User Support

April 2017

Kathryn R. Fingar, Ph.D., M.P.H., Iris Mabry-Hernandez, M.D., M.P.H., Quyen Ngo-Metzger, M.D., M.P.H., Tracy Wolff, M.D., M.P.H., Claudia A. Steiner, M.D., M.P.H., and Anne Elixhauser, Ph.D.


Introduction

Preeclampsia is a disorder of new-onset high blood pressure occurring after 20 weeks of gestation. The diagnosis of preeclampsia is characterized by high blood pressure¹ and either excess protein in the urine² or, in the absence of proteinuria, other signs or symptoms, such as thrombocytopenia, renal insufficiency, impaired liver function, pulmonary edema, or cerebral or visual symptoms.³

Although rare, eclampsia occurs when women suffering from preeclampsia during pregnancy develop seizures, which may be followed by coma, posing a threat to the life of the mother and baby. ⁴

Women with preexisting hypertension (high blood pressure before pregnancy or within the first 20 weeks of gestation) and gestational hypertension (onset of high blood pressure after 20 weeks of gestation) are at increased risk for preeclampsia/eclampsia, although many women who develop preeclampsia/eclampsia have no history of high blood pressure. ⁵ Other risk factors for preeclampsia/eclampsia include preexisting diabetes, renal disease, obesity, falling in the youngest or oldest categories of maternal age, multiple gestations, women giving birth for the first time, and race.^6,7

Black women are more likely to develop preeclampsia and to experience poorer outcomes associated with the condition, including progression to eclampsia and in rare cases, death.^8,9

In addition to increased risk of mortality, women with preeclampsia/eclampsia are more likely to experience cesarean section (C-section), placental abruption, disseminated intravascular coagulation, cerebral hemorrhage, pulmonary edema, and renal failure.^10,11,12 Infants born to mothers with preeclampsia/eclampsia are more likely to have intrauterine growth restriction, premature birth, and intrauterine death.¹³

In the United States, preeclampsia/eclampsia and other hypertensive disorders of pregnancy have increased over the last 2 decades.¹⁴ Preeclampsia/eclampsia is estimated to complicate between 3 and 6 percent of all pregnancies and is considered one of the most preventable causes of maternal death.^15,16 However, there is little recent national population-based data on the prevalence of the condition and its associated coexisting conditions and complications that can inform efforts to prevent preeclampsia/eclampsia.^17,18

This Healthcare Cost and Utilization Project (HCUP) Statistical Brief presents data on the prevalence of preeclampsia/eclampsia among inpatient delivery hospitalizations in 2014. The Brief describes trends in the rate of preeclampsia/eclampsia from 2005 through 2014, overall and by patient and hospital characteristics. Characteristics of deliveries with preeclampsia/eclampsia are examined in 2014.

Deliveries with preeclampsia/eclampsia are compared with all other deliveries, with respect to patient and hospital characteristics, coexisting conditions, and infant and maternal outcomes.^19,20 These characteristics are also compared across type of diagnosis: eclampsia, severe preeclampsia, mild or unspecified preeclampsia, and preeclampsia/eclampsia with preexisting hypertension. ²¹

Delivery hospitalizations represent the hospital stay for the mother and not the infant. Descriptions of infant outcomes are those conditions that appear on the maternal record. All differences between estimates noted in the text are 10 percent or greater.

Findings

Prevalence of delivery hospitalizations involving preeclampsia/eclampsia, 2014
The left side of Figure 1 displays all delivery hospitalizations in 2014 by presence of preeclampsia/eclampsia as well as other hypertension-related diagnoses complicating pregnancy, childbirth, and the puerperium. The right side of Figure 1 displays the subset of delivery hospitalizations with a diagnosis of preeclampsia/eclampsia in 2014 by type of preeclampsia/eclampsia diagnosis.

• In 2014, more than 1 in 10 delivery hospitalizations had a diagnosis of hypertension. Among these deliveries with any hypertension-related diagnosis, preeclampsia/eclampsia was the most common.
  
  In 2014, 409,495 delivery hospitalizations had a diagnosis of hypertension complicating pregnancy, childbirth, and the puerperium, representing 10.8 percent of 3.8 million total deliveries. Preeclampsia/eclampsia was the most common type of hypertension-related diagnosis (4.7 percent), followed by gestational hypertension (3.8 percent), preexisting hypertension (1.7 percent), and unspecified hypertension (0.6 percent).



