To characterize gout-related emergency department (ED) utilization using a nationally representative sample and to examine factors associated with the frequency and charges of gout-related ED visits.
To characterize gout-related emergency department (ED) utilization using a nationally representative sample and to examine factors associated with the frequency and charges of gout-related ED visits.
Using the National Emergency Department Sample data from 2006–2008, the weighted national frequency of gout visits was calculated along with the median ED charge and total national ED-related charges. Associations of several patient- and facility-level factors were examined with the occurrence of gout visits using multivariable logistic regression and with ED-related charges using multivariable linear regression.
Gout was the primary indication for 168,410 ED visits in 2006, 171,743 visits in 2007, and 174,823 visits in 2008, accounting for ∼0.2% of all visits annually and generating ED charges of more than $128 million in 2006, $144 million in 2007, and $166 million in 2008. Age, male sex, household income <$39,000, private insurance, and hospital locations in nonmetropolitan areas and the southern US were associated with an increased propensity for ED utilization in gout. Higher ED-related charges for gout were associated with female sex, age, a higher number of coded diagnoses, and a metropolitan residence.
Gout accounts for a substantial proportion of ED visits, leading to significant health care charges. Effective strategies to reduce gout burden in EDs could potentially benefit by targeting groups characterized by factors demonstrated to be related to a higher ED utilization in gout as identified by our study.
Gout affects approximately 4% of the US population, representing one of the most common forms of inflammatory arthritis affecting adults (1). With a frequency that continues to increase worldwide, the prevalence of gout is now estimated to be as high as 12–13% among individuals ≥80 years of age (1). With the disease frequency nearly doubling over the last few decades alone (1, 2), gout represents a major, growing health burden, recognizing its well-defined detrimental impact on several outcome domains, including patient morbidity, work-related disability, productivity loss, mortality, and rising health care costs (3–6). In a recent study by Wu et al, elderly gout patients were observed to have substantially higher health care utilization than elderly patients without gout (7). Moreover, it was estimated that gout-related costs account for 6% of all health care costs among elderly patients with the condition (7). With a rapidly aging population and an increasing incidence of disease-related risk factors, the burden posed by gout will continue to grow in the coming years.
Often characterized by acute flares of intense inflammatory arthritis, gout is speculated to account for a substantial number of ambulatory health care visits in the US and, in particular, visits to emergency departments (EDs) (8). This is highly salient, since ED visits often serve as a “bellwether” of performance in other sectors of the health care system. For example, suboptimal care related to either poor health care access or the delivery of low-quality care may reveal itself through increased ED utilization for the receipt of otherwise nonurgent or preventable care (9, 10). This may be particularly relevant to gout, a condition that has too often been characterized by suboptimal health care quality (11, 12) and disease flares that are often preventable with effective urate-lowering treatment and antiinflammatory prophylaxis (13, 14). To date, we are unaware of any comprehensive studies examining the overall frequency and factors related to gout-related ED utilization and charges in the US. The present study was undertaken to characterize gout-related ED utilization using a nationally representative sample and to examine factors independently associated with the frequency of gout-related visits and corresponding health care charges from 2006 through 2008.
This is among the first comprehensive efforts to examine the frequency and correlates of gout care in US emergency departments.
This study identifies several patient- and system-level factors associated with gout visits in addition to identifying correlates of total charges generated for visits.
The present study capitalized on annual data from the Nationwide Emergency Department Sample (NEDS) from the years 2006, 2007, and 2008 (15–17). The NEDS is part of the Healthcare Cost and Utilization Project (HCUP) sponsored by the US Agency for Healthcare Research and Quality (AHRQ); it contains event-level data but not unique identifiers so that individuals may be represented by multiple visits in any given year. The NEDS tracks ED visits from across the US and includes detailed characteristics of the patient (sex, age, insurance status, urban/rural designation of residence, total number of coded diagnoses for a given visit, and annual median income estimated using zip code of residence), the treating hospital (geographic region, metropolitan or nonmetropolitan, teaching versus nonteaching), and the nature of the ED visits (diagnoses and procedures performed). The NEDS also includes data specific to the total ED/inpatient charges generated for a given visit, although the NEDS does not contain data pertinent to direct or indirect health care costs. For each visit, up to 15 diagnostic codes are entered into the NEDS using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and up to 9 ICD-9-CM procedures and up to 15 additional procedures coded using Current Procedural Terminology. The NEDS is constructed using a 20% stratified sample of US EDs, allowing for the generation of precise national estimates both in terms of the indication for the ED visit (frequency of gout visits) and total corresponding ED-related charges.
