Outcomes in Patients Hospitalized for Periapical Abscess in the United States

Outcomes in Patients Hospitalized for Periapical Abscess in the United States

R E S E A R C H Outcomes in patients hospitalized for periapical abscess in the United States An analysis involving the use of a nationwide in...

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Outcomes in patients hospitalized for periapical abscess in the United States An analysis involving the use of a nationwide inpatient sample Veerasathpurush Allareddy, BDS, MBA, MHA, PhD; Chin-Yu Lin, DDS, MS, MSD, PhD; Andrea Shah, DMD; Min Kyeong Lee, DMD; Romesh Nalliah, BDS; Satheesh Elangovan, BDS, DSc; Veeratrishul Allareddy, BDS, MS; Nadeem Y. Karimbux, DMD, MMSc

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✷ Background. Severe infections resulting from periapical ® abscesses may warrant hospitalization. The authors conducted a study to investigate the factors affecting outcomes N for patients hospitalized for periapical abscess in the United C U U IN G ED A States in 2007. 4 RT ICLE Methods. The authors used the Nationwide Inpatient Sample of the Healthcare Cost and Utilization Project for 2007. They selected for analysis all hospitalizations attributed primarily to periapical abscess. Outcomes examined included hospitalization charges, length of stay and type of admission (emergency or urgent versus elective). They used multivariable regression analysis to examine the effects of patient-related factors (including age, sex, presence of comorbid conditions, insurance status, type of periapical abscess and discharge disposition) on outcomes. Results. In 2007, 7,886 hospitalizations were attributed primarily to periapical abscess. Total hospital charges were $105.8 million. Periapical abscess also resulted in a total of 23,001 hospitalization days. The mean hospitalization charges and length of stay were $13,590 and 2.92 days, respectively. The authors found an association between patients with comorbid conditions and higher charges and longer length of stay (P < .05). Of all hospitalizations, 91 percent occurred on an emergency or urgent basis. The percentage was significantly higher among uninsured patients than among those with private insurance (P < .05). Conclusion. The study provides nationally representative estimates of outcomes associated with hospitalizations due to periapical abscess, and it highlights the substantial resources needed to treat patients hospitalized for this condition. Key Words. Periapical abscess; access to care; hospitalization; outcomes; costs of care. JADA 2010;141(9):1107-1116. I

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ABSTRACT CON

eriapical abscess, a consequence of untreated infection of the root canal system, usually is well localized. However, under certain circumstances, these infections lead to cellulitis, osteitis or other serious complications, which, if left untreated, could be life threatening and warrant admission to a hospital.1-4 In patients with advanced infections, hospitalization may be necessary to administer treatments, including intravenous antibiotic medications, surgical incision with extraoral or intraoral drainage under general anesthesia and supportive care.2,5,6 The costs associated with hospitalization greatly exceed the costs of routine dental treatment for uncomplicated periapical abscesses in dental clinic settings.7 Uncomplicated periapical abscess can be treated in a general dental office without

Dr. Veerasathpurush Allareddy is an instructor, Department of Developmental Biology, School of Dental Medicine, Harvard University, 188 Longwood Ave., Boston, Mass. 02115, e-mail “[email protected]”. Address reprint requests to Dr. Allareddy. Dr. Lin is an instructor, Department of Developmental Biology, School of Dental Medicine, Harvard University, Boston. At the time this study was conducted, Dr. Shah was a fourth-year dental student, School of Dental Medicine, Harvard University, Boston. She is now an endodontics resident, Department of Endodontics, Tufts University, Boston. At the time this study was conducted, Dr. Lee was a fourth-year dental student, School of Dental Medicine, Harvard University, Boston. She is now an orthodontics resident, Department of Developmental Biology, School of Dental Medicine, Harvard University, Boston. Dr. Nalliah is a senior tutor, Department of Restorative Dentistry and Biomaterials Sciences, School of Dental Medicine, Harvard University, Boston. Dr. Elangovan is a resident, Department of Oral Medicine, Infection, and Immunity, School of Dental Medicine, Harvard University, Boston. Dr. Veeratrishul Allareddy is an assistant professor, Department of Oral Pathology, Radiology, and Medicine, The University of Iowa, Iowa City. Dr. Karimbux is an associate professor, Department of Oral Medicine, Infection, and Immunity, School of Dental Medicine, Harvard University, Boston.