• In 2014, of all delivery hospitalizations with a diagnosis of preeclampsia/eclampsia, over one-third had severe preeclampsia.
  
  In 2014, 176,925 delivery hospitalizations had a diagnosis of preeclampsia/eclampsia, representing 4.7 percent of 3.8 million total deliveries. Although the most severe form of the condition (eclampsia) was rare (1.4 percent), an additional 37.2 percent of deliveries with any diagnosis of preeclampsia/eclampsia had severe preeclampsia. Nearly half of deliveries with preeclampsia/eclampsia had mild or unspecified preeclampsia (46.9 percent), and 14.5 percent had preeclampsia/eclampsia with preexisting hypertension but lacked detail on the severity of the condition.
  
  In addition to the deliveries shown in Figure 1, in 2014 there were 21,180 hospitalizations during or after pregnancy involving preeclampsia/eclampsia, in which the hospital stay did not result in delivery (data not shown). Although this Brief focuses on delivery hospitalizations, these antepartum and postpartum stays contribute to the total burden of preeclampsia/eclampsia in the inpatient hospital setting.

Characteristics of delivery hospitalizations involving preeclampsia/eclampsia, 2014
Table 1 compares patient and hospital characteristics among deliveries with preeclampsia/eclampsia with all other deliveries in 2014.

• Compared with all other deliveries, those with preeclampsia/eclampsia were more likely to be among women in the youngest and oldest age categories, black women, women from the poorest areas, and women who delivered in the South.
  
  Overall, deliveries with preeclampsia/eclampsia were more likely than all other deliveries to be among women in the youngest and oldest age groups (8.2 vs. 6.4 percent among patients aged less than 20 years; 18.9 vs. 15.4 percent among women aged 35 years or older) and to be among black women (20.1 vs. 13.1 percent). In addition, preeclampsia/eclampsia was more common among women who resided in the poorest areas (31.9 vs. 27.7 percent in income quartile 1) and those who delivered in the South (42.6 vs. 38.3 percent).



• The mean length of stay and hospital costs were over 70 percent higher for deliveries with preeclampsia/eclampsia, compared with all other deliveries.
  
  The mean length of stay was 71 percent higher for deliveries with preeclampsia/eclampsia compared with all other deliveries (4.4 vs. 2.6 days). The average hospital cost per stay was 70 percent higher for deliveries with preeclampsia/eclampsia compared with all other deliveries ($7,500 vs. $4,400).



• There were differences in patient age and race/ethnicity across the types of preeclampsia/eclampsia.
  
  
  • Of deliveries with eclampsia, 21.3 percent were among teens. In comparison, less than 10 percent of deliveries with other diagnoses for severe preeclampsia or mild preeclampsia were among teens. Only 6.4 percent of all other deliveries without a diagnosis of preeclampsia/eclampsia were in this age group.
  • Nearly 1 in 3 deliveries (31.3 percent) with a diagnosis of preeclampsia/eclampsia with preexisting hypertension were among black women. In comparison, only 13.1 percent of all other deliveries were among black women.



• Deliveries involving preeclampsia/eclampsia with preexisting hypertension were associated with longer hospital stays. Hospital stays for more severe forms of preeclampsia/eclampsia were more expensive than the mild or unspecified type.
  
  The mean length of stay was highest for deliveries with a diagnosis of preeclampsia/eclampsia with preexisting hypertension (5.4 days compared with 4.8 days or fewer among deliveries with other preeclampsia/eclampsia diagnoses). The average hospital cost per stay was lower for deliveries with mild or unspecified preeclampsia ($6,300) than for deliveries with the other preeclampsia/eclampsia diagnoses ($8,500-$9,000).

Rate of preeclampsia/eclampsia among delivery hospitalizations, 2005-2014
Figure 2 displays the rate of preeclampsia/eclampsia per 1,000 deliveries by type of diagnosis from 2005 through 2014.

• From 2005 through 2014, the total rate of preeclampsia/eclampsia among delivery hospitalizations increased by 21 percent.
  
  The total rate of preeclampsia/eclampsia increased from 38.4 per 1,000 deliveries in 2005 to 46.6 per 1,000 deliveries in 2014, an increase of 21 percent. The largest increases were for deliveries with preeclampsia/eclampsia with preexisting hypertension (which increased by 83 percent, from 3.7 to 6.7 per 1,000 deliveries) and deliveries with severe preeclampsia (which increased by 50 percent over the 10-year span, from 11.6 to 17.4 per 1,000 deliveries).



