- Email: [email protected]
Coiling Among Aneurysmal Subarachnoid Hemorrhage Patients: A National Study
Health Disparities in Time to Aneurysm Clipping/Coiling Among Aneurysmal Subarachnoid Hemorrhage Patients: A National Study Frank J. Attenello1, Kelsey Wang 2, Timothy Wen 2, Steven Y. Cen3, May Kim-Tenser 3, Arun P. Amar1, Nerses Sanossian 3, Steven L. Giannotta1, William J. Mack1
Key words Aneurysm clipping - Aneurysm coiling - Hospital performance - Ruptured aneurysm - Subarachnoid hemorrhage - Surgery -
Abbreviations and Acronyms aSAH: Aneurysmal subarachnoid hemorrhage CI: Confidence interval ICD-9-CM: International Classification of Diseases, 9th Edition; Clinical Modification NIS: Nationwide Inpatient Sample OR: Odds ratio SAH: Subarachnoid hemorrhage From the 1Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, California, USA; 2Keck School of Medicine, University of Southern California, Los Angeles, California, USA; and 3Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA To whom correspondence should be addressed: Kelsey Wang, B.A. [E-mail: [email protected]] Citation: World Neurosurg. (2014) 82, 6:1071-1076. http://dx.doi.org/10.1016/j.wneu.2014.08.053 Journal homepage: www.WORLDNEUROSURGERY.org
- OBJECTIVE:
Previous studies have suggested disparities in quality of health care and time to treatment across socioeconomic groups. Such differences can be of greatest consequence in the setting of emergent medical conditions. Surgical or endovascular treatment of ruptured cerebral aneurysms within the first 3 days of aneurysmal subarachnoid hemorrhage (aSAH) is associated with improved outcome. We hypothesize that race and payer status disparities effect the time to treatment for ruptured aneurysms.
- METHODS:
Discharge data were collected from the Nationwide Inpatient Sample during the years 2002L2010. International Classification of Diseases, 9th Edition; Clinical Modification codes were used to identify patients with aSAH who were treated by either surgical clipping or endovascular coil embolization. Time to procedure was dichotomized into 1) treatment in 3 days or less or 2) treatment in greater than 3 days. Time to treatment was evaluated according to demographic factors, including race, payer status, and median zip code income via multivariable analysis.
- RESULTS:
A total of 78,070 aSAH admissions were treated by either aneurysm clip ligation or coil embolization. Hispanic race and Medicaid payer status were associated with increased time to treatment (P < 0.05).
- CONCLUSION:
Racial and socioeconomic factors are associated with delayed time to treatment in aSAH. Identification of factors underlying these delays and standardization of care may allow for more uniform treatment protocols and improved patient care.
Available online: www.sciencedirect.com 1878-8750/$ - see front matter Published by Elsevier Inc.
INTRODUCTION In 2006, the Institute of Medicine published a report entitled Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare. This document unveiled consistently lesser standards of care for racial minorities across the US health care system (34). A movement has since emerged to identify racial and health disparities, specifically in surgical and procedural-based fields. Parameters that have been assessed and analyzed include time to procedure, mortality, and clinical outcome (28, 33, 37). Previous studies across multiple medical specialties have noted wide disparities in access to health care systems and time to medical procedures for ethnic minorities and patients of disadvantaged socioeconomic
background (2, 37, 30). Specifically, disparities and lower standards of care have been associated with increased postoperative complications and death in the neurosurgical literature (18). Procedural delays and latencies are more impactful when surgical or invasive procedures are considered urgent, high risk, or critical. Aneurysmal subarachnoid hemorrhage (aSAH) is a major cause of morbidity and mortality in the United States. Cerebral aneurysm rupture is a medical emergency and typically treated with either microvascular clip ligation or endovascular coil embolization to prevent rebleeding (25). Previous studies have suggested that time to treatment is critical (3, 13, 24). Lawson et al. (24) demonstrated that surgery in the first 3 days after aneurysm rupture improves outcomes. This finding is well accepted for
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standard cases. Nonetheless, time to treatment disparities after aSAH has not been investigated across US population samples. Our study leverages records from a large national discharge database between 2002 and 2010 to address this topic. Time to treatment after aSAH is evaluated according to racial and socioeconomic status. We hypothesize that race and socioeconomic status factors are significant predictors for prolonged latency to definitive aneurysm treatment.
