Methods in Assessing Non-Traumatic Dental Care in Emergency Departments



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Predictive Factors

Demographics and Other Patient Factors


Many of the studies on ED dental care evaluated basic demographic and patient factors associated with presenting at the ED with non-traumatic dental problems. Wall(29) and Wall and Vujicic(24) included analyses by age group and primary payer in their studies of national ED visits for dental care. Cohen et al., in an analysis of MEPS data, studied associations of gender, race/ethnicity, family income, education, employment, and urban/rural status with medical and ED visits for dental problems, and found that only education was statistically associated with ED visits for dental problems.(25) Sun et al. explored age, gender, race/ethnicity, insurance type, and residence zip code level measures of poverty, education, and unemployment in their study of rates, costs, and predictors of NTDC related ED visits in Oregon.(44) Flores and Tomany-Korman specifically focused on racial/ethnic disparities in an analysis of 2003-2004 National Survey of Children’s Health, exploring many measures of oral and medical health status, access, and utilization.(43) Fields et al. investigated the effects of metropolitan residence status and insurance instability, along with other patient demographic and health predictors on healthcare utilization.(26) Hong et al. investigated gender, age, and race/ethnicity, along with zip code community and census level variables, and other access related variables in their studies.(82, 83) Lee H. et al. found increasing rates of ED dental care access associated with adults aged 18-44, Blacks, and the uninsured.(28) Stevens et al. explored physical, economic, and psychological factors, in addition to standard demographic factors, in characterizing health care access problems among older patients (65+) presenting at southeastern US ED.(76) In the various Okunseri et al. studies, analyses usually included age, race/ethnicity, gender, time (investigating trends over years), and insurance type, some with additional predictors of interest.(32-36, 50) For example, their study on analgesic medication ED prescription for NTDCs trends included having reported a dental problem as the reason for the ED visit and patient-reported severity of pain;(36) their study of ED waiting time for NTDCs included a triage category predictor variable.(32)

Other demographic and patient level factors have been studied. Ferayorni et al. investigated associations of being foreign born, as well as insurance status, with access to dental care and use of a pediatric ED as a primary source of care.(73) Lee J. et al., comparing dental care and ED visits for caries among North Carolina Medicaid children participating in WIC to those not participating in WIC, controlled for maternal educational level, maternal age, household income, and marital status in their analyses.(53) Patel et al., in their study of oral health status of patients presenting at the Hennepin County Medical Center ED in the period June through August of 2009, found age, ethnicity, and not having a routine dental checkup/cleaning in the last three years to be predictive of early and urgent dental needs.(75) Newacheck and Kim investigated health and dental care access and expenses focusing on differences for CSHCN.(27) Nakao et al. focused on autism spectrum disorders as a predictor of NTDC related ED visit rates and costs.(40) Note that some of the factors listed in the cited studies might be considered patient level factors, or might more appropriately fall into community/area level predictive factors or factors related to the access to care discussion that follows.

A variation on assessing predictive factors involves assessing factors specifically associated with hospital admission for NTDCs. Chi and Masterson found such hospital admissions associated with the number of complex chronic conditions in patients, being non-white, being publicly insured, and having lower income, while also assessing age and gender.(88) In a separate study, Chi et al. found that hospital admissions associated with NTDCs were slightly, though non-significantly, higher for children with intellectual and developmental disabilities (IDDs), but significantly lower for adults with IDDs.(89) Laurence et al. actually explored dental infection as a predictor of hospital admission among patients with sickle cell disease and patients with pneumonia.(38, 39)

In another variation on the standard demographics related to ED use for NTDCs, Cohen et al., in their study on health literacy issues in dental care, found males and Hispanics more likely to experience health literacy problems when seeking dental care from dentists, physicians and at EDs.(47) In another report on the same survey, Cohen et al. reported that reasons for contacting an ED for a NTDC varied by race, education level, and income, and interestingly, found that having been advised at the ED to contact a dentist for follow-up care varied by race, with 98% of whites reporting getting such advice, compared to only 16% of Hispanics.(48) Another example of a less common potential predictive factor is serious psychological distress (SPD), investigated by Dismuke et al. in association with different types of health and dental expenditures, including ED expenditures.(92) While they found SPD associated with higher ED related expenditures, SPD was associated with lower dental expenditures. Specific dentally related ED expenditures were not investigated in this study, so conclusions on the association of SPD and ED dental care can’t be drawn.