• Although rare, the rate of eclampsia decreased by 27 percent from 2005 through 2014.
  
  From 2005 through 2014, the rate of eclampsia decreased from 0.9 to 0.7 per 1,000 deliveries, a decrease of 27 percent. Deliveries with mild or unspecified preeclampsia remained stable at around 22 per 1,000 deliveries.

Table 2 presents the total rate of preeclampsia/eclampsia per 1,000 deliveries in 2005 and 2014, by patient and hospital characteristics.

• The rate of preeclampsia/eclampsia was highest among women in the oldest and youngest age groups in both 2005 and 2014, but the rate increased most rapidly among women aged 35 years or older.
  
  In 2005 and 2014, the rate of preeclampsia/eclampsia was highest among women younger than 20 years and women aged 40 years or older (59.3 and 73.5 per 1,000 deliveries, respectively, in 2014). From 2005 to 2014, the rate increased the most among women aged 35-39 years and 40 years and older (each with a 36 percent increase). The rate among women younger than 20 years increased by only 14 percent, the smallest increase of any age group.



• The rate of preeclampsia/eclampsia was higher among deliveries paid by Medicaid than among those paid by private insurance, but the rate increased more over time among deliveries paid by private insurance.
  
  Medicaid and private insurance paid for the vast majority of deliveries. In 2005, the rate of preeclampsia/eclampsia was 15 percent higher among deliveries paid by Medicaid than among those paid by private insurance (41.2 vs. 35.8 per 1,000 deliveries). In 2014, this difference decreased (49.0 vs. 45.1 per 1,000 deliveries), reflecting a 19 percent increase in the rate of preeclampsia/eclampsia among deliveries with Medicaid versus a 26 percent increase in the rate among deliveries with private insurance.
  
  Although Medicare paid for relatively fewer deliveries compared with the other payers, the rate of preeclampsia/eclampsia was highest among women with Medicare (53.4 per 1,000 deliveries in 2005 and 63.9 per 1,000 deliveries in 2014).



• The rate of preeclampsia/eclampsia was highest among women who resided in the poorest areas, but the rate rose more among those from the wealthiest areas.
  
  In both 2005 and 2014, the rate of preeclampsia/eclampsia was highest among women who resided in the poorest ZIP Codes (income quartile 1). During this time period, the rate increased from 44.3 to 53.2 per 1,000 deliveries among women in these areas—an increase of 20 percent. In comparison, the rate was 30.8 per 1,000 deliveries among women who resided in the wealthiest ZIP Codes (income quartile 4) in 2005 but increased by 28 percent to 39.4 per 1,000 deliveries in 2014.



• The rate of preeclampsia/eclampsia was highest among women who resided in nonmetropolitan areas, but the rate rose more among those from metropolitan areas.
  
  The rate of preeclampsia/eclampsia was highest among women who resided in micropolitan and rural areas in 2005 (43-44 per 1,000 deliveries) and rose by 12 percent (to 48-49 per 1,000 deliveries in 2014). In comparison, in large and small metropolitan areas, the rate of preeclampsia/eclampsia was 37-38 per 1,000 deliveries in 2005 and increased by 23 percent to 46-47 per 1,000 deliveries in 2014.



• The rate of preeclampsia/eclampsia was highest among women in the South, but the rate rose most rapidly in the Northeast.
  
  In both 2005 and 2014, the rate of preeclampsia/eclampsia was highest among deliveries in the South (43.1 and 51.6 per 1,000 deliveries, respectively). The rate of preeclampsia/eclampsia rose across all regions from 2005 through 2014. However, the increase was largest among deliveries in the Northeast, where the rate rose by 30 percent from 34.6 to 45.0 per 1,000 deliveries.

Figure 3 presents the rate of preeclampsia/eclampsia per 1,000 deliveries in 2014, by race/ethnicity and type of diagnosis.

• In 2014, the rate of preeclampsia/eclampsia was at least 50 percent higher among black women than among women of any other racial/ethnic group.
  
  In 2014, the total rate of preeclampsia/eclampsia was higher among black women than among women of other racial/ethnic groups. The total rate of preeclampsia/eclampsia was 69.8 per 1,000 deliveries among black women—about 60 percent higher than the rate among white women (43.3 per 1,000 deliveries).
  