METHODS Data Population Characteristics This study used discharge data from the Nationwide Inpatient Sample (NIS) during years 20022010. The NIS is one of the
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largest all-payer inpatient care databases in the United States, assembled annually by the Agency for Healthcare Research and Quality’s Healthcare Cost and Utilization Project. NIS contains discharge data from more than 1,000 hospitals representing 20% of all US hospital discharges. NIS also has a built in weighting system that can be applied to obtain national estimates of prevalence. Study Cohort Characteristics Inclusion criteria for this study were limited to the diagnosis of aSAH caused by a ruptured aneurysm with a corresponding procedure of either a microvascular clip or an endovascular coil. International Classification of Diseases, 9th Edition; Clinical Modification (ICD-9-CM) codes in the procedure and diagnosis fields of NIS were used to identify patients with a diagnosis of aSAH (ICD-9-CM: 430) and a corresponding aneurysm clipping (ICD-9-CM: 39.51) and coiling (ICD-9-CM: 39.79, 39.72, 39.52) procedure. Time to procedure was included as a continuous field (in days) in the NIS and was dichotomized into patients who waited 3 or fewer days and those who waited more than 3 days for repair of the aneurysm via either clipping or coiling. Patients who were treated with both an aneurysm clipping and coiling procedure and those missing time to procedure variable values were excluded from analysis. The NIS encoded patient and hospital factors into the database. Patient factors used in analysis included race (white, black, Hispanic, Asian or Pacific Islander, Native American, other), payer status (Medicare, Medicaid, Private Insurance, Self-pay, no charge), and sex (male, female). Other patient factors, such as age and number of comorbidities, were coded as continuous variables and converted into categorical age (<60 years, 6170 years, 7180 years, >80 years) and comorbidity (no comorbidities, 1 comorbidity, 2 or more comorbidities) variables for demographic and multivariable analyses. Hospital-level variables used in analysis included hospital bed size (small: <200 beds, medium: 201400 beds, large: >400 beds), teaching status (nonteaching, teaching), hospital region (Northeast, Midwest, South, West), and hospital location (urban and rural). These variables were included in NIS as categorical variables and were not modified. Additionally, missing values for any of the
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TIME TO ANEURYSM CLIPPING/COILING AMONG ASAH PATIENTS
variables were recoded to be included (as “missing variable”) in both demographic univariate and multivariable analyses. Statistical Analysis Univariate demographic analyses were conducted using survey-adjusted methods for all patient and hospital factors for the sample. The primary outcome of interest was the probability of waiting more than 3 days until aneurysm procedure. To evaluate this outcome, we fit a multivariable logistic regression model using surveyadjusted generalized estimating equations adjusting for the aforementioned patient and hospital factors. We had three main predictors of interest: patient race, payer status, and patient’s mean income based on ZIP code. Statistical significance was preset as a P < 0.05. All descriptive univariate and multivariable regression analyses were conducted using SAS 9.3 (Cary, North Carolina, USA). RESULTS Sample Demographics Between 2002 and 2010, 78,070 admissions were associated with aSAH and received either an aneurysm clipping or coiling procedure. Of the 78,070 admissions, 89% of the patients waited 3 or fewer days and 11% of patients waited more than 3 days for either a clipping or coiling procedure (Table 1). Of this group, 54% of patients with aSAH received clipping and 46% received coiling (Table 1). A total of 48% of the population was white, and 31% were nonwhite (13% black, 11% Hispanic, 3.4% Asian or Pacific Islander, 0.2% Native American, and 3.3% other, with 21% coded as missing) (Table 1). The majority of patients were insured privately (47%), followed by Medicare (22%), and Medicaid (15%) (Table 1). In univariate analysis, greater proportions of black, Hispanic, and Asian or Pacific Islander patients with aSAH (10.7%14.9%) waited more than 3 days for a clip or coil procedure compared with white patients (10.2%). Additionally, a larger proportion of Medicaid patients (13.6%) were shown to have waited more than 3 days for an aneurysm clipping or coiling compared with privately insured patients (9.9%). There were no major variations in proportion of patients waiting more than 3 days when we stratified the
