User Support

August 2021

Pamela L. Owens, Ph.D., Richard J. Manski, D.D.S., M.B.A., Ph.D., and Audrey J. Weiss, Ph.D.


Introduction

Oral health contributes to overall wellbeing and improved quality of life. Untreated poor dental health also can lead to negative general health outcomes.¹ Most oral diseases tend to be progressive and cumulative without intervention.² Tooth decay and periodontal disease are among the most prevalent chronic diseases worldwide and have been shown to be associated with a number of life-threatening conditions, including sepsis, diabetes, and heart disease.^2,3 Despite the increasing need for dental care, many Americans delay or do not receive it. Failure to receive treatment may make necessary the provision of less definitive and more costly care. Individuals who lack a usual source for dental care may visit hospital emergency departments (EDs) to seek relief for dental pain and related conditions.^4,5 The cost of dental-related visits to the ED is high, totaling more than $2 billion nationally in 2017.⁶

This Healthcare Cost and Utilization Project (HCUP) Statistical Brief presents statistics on ED visits involving dental conditions using weighted estimates from the 2018 Nationwide Emergency Department Sample (NEDS). Characteristics of dental-related ED visits, including visits that result in discharge from the ED (treat and release) and visits that result in admission to the hospital, are presented. The most common dental conditions are identified by type of ED visit. For ED visits with a dental condition as a secondary diagnosis, the most frequent first-listed or principal nondental conditions are presented. Because of the large sample size of the NEDS data, small differences can be statistically significant but not clinically important. Thus, only differences greater than or equal to 10 percent are discussed in the text.

Findings

Characteristics of ED visits related to dental conditions, 2018
Table 1 presents characteristics of ED visits related to dental conditions by type of ED visit—all ED visits, treat-and-release ED visits, and ED visits resulting in hospital admission—compared with all other non-dental-related ED visits.

• Of more than 2 million ED visits involving dental conditions in 2018, 95 percent resulted in discharge from the ED.
  
  In 2018, there were 2 million dental-related ED visits in the United States, accounting for 1.4 percent of the 143 million total ED visits. The vast majority of dental-related ED visits were treat and release (94.5 percent), with the remaining ED visits resulting in hospital admission (5.5 percent).



• The population rate of dental-related ED visits overall was highest among individuals aged 18-44 years, non-Hispanic Black individuals, and those residing in the lowest income communities.
  
  Individuals aged 18-44 years had the highest rate of dental-related ED visits overall (1,107.4 per 100,000 population) compared with all other age groups—more than double the rate of those aged 45-64 years (473.5) and approximately four to five times higher than the rate for children and older adults. In contrast, the rate of non-dental-related ED visits was highest for individuals aged 85 years and older, more than double the rate for each of the under 65 age groups.
  
  The rate of dental-related ED visits was more than 2.5 times higher for non-Hispanic Black individuals than for other race/ethnicity groups (1,362.4 vs. 520.9 or less per 100,000 population). Although Black individuals also had higher rates of non-dental-related ED visits than other race/ethnicity groups, the differential was smaller (about 1.8 times higher).
  
  Individuals residing in the lowest income communities (quartile 1) had the highest rate of dental-related ED visits (1,069.1 per 100,000 population) compared with those from higher community-level income areas. Although the rate for non-dental-related ED visits also was highest among those living in the lowest income communities, the rate differential between the lowest and highest income communities was greater among dental-related than non-dental-related ED visits (4.3 vs. 2.3 times higher).



• The highest and lowest population rates of dental-related ED visits by patient age group and location of residence differed by the type of ED visit.
  
  By age group, the population rate of dental-related treat-and-release ED visits was highest among individuals aged 18-44 years and lowest among those aged 85 years and older (1,073.9 vs. 129.7 per 100,000 population). In contrast, the rate of dental-related ED visits resulting in hospital admission increased with age, with the highest rate among those aged 85 years and older (67.8 per 100,000 population vs. 13.2 per 100,000 population among those younger than 18 years).
  
  By location of patient residence, the population rate of dental-related treat-and-release ED visits was highest among individuals residing in micropolitan areas and lowest among those residing in large metropolitan areas (897.1 vs. 473.7 per 100,000 population). In contrast, there was relatively little difference in the population rate of dental-related ED visits resulting in hospital admission by patient residence location, ranging from 30.6 per 100,000 population in rural areas to 34.8 per 100,000 population in medium and small metropolitan areas.

Figure 1 illustrates the primary expected payer mix of dental-related ED visits compared with all other non-dental-related ED visits. The figure also compares the expected payer source for dental-related treat-and-release ED visits with dental-related ED visits resulting in hospital admission.

• More than two-thirds of dental-related ED visits were expected to be billed to Medicaid or were self-pay/no charge.
  