  In 2014, there was no substantial difference in the total rate of preeclampsia/eclampsia between white women and Hispanic women (43.3 vs. 46.8 per 1,000 deliveries). Asian/Pacific Islanders had the lowest total rate of preeclampsia/eclampsia of any racial/ethnic group (28.8 per 1,000 deliveries).

Table 3 examines each type of preeclampsia/eclampsia as a percentage of total deliveries with any preeclampsia/eclampsia by race/ethnicity.

• Among women with preeclampsia/eclampsia, black women were more likely than women of other races/ethnicities to have a more severe diagnosis.
  
  The rate of each type of preeclampsia/eclampsia diagnosis was higher among black women than among women of other races/ethnicities (Figure 3). When the rate for each type of preeclampsia/eclampsia was examined as a percentage of the total rate for any preeclampsia/eclampsia, black women were more likely than other women to have a more severe diagnosis. Among women with preeclampsia/eclampsia, the percentage with a diagnosis of preeclampsia/eclampsia with preexisting hypertension (which does not distinguish between severe and mild cases of the condition) was much greater for black women than for white women (22.5 vs. 12.3 percent), as was the percentage with eclampsia (1.7 vs. 1.4 percent) and severe preeclampsia (38.5 vs. 34.3 percent). At the same time, the percentage with mild or unspecified preeclampsia was much lower among black women than among white women (37.3 vs. 51.9 percent). The percentage of women with mild or unspecified preeclampsia was also lower for Hispanic and Asian/Pacific Islander women compared with white women (45-46 percent vs. 51.9 percent).

Coexisting conditions and outcomes among deliveries with preeclampsia/eclampsia, 2014
Figure 4 displays the percentage of deliveries that resulted in C-section in 2014, according to the presence and type of preeclampsia/eclampsia.

• Over half of all deliveries with preeclampsia/eclampsia involved C-section.
  
  Among all deliveries with preeclampsia/eclampsia, 53.9 percent were by C-section, compared with 31.7 percent of deliveries not involving preeclampsia/eclampsia. The rate of C-section was over 60 percent for deliveries with a diagnosis of eclampsia, severe preeclampsia, and preeclampsia/eclampsia with preexisting hypertension. In comparison, the rate was 44.3 percent among deliveries with mild or unspecified preeclampsia.

Table 4 presents selected coexisting conditions for deliveries with preeclampsia/eclampsia, compared with all other deliveries, in 2014. The conditions displayed were chosen on the basis of prior literature and sorted according to their prevalence among deliveries with preeclampsia/eclampsia.

• Compared with all other deliveries, those with preeclampsia/eclampsia had a higher proportion of coexisting conditions.
  
  Coexisting conditions were more common among deliveries with preeclampsia/eclampsia than among all other deliveries. For example, obesity was a coexisting condition among 17.3 percent of deliveries with preeclampsia/eclampsia but among only 6.7 percent of all other deliveries.
  
  Among deliveries with preeclampsia/eclampsia, those with preexisting hypertension were more likely than those with other types of preeclampsia/eclampsia to have obesity (33.2 percent), gestational diabetes (17.1 percent), thyroid dysfunction (6.4 percent), preexisting diabetes (11.4 percent), and cardiovascular disorders (3.8 percent).
  
  Anemia occurred more frequently among deliveries with eclampsia (26.7 percent) than among deliveries with other types of preeclampsia/eclampsia (18.7 to 22.5 percent). Similarly, multiple gestations were more common among deliveries with severe preeclampsia (7.4 percent) than among deliveries with other types of preeclampsia/eclampsia (4.6 to 5.3 percent).

Table 5 presents select outcomes for deliveries with preeclampsia/eclampsia, compared with all other deliveries, in 2014. The conditions displayed were chosen on the basis of prior literature, grouped according to whether they were identified using procedure codes or diagnosis codes pertaining to the mother or infant, and sorted according to their prevalence among deliveries with preeclampsia/eclampsia.

• The rates of procedural interventions and adverse maternal outcomes were higher among deliveries with preeclampsia/eclampsia than among all other deliveries.
  
  Procedural interventions were more common among deliveries with preeclampsia/eclampsia than among other types of deliveries: blood transfusion was 4 times more common (42.7 vs. 10.5 per 1,000 deliveries), ventilation was 10 times more common (5.3 vs. 0.5 per 1,000 deliveries), and hysterectomy was 50 percent more common (1.6 vs. 1.0 per 1,000 deliveries).
  