sample by mean income based on ZIP code (Table 1). Multivariable Logistic Regression Analyses Multivariable logistic regression analysis adjusting for patient (race, payer status, comorbidities, sex, age category, mean income based on ZIP code) and hospital (hospital region, hospital teaching status, hospital bed size, hospital location) factors were performed to assess the likelihood of waiting more than 3 days for an aneurysm clipping or coiling. Hispanic patients had a 46% increased likelihood of delayed aSAH treatment compared with white patients (odds ratio [OR] 1.35, 95% confidence interval [95% CI] 1.121.63, P ¼ 0.0019; Table 2). Other races showed no statistically significant association with increased time to clip or coil (Table 2). Additionally, patients on Medicaid exhibited a 33% increased likelihood of waiting more than three days for a procedure compared to privately insured patients (OR 1.33, 95% CI 1.151.54, P ¼ 0.0001). Other payer statuses, other races, and median income by zip code showed no association with an increase in time to treatment (Table 2). Furthermore, analyses showed 2 or more patient comorbidities increased time to surgery (OR 1.18, 95% CI 1.011.37, P ¼ 0.0377; vs. no comorbidity); however, there was no significant predictive effect of one comorbidity compared with no comorbidity (Table 2). Patients with aSAH seen at teaching hospitals were 21% less likely to experience an increased time to treatment compared with nonteaching hospitals (OR 0.79, 95% CI 0.690.99, P ¼ 0.0362). There were no correlations between a prolonged time to treatment and sex, age, hospital region, hospital bed size, or hospital location (P > 0.05, Table 2). DISCUSSION Bekelis et al. (5) recently described treatment allocation disparities for unruptured cerebral aneurysms. The authors noted that ethnic minorities and those lacking insurance coverage had a lesser chance of receiving treatment (5). Although the preferred treatment modality for repair of ruptured aneurysms, either open or endovascular, varies between physicians and institutions, it is well established that ruptured aneurysms should be treated if
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feasible and safe. Further, latency from aneurysm rupture to surgery is critical, as a prolonged time to treatment results in higher morbidity and mortality (3, 13, 24) Of note, we chose 3 days as our time point of given the results of studies showing aSAH patients with treatment on posthemorrhage days 410 showing worse outcomes than those treated on days 03. Multivariable analysis of our data indicates that Hispanic patients are associated with longer periods of time (compared with white patients) for clip ligation or coil embolization of ruptured intracranial aneurysms. This finding is consistent with previous outcome studies on aSAH suggesting disparities according to race (8, 28, 35, 41). The pattern persists across urgent procedures in other medical subspecialties (3, 10, 16, 17, 40). Data from studies of cancer and traumatic brain injury suggest that Hispanic patients have significantly longer emergency department wait times and latencies to disease treatment than do white patients (4, 12, 19). Studies cite potential language barrier in communication with health providers. Such barriers may delay time to hospital admission or diagnosis after admission. Delays in admission may result in presentation in mid- to late vasospasm periods. In cardiac literature, nonwhite patients experienced significant delays to primary angioplasty after acute myocardial infarction (2). Of note, though recent studies have evaluated the effects of socioeconomic factors on postprocedural mortality, nonroutine discharge and length of stay, no previous studies have correlated these factors with time to aneurysm treatment (22). Our data demonstrate an association between Medicaid payer status and prolonged time to definitive aneurysm treatment after SAH. Socioeconomic factors and insurance status have previously been linked to poor outcomes using a range of metrics across medical disciplines (1, 11, 15, 20, 21, 23, 31, 32). Kapral et al. (20) demonstrated that low income patients are more likely to wait longer for carotid artery surgery. Further, delayed treatment times for Medicaid patients with appendicitis have been shown to result in increased rates of perforation (29). Ackerman et al. (1) suggest that lower socioeconomic status patients experience longer wait times for
TIME TO ANEURYSM CLIPPING/COILING AMONG ASAH PATIENTS
Table 1. Study Cohort Demographics (N ¼ 78,070) Waiting 3 or Fewer Days (n [ 69,619)
Waiting More Than 3 Days (n [ 8451)
Total (N)
N
%
N
%
Clipping
42,042
37,281
88.7
4761
11.3
Coiling
36,029
32,339
89.8
3690
10.2
White
37,972
34,082
89.8
3890
10.2
Black
10,265
9162
89.3
1103
10.7
Hispanic
8873
7552
85.1
1321
14.9
Asian Pacific Islander
2665
2313
86.8
352
13.2
170
170
100.0
DS
0.0
Procedure
Race
Native American Other
2575
2319
90.1
256
9.9
15,534
14,020
90.3
1514
9.7
Medicare
17,228
15,337
89.0
1891
11.0
Medicaid
11,375
9823
86.4
1552
13.6
Private Insurance
36,939
33,285
90.1
3654
9.9
7854
6979
88.9
875
11.1
860
783
91.0
77
9.0
3605
3225
89.5
380
10.5
187
187
100.0
DS
0.0
No comorbidities
12,129
10,959
90.4
1170
9.6
One comorbidity
18,376
18,374
100.0
2.06
0.0
Two or more comorbidities
44,595
39,464
88.5
5131
11.5
912
822
90.1
90
9.9
Male
24,611
21,603
87.8
3008
12.2
Female
53,249
47,817
89.8
5432
10.2
Missing
198
198
100.0
DS
0.0
60 years or younger
54,392
48,651
89.4
5741
10.6
Missing Payer Status
Self-pay No Charge Other Missing Comorbidities
Missing Sex
Age category
61e70 years old
13,798
12,251
88.8
1547
11.2
71e80 years old
7,210
6364
88.3
846
11.7
Over 80 years old
2,583
2272
88.0
311
12.0
82
82
100.0
DS
0.0
Missing Mean income based on ZIP code
DS, Data suppressed per HCUP Data User Agreement.
