 using quarterly HCUP inpatient data compared with State-level averages from April to December in 2016–2019 using the HCUP State Inpatient Databases (SID). The percentages of all hospitalizations and in-hospital deaths related to COVID-19 during the April–December 2020 timeframe are also provided. Because of the large sample size of the HCUP data, small differences can be statistically significant but not meaningful. Thus, only differences greater than or equal to 10 percent are discussed in the text.

This analysis is limited to discharges for patients treated in community, nonrehabilitation hospitals in 29 States (Arizona, California, Connecticut, Georgia, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Michigan, Minnesota, Mississippi, Missouri, New Jersey, New York, North Dakota, Ohio, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Vermont, Virginia, Washington, and Wisconsin) for which HCUP data were available for April–December 2016–2019 and April–December 2020. These States accounted for 67.3 percent of the resident U.S. population in 2019.4,5 Information contained in this Statistical Brief was primarily obtained from the HCUP Summary Trend Tables.6 The Summary Trend Tables, accessed as downloadable tables, provide State-specific monthly trends in hospital utilization for the most recent HCUP data available. These tables were also used to create the HCUP Visualization of Inpatient Trends in COVID-19 and Other Conditions7 and will be updated as more quarterly data become available.

Findings

State-level hospitalizations and in-hospital deaths, 2016–2019 and 2020
Figure 1 displays the number of hospitalizations and in-hospital deaths for each of the 29 States in April–December 2016–2019b and 2020, by quarter. Each dot in the figure represents the State-specific number of hospitalizations or in-hospital deaths. The average number of hospitalizations and in-hospital deaths across these 29 States is also presented.
Highlights
  • The decrease in the average number of all hospitalizations in the 29 States examined was largest in the second quarter (April–June; 20.1 percent decrease) of 2020 versus the same quarters in 2016–2019.


  • On average, the number of all-cause in-hospital deaths in the 29 States examined increased 38.5, 21.1, and 51.2 percent in the second (April–June; 5,400 deaths), third (July–September; 4,600 deaths), and fourth (October–December; 6,200 deaths) quarters of 2020, respectively, versus the same quarters in 2016–2019 (3,900, 3,800 and 4,100 deaths, respectively).

Figure 1. Number of hospitalizations (in thousands) and in-hospital deaths by quarter, April–December 2020 compared with the average of April–December 2016–2019, 29 States


Figure 1 is a scatter plot that shows the number of hospitalizations and in-hospital deaths for 29 States in April–December 2016–2019 and in April–December 2020, by quarter.

Notes: Number of in-hospital deaths is rounded to the nearest hundred. Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years. Each dot in the figure represents the State-specific number of hospitalizations or in-hospital deaths.
Source: Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project (HCUP), 2016–2019 State Inpatient Databases (SID) and 2020 quarterly data from 29 States (AZ, CA, CT, GA, IA, IL, IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, ND, NJ, NY, OH, OR, PA, SC, SD, TN, VA, VT, WA, and WI) (available as of October 2021)

Scatter plot that shows the number of hospitalizations and in-hospital deaths for 29 States in April–December 2016–2019 and in April–December 2020, by quarter. April–June 2016–2019: The number of hospitalizations ranged from 14,000 to 906,000 (average = 204,000). The number of in-hospital deaths ranged from 300 to 18,200 (average = 3,900). April–June 2020: The number of hospitalizations ranged from 10,000 to 730,000 (average = 163,000). The number of in-hospital deaths ranged from 200 to 27,300 (average = 5,400). July–September 2016–2019: The number of hospitalizations ranged from 13,000 to 919,000 (average = 204,000). The number of in-hospital deaths ranged from 300 to 17,100 (average = 3,800). July–September 2020: The number of hospitalizations ranged from 12,000 to 829,000 (average = 186,000). The number of in-hospital deaths ranged from 300 to 22,800 (average = 4,600). October–December 2016–2019: The number of hospitalizations ranged from 13,000 to 914,000 (average = 204,000). The number of in-hospital deaths ranged from 300 to 19,200 (average = 4,100). October–December 2020: The number of hospitalizations ranged from 11,000 to 828,000 (average = 185,000). The number of in-hospital deaths ranged from 300 to 29,100 (average = 6,200).