  Although rare, all the adverse maternal outcomes considered were more common among deliveries with preeclampsia/eclampsia than among other types of deliveries. This included renal failure, heart failure, and peripartum cardiomyopathy. These outcomes were also more common for each type of preeclampsia/eclampsia compared with all other deliveries, even for those with the least severe form of the condition, mild or unspecified preeclampsia.



• Compared with all other deliveries, those with preeclampsia/eclampsia were more likely to have adverse infant outcomes.
  
  Adverse infant outcomes were more common among deliveries with preeclampsia/eclampsia than among other types of deliveries: poor fetal growth (74.6 vs. 25.9 per 1,000 deliveries), intrauterine death (11.6 vs. 6.2 per 1,000 deliveries), and fetal distress (1.8 vs. 1.2 per 1,000 deliveries).
  
  Among deliveries with preeclampsia/eclampsia, those with preexisting hypertension or severe preeclampsia had the highest proportion of poor fetal growth (over 100 per 1,000 deliveries). Intrauterine death was most prevalent among deliveries with eclampsia (27.9 per 1,000 deliveries).

Data Source

The estimates in this Statistical Brief are based upon data from the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS), 2014. Historical data were drawn from the 2005-2013 National (Nationwide) Inpatient Sample (NIS).

Definitions

Diagnoses, procedures, ICD-9-CM, Clinical Classifications Software (CCS), and diagnosis-related groups (DRGs)
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.

All-listed procedures include all procedures performed during the hospital stay, whether for definitive treatment or for diagnostic or exploratory purposes. The first-listed procedure is the procedure that is listed first on the discharge record. Inpatient data define this as the principal procedure—the procedure that is performed for definitive treatment rather than for diagnostic or exploratory purposes (i.e., the procedure that was necessary to take care of a complication).

ICD-9-CM is the International Classification of Diseases, Ninth Revision, Clinical Modification, which assigns numeric codes to diagnoses and procedures. There are approximately 14,000 ICD-9-CM diagnosis codes. There are approximately 4,000 ICD-9-CM procedure codes.

CCS categorizes ICD-9-CM diagnosis codes into a manageable number of clinically meaningful categories.²² This clinical grouper makes it easier to quickly understand patterns of diagnoses. CCS categories identified as Other typically are not reported; these categories include miscellaneous, otherwise unclassifiable diagnoses that may be difficult to interpret as a group.

DRGs comprise a patient classification system that categorizes patients into groups that are clinically coherent and homogeneous with respect to resource use. DRGs group patients according to diagnosis, type of treatment (procedure), age, and other relevant criteria. Each hospital stay has one assigned DRG.

Case definition
The DRG and ICD-9-CM diagnosis codes used to identify delivery hospitalizations—overall and those with preeclampsia, eclampsia, and other types of hypertension complicating pregnancy, childbirth, and the puerperium—are shown in Tables 6 through 8.

ICD-9-CM diagnosis codes identifying coexisting conditions and maternal and infant outcomes are provided in Tables 9 and 10. Codes came from both Chapter 11 of the ICD manual on Complications of Pregnancy, Childbirth, and the Puerperium (ICD-9-CM codes 630-679), as well as from non-pregnancy-related chapters. Maternal outcomes are generally consistent with the definitions used by a prior study on severe obstetric morbidity.²³

Types of hospitals included in the HCUP National (Nationwide) Inpatient Sample
The National (Nationwide) Inpatient Sample (NIS) is based on 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). The NIS includes obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals. Beginning in 2012, long-term acute care hospitals are also excluded. 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 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 1 year will be counted each time as a separate discharge from the hospital.

Costs and charges
Total hospital charges were converted to costs using HCUP Cost-to-Charge Ratios based on hospital accounting reports from the Centers for Medicare & Medicaid Services (CMS).²⁴ 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 hospital-wide cost-to-charge ratio is used. Hospital charges reflect the amount the hospital billed for the entire hospital stay and do not include professional (physician) fees. For the purposes of this Statistical Brief, costs are reported to the nearest hundred.

Location of patients' residence
Place of residence is based on the Urban Influence Codes (UIC) for the urban-rural classification scheme for U.S. counties:

• Large metropolitan areas with at least 1 million residents
• Small metropolitan areas with less than 1 million residents
• Micropolitan
• Nonmetropolitan and nonmicropolitan counties (rural, noncore)

Median community-level income
Median community-level income is the median household income of the patient's ZIP Code of residence. Income levels are separated into population-based quartiles with cut-offs determined using ZIP Code demographic data obtained from the Nielsen Company. The income quartile is missing for patients who are homeless or foreign.