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Continues
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Table 1. Continued Waiting 3 or Fewer Days (n [ 69,619)
Waiting More Than 3 Days (n [ 8451)
Table 2. Predictors of Prolonged Wait for Aneurysm Clip/Coil OR
95% CI
P Value
Race Total (N)
N
%
N
%
White
Low
19,800
17,449
88.1
2351
11.9
Black
Medium
19,367
17,336
89.5
2031
10.5
High
18,080
16,071
88.9
2009
11.1
Very High
18,417
16,605
90.2
1812
9.8
2405
2158
89.7
247
10.3
Missing Hospital region Northeast
15,960
14,446
90.5
1514
9.5
Midwest
11,424
10,510
92.0
914
8.0
South
32,197
28,508
88.5
3689
11.5
West Missing
18,489
16,155
87.4
2334
12.6
0
0
0.0
0
0.0
Hospital teaching status Nonteaching
10,969
9496
86.6
1473
13.4
Teaching
66,511
59,603
89.6
6908
10.4
591
521
88.2
70
11.8
Missing Hospital bed size Low
1.03 0.86, 1.23
0.7488
Hispanic
1.35 1.12, 1.63
0.0019
Asian Pacific Islander
1.24 0.91, 1.71
0.1790
Native American 0.78 0.25, 2.41
0.6605
Other
0.96 0.72, 1.29
0.7904
Medicare
0.96 0.79, 1.17
0.6899
Medicaid
1.33 1.15, 1.54
0.0001
Payer status
Private Insurance
1.04 0.87, 1.24
0.6532
No charge
0.70 0.39, 1.24
0.4522
Other
0.95 0.72, 1.25
0.7114
Comorbidities No comorbidities
1.03 0.85, 1.26
0.7691
Two or more comorbidities
1.18 1.01, 1.37
0.0377
89.4
273
10.6
Medium
11,041
9686
87.7
1355
12.3
High
63,853
57,100
89.4
6753
10.6
Male
591
521
88.2
70
11.8
Female
Rural
1,223
1120
91.6
103
8.4
Urban
76,256
67,978
89.1
8278
10.9
60 years or younger
591
521
88.2
70
11.8
Missing
Reference
One comorbidity 2312
Hospital location
Reference
Self-pay
2,585
Missing
Reference
Sex Reference 0.80 0.72, 0.89
0.2189
0.77 0.55, 1.08
0.1343
61e70 years old 0.87 0.63, 1.20
0.3982
71e80 years old 0.95 0.69, 1.31
0.7391
Age category
DS, Data suppressed per HCUP Data User Agreement.
Over 80 years old
Reference
Mean income based on ZIP code
joint replacement surgery, leading to increased morbidity. Emergent aneurysm surgery is unlikely to be affected by issues of insurance clearance or selection according to provider as these patients present to emergency departments and warrant urgent admission or transfer. These noted disparities are more likely to result from lack of direct access to tertiary care facilities and specialized health care providers based on geographic disadvantages and routing of emergency services. Influences on health care access and outcome disparities are multifactorial (34). One critical factor is patient access. Ease of
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admission to the types of comprehensive health care facilities equipped to treat aSAH can be challenging for socioeconomically disadvantaged patients and those of minority backgrounds (6, 14, 26, 39). Many communities lack tertiary care facilities or systematic transfer policies designed to efficiently place patients in such centers. Presentation to lowvolume centers can lead to treatment delays and unfavorable outcomes (38). Cultural and socioeconomic factors may also impact an individual’s recognition of symptoms and the need to seek urgent medical attention. Previous studies have suggested that cultural and language barriers among
Low
1.15 0.95, 1.38
0.1476
Medium
1.04 0.90, 1.21
0.5665
High
1.12 0.96, 1.30
0.1451
Very High
Reference
Hospital region Northeast
Reference
Midwest
0.83 0.63, 1.11
0.2138
South
1.18 0.92, 1.52
0.1846
West
1.28 0.86, 1.90
0.2193
Hospital teaching status Continues
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Table 2. Continued OR Nonteaching Teaching
95% CI
P Value
Reference 0.79 0.63, 0.99
0.0362
Hospital bed size Low
Reference
Medium
1.28 0.78, 2.09
0.3361
High
1.03 0.63, 1.69
0.8973
Hospital location Rural Urban
Reference 1.14 0.71, 1.85
0.5872
OR, odds ratio; CI, confidence interval.