The NEDS is a publicly available all-payer ED database that at the time of this analysis included data from between 24 (2006) and 28 (2008) partnering US states that provide data directly to the HCUP. The NEDS includes data from more than 26 million records annually from ED visits from at least 950 hospitals across the US. National estimates were generated using discharge weights, allowing for detailed descriptions of more than 120 million ED visits occurring in the US annually. For this study, we limited analyses to the ED visits of patients ages ≥18 years. Visits were categorized as 1) those with gout coded as the primary diagnosis, 2) those with gout coded as a secondary diagnosis, and 3) those without a gout code either as a primary or secondary diagnosis.
The discharge weights defined in the NEDS data were used as the sample weights in the data analysis to obtain national estimates. The discharge weights were calculated by poststratification based on the ratio of the number of ED visits from hospitals in the American Hospital Association universe compared to the adjusted number of ED visits in the sample hospitals. The sample weighted national frequencies of gout visits were calculated for each year of followup (2006 through 2008) along with corresponding median ED charges and total national ED-related charges. Frequencies and charges for ED visits without gout and those with gout codes as a secondary diagnosis were also calculated. To mitigate bias from missing data, estimates for the total charges were generated using the product of the number of cases and the average ED charge. National estimates of the total number of primary gout- and nongout-related visits within several categorical divisions defined by the AHRQ (female sex, income bracket, urban/rural residence, and insurance status) were also calculated and adjusted slightly. The purpose of this adjustment was to ensure that the estimated percentage of total visits within each category matched the estimate of the percentage of visits within each category obtained from only the nonmissing cases. The assumption here was that information on sex, income, urban/rural residence, and insurance status would be missing in equal proportions of gout- and nongout-related visits.
To identify factors associated with gout-related ED visits relative to other indications, subsequent analyses were limited to data from ED visits in which gout (ICD-9-CM code 274.xx) was the primary coded diagnosis and visits for which gout was not provided as a primary or secondary diagnosis, with the latter group serving as the referent group. Multivariable logistic regression was used to examine the associations of the aforementioned patient- and facility-level characteristics, with the likelihood of a given visit resulting in gout being listed as the primary diagnosis. Multivariable linear regression was used to examine the associations of these same characteristics with ED-related charges. Categorical variables were modeled using “dummy” variables with a referent category. The focus of this latter analysis was to identify patient-level factors independently associated with ED charge, adjusting for facility-level characteristics. To account for the hierarchical data structure, all analyses accounted for clustering by the participating facility and assumed only one ED visit per unique individual annually. All analyses were completed using the SURVEYMEANS, SURVEYFREQ, SURVEYREG, and SURVEYLOGISTIC procedures in SAS, version 9.2, to account for the complex sampling design of the NEDS.
The frequency and charges secondary to ED-related gout visits, from the years 2006 through 2008, are shown in Table 1. Of the more than 280 million ED visits occurring during this timeframe, >2 million visits (0.7%) included gout as either a primary or secondary diagnosis. Gout served as the primary indication for 168,410 ED visits in 2006, 171,743 visits in 2007, and 174,823 visits in 2008, accounting for ∼0.2% of all ED visits annually. The median charge per ED visit with gout as the primary diagnosis in 2006 was $540, accounting for a total of more than $128 million in health care charges. By 2008, the median charge per ED visit with gout as the primary diagnosis increased to $667 per visit, accounting for more than $166 million in health care charges. In general, ED-related visit charges were lower for visits in which gout was the primary diagnosis compared to visits in which gout was coded as a secondary diagnosis or visits in which gout was not coded as a diagnosis. The proportional increase in the median primary gout-related ED charge observed from 2006 through 2008 (24% increase) was similar to that observed for nongout visits over the same timeframe (27% increase).