  Medicaid was the primary expected payer for more than two in five dental-related ED visits (42.2 percent), compared with less than one-third of non-dental-related ED visits (32.4 percent). Another one-fourth of dental-related ED visits (26.1 percent) were expected to be self-pay/no charge, compared with 11.8 percent of non-dental-related ED visits.
  
  A higher percentage of dental-related treat-and-release ED visits than dental-related ED visits resulting in hospital admission had Medicaid as the expected payer (42.7 vs. 34.6 percent); the opposite was true for Medicare as the expected payer (9.4 percent of treat-and-release ED visits vs. 31.5 percent of ED visits resulting in admission).

First-listed or principal versus secondary diagnoses among ED visits involving dental conditions, 2018
Figure 2 displays the percentage of ED visits specifically for a dental condition (i.e., the dental condition was the first-listed diagnosis for treat-and-release ED visits or the principal diagnosis for ED visits resulting in hospital admission) versus those ED visits primarily for a nondental condition where a dental condition was a secondary diagnosis, by type of ED visit.

• The majority of dental-related treat-and-release ED visits were primarily for a dental condition, whereas the majority of dental-related ED visits resulting in hospital admission were principally for a nondental condition.
  
  Eighty percent of dental-related treat-and-release ED visits were primarily for a dental condition, whereas 20 percent of visits were primarily for a nondental condition. In contrast, among dental-related ED visits resulting in hospital admission, only about 10 percent were principally for a dental condition and nearly 90 percent were principally for a nondental condition.

Table 2 shows the five most common groups of dental conditions among all dental-related ED visits, by type of ED visit and by whether the ED visit was primarily for the dental condition (first-listed or principal diagnosis only), included only secondary dental conditions, or included either principal or secondary dental conditions (any-listed diagnosis).

• Among treat-and-release ED visits with a principal diagnosis of a dental condition, 92.7 percent were for one of three groups of conditions: loss of teeth and similar disorders, diseases of pulp and periapical tissues, and dental caries.
  
  The three most common groups of dental conditions among dental-related treat-and-release ED visits with a first-listed, secondary only, or any-listed diagnosis of a dental condition were:
  
  • Loss of teeth and similar disorders (38.4, 78.0, and 46.3 percent of visits, respectively)
  • Diseases of pulp and periapical tissues (33.1, 31.4, and 32.8 percent of visits, respectively)
  • Dental caries (21.2, 67.4, and 30.4 percent of visits, respectively)



• Among ED visits resulting in hospital admission with a principal diagnosis of a dental condition, 85.3 percent were for diseases of pulp and periapical tissues.
  
  The most common group of dental conditions among dental-related ED visits resulting in hospital admission was diseases of pulp and periapical tissues for visits with a principal or any-listed diagnosis of a dental condition (85.3 and 37.7 percent of visits, respectively) and dental caries for visits with only a secondary diagnosis of a dental condition (37.1 percent of visits).

Table 3 presents the five most common nondental conditions among ED visits with a dental condition as a secondary diagnosis only, by type of ED visit.

• Fracture of head and neck was the most common first-listed nondental condition among treat-and-release ED visits with a secondary diagnosis of a dental condition.
  
  Among dental-related ED visits with only a secondary diagnosis of a dental condition, the most common first-listed nondental diagnosis for treat-and-release ED visits was fracture of head and neck (6.5 percent) and the most common principal nondental diagnosis for ED visits resulting in hospital admission was septicemia (13.2 percent).

References

¹ Joshipura KJ, Rimm EB, Douglass CW, Trichopoulos D, Ascherio A, Willett WC. Poor oral health and coronary heart disease. Journal of Dental Research. 1996;75(9):1631-6
² National Institute of Dental and Craniofacial Research. Oral Health in America: A Report of the Surgeon General. 2000. Rockville, MD: U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Dental and Craniofacial Research. www.nidcr.nih.gov/sites/default/files/2017-10/hck1ocv.%40www.surgeon.fullrpt.pdf. Accessed June 30, 2021.
³ Eke PI, Dye BA, Wei L, Slade GD, Thornton-Evans GO, Borgnakke WS, et al. Update on prevalence of periodontitis in adults in the United States: NHANES 2009-2012. Journal of Periodontology. 2015;86(5):611-22.
⁴ Cohen LA, Manski RJ, Magder LS, Mullins D. A Medicaid population's use of physicians' offices for dental problems. American Journal of Public Health. 2003;93(8):1297-301.
⁵ Cohen LA, Manski RJ, Magder LS, Mullins D. Dental visits to hospital emergency departments by adults receiving Medicaid: assessing their use. Journal of the American Dental Association. 2002;133(6):715-24.
⁶ American Dental Association Health Policy Institute. Emergency Department Visits for Dental Conditions - A Snapshot. April 2020. www.ada.org/~/media/ADA/Science%20and%20Research/HPI/Files/HPIgraphic_0420_1.pdf?la=en. Accessed June 29, 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 2018 Nationwide Emergency Department Sample (NEDS).^a Supplemental sources included population denominator data for use with HCUP databases, derived from information available from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau.^b