Hispanic patients lead to treatment delays, which can result in adverse outcomes (26). Correlations between treatment delays and inferior patient outcomes for individuals of Hispanic background and those insured by Medicaid are supported in studies of other neurosurgical procedures (9, 27). El-Sayed et al. (9) demonstrated that Medicaid patients had more postoperative complications and longer stays in the intensive care unit/hospital after neurosurgical procedures than privately insured patients. Similarly, Curry et al. (7) found that Medicaid patients endured the greatest inhospital mortality rates after craniotomy. Disease-specific determinants may vary according to ethnicity and/or socioeconomic background. When measuring clinical outcome as a primary end point, comorbidities and disease susceptibility can profoundly impact surgical results. These factors, however, are unlikely to confound measurements of latency to an emergent procedure. Delays in definitive treatment of acute, life-threatening conditions reflect deficiencies in systems of care. That these delays are associated with ethnic and socioeconomic determinants is concerning. There are limitations to this study, principally associated with the use of a large national discharge database. Residual bias and confounding may persist despite thorough adjustment in multivariable regression analyses. Coding inaccuracies can affect large, administrative databases. These imprecisions, however, have been shown to be minor (36). Not all US hospitals
are included in the database during the time period of study. Variations in geography, size, and academic status of the sample institutions could potentially affect results. However, the large scope and diversity of hospitals included in the database limit such an impact. The NIS does not provide clinical admission details, such as disease severity or Hunt and Hess grade. This limits the ability to control for such potentially confounding factors in a multivariable analysis. Furthermore, although it is unlikely that significant differences exist in time to presentation, the NIS lacks data regarding this variable. Finally, the use of mean income of zip code as a proxy for socioeconomic status may suffer from potential variation in status among inhabitants of a given region. CONCLUSION Our study suggests racial and socioeconomic disparities in times to treatment of aSAH. Notably, Hispanic patients and those insured with Medicaid experience prolonged times to clip ligation and coil embolization procedures. Future studies are necessary to identify the potential root causes of these inequalities. Ultimately, identifying the factors contributing to these delays could help standardize systems of care so that patients with aSAH experience more uniform treatment regardless of socioeconomic status and race to provide improved patient care and clinical outcomes. REFERENCES 1. Ackerman IN, Graves SE, Wicks IP, Bennell KL, Osborne RH: Severely compromised quality of life in women and those of lower socioeconomic status waiting for joint replacement surgery. Arthritis Reum 53:653-658, 2005. 2. Angeja BG, Gibson CM, Chin R, Frederick PD, Every NR, Ross AM, Stone GW, Barron HV: Predictors of door-to-balloon delay in primary angioplasty. Am J Cardiol 89:1156-1161, 2002. 3. Baskaya MK, Kelley R, Nanda A, Vannemreddy P: Delayed diagnosis of intracranial aneurysms: confounding factors in clinical presentation and the influence of misdiagnosis on outcome. South Med J 94:1108-1111, 2001. 4. Bazarian JJ, Pope C, McClung J, Cheng YT, Flesher W: Ethnic and racial disparities in emergency department care for mild traumatic brain injury. Acad Emerg Med 10:1209-1217, 2003. 5. Bekelis K, Missios S, Labropoulos N: Regional and socioeconomic disparities in the treatment of
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29. Pieracci FM, Eachempati SR, Barie PS, Callahan MA: Insurance status, but not race, predicts perforation in adult patients with acute appendicitis. J Am Coll Surg 205:445-452, 2007. 30. Ramirez A, Perez-Stable E, Penedo F, Talavera G, Carrillo JE, Fernández M, Holden A, Munoz E, San Miguel S, Gallion K: Reducing time-to-reatment in underserved Latinas with breast cancer. Cancer 120:752-760, 2014. 31. Santry HP, Gillen DL, Lauderdale DS: TRends in bariatric surgical procedures. JAMA 294:1909-1917, 2005. 32. Saposnik G, Jeerakathil T, Selchen D, Baibergenova A, Hachinski V, Kapral MK; Stroke Outcome Research Canada Working Group: Socioeconomic status, hospital volume, and stroke fatality in Canada. Stroke 39:3360-3366, 2008. 33. Shah A, Chao KSC, Østbye T, Castleberry A, Pietrobon R, Gloor B, Clary B, White R, Worni M: Trends in racial disparities in pancreatic cancer surgery. J Gastrointest Surg 17:1897-1906, 2013.
38. Vespa P, Diringer M: High-volume centers. Neurocrit Care 15:369-372, 2011. 39. Weinick RM, Zuvekas SH, Cohen JW: Racial and ethnic differences in access to and use of health care services, 1977 to 1996. Med Care Res Rev 57: 36-54, 2000. 40. Weller I, Wai EK, Jaglal S, Kreder HJ: The effect of hospital type and surgical delay on mortality after surgery for hip fracture. J Bone Joint Surg Br 87-B: 361-366, 2005. 41. Zacharia BE, Grobelny BT, Komotar RJ, Sander Connolly E, Mocco J: The influence of race on outcome following subarachnoid hemorrhage. J Clin Neurosci 17:34-37, 2010.