Figure 2 presents the number of hospitalizations and in-hospital deaths by census region, comparing April–December 2020 with the average from April–December 2016–2019.c The percentage of all hospitalizations and in-hospital deaths related to COVID-19 in April–December 2020 is also presented. Similar State-level data are provided in the Appendix.

Figure 2. Number of hospitalizations, in-hospital deaths, and percentage of each related to COVID-19 in April–December 2020 compared with the average of all hospitalizations in April–December 2016–2019, 29 States


Figure 2 is a combined bar chart and table that shows the number of hospitalizations and in-hospital deaths in 29 States by region.

Notes: Number of hospitalizations and in-hospital deaths is rounded to the nearest hundred. Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years. // indicates a break in the axis.
Source: Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project (HCUP), 2016–2019 State Inpatient Databases (SID) and 2020 quarterly data from 29 States (AZ, CA, CT, GA, IA, IL, IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, ND, NJ, NY, OH, OR, PA, SC, SD, TN, VA, VT, WA, and WI) (available as of October 2021)

Combined bar chart and table that shows the number of hospitalizations and in-hospital deaths in 29 States by region. The figure compares statistics for April–December 2020 with the average from April–December 2016–2019. It also presents the percentage of hospitalizations and in-hospital deaths related to COVID-19 in April–December 2020. Data are provided in Supplemental Table 1.


Patient characteristics associated with hospitalizations and in-hospital deaths, 2016-2019 and 2020
Figure 3 presents the number of hospitalizations and in-hospital deaths in 29 States combined by location of patient residence (large metro, medium/small metro, and rural), comparing April–December 2020 with the average from April–December 2016–2019.d The percentage of hospitalizations and in-hospital deaths related to COVID-19 in April–December 2020 is also presented.


Figure 3. Number of hospitalizations, in-hospital deaths, and percentage of each related to COVID-19 by location of patient residence in April–December 2020 compared with the average of all hospitalizations in April–December 2016–2019, 29 States


Figure 3 is a combined bar chart and table that shows the number of hospitalizations and in-hospital deaths in 29 States by location of patient residence.

Notes: Number of hospitalizations and in-hospital deaths is rounded to the nearest hundred. Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years.
Source: Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project (HCUP), 2016–2019 State Inpatient Databases (SID) and 2020 quarterly data from 29 States (AZ, CA, CT, GA, IA, IL, IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, ND, NJ, NY, OH, OR, PA, SC, SD, TN, VA, VT, WA, and WI) (available as of October 2021)

Combined bar chart and table that shows the number of hospitalizations and in-hospital deaths in 29 States by location of patient residence. The figure compares statistics for April–December 2020 with the average from April–December 2016–2019. It also presents the percentage of hospitalizations and in-hospital deaths related to COVID-19 in April–December 2020. Data are provided in Supplemental Table 2.


Figure 4 presents the number of hospitalizations and in-hospital deaths in 29 States combined by patient race/ethnicity, comparing April–December 2020 with the average from April–December 2016–2019.e The percentage of hospitalizations and in-hospital deaths related to COVID-19 in April–December 2020 is also presented.


Figure 4. Number of hospitalizations, in-hospital deaths, and percentage of each related to COVID-19 by patient race/ethnicity in April–December 2020 compared with the average of all hospitalizations in April–December 2016–2019, 29 States


Figure 4 is a combined bar chart and table that shows the number of hospitalizations and in-hospital deaths in 29 States by patient race/ethnicity.

Abbreviation: NH, non-Hispanic
Notes: Number of hospitalizations and in-hospital deaths is rounded to the nearest hundred. Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years.
Source: Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project (HCUP), 2016–2019 State Inpatient Databases (SID) and 2020 quarterly data from 29 States (AZ, CA, CT, GA, IA, IL, IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, ND, NJ, NY, OH, OR, PA, SC, SD, TN, VA, VT, WA, and WI) (available as of October 2021)

Combined bar chart and table that shows the number of hospitalizations and in-hospital deaths in 29 States by patient race/ethnicity. The figure compares statistics for April–December 2020 with the average from April–December 2016–2019. It also presents the percentage of hospitalizations and in-hospital deaths related to COVID-19 in April–December 2020. Data are provided in Supplemental Table 3.