In addition to evaluation of demographics of subjects accessing EDs for dental care, area factors have also been investigated, which goes beyond subject factors to environmental factors in exploring associations with ED dental care. For example, DeVoe et al. studied different aspects of general and dental health care access, including use of EDs, with a primary focus on investigating differences by urban/rural residence status.(54) Martin et al. focused on urban/rural residence status in their study of dental care utilization, while also controlling for age, gender, race/ethnicity, and special healthcare need status.(46) DeLia et al. merged census data, NJ Family Health Survey data (for statewide insurance coverage distribution), and NJ dentist licensure data by zip code with NJ hospital discharge data and found ED use was associated with local dentist supply and use of EDs for other conditions.(93) Hong et al. included census data in one study,(82) and American Community Survey 5-Year Estimates data in another study(83) to combine patient level variables with community level variables including income, education level, and primary language spoken in homes. They studied predictors of dental related ED visits, finding community level income and language spoken at home to be significant predictors. Likewise, Nalliah found ED visits for caries associated with low-income area residence.(23) Authors and ED dental care patient characteristic predictors studied are summarized in Table 11.

Table 11: Authors and ED Dental Care Patient Characteristic Predictors Studied

Authors

ED Dental Care Patient Characteristic Predictors

Wall(29)

Age group, primary payer

Wall and Vujicic(24)

Age group, primary payer

Cohen et al. (25)

Gender, race/ethnicity, family income, education, employment, and urban/rural status

Sun et al.(44)

Age, gender, race/ethnicity, insurance type, and residence zip code level measures of poverty, education, and unemployment

Flores and Tomany-

Korman(43)



Racial/ethnic disparities

Fields et al.(26)

Metropolitan residence status and insurance instability, along with other patient demographic and health predictors

Hong et al. (82, 83)

Gender, age, race/ethnicity, zip code community and census level variables, and other access related variables

Lee H. et al.(28)

Age, race/ethnicity, insurance status

Stevens et al.(76)

Physical, economic, and psychological factors, demographic factors

Okunseri et al.(32-36, 50)

Age, race/ethnicity, gender, time (investigating trends over years), insurance type,

additional predictors for specific research questions: triage category, patient reported dental pain and severity of pain



Ferayorni et al.(73)

Being foreign born, insurance status, access to dental care, pediatric ED as a primary source of care

Lee J. et al.(53)

WIC participation among Medicaid children, maternal educational level, maternal age, household income, and marital status

Patel et al.(75)

Age, race/ethnicity, not having a routine dental checkup/cleaning in the last 3 years

Newacheck and Kim(27)

Differences for CSHCN

Nakao et al.(40)

Autism spectrum disorders

Chi and Masterson(88)

Number of patient complex chronic conditions, race/ethnicity, insurance type, income, age, gender

Chi et al.(89)

Intellectual and developmental disabilities

Laurence et al.(38, 39)

Dental infection as a predictor of hospital admission

Cohen et al.(47)

Gender, race/ethnicity

Cohen et al.(48)

Education level, income, race/ethnicity

Dismuke et al.(92)

Serious psychological distress (SPD)

DeVoe et al.(54)

Urban/rural residence status

Martin et al.(46)

Urban/rural residence status, age, gender, race/ethnicity, and special healthcare need status

DeLia et al.(93)

Insurance, local dentist supply, use of EDs for other conditions than dental

Hong et al. (82) (83)

Patient level variables and community level variables including income, education level, and primary language spoken in homes

Nalliah(23)

Low-income area residence


Access Issues/Policy Changes


Access related factors are often investigated in relation to ED use for NTDCs. One primary access factor often investigated is dental insurance. Having insurance is often included with other subject level demographic factors as mentioned previously (23, 25, 26, 67, 73), and often includes designation of whether the insurance is private or public. In another study focusing on young adults, Lewis found people without insurance or on Medicaid were more likely to use EDs for dental problems in general,(30) and likewise for young adults.(31) While some studies include insurance with a mix of other patient demographic characteristics, some researchers focus primarily on insurance status and other access issues related to healthcare utilization. Walker et al. analyzed 2008 NEDS data with a primary objective of determining if insurance status and rural residence were predictors of ED visits with caries diagnoses among working-age adults.(37) Dorfman et al. investigated insurance status and other patient reported access issues related to primary medical and dental care, duration of NTDC symptoms, diagnosis, and seeking care at a hospital PED in interviews of patients accessing the PED for NTDCs.(72) The patient survey used in this study asked a number of questions about barriers to dental care with private practicing dentists. Lee et al. studied dental care access and ED visits with a primary diagnosis of caries through Medicaid claims for North Carolina Medicaid children, with WIC participation as the primary predictor of interest.(53) These studies can be grouped into a category that describes individual factors as predictors of ED use for NTDCs.