Payer
Payer is the expected payer for the hospital stay. To make coding uniform across all HCUP data sources, payer combines detailed categories into general groups:

• Medicare: includes patients covered by fee-for-service and managed care Medicare
• Medicaid: includes patients covered by fee-for-service and managed care Medicaid
• Private Insurance: includes Blue Cross, commercial carriers, and private health maintenance organizations (HMOs) and preferred provider organizations (PPOs)
• Uninsured: includes an insurance status of self-pay and no charge
• Other: includes Workers' Compensation, TRICARE/CHAMPUS, CHAMPVA, Title V, and other government programs

Hospital stays billed to the State Children's Health Insurance Program (SCHIP) may be classified as Medicaid, Private Insurance, or Other, depending on the structure of the State program. Because most State data do not identify patients in SCHIP specifically, it is not possible to present this information separately.

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

Region
Region is one of the four regions defined by the U.S. Census Bureau:

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

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, Asian/Pacific Islander, and non-Hispanic Other, including American Indian/Alaska Native.

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
District of Columbia 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
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 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
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 Health Care Authority
Wisconsin Department of Health Services
Wyoming Hospital Association

About Statistical Briefs

HCUP Statistical Briefs are descriptive summary reports presenting statistics on hospital inpatient, ambulatory surgery, and emergency department use and costs, quality of care, access to care, medical conditions, procedures, patient populations, and other topics. The reports use HCUP administrative healthcare data.

About the NIS

The HCUP National (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 includes all payers. 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 the national and regional levels for specific subgroups of patients. In addition, NIS data are standardized across years to facilitate ease of use. Over time, the sampling frame for the NIS has changed; thus, the number of States contributing to the NIS varies from year to year. The NIS is intended for national estimates only; no State-level estimates can be produced.

The 2012 NIS was redesigned to optimize national estimates. The redesign incorporates two critical changes:

• Revisions to the sample design—starting with 2012, the NIS is now a sample of discharge records from all HCUP-participating hospitals, rather than a sample of hospitals from which all discharges were retained (as is the case for NIS years before 2012).
• Revisions to how hospitals are defined—the NIS now uses the definition of hospitals and discharges supplied by the statewide data organizations that contribute to HCUP, rather than the definitions used by the American Hospital Association (AHA) Annual Survey of Hospitals.

The new sampling strategy is expected to result in more precise estimates than those that resulted from the previous NIS design by reducing sampling error: for many estimates, confidence intervals under the new design are about half the length of confidence intervals under the previous design. The change in sample design for 2012 necessitates recomputation of prior years' NIS data to enable analyses of trends that use the same definitions of discharges and hospitals.

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:

• HCUP Fast Stats at https://datatools.ahrq.gov/hcup-fast-stats for easy access to the latest HCUP-based statistics for health 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 National (Nationwide) Inpatient Sample (NIS), please refer to the following database documentation:

Agency for Healthcare Research and Quality. Overview of the National (Nationwide) Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality. Updated December 2016. www.hcup-us.ahrq.gov/nisoverview.jsp. Accessed January 31, 2017.

Suggested Citation

Fingar KR (IBM Watson Health), Mabry-Hernandez I (AHRQ), Ngo-Metzger Q (AHRQ), Wolff T (AHRQ), Steiner CA (Institute for Health Research, Kaiser Permanente), Elixhauser A (AHRQ). Delivery Hospitalizations Involving Preeclampsia and Eclampsia, 2005-2014. HCUP Statistical Brief #222. April 2017. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb222-Preeclampsia-Eclampsia-Delivery-Trends.pdf.

Acknowledgments

The authors would like to acknowledge the contributions of Minya Sheng 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 e-mail us at hcup@ahrq.gov or send a letter to the address below:

Sharon Arnold, Ph.D., Acting Director
Center for Delivery, Organization, and Markets
Agency for Healthcare Research and Quality
5600 Fishers Lane
Rockville, MD 20857


This Statistical Brief was posted online on April 25, 2017.