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the need for hospitalization. Moreover, periapical Healthcare Cost and Utilization Project (HCUP) abscess can be prevented by maintaining a for 2007 that the Agency for Healthcare Research healthy dentition and periodontium. In addition and Quality (AHRQ), Rockville, Md., made availto daily maintenance, regular dental office visits able for research purposes.15 The NIS is a 20 perand radiographs are essential to prevent caries, cent stratified probability sample of all nonfedwhich can lead to periapical abscess. eral acute care general hospitals in the United Investigators in several studies have examined States and provides hospital discharge informaoutcomes in patients hospitalized for odontogenic tion regarding 8,043,415 hospitalizations from infections.6,8-12 These are single-center studies. To 1,044 hospitals in 40 states.15 Each discharge in our knowledge, there are no population-based estithe NIS data set has a discharge weight variable mates of outcomes in patients hospitalized for that researchers can use to produce nationally odontogenic infections in which investigators used representative estimates. nationally representative samples in the United Because this study was a secondary data States. Cohen and colleagues13 examined hospital analysis of hospital discharge data sets made admissions associated with nontrauavailable by AHRQ, we did not need matic dental emergencies. However, to obtain institutional review board The authors focused their sample was restricted to approval. One of us (Veerasathpuon three outcome patients enrolled in Medicaid. Pubrush Allareddy) obtained data from lished population-based data from AHRQ after completing the data variables: hospital England have helped to identify two user agreement with HCUP and charges, length of public health issues. First, a gradual conducted all data analyses. stay in the hospital increase in the number of episodes We selected for analysis all hosand type of admission of care for dental problems occurred pital discharges with a primary (emergency or urgent diagnosis code for periapical abscess through the National Health Service versus elective). (NHS) across the nine years of the (International Classification of Disstudy.14 Second, the investigators eases, Ninth Revision, Clinical Modalso found that children from low ification16 [ICD-9-CM] diagnosis socioeconomic areas had more episodes of care codes 522.5 [periapical abscess without sinus through the NHS than did those from high socioinvolvement] and 522.7 [periapical abscess with economic areas. sinus involvement]). Nationally representative population-based Outcome variables. In this study, we focused data could serve as benchmarks for future studies on three outcome variables: hospital charges, exploring longitudinal trends regarding hospitallength of stay in the hospital and type of admisizations for preventable conditions such as perision (emergency or urgent versus elective). We apical abscesses. Such data also could enable oral obtained information regarding the outcome varihealth care providers and policymakers to ables from the data set. Hospital charges (in dolexamine issues pertaining to access to medical lars) reflect the total amount that the hospital and dental care in hospitals and shape policies to charged to the patient and not the actual costs address these issues, as well as help identify the incurred by the hospital or the amount reimpopulation at higher risk of developing odontobursed to the hospital by a third-party payer. All genic infections severe enough to warrant hoshospital charges are in 2007 dollars. Length of pital admissions. stay refers to the number of days that a patient The objectives of this study were to document was in the hospital after admission. Admission the epidemiology of hospital admissions attribtype indicates the source of admission into the uted primarily to periapical abscesses in the hospital and is coded 1 (elective admission) or 0 United States, to examine outcomes including (emergency or urgent admission). hospital charges and length of stay and to identify factors that are associated with poor outcomes ABBREVIATION KEY. AHRQ: Agency for Healthcare among hospitalized patients. Research and Quality. HCUP: Healthcare Cost MATERIALS AND METHODS

Data source and patient selection. We used the Nationwide Inpatient Sample (NIS) of the 1108

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and Utilization Project. ICD-9-CM: International Classification of Diseases, Ninth Revision, Clinical Modification. NHS: National Health Service. NIS: Nationwide Inpatient Sample.