Other studies, however, investigate access in terms of population level, community level, or area level predictors. Okunseri et al., in a study of the Wisconsin Medicaid population, evaluated county of residence for DHPSA designation, in addition to Urban Influence Code (a measure for rurality), race/ethnicity, age, and gender as predictors of treatment for NTDCs in EDs and physician offices.(50) Pajewski and Okunseri, in another analysis of Wisconsin Medicaid data focusing on follow-up treatment after an NTDC ED visit among adult Medicaid patients, used similar predictor variables, with a generated variable on low-income population to dentist ratio.(51) In addition to age, gender, race, and income, Shortridge and Moore focused on urban/rural residence, dental DHPSA residence, and state Medicaid policies to assess similarities and differences in ED dental care rates in three states.(57)

Davis et al. found that a Minneapolis-St. Paul population with commercial dental insurance utilized EDs for oral problems at a much lower rate than the metropolitan population in general.(77) Hom et al. studied individuals under 18 years old in North Carolina using hospital EDs to assess whether the proportion of people accessing EDs for oral problems varied by hospital population insurance mix, and found that a higher proportion of dentally related ED visits were covered by Medicaid than ED visits in general, and that hospitals serving populations with larger proportions of children on Medicaid have a greater proportion of total ED visits that are for dental care.(45)

A more basic access barrier is the lack of available dental care. Hardie et al., in analyzing 2012 ED admission data from a rural Maryland hospital to characterize frequents users of the ED, found that many of the return visits involved dental diagnoses, and that the community had no dental facilities, with dental care only available in an adjacent state or at a dental clinic two hours away.(69) Related to lack of local dental facilities is the issue of dental facilities’ business hours. Some investigators have included time of day and day of week in their analyses of ED use for dental problems. Hong et al. found that weekends were associated with higher proportion of ED visits for dental problems.(82) Lewis et al. found that weekends and after-hour weekdays were associated with increased use of EDs for dental problems.(30) In addition to exploring rates and trends of visits for dental complaints at a Louisiana ED, Waldrop et al. found that non-emergent dental conditions were more likely to present during normal business hours, while emergent dental conditions were seen more between 7:00 PM and 7:00 AM.(70) While Lee et al. studied patient factors predictive of increasing rates of ED dental visits, they also compared increasing ED dental visit rates to unchanging asthma visit rates and concluded that the difference was likely due to decreasing access to community dental care.(28)

Related to availability of care is the issue of medical and dental homes. Romaire et al. analyzed MEPS data subsets of children aged 0 to 17 years in one study and CSHCN children 0 to 17 years in another study to explore effects of having a medical home on healthcare access and expenses, including ED and dental visits, for these child subpopulations.(41, 42)

Many publications address magnitude and changes in ED dental care related to changes in policy, particularly those for dental insurance coverage. For example, Becker et al. assessed changes in overall health care expenditures and utilization, including care provided in EDs (ED dental care was not specifically assessed), following an expansion of Children’s Health Insurance Program (CHIP) coverage in Alabama.(90) They found that though new expansion enrollees had higher care costs and utilization, their utilization rate of EDs was lower. McCormick, D. et al. investigated health care access issues following health care reform in Massachusetts, finding higher numbers of Medicaid and Commonwealth Care ED patients reporting delayed dental care or not getting dental care compared to privately insured patients.(71) In another study of the effects of Massachusetts healthcare reform, Neely et al. explored dental related ED visit rates and costs at Boston Medical Center, but specifically explored changes in rates and costs three years before and two years after Massachusetts health care reform.(68) Singhal et al. assessed differential effects based on patient age, sex, race/ethnicity, and geographic location, but their primary predictor of interest was changing Medicaid policy in California that eliminated adult dental benefits.(55) The investigators looked at rates of dental ED visits before and after the policy change and compared them to rates for other ambulatory care-sensitive conditions (asthma, headache, abdominal pain, diabetes, and back pain) during the same time period. Similarly, while controlling for other demographic factors, Wallace et al. assessed changes among continuously enrolled Oregon Medicaid patients in unmet dental needs, utilization of preventive services, and ED dental visit rates and associated costs after the elimination of dental benefits.(56)