Figure 5 presents the number of hospitalizations and in-hospital deaths in 29 States combined by primary expected payer, comparing April–December 2020 with the average from April–December 2016–2019.f The percentage of hospitalizations and in-hospital deaths related to COVID-19 in April–December 2020 is also presented.

  • The number of all hospitalizations decreased in April–December 2020 versus the average in April–December 2016–2019 for all expected payers, ranging from a 10.6 percent decrease for expected payers of Medicaid and self-pay/no charge to a 14.4 percent decrease for Medicare.

    In April–December 2020, the percentage of hospitalizations related to COVID-19 was nearly twice as high for stays with Medicare as an expected payer (8.9 percent) as those with Medicaid as an expected payer (4.7 percent).


  • The number of all-cause in-hospital deaths increased in April–December 2020 versus the average in April–December 2016–2019 for all expected payers, ranging from a 29.0 percent increase for stays with an expected payer of private insurance (56,900 to 73,400 deaths) to a 45.8 percent increase for those with an expected payer of Medicaid (38,000 to 55,400 deaths).

    The percentage of in-hospital deaths related to COVID-19 in April–December 2020 ranged from 23.5 percent for stays with self-pay/no charge as an expected payer to 33.0 percent for stays with Medicare as an expected payer.

Figure 5. Number of hospitalizations, in-hospital deaths, and percentage of each related to COVID-19 by primary expected payer in April–December 2020 compared with the average of all hospitalizations in April–December 2016–2019, 29 States


Figure 5 is a combined bar chart and table that shows the number of hospitalizations and in-hospital deaths in 29 States by primary expected payer.

Notes: Number of hospitalizations and in-hospital deaths is rounded to the nearest hundred. Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years.
* Self-pay/No charge: includes self-pay, no charge, charity, and no expected payment.
Source: Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project (HCUP), 2016–2019 State Inpatient Databases (SID) and 2020 quarterly data from 29 States (AZ, CA, CT, GA, IA, IL, IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, ND, NJ, NY, OH, OR, PA, SC, SD, TN, VA, VT, WA, and WI) (available as of October 2021)

Combined bar chart and table that shows the number of hospitalizations and in-hospital deaths in 29 States by primary expected payer. The figure compares statistics for April–December 2020 with the average from April–December 2016–2019. It also presents the percentage of hospitalizations and in-hospital deaths related to COVID-19 in April–December 2020. Data are provided in Supplemental Table 4.


Figure 6 presents the number of hospitalizations and in-hospital deaths in 29 States combined by community-level income, comparing April–December 2020 with the average from April–December 2016–2019.g The percentage of hospitalizations and in-hospital deaths related to COVID-19 in April–December 2020 is also presented.

  • The number of all hospitalizations decreased 14.7 percent for patients from the highest income quartile in April–December 2020 versus the average in April–December 2016–2019 (3.8 to 3.3 million hospitalizations).

    In April–December 2020, the percentage of hospitalizations related to COVID-19 was highest for patients residing in the lowest income quartile (7.8 percent).


  • The number of all-cause in-hospital deaths increased in April–December 2020 versus the average in April–December 2016–2019 for all income quartiles. The increase was largest in the lowest income quartile (45.9 percent; 95,600 to 139,500 deaths) and smallest for those in the highest income quartile (27.0 percent; 72,900 to 92,600 deaths).

    Across 29 States, the percentage of in-hospital deaths related to COVID-19 in April–December 2020 was highest in the bottom income quartile (32.9 percent) and lowest in the top income quartile (28.4 percent).

Figure 6. Number of hospitalizations, in-hospital deaths, and percentage of each related to COVID-19 by community-level income in April–December 2020 compared with the average of all hospitalizations in April–December 2016–2019, 29 States


Figure 6 is a combined bar chart and table that shows the number of hospitalizations and in-hospital deaths in 29 States by community-level income.

Abbreviation: Q, quartile
Notes: Number of hospitalizations and in-hospital deaths is rounded to the nearest hundred. Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years. Quartile is based on the national distribution of community-level income.
Source: Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project (HCUP), 2016–2019 State Inpatient Databases (SID) and 2020 quarterly data from 29 States (AZ, CA, CT, GA, IA, IL, IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, ND, NJ, NY, OH, OR, PA, SC, SD, TN, VA, VT, WA, and WI) (available as of October 2021)

Combined bar chart and table that shows the number of hospitalizations and in-hospital deaths in 29 States by community-level income. The figure compares statistics for April–December 2020 with the average from April–December 2016–2019. It also presents the percentage of hospitalizations and in-hospital deaths related to COVID-19 in April–December 2020. Data are provided in Supplemental Table 5.



