STATISTICAL BRIEF #296
Kimberly W. McDermott, Ph.D., Lawrence D. Reid, Ph.D., and Pamela L. Owens, Ph.D.
Maternal health coverage is an important element of health insurance coverage in the U.S. For example, under the Affordable Care Act pregnancy, maternal, and newborn care comprise essential health benefits that must be covered by all Marketplace plans.1 Coverage of these services also has implications for access to and quality of care. One study found that pregnant women covered by Medicaid or with no insurance have higher rates of emergency department (ED) visits during pregnancy than pregnant women covered by private insurance.2 As pregnancy-related complications were the fifth most common reason for ED visits for women aged 15-64 years in 2018,3 information on ED use among pregnant women by expected payer provides useful information for analysts and policymakers and helps identify areas of focus for quality improvement efforts.
This Healthcare Cost and Utilization Project (HCUP) Statistical Brief presents statistics on treat-and-release ED visits (i.e., visits that result in discharge from the ED and do not result in admission to the same hospital) for pregnant womena aged 12-55 years using weighted estimates from the 2019 Nationwide Emergency Department Sample (NEDS). The distribution of ED visits and aggregate ED costs by primary expected payer is presented overall as well as by patient age group and race and ethnicity. Corresponding statistics for ED visits for nonpregnant womenb aged 12-55 years are provided for comparison. Because of the large sample size of the NEDS data, small differences can be statistically significant. Thus, only differences greater than or equal to 10 percent are discussed in the text.
Distribution of the number and aggregate costs of treat-and-release ED visits for women aged 12-55 years, by primary expected payer, 2019
Figure 1 presents the distribution of treat-and-release ED visits and associated costs for pregnant and nonpregnant women by primary expected payer.
Figure 1. Distribution of treat-and-release ED visits and associated aggregate costs for pregnant and nonpregnant women aged 12-55 years, by primary expected payer, 2019
Bar chart showing the distribution of treat-and-release emergency department visits and associated costs for pregnant and nonpregnant women by primary expected payer in 2019. Visits for pregnant women (3.8 million visits [9.2%]): Medicaid: 54.3%, private: 31.0%, self-pay/no charge: 10.0%, other: 4.6%. Visits for nonpregnant women (37.7 million visits [90.8%]): Medicaid: 37.0%, private: 35.3%, self-pay/no charge: 17.3%, other: 10.3%. Costs ($ billions) for pregnant women ($2.0 billion [8.2%]): Medicaid: 51.3%, private: 33.3%, self-pay/no charge: 10.4%, other: 4.8%. Costs ($ billions) for nonpregnant women ($22.8 billion [91.8%]: Medicaid: 33.8%, private: 40.2%, self-pay/no charge: 14.9%, other: 10.9%.
Table 1 presents overall and by primary expected payer the total number of visits, mean cost per visit, and aggregate costs for treat-and-release ED visits for pregnant women versus nonpregnant women in 2019.
Table 1. Number of visits, mean cost, and aggregate costs of treat-and-release ED visits for pregnant and nonpregnant women aged 12-55 years, by primary expected payer, 2019
Distribution of treat-and-release ED visits for women aged 12-55 years, by primary expected payer and patient characteristic, 2019
Figure 2 presents the distribution of treat-and-release ED visits for pregnant and nonpregnant women by primary expected payer and patient age group in 2019.