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R E S E A R C H

Independent variables. The independent using simple linear regression analysis, with logvariables included age; sex; periapical abscess transformed hospital charges as the outcome variwith or without sinus involvement; insurance able. We included in the final multivariable linear status (Medicare, Medicaid, private insurance regression model all of the comorbid conditions [including Blue Cross, commercial carriers, prithat were associated significantly with hospital vate health maintenance organizations and precharges at P < .05 in the simple linear regression ferred provider organizations], uninsured [selfanalysis. pay or no charge] and other insurance plans Association between length of stay and [including workers’ compensation, Civilian independent variables. We also used a multiHealth and Medical Program of the Uniformed variable linear regression analysis to examine the Services, Civilian Health and Medical Program association between length of stay (outcome variof the Department of Veterans Affairs, Title V able) and the independent variables (age, sex, and other government programs]); presence of periapical abscess with or without sinus involvecomorbid conditions, which we obtained from the ment, insurance status, presence of comorbid conNIS disease severity measurement ditions, type of admission and hosfiles; and disposition information pital characteristics). Because of Total hospital charges the skewed nature of the data, we (routine discharge versus others). for treating patients We also obtained information also log transformed the length-ofregarding hospital-related factors, stay data. We used the same anawith periapical such as teaching status (teaching or lytical approach for the multivariabscesses in U.S. nonteaching), location (rural or able linear regression analysis hospitals in 2007 urban), geographical region (Northexamining the association between were $105.8 million. east, Midwest, South or West) and length of stay and the independent bed size (that is, number of beds) variables as that used for the hos(small, medium or large).15 pital charges model. According to the NIS data set, a hospital was Association between type of admission and considered to be a teaching hospital if it had an independent variables. We used multivariable American Medical Association–approved residency logistic regression analysis to examine the assoprogram, was a member of the Council of Teaching ciation between type of admission (elective versus Hospitals or had a ratio of full-time–equivalent emergency or urgent) and the independent variinterns and residents to beds of 1:4 or higher.15 On ables (age, sex, periapical abscess with or without the basis of the total number of beds, geographical sinus involvement, insurance status, presence of location (urban or rural) and geographical region comorbid conditions [that is, all conditions that (Northeast, Midwest, South or West), AHRQ claswere associated significantly with type of admissified hospitals in the NIS data set as small, sion in the simple logistic regression analysis] medium or large.15 We obtained information and hospital characteristics). We computed the regarding these variables from the data set. odds of being admitted on an elective basis. Analytic approach. Association between We conducted all regression analyses using hospital charges and independent variables. statistical software (SAS-Callable SUDAAN, verWe used a multivariable linear regression sion 10.0.1, SAS Institute, Cary, N.C.). We comanalysis to examine the association between hosputed variances according to the Taylor linearizapital charges (outcome variable) and the indepention methods by using a “with replacement” dent variables (age, sex, periapical abscess with design. The NIS hospital stratum was the stratifior without sinus involvement, insurance status, cation unit, and each hospitalization was the unit presence of comorbid conditions, disposition inforof analysis. We used the discharge weight varimation, type of admission and hospital characterable to project national estimates. In all of the istics). Because the hospital charge data were models, we adjusted for the effects of clustering of highly skewed, we log transformed the data and outcomes within hospitals. used these log-transformed hospital charges as All statistical tests were two-sided, and we conthe outcome variable in the multivariable linear sidered P < .05 to be statistically significant. We regression model. The NIS data set provided performed all statistical analyses using statistical information regarding 28 comorbid conditions.15,17 software (SAS, version 9.2, and SAS-Callable We tested each comorbid condition bivariately by SUDAAN, SAS Institute). JADA 141(9)

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RESULTS

TABLE 1

Characteristics of hospitalizations. Tables 1 and 2 summarize the descriptive characteristics of hospitalizations that occurred primarily as a result of periapical abscesses. In 2007, 7,886 hospitalizations were attributed primarily to periapical abscess. Of these, 213 (2.69 percent) involved sinus formation. Because 10 of the 40 participating states did not provide information regarding race, these data were not available for 2,327 hospitalizations. Among hospitalizations for which information regarding race was available, 61.44 percent occurred among whites, 20.07 percent among African-Americans, 13.01 percent among Hispanics, 1.27 percent among Asian/ Pacific Islanders, 0.44 percent among American Indians and 3.77 percent among patients of other races. Factors associated with hospital charges. Total hospital charges for treating patients with periapical abscesses in U.S. hospitals were $105.8 million in 2007 dollars. Mean charges per hospitalization were $13,590. Table 3 (page 1112) summarizes the results of the 1110

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Characteristics of hospitalizations attributed primarily to periapical abscess in 2007.* CHARACTERISTIC

NO. (%) OF HOSPITALIZATIONS (N = 7,886)

Patient’s Sex Male Female Missing data

3,654 (46.7) 4,178 (53.3) 54

Primary Diagnosis Periapical abscess without sinus involvement Periapical abscess with sinus involvement

7,673 (97.3) 213 (2.7)

Type of Admission Emergency or urgent Elective Missing data

7,141 (90.9) 715 (9.1) 30

Insurance Status Medicare Medicaid Private insurance Uninsured Other insurance plans Missing data

1,460 (18.6) 1,812 (23.1) 2,488 (31.6) 1,684 (21.4) 417 (5.3) 25

Disposition of Patient’s Discharge Routine Transfer to another acute care hospital Transfer to skilled nursing facility, intermediate care facility or another type of facility Home health care Discharged against medical advice, patient died in hospital or discharged but destination unknown†

7,244 (91.9) 98 (1.2) 252 (3.2) 187 105

(2.4) (1.3)

Race White African-American Hispanic Asian/Pacific Islander American Indian Other Missing data

3,416 (61.4) 1,116 (20.1) 723 (13.0) 70 (1.3) 24 (0.4) 210 (3.8) 2,327

Presence of Comorbid Condition ‡ AIDS Alcohol abuse Deficiency anemias Rheumatoid arthritis/collagen vascular diseases Chronic blood loss anemia Congestive heart failure Chronic pulmonary disease Coagulopathy Depression Diabetes, uncomplicated Diabetes with chronic complications Drug abuse Hypertension Hypothyroidism Liver disease Lymphoma Metabolic (fluid and electrolyte) disorders Metastatic cancer Neurological disorders Obesity Paralysis Peripheral vascular disorders Psychoses Pulmonary circulation disorders Renal failure Solid tumor without metastasis Valvular disease Weight loss