|Total visits, no. (% of all visits)||168,410 (0.2)||171,743 (0.2)||174,823 (0.2)|
|Median (IQR)||$540 ($309–935)||$608 ($350–1,016)||$667 ($387–1,143)|
|Total visits, no. (% of all visits)||448,885 (0.5)||502,479 (0.5)||574,767 (0.6)|
|Median (IQR)||$960 ($564–1,549)||$1,004 ($594–1,649)||$1,187 ($721–1,928)|
|Total visits, no. (% of all visits)||92,989,246 (99.3)||94,693,342 (99.3)||97,766,093 (99.2)|
|Median (IQR)||$842 ($421–1,670)||$928 ($483–1,861)||$1,068 ($554–2,116)|
Gout-related ED visits were most commonly coded as level 2 (∼15–16% of the total visits with gout as the primary diagnosis) and level 3 (∼22–28%) encounters (data not shown). Diagnostic and/or therapeutic procedures coded in >10% of all primary gout-related ED visits in 2008 included serum urate measurement (coded in 16% of gout visits in 2008), therapeutic injection or infusion (13% of visits), complete blood count measurement (13% of visits), and venipuncture for collection of venous blood (11% of visits). Coded procedures in 2006 and 2007 were similar in frequency (data not shown).
Patient and hospital characteristics for gout (primary diagnostic code) and nongout ED visits in 2008 are shown in Table 2. Visit-related characteristics for 2006 and 2007 were similar (data not shown). Compared to ED visits for nongout diagnoses and consistent with known gout epidemiology, gout-related ED visits more commonly involved men and were more frequent with each additional year of age. Other patient-level factors independently associated with gout visits (versus nongout visits) included residence in a zip code with a lower median income, a lower total number of coded diagnoses, and the presence of Medicare or other types of insurance. After adjusting for confounders such as older age, Medicare was less likely to be the expected payer for gout visits than nongout visits referent to private insurance (odds ratio [OR] 0.77; 95% confidence interval [95% CI] 0.73, 0.80) (Table 2). In other words, referent to those with private insurance, patients with Medicare were 23% less likely to visit the ED for gout than for a nongout indication, after adjusting for multiple other patient- and facility-level factors. Hospital characteristics associated with an increased frequency of gout-related ED visits in 2008, compared to ED visits related to a nongout-related diagnosis, included a location in the southern US (OR 1.54; 95% CI 1.38, 1.71 versus the western region) and a rural/micropolitan facility (typically defined as an urban core of <50,000 people; OR 0.86 [95% CI 0.77, 0.95] for a metropolitan facility referent to a micropolitan/nonmetropolitan area) (Table 2).
|Gout, primary (n = 174,823)||Other diseases (n = 97,766,093)||Multivariable association of factor with gout visit vs. nongout visit, OR (95% CI)|
|Women, no. (%)||39,160 (22.4)||56,019,971 (57.3)||0.21 (0.20, 0.22)†|
|Age, mean ± SD years||54.8 ± 0.16||46.6 ± 0.15||1.03 (1.03, 1.04)†|
|Household income, no. (%)|
|<$39,000||64,685 (37.0)||30,796,319 (31.5)||Referent|
|$39,000–48,999||49,475 (28.3)||29,232,062 (29.9)||0.81 (0.77, 0.86)†|
|$49,000–63,999||33,216 (19.0)||20,824,178 (21.3)||0.79 (0.74, 0.85)†|
|≥$64,000||27,272 (15.6)||16,815,768 (17.2)||0.75 (0.69, 0.82)†|
|No. of coded diagnoses, mean ± SD||3.2 ± 0.05||3.9 ± 0.04||0.87 (0.86, 0.88)†|
|Urban/rural residence, no. (%)|
|Micropolitan/not metropolitan||44,230 (25.3)||20,042,049 (20.5)||Referent|
|Metropolitan (large or small)||130,593 (74.7)||77,724,044 (79.5)||1.04 (0.97, 1.11)‡|
|Insurance status, no. (%)|
|Private, including HMO||57,692 (33.0)||32,458,343 (33.2)||Referent|
|Medicare||58,915 (33.7)||25,125,886 (25.7)||0.77 (0.73, 0.80)†|
|Medicaid||18,706 (10.7)||15,838,107 (16.2)||0.98 (0.92, 1.05)‡|
|Self-pay||33,042 (18.9)||18,380,025 (18.8)||0.98 (0.92, 1.03)‡|
|No charge||1,399 (0.8)||879,895 (0.9)||0.86 (0.68, 1.08)‡|
|Other||5,245 (3.0)||5,181,603 (5.3)||0.52 (0.45, 0.61)†|
|Hospital region, no. (%)|
|West||26,269 (15.0)||16,956,717 (17.3)||Referent|
|Northeast||30,996 (17.7)||19,144,278 (19.6)||1.05 (0.93, 1.19)‡|