¹ >140/90 mm Hg on two occasions 4 hours apart.
² >300 mg/dL on a 24-hour urine protein test, protein:creatinine ratio of >0.3 mg/mmol, or urine protein dipstick reading >1 if quantitative analysis is not available.
³ American College of Obstetricians and Gynecologists. Hypertension in Pregnancy. Washington, DC: American College of Obstetricians and Gynecologists; 2013.
⁴ Ibid.
⁵ Mammaro A, Carrara S, Cavaliere A, Ermito S, Dinatale A, Pappalardo EM, et al. Hypertensive disorders of pregnancy. Journal of Prenatal Medicine. 2009;3(1):1-5.
⁶Ibid.
⁷ Report of the National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy. American Journal of Obstetrics & Gynecology. 2000;183:S1-S22.
⁸ Shahul S, Tung A, Minhaj M, Nizamuddin J, Wenger J, Mahmood E, et al. Racial disparities in comorbidities, complications, and maternal and fetal outcomes in women with preeclampsia/eclampsia. Hypertension in Pregnancy. 2015;34(4):506-15.
⁹Tanaka M, Jaamaa G, Kaiser M, Hills E, Soim A, Zhu M, et al. Racial disparity in hypertensive disorders of pregnancy in New York State: a 10-year longitudinal population-based study. American Journal of Public Health. 2007;97(1):163-70.
¹⁰ Ibid.
¹¹ Report of the National High Blood Pressure Education Program Working Group on High Blood Pressure in Pregnancy. American Journal of Obstetrics and Gynecology. 2000;183:S1-S22.
¹² Kuklina EV, Ayala C, Callaghan WM. Hypertensive disorders and severe obstetric morbidity in the United States. Obstetrics and Gynecology. 2009;113(6):1299-306.
¹³ Mammaro A, Carrara S, Cavaliere A, Ermito S, Dinatale A, Pappalardo EM, et al. Hypertensive disorders of pregnancy. Journal of Prenatal Medicine. 2009;3(1):1-5.
¹⁴ Centers for Disease Control and Prevention. Data on Selected Pregnancy Complications in the United States. October 2016. www.cdc.gov/reproductivehealth/maternalinfanthealth/pregnancy-complications-data.htm. Accessed March 29, 2017.
¹⁵ Shahul et al., 2015. Op. cit.
¹⁶ D'Alton ME, Main EK, Menard MK, Levy BS. The National Partnership for Maternal Safety. Obstetrics and Gynecology. 2014;123:973-7.
¹⁷ Ananth CV, Keyes KM, Wapner RJ. Pre-eclampsia rates in the United States, 1980-2010: age-period-cohort analysis. BMJ. 2013;347:f6564.
¹⁸ Wallis AB, Saftlas AF, Hsia J, Atrash HK. Secular trends in the rates of preeclampsia, eclampsia, and gestational hypertension, United States, 1987-2004. American Journal of Hypertension. 2008;21:521-6.
¹⁹ Kuklina EV, Meikle SF, Jamieson DJ, Whiteman MK, Barfield WD, Hills SD, et al. Severe obstetric morbidity in the United States: 1998-2005. Obstetrics and Gynecology. 2009;113(2 Pt 1):293-9.
²⁰ Callaghan WM, Creanga AA, Kuklina EV. Severe maternal morbidity among delivery and postpartum hospitalizations in the United States. Obstetrics and Gynecology. 2012;120(5):1029-36.
²¹ The first three categories are defined by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes for mild or unspecified preeclampsia (642.4), severe preeclampsia (642.5), and eclampsia (642.6). These codes are used if preexisting hypertension was not present. The last category is defined by the code 642.7, which is used if preexisting hypertension was present with preeclampsia/eclampsia. However, records with this code lack detail on the severity of preeclampsia/eclampsia.
²² Agency for Healthcare Research and Quality. HCUP Clinical Classifications Software (CCS) for ICD-9-CM. Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality. Updated October 2016. www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Accessed January 31, 2017.
²³ Kuklina EV, Meikle SF, Jamieson DJ, Whiteman MK, Barfield WD, Hills SD, et al. Severe obstetric morbidity in the United States: 1998-2005. Obstetrics and Gynecology. 2009;113(2 Pt 1):293-9.
²⁴ Agency for Healthcare Research and Quality. HCUP Cost-to-Charge Ratio (CCR) Files. Healthcare Cost and Utilization Project (HCUP). 2001-2014. Rockville, MD: Agency for Healthcare Research and Quality. Updated November 2016. www.hcup-us.ahrq.gov/db/state/costtocharge.jsp. Accessed January 31, 2017.