Figure 2. Distribution of treat-and-release ED visits for pregnant and nonpregnant women aged 12-55 years, by primary expected payer and patient age group, 2019
Bar chart showing the distribution of treat-and-release emergency department visits for pregnant and nonpregnant women by primary expected payer and patient age group in 2019. Visits for pregnant women: 12-17 years (91,300 visits [2.4%]): Medicaid: 72.9%, private: 15.1%, self-pay/no charge: 9.6%, other: 2.2%. 18-24 years (1,378,300 visits [36.2%]): Medicaid: 61.0%, private: 24.7%, self-pay/no charge: 10.3%, other: 3.9%. 25-34 years (1,846,900 visits [48.5%]): Medicaid: 51.5%, private: 33.9%, self-pay/no charge: 9.5%, other: 4.9%. 35-55 years (488,300 visits [12.8%]): Medicaid: 42.4%, private: 40.7%, self-pay/no charge: 10.7%, other: 5.9%. Visits for nonpregnant women: 12-17 years (3,687,800 visits [9.8%]): Medicaid: 55.6%, private: 33.0%, self-pay/no charge: 7.7%, other: 3.6%. 18-24 years (6,760,200 [17.9%]): Medicaid: 37.6%, private: 36.6%, self-pay/no charge: 20.0%, other: 5.6%. 25-34 years (9,913,700 visits [26.3%]): Medicaid: 40.5%, private: 30.5%, self-pay/no charge: 20.7%, other: 8.0%. 35-55 years (17,349,800 visits [46.0%]): Medicaid: 30.7%, private: 37.9%, self-pay/no charge: 16.3%, other: 14.9%.
Figure 3 presents the distribution of treat-and-release ED visits for pregnant women versus nonpregnant women by primary expected payer and patient race and ethnicity in 2019.
Figure 3. Distribution of treat-and-release ED visits for pregnant and nonpregnant women aged 12-55 years, by primary expected payer and patient race and ethnicity, 2019
Bar chart showing the distribution of treat-and-release emergency department visits for pregnant women versus nonpregnant women by primary expected payer and patient race and ethnicity (Hispanic, Black non-Hispanic [NH], White NH, and other NH) in 2019. Visits for pregnant women: Hispanic (859,300 visits [23.0%]): Medicaid: 57.3%, private: 23.4%, self-pay/no charge: 14.7%, other: 4.4%. Black NH (1,056,000 visits [28.2%]): Medicaid: 62.9%, private: 23.2%, self-pay/no charge: 9.9%, other: 3.9%. White NH (1,551,400 visits [41.4%]): Medicaid: 47.9%, private: 39.8%, self-pay/no charge: 7.1%, other: 5.0%. Other NH (277,000 visits [7.4%]): Medicaid: 49.4%, private: 34.7%, self-pay/no charge: 10.6%, other: 5.3%. Visits for nonpregnant women: Hispanic (6,202,100 visits [16.8%]): Medicaid: 42.6%, private: 27.9%, self-pay/no charge: 21.2%, other: 8.2%. Black NH (9,275,000 visits [25.1%]): Medicaid: 40.6%, private: 28.3%, self-pay/no charge: 20.8%, other: 10.1%. White NH (19,226,700 visits [52.0%]): Medicaid: 33.6%, private: 40.5%, self-pay/no charge: 14.5%, other: 11.3%. Other NH (2,253,400 visits [6.1%]): Medicaid: 36.0%, private: 38.0%, self-pay/no charge: 16.2%, other: 9.6%.
Figures 4 and 5 present the distribution of treat-and-release ED visits for pregnant women versus nonpregnant women aged 12-24 years (Figure 4) and aged 25-55 years (Figure 5) by primary expected payer and select patient characteristics. Figure 4 shows the distribution of ED visits for women aged 12-24 years by primary expected payer, patient age group, and patient race and ethnicity in 2019.
Figure 4. Distribution of treat-and-release ED visits for pregnant and nonpregnant women aged 12-24 years, by primary expected payer, patient age group, and patient race and ethnicity, 2019
Bar chart showing the distribution of treat-and-release emergency department visits for women aged 12-24 years by primary expected payer, patient age group, and patient race and ethnicity (Hispanic, Black non-Hispanic [NH], White NH, and other NH) in 2019. Data are provided in Supplemental Table 1.
Figure 5 presents the distribution of treat-and-release ED visits for pregnant women versus nonpregnant women aged 25-55 years by primary expected payer, patient age group, and patient race and ethnicity in 2019.