References

1 Agency for Healthcare Research and Quality. HCUP Fast Stats – Trends in Inpatient Stays. Healthcare Cost and Utilization Project (HCUP). www.hcup-us.ahrq.govhttps://datatools.ahrq.gov/hcup-fast-stats?type=subtab&tab=hcupfsis&count=1. Accessed August 27, 2021.
2 Healthcare Cost and Utilization Project (HCUP) Statistical Briefs Series on COVID-19-Related Hospitalizations in 13 States (HCUP Statistical Briefs #273–276). June 2021. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/statbriefs.jsp. Accessed August 29, 2021.
3 Centers for Medicare & Medicaid Services. CMS Adult Elective Surgery and Procedures Recommendations: Limit All Non-essential Planned Surgeries and Procedures, Including Dental, Until Further Notice. April 7, 2020.www.cms.gov/files/document/covid-elective-surgery-recommendations.pdf. Accessed August 27, 2021.
4 U.S. Census Bureau, Population Division. Annual Estimates of the Resident Population by Sex, Race, and Hispanic Origin for the United States: April 1, 2010 to July 1, 2019 (SC-EST2019-ALLDATA6). October 2021. www.census.gov/data/tables/time-series/demo/popest/2010s-state-detail.html#par_textimage_673542126. Accessed December 1, 2021.
5 U.S. Census Bureau, Population Division. Annual Estimates of the Resident Population by Sex, Race, and Hispanic Origin for Arizona, California, Connecticut, Georgia, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Michigan, Minnesota, Mississippi, Missouri, New Jersey, New York, North Dakota, Ohio, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Vermont, Virginia, Washington, and Wisconsin: April 1, 2010 to July 1, 2019 (SC-EST2019-ALLDATA6). October 2021. www.census.gov/data/tables/time-series/demo/popest/2010s-state-detail.html#par_textimage_673542126. Accessed December 1, 2021.
6 Agency for Healthcare Research and Quality. HCUP Summary Trend Tables. Healthcare Cost and Utilization Project (HCUP). Updated December 2020. www.hcup-us.ahrq.gov/reports/trendtables/summarytrendtables.jsp. Accessed February 10, 2021.
7 Agency for Healthcare Research and Quality. HCUP Visualization of Inpatient Trends in COVID-19 and Other Conditions. Healthcare Cost and Utilization Project (HCUP). June 2021. www.hcup-us.ahrq.gov/reports/trendtables/summarytrendtables.jsp. Accessed July 26, 2021.


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 2016–2019 State Inpatient Databases (SID) and 2020 quarterly inpatient data. Information based on quarterly data should be considered preliminary, as additional quarterly data may become available over time. This analysis is limited to patients treated in community, nonrehabilitation hospitals in 29 States (Arizona, California, Connecticut, Georgia, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Michigan, Minnesota, Mississippi, Missouri, New Jersey, New York, North Dakota, Ohio, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Vermont, Virginia, Washington, and Wisconsin) for which HCUP data were available for April–December 2016–2019 and April–December 2020. These States account for the following percentages of the resident U.S. population: 67.3 percent of the total population, 69.1 percent of the non-Hispanic White population, 68.2 percent of the non-Hispanic Black population, 59.0 percent of the Hispanic population, and 71.5 percent of the other non-Hispanic race/ethnicity population, including but not limited to American Indian, Alaska Native, Asian, Native Hawaiian, and other Pacific Islander.4,5 All of the information for 2020 contained in this Statistical Brief can be found in the HCUP Summary Trend Tables at Summary Trend Tables at www.hcup-us.ahrq.gov/reports/trendtables/summarytrendtables.jsp.

The HCUP inpatient data contain the universe of the inpatient discharge abstracts in the participating HCUP States, translated into a uniform format to facilitate multistate comparisons and analyses. The inpatient data encompass more than 95 percent of all U.S. community hospital discharges. The inpatient data 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.

Types of hospitals included in HCUP State Inpatient Databases (and quarterly inpatient data) This analysis used SID and quarterly inpatient data limited to information 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 center 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.