57 117 549 124 27 218 828 160 552 965 153 250 1,942 432 115 64 916 53 404 432 112 69 256 41 273 79 236 72

(0.7) (1.5) (7.0) (1.6) (0.3) (2.8) (10.5) (2.0) (7.0) (12.2) (1.9) (3.2) (24.6) (5.5) (1.5) (0.8) (11.6) (0.7) (5.1) (5.5) (1.4) (0.9) (3.2) (0.5) (3.5) (1.0) (3.0) (0.9)

* Source: Agency for Healthcare Research and Quality.15 † There were 10 or fewer hospitalizations for each of these discharges. Because the Healthcare Cost and Utilization Project data user agreement precludes presentation of these estimates, they were combined into one group. ‡ Numbers total more than 7,886 because a hospitalization could involve more than one comorbid condition.

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R E S E A R C H

associated significantly with increased hospital charges (P < .05). Factors assoHospital Teaching Status ciated with length Nonteaching 4,082 (51.8) of stay. The total Teaching 3,794 (48.2) Missing data 10 length of stay for all Hospital Location hospitalizations was Rural 1,251 (15.9) 23,001 days. The Urban 6,625 (84.1) Missing data 10 mean length of stay Hospital Bed Size per hospitalization Small 1,030 (13.1) was 2.92 days. Table 4 Medium 1,921 (24.4) Large 4,925 (62.5) (page 1113) provides a Missing data 10 summary of the Region of Country results of the multiNortheast 1,695 (21.5) Midwest 1,865 (23.6) variable linear regresSouth 3,187 (40.4) sion analysis for West 1,139 (14.4) length of stay. The TABLE 2 significant predictors Characteristics of hospitalizations attributed primarily of length of stay included periapical to periapical abscess in 2007. abscess with sinus CHARACTERISTIC MEAN (SEM*) 25TH MEDIAN 75TH involvement, routine PERCENTILE PERCENTILE discharge, age and Patient’s Age in Years 37.52 (0.88) 21.37 36.05 50.83 presence of comorbid Hospital Charges in 2007 13,590 (531.55) 5,958 9,748 15,978 conditions. Patients Dollars who were hospitalized Length of Hospital Stay 2.92 (0.06) 1.09 1.88 3.02 in Days for periapical abscess with sinus involveNo. of Procedures Performed 1.07 (0.05) 0 0.18 1.38 During Hospitalization ment had a longer * SEM: Standard error of the mean. stay than did patients without sinus involvemultivariable linear regression analysis for hospital ment. Patients who received a routine discharge charges. The significant predictors of hospital from the hospital had a shorter stay compared charges included the patient’s age and presence of with that for patients who received other types of comorbid conditions. Each one-year increase in discharges. Each one-year increase in the age was associated with a $39 increase in hospital patient’s age was associated with a longer stay. charges (P = .042). In the bivariate simple linear regression In the bivariate regression analysis in which we analysis, 16 of the 28 comorbid conditions were examined the independent association between hosassociated significantly with length of stay in the pital charges and presence of comorbid conditions, hospital. After we adjusted for other independent 18 of the 28 comorbid conditions were associated variables in the multivariable linear regression significantly with higher hospital charges compared analysis, we found that only hospitalizations with charges for hospitalizations that did not involving deficiency anemias, chronic pulmonary involve these conditions (P < .05). However, after disease, fluid and electrolyte disorders, valvular we adjusted for the simultaneous effects of other disease or weight loss were associated with longer independent variables, the results show that only hospital stays. 12 conditions (deficiency anemias, rheumatoid Factors associated with elective admisarthritis and collagen vascular diseases, chronic sions. Table 5 (page 1114) summarizes the blood loss anemia, congestive heart failure, chronic results of the multivariable logistic regression pulmonary disease, coagulopathy, hypertension, analysis for type of hospital admission. A lack of metabolic disorders, metastatic cancer, neurological insurance was associated with lower odds of disorders, valvular diseases and weight loss) were being admitted on an elective basis compared TABLE 1 (CONTINUED)

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TABLE 3

Multivariable linear regression analysis of characteristics associated with hospital charges.*† CHARACTERISTIC

BETA COEFFICIENT (95% CI‡)

CHANGE FROM MEAN (%)

CHANGE FROM MEAN ($)

P VALUE

−0.0122 (−0.0861 - 0.0616)

−1.2

−165

.745

Reference







0.1578 (−0.0628 - 0.3784)

17.1

2,323

.160

Reference







Type of Admission Elective

−0.0122 (−0.1357 - 0.1113)

−1.2

−165

.846

Emergency or urgent

Reference







Insurance Status Medicare

−0.1139 (−0.2491 - 0.0213)

−10.8

−1,463

.098

Medicaid

−0.0619 (−0.1873 - 0.0635)

−6.0

−816

.332

Uninsured

0.0406 (−0.0758 - 0.1570)