Figure 5. Distribution of treat-and-release ED visits for pregnant and nonpregnant women aged 25-55 years, by primary expected payer, patient age group, and patient race and ethnicity, 2019
Bar chart showing the distribution of treat-and-release emergency department visits for pregnant women versus nonpregnant women aged 25-55 years by primary expected payer, patient age group, and patient race and ethnicity (Hispanic, Black non-Hispanic [NH], White NH, and other NH) in 2019. Data are provided in Supplemental Table 2.
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.
The estimates in this Statistical Brief are based upon data from the 2019 HCUP Nationwide Emergency Department Sample (NEDS). See more information about the NEDS in the "About the NEDS" section below.
Diagnoses, ICD-10-CM, Clinical Classifications Software Refined (CCSR)
for ICD-10-CM Diagnoses
Diagnoses are coded in ICD-10-CM, the International Classification of Diseases, Tenth Revision, Clinical Modification. There are over 70,000 ICD-10-CM diagnosis codes.
The CCSR aggregates ICD-10-CM diagnosis codes into a manageable number of clinically meaningful categories.c The CCSR is intended to be used analytically to examine patterns of healthcare in terms of cost, utilization, and outcomes; rank utilization by diagnoses; and risk-adjust by clinical condition. The CCSR capitalizes on the specificity of the ICD-10-CM coding scheme and allows ICD-10-CM codes to be classified in more than one category. Approximately 10 percent of diagnosis codes are associated with more than one CCSR category because the diagnosis code documents either multiple conditions or a condition along with a common symptom or manifestation. ICD-10-CM coding definitions for each CCSR category presented in this Statistical Brief can be found in the CCSR reference file, available at www.hcup-us.ahrq.gov/toolssoftware/ccsr/ccs_refined.jsp#download. For this Statistical Brief, v2021.2 of the CCSR was used.
Procedures, Healthcare Common Procedure Coding System (HCPCS)/Current
Procedural Terminology (CPT®), Clinical Classifications Software for
Services and Procedures (CCS-Services and Procedures)
ED procedures on an outpatient record are coded in HCPCS Level I (CPT) and Level II procedure codes. There are approximately 17,700 total procedure codes.
The CCS-Services and Procedures provides a method for classifying CPT and HCPCS Level II codes into clinically meaningful procedure categories.d More than 10,000 CPT codes and 7,000 HCPCS Level II codes are collapsed into over 240 categories that may be more useful for presenting descriptive statistics than are individual CPT or HCPCS Level II codes.
|CCSR category||CCSR category description|
|PRG003||Spontaneous abortion and complications of spontaneous abortion|
|PRG004||Induced abortion and complications of termination of pregnancy|
|PRG005||Ectopic pregnancy and complications of ectopic pregnancy|
|PRG006||Molar pregnancy and other abnormal products of conception|
|PRG007||Complications following ectopic and/or molar pregnancy|
|PRG008||Supervision of high-risk pregnancy|
|PRG009||Early, first or unspecified trimester hemorrhage|
|PRG010||Hemorrhage after first trimester|
|PRG011||Early or threatened labor|
|PRG013||Maternal care related to fetal conditions|
|PRG014||Polyhydramnios and other problems of amniotic cavity|
|PRG015||Obstetric history affecting care in pregnancy|
|PRG017||Maternal care for abnormality of pelvic organs|
|PRG018||Maternal care related to disorders of the placenta and placental implantation|
|PRG019||Diabetes or abnormal glucose tolerance complicating pregnancy; childbirth; or the puerperium|
|PRG020||Hypertension and hypertensive-related conditions complicating pregnancy; childbirth; and the puerperium|
|PRG021||Maternal intrauterine infection|
|PRG023||Complications specified during childbirth|
|PRG024||Malposition, disproportion or other labor complications|
|PRG025||Anesthesia complications during pregnancy|
|PRG026||OB-related trauma to perineum and vulva|
|PRG027||Complications specified during the puerperium|
|PRG028||Other specified complications in pregnancy|
|PRG029||Uncomplicated pregnancy, delivery or puerperium|
|PRG030||Maternal outcome of delivery|
|CCS category||CCS category description|
|122||Removal of ectopic pregnancy|
|126||Abortion (termination of pregnancy)|
|127||Dilatation and curettage (D&C), aspiration after delivery or abortion|
|135||Forceps, vacuum, and breech delivery|
|137||Other procedures to assist delivery|
|140||Repair of current obstetric laceration|
|141||Other therapeutic obstetrical procedures including antepartum and postpartum care|
Types of hospitals included in the HCUP Nationwide Emergency Department Sample
The Nationwide Emergency Department Sample (NEDS) is based on ED data from community acute care hospitals, which are defined as short-term, non-Federal, general, and other specialty hospitals available to the public. Included among community hospitals are pediatric institutions and hospitals that are part of academic medical centers. Excluded are long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals. Hospitals included in the NEDS have EDs, and no more than 90 percent of their ED visits result in admission.