A slight variation on policy change is change in healthcare coverage status. Feinglass et al. compared new Access DuPage (a healthcare program for low- income, uninsured residents of DuPage County, IL) enrollees to those who had been enrolled in Access DuPage for more than a year, and found that though there were many improvements in aspects of health, there was no improvement in dental care access, nor a decrease in ED use for the longer-term enrollees.(85) Likewise, Kempe et al. explored changes in care and access for general health, dental health, and ED care for Colorado residents before and one year after enrollment in Colorado’s CHP+ program, finding generally better healthcare access, better dental access, but no change in ED access for health issues.(52) Lave et al. followed new enrollees in Western Pennsylvania health insurance programs for low-income, uninsured residents to track changes in health care access during the first year following enrollment.(86)

Another area of potential policy change relates to patient care and related ED procedures. Hayes et al. studied whether providing medications to patients presenting to an urban ED with infections (including dental infections) differed in return rate to the ED from patients receiving only prescriptions.(74) While providing medications reduced return rates for some types of infection, there was no statistical difference seen among those presenting with dental infections.



Though not the subject of this report, another predictive factor studied by some researchers has been actual intervention programs designed to curb ED use for NTDCs. A companion document to this report is addressing ED dental care interventions. However, intervention programs do represent another predictive factor of ED use for dental care, and their effects have been evaluated. For example, researchers concluded that a Calhoun County, Michigan program significantly reduced the number of patients presenting at a local hospital for dental pain.(94) McCormick et al. found a 52% reduction in ED patients with dental complaints and a 66% reduction in ED patients with two or more visits after instituting a diversion program to a hospital emergency dental clinic.(67) Roghmann and Goldman explored the effects of a new neighborhood health center providing continuous dental care in reducing the number of ED dental emergency visits to area hospitals.(84) Authors and dental access and policy change predictors studied are summarized in Table 12.

Table 12: Authors and ED Dental Access and Policy Change Predictors Studied

Authors

ED Dental Access and Policy Change Predictors

Many studies, e.g.,(23, 25, 26, 67, 73)

Having insurance and whether insurance is public or private

Lewis(30, 31)

Insurance status and type

Walker et al.(37)

Insurance status, rural residence

Dorfman et al.(72)

Insurance status and other patient reported access issues

Lee et al.(53)

WIC participation (among Medicaid children)

Okunseri et al.(50)

County of residence for DHPSA designation, Urban Influence Code (a measure for rurality)

Pajewski and Okunseri(51)

Generated variable on low-income population to dentist ratio

Shortridge and Moore(57)

Urban/rural residence, dental HPSA residence, and state Medicaid policies

Davis et al.(77)

Insurance status and type

Hom et al.(45)

Hospital population insurance mix

Hardie et al.(69)

Dental clinic proximity

Hong et al.(82)

Weekends vs. weekdays

Lewis et al.(30)

Weekends vs. weekdays, after hours vs. normal business hours

Waldrop et al.(70)

After hours vs. normal business hours

Romaire et al.(41, 42)

Having a medical home

Becker et al.(90)

Expansion of state Children’s Health Insurance Program (CHIP) coverage

McCormick et al.(71)

State health care reform related to insurance type

Neely et al.(68)

State health care reform

Singhal et al.(55)

Changing Medicaid policy in California eliminating adult dental benefits

Wallace et al.(56)

Elimination of Medicaid dental benefits

Feinglass et al.(85)

Enrollment in a county healthcare program for low-income, uninsured residents

Kempe et al.(52)

Enrollment in state CHP+ program

Lave et al.(86)

Enrollment in a state regional health insurance program for low-income uninsured residents

Hayes et al.(74)

Program providing medications to patients with infections vs. receiving only prescriptions

Higbea et al.(94)

Local ED dental care diversion program

McCormick et al.(67)

Hospital diversion program to a hospital emergency dental clinic

Roghmann and

Goldman(84)



New neighborhood health center providing continuous dental care


Drug Seeking Behavior (DSB)


An alternative predictor of ED utilization for dental problems that some researchers have explored is patients that access EDs reporting dental pain to obtain prescriptions for opioids. Fox et al. conducted chart reviews in a two-hospital system to study the effects of an instituted prescribing guideline on opioid prescribing for patients with oral pain complaints.(78) In the Grover et al. chart review studies, patient behaviors and complaints when presenting at a hospital ED, including oral pain complaints, were investigated to assess their relation to DSB.(80, 81) Weiner et al., in a study comparing emergency provider impression to objective criteria in a state prescription drug monitoring program in identifying DSB, also assessed predictors of DSB including requesting opioids by name, multiple visits for the same complaint, suspicious history, reporting stolen medications, and symptoms out of proportion to examination.(79) DSB impacts on reported ED dental care utilization must be considered.
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