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 conditions that coexist at the time of admission that require or affect patient care treatment received or management, or that develop during the inpatient stay. All-listed diagnoses include the principal diagnosis plus the secondary conditions.

ICD-10-CM is the International Classification of Diseases, Tenth Revision, Clinical Modification. There are over 70,000 ICD-10-CM diagnosis codes.

Case definition
COVID-19-related hospitalizations and in-hospital deaths, defined by the discharge disposition, are identified by any-listed ICD-10-CM code of U07.1 (2019 novel coronavirus disease) on the discharge record. Per coding guidelines,h the use of U07.1 is based on documentation by the provider or documentation of a positive COVID-19 test result. The ICD-10-CM code for COVID-19 was implemented beginning April 1, 2020. As such, there may be some measurement error in the identification of cases.

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 1 year will be counted each time as a separate discharge from the hospital.

Location of patients' residence
Place of residence is based on the urban-rural classification scheme for U.S. counties developed by the National Center for Health Statistics (NCHS) and based on the Office of Management and Budget (OMB) definition of a metropolitan service area as including a city and a population of at least 50,000 residents. For this Statistical Brief, we collapsed the NCHS codes into the following three categories:

Large metropolitan (metro) area:
  • Large Central Metropolitan: Counties in a metropolitan area with 1 million or more residents that satisfy at least one of the following criteria: (1) containing the entire population of the largest principal city of the metropolitan statistical area (MSA), (2) having their entire population contained within the largest principal city of the MSA, or (3) containing at least 250,000 residents of any principal city in the MSA
  • Large Fringe Metropolitan: Counties in a metropolitan area with 1 million or more residents that do not qualify as large central metropolitan counties
Medium/small metro area:
  • Medium Metropolitan: Counties in a metropolitan area of 250,000-999,999 residents
  • Small Metropolitan: Counties in a metropolitan area of 50,000-249,999 residents
Rural area:
  • Micropolitan: Counties in a nonmetropolitan area of 10,000-49,999 residents
  • Noncore: Counties in a nonmetropolitan and nonmicropolitan area
Reporting of race and ethnicity
Data on Hispanic ethnicity are collected differently among the States and also can differ from the census methodology of collecting information on race (White, Black, Asian/Pacific Islander, American Indian/Alaska Native, Other [including mixed race]) separately from ethnicity (Hispanic, non-Hispanic). State data organizations often collect Hispanic ethnicity as one of several categories that include race. Therefore, for multistate analyses, HCUP creates the combined categorization of race and ethnicity for data from States that report ethnicity separately. When a State data organization collects Hispanic ethnicity separately from race, HCUP uses Hispanic ethnicity to override any other race category to create a Hispanic category for the uniformly coded race/ethnicity data element, while also retaining the original race and ethnicity data. This Statistical Brief reports race/ethnicity for the following categories: Hispanic, non-Hispanic White, non-Hispanic Black, and non-Hispanic Other (Asian/Pacific Islander, American Indian/Alaska Native, Other).

Expected payer
To make coding uniform across all HCUP data sources, the primary expected payer for the hospital stay combines detailed categories into general groups:
  • Medicare: includes fee-for-service and managed care Medicare
  • Medicaid: includes fee-for-service and managed care Medicaid
  • Private insurance: includes commercial nongovernmental payers, regardless of the type of plan (e.g., private health maintenance organizations [HMOs], preferred provider organizations [PPOs])
  • Self-pay/No charge: includes self-pay, no charge, charity, and no expected payment
  • Other payers: includes other Federal and local government programs (e.g., TRICARE, CHAMPVA, Indian Health Service, Black Lung, Title V) and Workers' Compensation
Due to variability in coding in "other" payer by State (from 1.6 to 7.4 percent) and difficulty with interpretation, estimates of "other" expected payers were excluded from the Statistical Brief. Less than 0.01 percent of discharges were missing information on expected payer.

Prior to 2017, hospital stays that were expected to be billed to the State Children's Health Insurance Program (SCHIP) may be classified as Medicaid or Other, depending on the structure of the State program. Because most State data do not identify SCHIP as a separate expected payer, it is not possible to present this information separately. Beginning with 2017 data, hospital stays that were expected to be billed to SCHIP are included under Medicaid.

For this Statistical Brief, when more than one payer is listed for a hospital discharge, the first-listed payer is used.