Conflict of interest statement: The authors declare that the article content was composed in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
34. Smedley BD, Stith AY, Nelson AR: Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care (with CD). Washington, DC: National Academies Press; 2009.
Received 21 February 2014; accepted 27 August 2014; published online 29 August 2014
35. Sonnenday C, Dimick J, Schulick R, Choti M: Racial and geographic disparities in the utilization of surgical therapy for hepatocellular carcinoma. J Gastrointest Surg 11:1636-1646, 2007.
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Citation: World Neurosurg. (2014) 82, 6:1071-1076. http://dx.doi.org/10.1016/j.wneu.2014.08.053
Available online: www.sciencedirect.com 1878-8750/$ - see front matter Published by Elsevier Inc.
WORLD NEUROSURGERY, http://dx.doi.org/10.1016/j.wneu.2014.08.053
Key words Aneurysm clipping - Aneurysm coiling - Hospital performance - Ruptured aneurysm - Subarachnoid hemorrhage - Surgery -
Abbreviations and Acronyms aSAH: Aneurysmal subarachnoid hemorrhage CI: Confidence interval ICD-9-CM: International Classification of Diseases, 9th Edition; Clinical Modification NIS: Nationwide Inpatient Sample OR: Odds ratio SAH: Subarachnoid hemorrhage From the 1Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, California, USA; 2Keck School of Medicine, University of Southern California, Los Angeles, California, USA; and 3Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA To whom correspondence should be addressed: Kelsey Wang, B.A. [E-mail: [email protected]] Citation: World Neurosurg. (2014) 82, 6:1071-1076. http://dx.doi.org/10.1016/j.wneu.2014.08.053 Journal homepage: www.WORLDNEUROSURGERY.org
- OBJECTIVE:
Previous studies have suggested disparities in quality of health care and time to treatment across socioeconomic groups. Such differences can be of greatest consequence in the setting of emergent medical conditions. Surgical or endovascular treatment of ruptured cerebral aneurysms within the first 3 days of aneurysmal subarachnoid hemorrhage (aSAH) is associated with improved outcome. We hypothesize that race and payer status disparities effect the time to treatment for ruptured aneurysms.
- METHODS:
Discharge data were collected from the Nationwide Inpatient Sample during the years 2002L2010. International Classification of Diseases, 9th Edition; Clinical Modification codes were used to identify patients with aSAH who were treated by either surgical clipping or endovascular coil embolization. Time to procedure was dichotomized into 1) treatment in 3 days or less or 2) treatment in greater than 3 days. Time to treatment was evaluated according to demographic factors, including race, payer status, and median zip code income via multivariable analysis.
- RESULTS:
A total of 78,070 aSAH admissions were treated by either aneurysm clip ligation or coil embolization. Hispanic race and Medicaid payer status were associated with increased time to treatment (P < 0.05).
- CONCLUSION:
Racial and socioeconomic factors are associated with delayed time to treatment in aSAH. Identification of factors underlying these delays and standardization of care may allow for more uniform treatment protocols and improved patient care.
Available online: www.sciencedirect.com 1878-8750/$ - see front matter Published by Elsevier Inc.
INTRODUCTION In 2006, the Institute of Medicine published a report entitled Unequal Treatment: Confronting Racial and Ethnic Disparities in Healthcare. This document unveiled consistently lesser standards of care for racial minorities across the US health care system (34). A movement has since emerged to identify racial and health disparities, specifically in surgical and procedural-based fields. Parameters that have been assessed and analyzed include time to procedure, mortality, and clinical outcome (28, 33, 37). Previous studies across multiple medical specialties have noted wide disparities in access to health care systems and time to medical procedures for ethnic minorities and patients of disadvantaged socioeconomic
background (2, 37, 30). Specifically, disparities and lower standards of care have been associated with increased postoperative complications and death in the neurosurgical literature (18). Procedural delays and latencies are more impactful when surgical or invasive procedures are considered urgent, high risk, or critical. Aneurysmal subarachnoid hemorrhage (aSAH) is a major cause of morbidity and mortality in the United States. Cerebral aneurysm rupture is a medical emergency and typically treated with either microvascular clip ligation or endovascular coil embolization to prevent rebleeding (25). Previous studies have suggested that time to treatment is critical (3, 13, 24). Lawson et al. (24) demonstrated that surgery in the first 3 days after aneurysm rupture improves outcomes. This finding is well accepted for
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standard cases. Nonetheless, time to treatment disparities after aSAH has not been investigated across US population samples. Our study leverages records from a large national discharge database between 2002 and 2010 to address this topic. Time to treatment after aSAH is evaluated according to racial and socioeconomic status. We hypothesize that race and socioeconomic status factors are significant predictors for prolonged latency to definitive aneurysm treatment.