Unit of analysis
The unit of analysis is the ED visit, not a person or patient. This means that a person who is seen in the ED multiple times in 1 year will be counted each time as a separate visit in the ED.
Costs and charges
Total ED charges were converted to costs using the HCUP Cost-to-Charge Ratios for ED Files, which are based on hospital accounting reports from the Centers for Medicare & Medicaid Services (CMS).e Costs reflect the actual expenses incurred in the production of hospital services, such as wages, supplies, and utility costs; charges represent the amount a hospital billed for the case. For each hospital, a cost-to-charge ratio constructed specifically for the hospital ED is used. Hospital charges reflect the amount the hospital billed for the entire ED visit and do not include professional (physician) fees.
Total charges were not available on all NEDS records. For ED visits that did not result in admission (the focus of this Statistical Brief), 1 percent of records were missing ED charges; thus, ED costs could not be estimated for these visits. For this Statistical Brief, the methodology used to estimate aggregate costs was analogous to what is recommended to estimate aggregate charges in the Introduction to the HCUP NEDS documentation.f Aggregate costs were estimated as the product of the number of visits and average cost per visit.
How HCUP estimates of costs differ from National Health Expenditure Accounts
There are a number of differences between the costs cited in this Statistical Brief and spending as measured in the National Health Expenditure Accounts (NHEA), which are produced annually by CMS.g The largest source of difference comes from the HCUP coverage of ED treatment only in contrast to the NHEA inclusion of inpatient and other outpatient costs associated with other hospital-based outpatient clinics and departments as well. The outpatient portion of hospitals' activities has been growing steadily and may exceed half of all hospital revenue in recent years. On the basis of the American Hospital Association Annual Survey, 2018 outpatient gross revenues (or charges) were about 49 percent of total hospital gross revenues.h
Smaller sources of differences come from the inclusion in the NHEA of hospitals that are excluded from HCUP. These include Federal hospitals (Department of Defense, Veterans Administration, Indian Health Service, and Department of Justice [prison] hospitals) as well as psychiatric, substance abuse, and long-term care hospitals. A third source of difference lies in the HCUP reliance on billed charges from hospitals to payers, adjusted to provide estimates of costs using hospital-wide cost-to-charge ratios, in contrast to the NHEA measurement of spending or revenue. HCUP costs estimate the amount of money required to produce hospital services, including expenses for wages, salaries, and benefits paid to staff as well as utilities, maintenance, and other similar expenses required to run a hospital. NHEA spending or revenue measures the amount of income received by the hospital for treatment and other services provided, including payments by insurers, patients, or government programs. The difference between revenues and costs includes profit for for-profit hospitals or surpluses for nonprofit hospitals.
To make coding uniform across all HCUP data sources, the primary expected payer for the ED visit combines detailed categories into general groups:
ED visits that were expected to be billed to the State Children's Health Insurance Program (SCHIP) are included under Medicaid.
For this Statistical Brief, when more than one payer is listed for an ED visit, the first-listed payer is used.