4.1

563

.493

0.106 (−0.0932 - 0.3051)

11.2

1,520

.296

Reference







−0.0704 (−0.2340 - 0.0932)

−6.8

−924

.398

Reference







Presence of Comorbid Condition Deficiency anemias

0.2534 (0.1055 - 0.4012)

28.8

3919

< .008§

Rheumatoid arthritis/collagen vascular diseases

0.3077 (0.0015 - 0.6139)

36.0

4,896

.048§

Chronic blood loss anemia

0.7889 (0.2271 - 1.3507)

120.1

16,321

.006§

Congestive heart failure

0.3212 (0.0797 - 0.5626)

37.9

5,148

.009§

Chronic pulmonary disease

0.1662 (0.0495 - 0.2829)

18.1

2,457

.005§

Patient’s Sex Female Male Primary Diagnosis Periapical abscess with sinus involvement Periapical abscess without sinus involvement

Other insurance plans Private insurance Disposition of Patient’s Discharge Routine Other type

0.4441 (0.1692 - 0.7189)

55.9

7,598

.002§

Diabetes, uncomplicated

0.0476 (−0.0744 - 0.1697)

4.9

662

.444

Drug abuse

0.1401 (−0.1033 - 0.3835)

15.0

2,044

.258

0.1036 (0.0014 - 0.2058)

10.9

1,483

.046§

Hypothyroidism

0.1015 (−0.0701 - 0.2731)

10.7

1,452

.245

Liver disease

0.1157 (−0.2257 - 0.4572)

12.3

1,667

.506

Metabolic (fluid and electrolyte) disorders

0.1834 (0.0697 - 0.2972)

20.1

2,736

.002§

Metastatic cancer

0.5075 (0.0093 - 1.0056)

66.1

8,984

.045§

Neurological disorders

0.3081 (0.1484 - 0.4678)

36.1

4,904

< .002§

Pulmonary circulation disorders

0.1703 (−0.2148 - 0.5553)

18.6

2,523

.385

Solid tumor without metastasis

0.286 (−0.0477 - 0.6197)

33.1

4,499

.092

Valvular disease

0.2716 (0.0323 - 0.5108)

31.2

4,241

.026§

Weight loss

0.4887 (0.0581 - 0.9194)

63.0

8,564

.026§

Age in Years (One-Year Increase)

0.0029 (0.0001 - 0.0057)

0.3

39

.042§

Coagulopathy

Hypertension

* † ‡ §

The outcome variable is log-transformed hospital charges. The effective sample size (number of hospitalizations) for the multivariable linear regression model is 7,613. CI: Confidence interval. Statistically significant at P < .05 (two sided).

with the odds for patients with private insurance coverage, even after we adjusted for patient-related and hospital-related confounding factors. In the simple logistic regression analyses, eight of the 28 comorbid conditions were associated significantly with type of admission. In the multivariable logistic regression 1112

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analysis, after we adjusted for other factors, coagulopathy, peripheral vascular disease and valvular disease were associated significantly with being hospitalized on an elective basis. Sensitivity analysis. The NIS data set did not provide information about race for almost 30 percent of all hospital discharges. In the sensi-

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R E S E A R C H

TABLE 4

Multivariable linear regression analysis of characteristics associated with length of hospital stay.*† CHARACTERISTIC

BETA COEFFICIENT (95% CI‡)

CHANGE FROM MEAN (%)

CHANGE FROM MEAN (DAYS)

P VALUE

0.0363 (−0.0216 - 0.0942)

3.7

0.11

.218

Reference







0.1877 (0.0011 - 0.3744)

20.7

0.60

.049§

Reference







Type of Admission Elective

−0.0134 (−0.1174 - 0.0906)

−1.3

−0.04

.800

Emergency or urgent

Reference







Patient’s Sex Female Male Primary Diagnosis Periapical abscess with sinus involvement Periapical abscess without sinus involvement

Insurance Status Medicare

−0.0099 (−0.1132 - 0.0935)

−1.00

−0.03

.851

Medicaid

0.0648 (−0.0247 - 0.1543)

6.7

0.19

.155

Uninsured

0.0476 (−0.0333 - 0.1285)

4.9

0.14

.248

Other insurance plans

0.0827 (−0.0646 - 0.2300)

8.6

0.25

.270

Reference







−0.1812 (−0.3092 - 0.0532)

−16.6

−0.48

.006§

Reference







Private insurance Disposition of Patient’s Discharge Routine Other type Presence of Comorbid Conditions Deficiency anemias

0.1723 (0.0379 - 0.3068)

18.8

0.55

.012§

Rheumatoid arthritis/collagen vascular diseases

0.1541 (−0.0896 - 0.3977)

16.7

0.49

.215

Chronic blood loss anemia

0.6246 (−0.0253 - 1.2745)

86.8

2.53

.06

Congestive heart failure

0.0931 (−0.1067 - 0.2929)