METHODS Data Population Characteristics This study used discharge data from the Nationwide Inpatient Sample (NIS) during years 20022010. The NIS is one of the
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largest all-payer inpatient care databases in the United States, assembled annually by the Agency for Healthcare Research and Quality’s Healthcare Cost and Utilization Project. NIS contains discharge data from more than 1,000 hospitals representing 20% of all US hospital discharges. NIS also has a built in weighting system that can be applied to obtain national estimates of prevalence. Study Cohort Characteristics Inclusion criteria for this study were limited to the diagnosis of aSAH caused by a ruptured aneurysm with a corresponding procedure of either a microvascular clip or an endovascular coil. International Classification of Diseases, 9th Edition; Clinical Modification (ICD-9-CM) codes in the procedure and diagnosis fields of NIS were used to identify patients with a diagnosis of aSAH (ICD-9-CM: 430) and a corresponding aneurysm clipping (ICD-9-CM: 39.51) and coiling (ICD-9-CM: 39.79, 39.72, 39.52) procedure. Time to procedure was included as a continuous field (in days) in the NIS and was dichotomized into patients who waited 3 or fewer days and those who waited more than 3 days for repair of the aneurysm via either clipping or coiling. Patients who were treated with both an aneurysm clipping and coiling procedure and those missing time to procedure variable values were excluded from analysis. The NIS encoded patient and hospital factors into the database. Patient factors used in analysis included race (white, black, Hispanic, Asian or Pacific Islander, Native American, other), payer status (Medicare, Medicaid, Private Insurance, Self-pay, no charge), and sex (male, female). Other patient factors, such as age and number of comorbidities, were coded as continuous variables and converted into categorical age (<60 years, 6170 years, 7180 years, >80 years) and comorbidity (no comorbidities, 1 comorbidity, 2 or more comorbidities) variables for demographic and multivariable analyses. Hospital-level variables used in analysis included hospital bed size (small: <200 beds, medium: 201400 beds, large: >400 beds), teaching status (nonteaching, teaching), hospital region (Northeast, Midwest, South, West), and hospital location (urban and rural). These variables were included in NIS as categorical variables and were not modified. Additionally, missing values for any of the
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variables were recoded to be included (as “missing variable”) in both demographic univariate and multivariable analyses. Statistical Analysis Univariate demographic analyses were conducted using survey-adjusted methods for all patient and hospital factors for the sample. The primary outcome of interest was the probability of waiting more than 3 days until aneurysm procedure. To evaluate this outcome, we fit a multivariable logistic regression model using surveyadjusted generalized estimating equations adjusting for the aforementioned patient and hospital factors. We had three main predictors of interest: patient race, payer status, and patient’s mean income based on ZIP code. Statistical significance was preset as a P < 0.05. All descriptive univariate and multivariable regression analyses were conducted using SAS 9.3 (Cary, North Carolina, USA). RESULTS Sample Demographics Between 2002 and 2010, 78,070 admissions were associated with aSAH and received either an aneurysm clipping or coiling procedure. Of the 78,070 admissions, 89% of the patients waited 3 or fewer days and 11% of patients waited more than 3 days for either a clipping or coiling procedure (Table 1). Of this group, 54% of patients with aSAH received clipping and 46% received coiling (Table 1). A total of 48% of the population was white, and 31% were nonwhite (13% black, 11% Hispanic, 3.4% Asian or Pacific Islander, 0.2% Native American, and 3.3% other, with 21% coded as missing) (Table 1). The majority of patients were insured privately (47%), followed by Medicare (22%), and Medicaid (15%) (Table 1). In univariate analysis, greater proportions of black, Hispanic, and Asian or Pacific Islander patients with aSAH (10.7%14.9%) waited more than 3 days for a clip or coil procedure compared with white patients (10.2%). Additionally, a larger proportion of Medicaid patients (13.6%) were shown to have waited more than 3 days for an aneurysm clipping or coiling compared with privately insured patients (9.9%). There were no major variations in proportion of patients waiting more than 3 days when we stratified the