|Midwest||32,781 (18.8)||22,825,597 (23.3)||0.98 (0.88, 1.11)‡|
|South||84,777 (48.5)||38,839,501 (39.7)||1.54 (1.38, 1.71)†|
|Urban/rural residence, no. (%)|
|Micropolitan/not metropolitan||42,530 (24.3)||18,580,680 (19.0)||Referent|
|Metropolitan (large or small)||132,293 (75.7)||79,185,413 (81.0)||0.86 (0.77, 0.95)§|
|Metropolitan nonteaching or nonmetropolitan||118,537 (67.8)||62,523,289 (64.0)||Referent|
|Metropolitan teaching||56,286 (32.2)||35,242,805 (36.0)||0.98 (0.89, 1.08)‡|
Patient-level factors associated with ED charges in 2008 were subsequently examined for visits in which gout was listed as the primary diagnosis (Table 3). Results for 2006 and 2007 were similar to those from 2008 (data not shown). After multivariable adjustment, patient characteristics associated with higher ED-related charges for gout included female sex, each additional year of age, a higher number of coded diagnoses, and a metropolitan residence. Gout patients residing in zip codes with the lowest annual median income (<$39,000) incurred charges that on average were $68 higher per visit than those for individuals residing in zip codes with a median income of $39,000–$48,999 (P = 0.024). There were no significant differences in ED-related charges between patients with a lower income and those residing in zip codes with higher median incomes (those exceeding $49,000 annually). Hospital characteristics associated with higher gout-related ED charges (data not shown) included a metropolitan location with a mean difference of $176 per visit compared to gout visits in rural/micropolitan EDs (P = 0.001). Although gout visits were more frequent in this region, related ED charges were significantly less in the southern US, with total visit-related charges on average $138 lower than those incurred in the western US (P < 0.001).
|β (95% CI)||P||β (95% CI)||P|
|Women||169.03 (133.87, 204.18)||< 0.0001||49.80 (14.23, 85.36)||0.006|
|Age, years||9.34 (8.15, 10.52)||< 0.0001||4.78 (3.58, 5.99)||< 0.0001|
|$39,000–48,999||−59.47 (−116.17, −2.77)||0.040||−68.20 (−127.46, −8.94)||0.024|
|$49,000–63,999||39.00 (−30.14, 108.13)||0.269||−35.44 (−107.97, 37.09)||0.339|
|≥$64,000||85.32 (−3.71, 174.34)||0.061||−34.66 (−130.23, 60.91)||0.477|
|Number of coded diagnoses||81.40 (67.93, 94.87)||< 0.0001||67.25 (54.01, 80.49)||< 0.0001|
|Micropolitan or nonmetropolitan||Referent||Referent|
|Large/medium/small metropolitan||292.56 (224.81, 360.30)||< 0.0001||94.38 (27.11, 161.65)||0.006|
|Private, including HMO||Referent||Referent|
|Medicare||220.50 (181.98, 259.03)||< 0.0001||10.52 (−30.92, 52.00)||0.619|
|Medicaid||4.80 (−41.97, 51.57)||0.841||−21.79 (−70.41, 26.83)||0.380|
|Self-pay||−52.86 (−94.33, −11.38)||0.013||−4.15 (−44.35, 36.05)||0.840|
|No charge||−5.10 (−155.45, 145.25)||0.947||−38.88 (−195.10, 117.33)||0.626|
|Other||128.21 (−13.57, 269.98)||0.077||133.21 (−6.89, 273.31)||0.063|
Of the more than 280 million ED visits occurring in the US from 2006 through 2008, gouty arthritis was coded as either a primary or secondary diagnosis in more than 2 million (0.7%) of these ambulatory encounters. The NEDS is constructed using a 20% stratified sample of US EDs, allowing for the generation of precise national estimates both in terms of the indications for ED visits (frequency of gout visits) and total corresponding ED-related charges. We identified both patient-level factors associated with an increased propensity for ED utilization in gout that included age, male sex, a household income of less than $39,000, and insurance status, in addition to a hospital/ED location in a nonmetropolitan area or in the southern US. Not surprisingly, gout-related visits in this study accounted for a substantial amount of total health care charges, with total charges exceeding $166 million in 2008 alone for ED visits primarily related to gouty arthritis. ED visits for gout, coded either as a primary or secondary diagnosis, accounted for 0.7% of all ED-related charges in 2008. These results suggest that gout care contributes to the formidable and growing consumption of health care resources across US EDs.