9.8

0.28

.360

0.1078 (0.0087 - 0.2069)

11.4

0.33

.033§

Coagulopathy

0.1860 (−0.0595 - 0.4315)

20.4

0.60

.137

Depression

0.1126 (−0.0172 - 0.2423)

11.9

0.35

.089

−0.0254 (−0.1155 - 0.0646)

−2.5

−0.07

.579

0.0853 (−0.0460 - 0.2167)

8.9

0.26

.202

0.1864 (0.0834 - 0.2893)

20.5

0.60

< .004§

Metastatic cancer

0.4580 (−0.0612 - 0.9772)

58.1

1.70

.084

Neurological disorders

0.1511 (−0.0099 - 0.3121)

16.3

0.48

.066

Pulmonary circulation disorders

0.3994 (−0.2494 - 1.0482)

49.1

1.43

.227

Renal failure

0.0308 (−0.1289 - 0.1906)

3.1

0.09

.704

Valvular disease

0.2779 (0.0881 - 0.4677)

32.0

0.93

.004§

Weight loss

0.5656 (0.2525 - 0.8788)

76.1

2.22

< .004§

Age in Years (One-Year Increase)

0.0025 (0.0004 - 0.0046)

0.3

0.007

.018§

Chronic pulmonary disease

Hypertension Hypothyroidism Metabolic (fluid and electrolyte) disorders

* † ‡ §

The outcome variable is log-transformed hospital charges. The effective sample size (number of hospitalizations) for the multivariable linear regression model is 7,513. CI: Confidence interval. Statistically significant at P < .05 (two sided).

tivity analysis in which we included race in the multivariable models, race was not associated significantly with outcomes, including hospital charges, length of stay and admission type. DISCUSSION

This study provides nationally representative data regarding U.S. hospitalizations attributed

primarily to periapical abscess. Although several single-center studies have examined outcomes during hospitalizations for odontogenic infections,6,8,10-12 this is the first study, to our knowledge, to use a nationally representative sample to examine hospitalization outcomes and to document resource utilization involved in treating patients with periapical abscess. We focused on JADA 141(9)

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sequently, the overall economic burden associated with periapical abscesses Multivariable logistic regression analysis likely is substantial. of characteristics associated with type Comorbidity and disease of admission.*† severity. As expected, the results of our study revealed that hospital CHARACTERISTIC ODDS RATIO P VALUE (95% CI‡) charges and length of stay increased Patient’s Sex with increasing comorbid burden. More Female 1.13 (0.77 - 1.65) .527 severe comorbid conditions require Male Reference — more resources to treat, and this is Primary Diagnosis reflected in the higher hospital charges Periapical abscess with sinus involvement 2.12 (0.99 - 4.52) .051 and longer hospital stays. These results Periapical abscess without sinus involvement Reference — are consistent with those of several Insurance Status studies in which investigators used the Medicare 1.56 (0.90 - 2.69) .113 Medicaid 0.63 (0.38 - 1.04) .068 same data set to examine outcomes Uninsured 0.49 (0.28 - 0.87) .016§ after hospitalization for a wide specOther insurance plans 0.59 (0.23 - 1.50) .266 trum of medical conditions and surgical Private insurance Reference — procedures.17-20 Presence of Comorbid Conditions In our study, routine discharge was Congestive heart failure 1.12 (0.43 - 2.92) .820 Chronic pulmonary disease 1.34 (0.80 - 2.22) .261 associated significantly with a shorter Coagulopathy 4.53 (1.74 - 11.79) .002§ length of stay compared with that for Hypertension 0.83 (0.54 - 1.29) .406 patients transferred to long-term faciliNeurological disorders 1.46 (0.75 - 2.84) .270 ties or other short-term acute care facilParalysis 2.33 (0.89 - 6.15) .086 Peripheral vascular disorders 4.13 (1.22 - 14.01) .023§ ities. It is likely that patients who were Valvular disease 2.90 (1.25 - 6.77) .014§ discharged on a routine basis had less Age in Years (One-Year Increase) 1.00 (0.99 - 1.01) .758 severe illness, which enabled them to be discharged earlier than other * The outcome variable is the odds of being hospitalized on an elective basis. † The effective sample size (number of hospitalizations) for the multivariable logistic patients. Increasing age also was assoregression model is 7,703. ciated with a longer stay in the hos‡ CI: Confidence interval. § Statistically significant at P < .05 (two sided). pital. It is likely that older patients had more comorbid conditions or a more three outcome measures: hospital charges, length severe case of periapical abscess that contributed of stay and type of admission (emergency or urgent to their longer hospital stay. As expected, disversus elective). The results of this study suggest charges of patients who had periapical abscess that substantial resources are required to treat with sinus involvement were associated with a patients with periapical abscess. longer hospital stay compared with that assoEconomic burden. The study results reflect ciated with discharges of patients who had perithe charges levied by the hospitals, not the apical abscess without sinus involvement. actual costs incurred by them. Actual hospital Most of the hospitalizations in our study costs may be much less. However, we should note occurred on an emergency or urgent basis. This that although our data set captured charges was particularly pronounced in patients who did associated with hospitalizations, it did not pronot have insurance coverage. These findings sugvide information about money spent on medicagest that this population could be facing barriers tions, outpatient care, postdischarge care and to obtaining routine dental care and that the disother costs involved with treating periapical ease progressed enough to warrant admission to abscess or underlying dental conditions. In addithe hospital on an emergency or urgent basis. tion, the indirect costs associated with seeking However, further empirical support for this possicare (for example, travel costs) and work days bility is needed. These results are consistent with lost because of hospitalization may be substanthose of a study8 in which investigators reported tial for the patient. Nationwide estimates from that uninsured patients were more likely than our study suggest that hospitalizations due to others to seek admission to the hospital system periapical abscesses accounted for 23,001 hospithrough the emergency department for several talization days in the United States in 2007. Conconditions.