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 and ethnicity data element, while also retaining the original race and ethnicity data. This Statistical Brief reports race and ethnicity for the following categories: Hispanic, non-Hispanic White, non-Hispanic Black, and non-Hispanic Other (including Asian/Pacific Islander and American Indian/Alaska Native).
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
Hawaii University of Hawai’i at Hilo
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
The HCUP Nationwide Emergency Department Sample (NEDS) is a unique and powerful database that yields national estimates of emergency department (ED) visits. The NEDS was constructed using records from both the HCUP State Emergency Department Databases (SEDD) and the State Inpatient Databases (SID). The SEDD capture information on ED visits that do not result in an admission (i.e., patients who were treated in the ED and then released from the ED, or patients who were transferred to another hospital); the SID contain information on patients initially seen in the ED and then admitted to the same hospital. The NEDS was created to enable analyses of ED utilization patterns and support public health professionals, administrators, policymakers, and clinicians in their decision making regarding this critical source of care. The NEDS is produced annually beginning in 2006. Over time, the sampling frame for the NEDS has changed; thus, the number of States contributing to the NEDS varies from year to year. The NEDS is intended for national estimates only; no State-level estimates can be produced. The unweighted sample size for the 2019 NEDS is 33,147,251 (weighted, this represents 143,432,284 ED visits). Of these weighted visits, 20,373,534 (14.2 percent) were admitted to the same hospital.For More Information
For other information on pregnancy and childbirth, refer to the HCUP Statistical Briefs located at www.hcup-us.ahrq.gov/reports/statbriefs/sb_pregnancy.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 Nationwide Emergency Department Sample (NEDS), please refer to the following database documentation:
Agency for Healthcare Research and Quality. Overview of the Nationwide Emergency Department Sample (NEDS). Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality. Updated October 2021. www.hcup-us.ahrq.gov/nedsoverview.jsp. Accessed March 9, 2022.Suggested Citation
McDermott KW (IBM), Reid LD (AHRQ), Owens PL (AHRQ). Expected Payers and Patient Characteristics of Maternal Emergency Department Care, 2019. HCUP Statistical Brief #296. June 2022. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb296-Payers-Maternal-ED-2019.pdf.Acknowledgments
The authors would like to acknowledge the contributions of Marguerite Barrett of M.L. Barrett, Inc., and Minya Sheng of IBM.
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 firstname.lastname@example.org. 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 June 28, 2022.a ED visits for pregnant women were identified by the presence of a pregnancy-related diagnosis or procedure code on the record. Most ED visits for pregnant women (94.3 percent) were for a pregnancy-related condition; 5.7 percent of visits were for conditions unrelated to pregnancy.
|Supplemental Table 1. Distribution of treat-and-release ED visits for pregnant and nonpregnant women aged 12-24 years, by primary expected payer, patient age group, and patient race and ethnicity, 2019, for data presented in Figure 4|
|Race and ethnicity||Total number of visits||% of visits||Distribution by payer, %|
|Pregnant girls aged 12-17 years|
|Nonpregnant girls aged 12-17 years|
|Pregnant women aged 18-24 years|
|Nonpregnant women aged 18-24 years|
|* Self-pay/No charge: includes self-pay, no charge, charity, and no expected payment.|
|Supplemental Table 2. Distribution of treat-and-release ED visits for pregnant and nonpregnant women aged 25-55 years, by primary expected payer, patient age group, and patient race and ethnicity, 2019, for data presented in Figure 5|
|Race and ethnicity||Total number of visits||% of visits||Distribution by payer, %|
|Pregnant women aged 25-34 years|
|Nonpregnant women aged 25-34 years|
|Pregnant women aged 35-55 years|
|Nonpregnant women aged 35-55 years|
|* Self-pay/No charge: includes self-pay, no charge, charity, and no expected payment.|
|Internet Citation: Statistical Brief #296. Healthcare Cost and Utilization Project (HCUP). June 2022. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb296-Payers-Maternal-ED-2019.jsp.|
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