With a well-documented increase in disease incidence, ED utilization for gout will only increase in the absence of effective interventions focused on shifting gout care away from EDs and into primary care clinics. The availability of highly novel but often more expensive diagnostic imaging modalities (18) and therapies (19, 20) may further add to escalations in gout-related ED charges and overall management-related costs in the near future.
The ED burden posed by gout is considerable, particularly when taking into account that both acute and chronic forms of gout are highly “treatable” and perhaps, to some degree, even preventable. Health services research in other chronic health conditions has demonstrated that the number of ED visits due to acute disease exacerbations may be highly indicative of suboptimal disease management and poor treatment adherence (9, 10). Although our study did not directly address or even measure such factors, there are several areas in gout care that have been consistently characterized as suboptimal and therefore potentially remediable in future efforts to reduce ED utilization for gout. These include both the underuse and suboptimal dosing of urate-lowering therapy in gout treatment. Although studies have consistently shown that effective urate-lowering therapy reduces the frequency of gout attacks and tophus size (19, 21, 22), underutilization and inappropriate dosing by physicians is commonplace (11, 12) and could be contributing to the frequency of ED gout care.
With the possible exception of increasing age and male sex, both of which are known risk factors for gout, reasons for the associations of select patient- and facility-level factors with gout ED use and related charges remain unclear. It is quite possible that factors such as median income less than $39,000 and facility locations in rural and southern US regions serve as surrogates for poor health care access, including poor access to providers with expertise in gout management; a workforce shortage has already been observed and is projected to increase for rheumatologists nationally (23). Likewise, these regional factors may be associated with other unmeasured confounders such as the prevalence of gout and other gout-related risk factors such as race/ethnicity, dietary differences, and differences in alcohol consumption across populations. It is possible that factors associated with gout-related ED visits and the corresponding charges generated may be operative through differences in treatment adherence or important practice pattern variations that could be directly or indirectly reflected in ED utilization. It is noteworthy that women with gout in our study incurred ED charges that were on average $50 higher than their male counterparts. Although the precise reasons for this are not clear, higher charges for ED visits in women could be explained by the use of more diagnostic testing in order to rule out alternative diagnoses, since the pretest probability of gout may be lower in women and gouty arthritis may present atypically more often in women relative to men (24, 25). Consistent with sex-based differences observed for gout-related charges in the ED, women with gout previously have been shown to be much more likely than men with gout to undergo serum urate testing (26).
To our knowledge, the present study is among the first national estimates of gout-related ED utilization in the US. A major strength of this study centers on its use of the NEDS database, a large representative sample of ED visits occurring nationally over a 3-year span. In addition to allowing us to generate national estimates of gout visit frequency, the NEDS contains a rich array of patient- and facility-level variables, allowing us to examine factors potentially driving gout frequency and related health care charges. If interventions are to be undertaken to reduce gout burden in EDs, then these results suggest that efforts could be targeted to patient populations characterized by factors that relate to higher ED utilization for gout, as demonstrated in this study.
Recognizing these important strengths, there are also limitations to this study, most notably the lack of patient-level data. Although they are not currently available in the NEDS, the availability of patient-level data would allow for highly informative analyses that could include assessments of the frequency and total charges resulting from repeat ED visits. This study estimated the total charges secondary to gout-related ED visits and not the actual health care costs. It is likely that ED charges are dramatically inflated relative to actual direct costs. In a study involving 6 community hospitals, for instance, average ED charges were 83% higher than corresponding direct costs (27). In this same study, marginal ED costs (the extra cost for visiting the ED per se) accounted for 42% of the total costs. Extrapolating these data to our results, the total direct costs for gout-related visits to the ED (as a primary diagnosis) in 2008 would approach $90 million, with a marginal cost of approximately $38 million. In addition to the absence of actual costs data, the NEDS database does not include laboratory or medication data, prohibiting analyses that could provide added insight to these observations. Future studies will need to be completed to more precisely define what factors independently determine gout-related ED use, to what degree such utilization is truly “preventable,” and to determine what impact these visits have on both patient outcomes and overall gout-related health care costs.
All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Mikuls had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study conception and design. Garg, Saag, Mikuls.
Acquisition of data. Mikuls.
Analysis and interpretation of data. Garg, Sayles, Yu, Michaud, Singh, Saag, Mikuls.