TABLE 5

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Policy implications. These findings have several policy implications. The results highlight the substantial financial burden associated with periapical abscesses, which can be prevented by routine, periodic dental care. Furthermore, the findings shed light on the uninsured population, which is at a higher risk of seeking admission into hospitals on an emergency or urgent basis, and on those (elderly patients and patients with comorbid conditions) who are associated with poorer outcomes. Educational interventions highlighting the critical importance of maintaining good oral health should be targeted toward these segments of the population. Treatment in dental offices. Finally, these findings suggest that practitioners can manage the care of patients with periapical abscesses in a dental office at a lower cost (endodontic treatment or extraction) than that incurred through hospitalization. The American Dental Association’s 2007 Survey of Dental Fees7 reported that the mean cost of endodontic treatment by an endodontist was $1,041 and the mean cost of surgical extraction of an erupted tooth by an oral surgeon was $232. We need to keep in mind, however, that hospitalized patients may have a more severe condition than that of patients treated in a dental office. The differences in costs between those in dental office settings and those in hospitals could be attributed in part to this difference. In addition, the increased risk to patients who receive treatment for peripical abscess in a hospital, such as infection, and the increased need for advanced antibiotic therapy and surgery relative to those for patients treated in a dental office could lead to higher costs in hospitals. Study limitations. Because we used hospital discharge data, our analysis has several shortfalls, and readers should keep this in mind when interpreting the study results.21-26 We identified hospitalizations attributed primarily to periapical abscesses by using ICD-9-CM codes. The actual severity of the condition, the extent of spread of infection and the number of teeth involved are not captured in our data set. It is reasonable to assume that patients with more severe conditions require more resource utilization. The multivariable analyses we used to examine predictors of outcomes do not control for these effects. However, the global estimates of the total hospitalization charges and length of stay are not affected by the lack of these data. Periapical abscesses warranting a patient’s admission into the hospital

likely are the most severe cases and, thus, are not representative of most cases of the condition, which are more likely to be treated in a dental office. Consequently, the outcome estimates of our study reflect the most severe cases. As alluded to earlier, our data set did not provide information about the postdischarge status of participants, and, hence, we were not able to present any posthospitalization follow-up data. With regard to comorbid conditions, we adjusted only for those 28 conditions identified by the software algorithm provided by the HCUP. There could be other comorbid conditions that influence outcomes and these would not have been accounted for in our study. The hospital charge and length of stay data were highly skewed. Even though we attempted to address this issue by log transforming the data, our results should be interpreted with caution. The NIS does not provide information regarding outpatient charges and other costs. Consequently, we were unable to compare inpatient charges with outpatient charges in this study. Thus, the charges we presented could be an underestimate of the actual economic burden associated with treating periapical abscess in hospitals. We used the patient’s primary insurance payer as one of the independent variables. Many older patients with Medicare coverage likely also have supplementary insurance coverage through Medicaid or private insurance plans. This could influence hospital charges and length of stay substantially. When we examined secondary payers in the data set, only 1,867 discharges included information regarding a secondary payer. Had we included secondary payers in the regression models, the sample size would have been decreased greatly. As a result, we did not include secondary payers in the regression analyses, and readers should interpret these results with caution. CONCLUSIONS

The results of this study provide nationally representative estimates of hospitalization charges and length of stay associated with hospitalizations attributed primarily to periapical abscess in the United States during 2007. More than 90 percent of the hospitalizations occurred on an emergency or urgent basis, and this finding was more pronounced among patients who were uninsured. Several comorbid conditions were associated significantly with increased hospital charges and longer hospital stay. This study highlights the JADA 141(9)