Definitions

Diagnoses, ICD-10-CM, and Clinical Classifications Software Refined (CCSR) for ICD-10-CM Diagnoses
For emergency department (ED) visits that are treated and released, the first-listed diagnosis represents the condition, symptom, or problem identified in the medical record to be chiefly responsible for the ED services provided. In cases where the first-listed diagnosis is a symptom or problem, a diagnosis has not been established (confirmed) by the provider. For ED visits that result in an inpatient admission, the first-listed diagnosis is the principal diagnosis, the 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 the ED visit or inpatient admission, that require or affect patient care treatment received or management, or that develop during the inpatient stay. All-listed diagnoses include the first-listed (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.

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. For this Statistical Brief, the principal diagnosis code is assigned to a single default CCSR based on clinical coding guidelines, etiology and pathology of diseases, and standards set by other Federal agencies. The assignment of the default CCSR for the first-listed diagnosis for outpatient data is available starting with version v2021.1 of the software tool. 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, v2021.1 of the CCSR was used.

Case definition
Dental-related ED visits were defined as those with any ICD-10-CM diagnosis code in CCSR DIG002, Disorders of Teeth and Gingiva. DIG002 includes 229 ICD-10-CM diagnosis codes related to dental caries, cysts in the oral region, dentofacial anomalies, periodontitis, diseases of pulp and periapical tissues, dislocation of a tooth, disorders of tooth development and eruption, embedded or impacted teeth, gingival disorders, cracked tooth and other disease of hard tissues of teeth, other diseases of the jaw, and loss of teeth and similar disorders of teeth and supporting structures (Appendix A).

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.

Population rates
Rates of ED visits per 100,000 population were calculated using 2018 ED visit totals in the numerator and Claritas^d estimates of the 2018 U.S. population in the denominator. Individual patients seen in the ED multiple times are counted more than once in the numerator.

Population rate of ED visits related to dental conditions equals number of dental-related ED visits divided by the number of U.S. residents times 100,000

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 Black, non-Hispanic White, and non-Hispanic Other.

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:

• 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 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
• Micropolitan: Counties in a nonmetropolitan area of 10,000-49,999 residents
• Noncore (rural): Counties in a nonmetropolitan and nonmicropolitan area

For this Statistical Brief, we combined the large central and large fringe metropolitan categories and the medium and small metropolitan categories.

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.^e The value ranges for the income quartiles vary by year. The income quartile is missing for patients who are homeless or foreign.

Expected payer
To make coding uniform across all HCUP data sources, the primary expected payer for the ED visit 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

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.

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:

About the NEDS

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 2018 NEDS is 35,807,950 (weighted, this represents 143,454,430 ED visits).

For More Information

For previous information on ED visits related to dental conditions, refer to the HCUP Statistical Brief located at www.hcup-us.ahrq.gov/reports/statbriefs/sb143.pdf.

For additional HCUP statistics, visit:

• HCUP Fast Stats at https://datatools.ahrq.gov/hcup-fast-stats for easy access to the latest HCUP-based statistics for healthcare information topics
• HCUPnet, HCUP's interactive query system, at datatools.ahrq.gov/hcupnet
• HCUP Summary Trend Tables at www.hcup-us.ahrq.gov/reports/trendtables/summarytrendtables.jsp for monthly information on hospital utilization

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 November 2020. www.hcup-us.ahrq.gov/nedsoverview.jsp. Accessed January 22, 2021.

Suggested Citation

Owens PL (AHRQ), Manski RJ (AHRQ), Weiss AJ (IBM Watson Health). Emergency Department Visits Involving Dental Conditions, 2018. HCUP Statistical Brief #280. August 2021. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb280-Dental-ED-Visits-2018.pdf.

Acknowledgments

The authors would like to acknowledge the contributions of Minya Sheng of IBM Watson Health and Marguerite Barrett of M.L. Barrett, Inc.

***

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 August 19, 2021.


^a Note that race/ethnicity data are not included on the publicly available NEDS.
^b Claritas. Claritas Demographic Profile by ZIP Code. https://claritas360.claritas.com/mybestsegments/. Accessed January 22, 2021.
^c Agency for Healthcare Research and Quality. HCUP Clinical Classifications Software Refined (CCSR) for ICD-10-CM Diagnoses. Healthcare Cost and Utilization Project (HCUP). Agency for Healthcare Research and Quality. Updated March 2021. www.hcup-us.ahrq.gov/toolssoftware/ccsr/dxccsr.jsp. Accessed June 14, 2021.
^d Claritas. Claritas Demographic Profile by ZIP Code. https://claritas360.claritas.com/mybestsegments/. Accessed January 22, 2021.
^e Claritas. Claritas Demographic Profile by ZIP Code. https://claritas360.claritas.com/mybestsegments/. Accessed January 22, 2021.