Community-level income
Community-level income is based on the median household income of the patient's ZIP Code of residence. Quartiles are defined so that the total U.S. population is evenly distributed. Cut-offs for the quartiles are determined annually using ZIP Code demographic data obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau.i The value ranges for the income quartiles vary by year. Patients in the first quartile are assigned to the lowest income category, patients in the middle two quartiles are assigned to the middle income category, and patients in the highest quartile are assigned to the highest income category. The income quartile is missing for patients who are homeless or foreign.

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:

For More Information

For information on COVID-19 resources at AHRQ, refer to the AHRQ COVID-19 Resources page: www.ahrq.gov/coronavirus/index.html. For other information on COVID-19 healthcare utilization, refer to the HCUP Statistical Briefs located at www.hcup-us.ahrq.gov/reports/statbriefs/sb_covid.jsp.

For additional HCUP statistics, visit:
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 October 2020. www.hcup-us.ahrq.gov/sidoverview.jsp. Accessed January 22, 2021.

Suggested Citation

Reid LD (AHRQ), Fang Z (AHRQ). Changes in Hospitalizations and In-Hospital Deaths in the Initial Period of the COVID-19 Pandemic (April–December 2020), 29 States.HCUP Statistical Brief #290. April 2022. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb290-COVID-19-AllHospital.pdf.

Acknowledgments

The authors would like to acknowledge the contributions of Marguerite Barrett of M.L. Barrett, Inc., in addition to Molly Hensche, Brendan Leonard, Minya Sheng, Audrey Weiss, and Jennifer Welch of IBM Watson Health.

***

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 email 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 April 5, 2022.


a Each hospitalization was assigned to a single hospitalization type hierarchically, based on the following order of hospital stay principal diagnoses: maternal, neonatal, mental health/substance use, injury, surgical, and medical.
b Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years.
c Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years.
d Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years
e Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years.
f Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years.
g Counts for 2016–2019 represent the mean number of hospitalizations or in-hospital deaths during April–December across these 4 years.
h Centers for Disease Control and Prevention, National Center for Health Statistics. ICD-10-CM Official Guidelines for Coding and Reporting, FY 2021 (October 1, 2020 - September 30, 2021). www.cdc.gov/nchs/data/icd/10cmguidelines-FY2021.pdf. Accessed March 18, 2021.
i Claritas. Claritas Demographic Profile by ZIP Code. www.claritas360.claritas.com/mybestsegments/Exit Disclaimer. Accessed June 27, 2021.



Supplemental Table 1. Number of hospitalizations, in-hospital deaths, and percentage of each related to COVID-19 in April–December 2020 compared with the average of all hospitalizations in April–December 2016–2019, 29 States, for data presented in Figure 2
Region Time period Number of hospitalizations Apr-Dec, 2020 percent related to COVID-19 Number of in-hospital deaths Apr-Dec, 2020 percent related to COVID-19
29 States
(29 out of 50 States + DC; 67% of the population)
Apr-Dec, 2016-2019 17,743,100 - 341,600 -
Apr-Dec, 2020 15,477,600 6.9% 467,200 30.8%
Northeast
(6 out of 9 States; 83% of the population)
Apr-Dec, 2016-2019 4,072,300 - 81,000 -
Apr-Dec, 2020 3,336,200 6.6% 111,000 33.8%
Midwest
(11 out of 12 States; 97% of the population)
Apr-Dec, 2016-2019 5,735,200 - 102,000 -
Apr-Dec, 2020 5,064,300 7.2% 140,800 30.9%
South
(8 out of 16 States + DC; 39% of the population)
Apr-Dec, 2016-2019 3,941,600 - 79,800 -
Apr-Dec, 2020 3,553,100 7.2% 110,600 28.5%
West
(4 out of 13 States; 75% of the population)
Apr-Dec, 2016-2019 3,994,000 - 78,800 -
Apr-Dec, 2020 3,524,000 6.4% 104,800 30.1%