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substantial resources used to treat patients hospitalized for periapical abscess. Health care policymakers and providers must focus on implementing programs to educate the public about the importance of seeking routine, periodic dental care and must make efforts to minimize barriers to seeking and obtaining dental care. ■ Disclosure. None of the authors reported any disclosures. 1. Ferrera PC, Busino LJ, Snyder HS. Uncommon complications of odontogenic infections. Am J Emerg Med 1996;14(3):317-322. 2. Flynn TR. Surgical management of orofacial infections. Atlas Oral Maxillofac Surg Clin North Am 2000;8(1):77-100. 3. Flynn TR. The swollen face: severe odontogenic infections. Emerg Med Clin North Am 2000;18(3):481-519. 4. van Merkesteyn JP, Groot RH, van den Akker HP, Bakker DJ, Borgmeijer-Hoelen AM. Treatment of chronic suppurative osteomyelitis of the mandible. Int J Oral Maxillofac Surg 1997;26(6):450-454. 5. Dahlén G. Microbiology and treatment of dental abscesses and periodontal-endodontic lesions. Periodontol 2000 2002;28:206-239. 6. Seppänen L, Lauhio A, Lindqvist C, Suuronen R, Rautemaa R. Analysis of systemic and local odontogenic infection complications requiring hospital care. J Infect 2008;57(2):116-122. 7. American Dental Association. 2007 Survey of Dental Fees. Chicago: American Dental Association Survey Center. September 2007. 8. Flynn TR, Shanti RM, Hayes C. Severe odontogenic infections, part 2: prospective outcomes study. J Oral Maxillofac Surg 2006;64(7): 1104-1113. 9. Flynn TR, Shanti RM, Levi MH, Adamo AK, Kraut RA, Trieger N. Severe odontogenic infections, part 1: prospective report. J Oral Maxillofac Surg 2006;64(7):1093-1103. 10. Peters ES, Fong B, Wormuth DW, Sonis ST. Risk factors affecting hospital length of stay in patients with odontogenic maxillofacial infections. J Oral Maxillofac Surg 1996;54(12):1386-1391; discussion 1391-1392. 11. Wang J, Ahani A, Pogrel MA. A five-year retrospective study of odontogenic maxillofacial infections in a large urban public hospital. Int J Oral Maxillofac Surg 2005;34(6):646-649.

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12. Zeng Y, Sheller B, Milgrom P. Epidemiology of dental emergency visits to an urban children’s hospital. Pediatr Dent 1994;16(6):419-423. 13. Cohen LA, Magder LS, Manski RJ, Mullins CD. Hospital admissions associated with nontraumatic dental emergencies in a Medicaid population. Am J Emerg Med 2003;21(7):540-544. 14. Moles DR, Ashley P. Hospital admissions for dental care in children: England 1997-2006. Br Dent J 2009;206(7):E14; discussion 378-379. 15. Agency for Healthcare Research and Quality. Healthcare Cost and Utilization Project (HCUP), Nationwide Inpatient Sample (NIS), Year 2007 Documentation. “www.hcup-us.ahrq.gov/databases.jsp”. Accessed Aug. 10, 2010. 16. ICD9.chrisendres.com. Diseases of oral cavity, salivary glands and jaws (520-529). “www.icd9.chrisendres.com/index.php?action= child&recordid=5165”. Accessed Aug. 4, 2010. 17. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care 1998;36(1):8-27. 18. Allareddy V, Konety BR. Characteristics of patients and predictors of in-hospital mortality after hospitalization for head and neck cancers. Cancer 2006;106(11):2382-2388. 19. Ludbrook JJ, Truong PT, MacNeil MV, et al. Do age and comorbidity impact treatment allocation and outcomes in limited stage smallcell lung cancer? A community-based population analysis. Int J Radiat Oncol Biol Phys 2003;55(5):1321-1330. 20. Shwartz M, Iezzoni LI, Moskowitz MA, Ash AS, Sawitz E. The importance of comorbidities in explaining differences in patient costs. Med Care 1996;34(8):767-782. 21. Iezzoni LI. Using administrative diagnostic data to assess the quality of hospital care: pitfalls and potential of ICD-9-CM. Int J Technol Assess Health Care 1990;6(2):272-281. 22. Iezzoni LI. Risk adjustment for medical effectiveness research: an overview of conceptual and methodological considerations. J Investig Med 1995;43(2):136-150. 23. Iezzoni LI. Assessing quality using administrative data. Ann Intern Med 1997;127(8 pt 2):666-674. 24. Iezzoni LI. The risks of risk adjustment. JAMA 1997;278(19): 1600-1607. 25. Iezzoni LI, ed. Risk Adjustment for Measuring Health Care Outcomes. 3rd ed. Chicago: Health Administration Press; 2003. 26. Iezzoni LI, Foley SM, Daley J, Hughes J, Fisher ES, Heeren T. Comorbidities, complications, and coding bias: does the number of diagnosis codes matter in predicting in-hospital mortality? JAMA 1992; 267(16):2197-2203.

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