Supplemental Table 2. Number of hospitalizations, in-hospital deaths, and percentage of each related to COVID-19 by location of patient residence in April–December 2020 compared with the average of all hospitalizations in April–December 2016–2019, 29 States, for data presented in Figure 3
Patient location Time period Number of hospitalizations Apr-Dec, 2020 percent related to COVID-19 Number of in-hospital deaths Apr-Dec, 2020 percent related to COVID-19
Large metro Apr-Dec, 2016-2019 10,074,000 - 185,500 -
Apr-Dec, 2020 8,714,400 7.3% 263,300 33.3%
Medium/small metro Apr-Dec, 2016-2019 4,914,600 - 96,500 -
Apr-Dec, 2020 4,368,000 6.2% 126,100 27.6%
Rural Apr-Dec, 2016-2019 2,725,500 - 59,000 -
Apr-Dec, 2020 2,374,700 6.8% 77,000 27.7%



Supplemental Table 3. Number of hospitalizations, in-hospital deaths, and percentage of each related to COVID-19 by patient race/ethnicity in April–December 2020 compared with the average of all hospitalizations in April–December 2016–2019, 29 States, for data presented in Figure 4
Patient race/ethnicity Time period Number of hospitalizations Apr-Dec, 2020 percent related to COVID-19 Number of in-hospital deaths Apr-Dec, 2020 percent related to COVID-19
White NH Apr-Dec, 2016-2019 11,316,400 - 237,900 -
Apr-Dec, 2020 9,629,100 5.7% 295,400 25.9%
Black NH Apr-Dec, 2016-2019 2,722,100 - 47,500 -
Apr-Dec, 2020 2,451,900 8.5% 74,000 34.9%
Hispanic Apr-Dec, 2016-2019 1,846,200 - 22,800 -
Apr-Dec, 2020 1,743,900 11.2% 47,600 51.4%
Other NH Apr-Dec, 2016-2019 1,279,100 - 22,600 -
Apr-Dec, 2020 1,135,900 7.7% 35,200 36.7%
Abbreviation: NH, non-Hispanic



Supplemental Table 4. Number of hospitalizations, in-hospital deaths, and percentage of each related to COVID-19 by primary expected payer in April–December 2020 compared with the average of all hospitalizations in April–December 2016–2019, 29 States, for data presented in Figure 5
Primary expected payer Time period Number of hospitalizations Apr-Dec, 2020 percent related to COVID-19 Number of in-hospital deaths Apr-Dec, 2020 percent related to COVID-19
Private insurance Apr-Dec, 2016-2019 5,210,600 - 56,900 -
Apr-Dec, 2020 4,534,100 5.8% 73,400 28.4%
Medicare Apr-Dec, 2016-2019 7,203,100 - 222,800 -
Apr-Dec, 2020 6,167,300 8.9% 302,900 33.0%
Medicaid Apr-Dec, 2016-2019 4,225,400 - 38,000 -
Apr-Dec, 2020 3,776,200 4.7% 55,400 26.3%
Self-pay/No charge* Apr-Dec, 2016-2019 599,200 - 9,500 -
Apr-Dec, 2020 535,900 6.5% 13,300 23.5%
* Self-pay/No charge: includes self-pay, no charge, charity, and no expected payment.



Supplemental Table 5. Number of hospitalizations, in-hospital deaths, and percentage of each related to COVID-19 by community-level income in April–December 2020 compared with the average of all hospitalizations in April–December 2016–2019, 29 States, for data presented in Figure 6
Community-level income Time period Number of hospitalizations Apr-Dec, 2020 percent related to COVID-19 Number of in-hospital deaths Apr-Dec, 2020 percent related to COVID-19
Lowest (Q1) Apr-Dec, 2016-2019 4,897,700 - 95,600 -
Apr-Dec, 2020 4,290,300 7.8% 139,500 32.9%
Middle (Q2-Q3) Apr-Dec, 2016-2019 8,777,100 - 168,200 -
Apr-Dec, 2020 7,707,300 6.9% 228,700 30.7%
Highest (Q4) Apr-Dec, 2016-2019 3,825,900 - 72,900 -
Apr-Dec, 2020 3,262,200 5.9% 92,600 28.4%
Abbreviation: Q, quartile

Internet Citation: Statistical Brief #290. Healthcare Cost and Utilization Project (HCUP). May 2022. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb290-COVID-19-AllHospital.jsp.
Are you having problems viewing or printing pages on this website?
If you have comments, suggestions, and/or questions, please contact hcup@ahrq.gov.
Privacy Notice, Viewers & Players
Last modified 5/2/22