sample by mean income based on ZIP code (Table 1). Multivariable Logistic Regression Analyses Multivariable logistic regression analysis adjusting for patient (race, payer status, comorbidities, sex, age category, mean income based on ZIP code) and hospital (hospital region, hospital teaching status, hospital bed size, hospital location) factors were performed to assess the likelihood of waiting more than 3 days for an aneurysm clipping or coiling. Hispanic patients had a 46% increased likelihood of delayed aSAH treatment compared with white patients (odds ratio [OR] 1.35, 95% confidence interval [95% CI] 1.121.63, P ¼ 0.0019; Table 2). Other races showed no statistically significant association with increased time to clip or coil (Table 2). Additionally, patients on Medicaid exhibited a 33% increased likelihood of waiting more than three days for a procedure compared to privately insured patients (OR 1.33, 95% CI 1.151.54, P ¼ 0.0001). Other payer statuses, other races, and median income by zip code showed no association with an increase in time to treatment (Table 2). Furthermore, analyses showed 2 or more patient comorbidities increased time to surgery (OR 1.18, 95% CI 1.011.37, P ¼ 0.0377; vs. no comorbidity); however, there was no significant predictive effect of one comorbidity compared with no comorbidity (Table 2). Patients with aSAH seen at teaching hospitals were 21% less likely to experience an increased time to treatment compared with nonteaching hospitals (OR 0.79, 95% CI 0.690.99, P ¼ 0.0362). There were no correlations between a prolonged time to treatment and sex, age, hospital region, hospital bed size, or hospital location (P > 0.05, Table 2). DISCUSSION Bekelis et al. (5) recently described treatment allocation disparities for unruptured cerebral aneurysms. The authors noted that ethnic minorities and those lacking insurance coverage had a lesser chance of receiving treatment (5). Although the preferred treatment modality for repair of ruptured aneurysms, either open or endovascular, varies between physicians and institutions, it is well established that ruptured aneurysms should be treated if
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feasible and safe. Further, latency from aneurysm rupture to surgery is critical, as a prolonged time to treatment results in higher morbidity and mortality (3, 13, 24) Of note, we chose 3 days as our time point of given the results of studies showing aSAH patients with treatment on posthemorrhage days 410 showing worse outcomes than those treated on days 03. Multivariable analysis of our data indicates that Hispanic patients are associated with longer periods of time (compared with white patients) for clip ligation or coil embolization of ruptured intracranial aneurysms. This finding is consistent with previous outcome studies on aSAH suggesting disparities according to race (8, 28, 35, 41). The pattern persists across urgent procedures in other medical subspecialties (3, 10, 16, 17, 40). Data from studies of cancer and traumatic brain injury suggest that Hispanic patients have significantly longer emergency department wait times and latencies to disease treatment than do white patients (4, 12, 19). Studies cite potential language barrier in communication with health providers. Such barriers may delay time to hospital admission or diagnosis after admission. Delays in admission may result in presentation in mid- to late vasospasm periods. In cardiac literature, nonwhite patients experienced significant delays to primary angioplasty after acute myocardial infarction (2). Of note, though recent studies have evaluated the effects of socioeconomic factors on postprocedural mortality, nonroutine discharge and length of stay, no previous studies have correlated these factors with time to aneurysm treatment (22). Our data demonstrate an association between Medicaid payer status and prolonged time to definitive aneurysm treatment after SAH. Socioeconomic factors and insurance status have previously been linked to poor outcomes using a range of metrics across medical disciplines (1, 11, 15, 20, 21, 23, 31, 32). Kapral et al. (20) demonstrated that low income patients are more likely to wait longer for carotid artery surgery. Further, delayed treatment times for Medicaid patients with appendicitis have been shown to result in increased rates of perforation (29). Ackerman et al. (1) suggest that lower socioeconomic status patients experience longer wait times for
TIME TO ANEURYSM CLIPPING/COILING AMONG ASAH PATIENTS
Table 1. Study Cohort Demographics (N ¼ 78,070) Waiting 3 or Fewer Days (n [ 69,619)
Waiting More Than 3 Days (n [ 8451)
Total (N)
N
%
N
%
Clipping
42,042
37,281
88.7
4761
11.3
Coiling
36,029
32,339
89.8
3690
10.2
White
37,972
34,082
89.8
3890
10.2
Black
10,265
9162
89.3
1103
10.7
Hispanic
8873
7552
85.1
1321
14.9
Asian Pacific Islander
2665
2313
86.8
352
13.2
170
170
100.0
DS
0.0
Procedure
Race
Native American Other
2575
2319
90.1
256
9.9
15,534
14,020
90.3
1514
9.7
Medicare
17,228
15,337
89.0
1891
11.0
Medicaid
11,375
9823
86.4
1552
13.6
Private Insurance
36,939
33,285
90.1
3654
9.9
7854
6979
88.9
875
11.1
860
783
91.0
77
9.0
3605
3225
89.5
380
10.5
187
187
100.0
DS
0.0
No comorbidities
12,129
10,959
90.4
1170
9.6
One comorbidity
18,376
18,374
100.0
2.06
0.0
Two or more comorbidities
44,595
39,464
88.5
5131
11.5
912
822
90.1
90
9.9
Male
24,611
21,603
87.8
3008
12.2
Female
53,249
47,817
89.8
5432
10.2
Missing
198
198
100.0
DS
0.0
60 years or younger
54,392
48,651
89.4
5741
10.6
Missing Payer Status
Self-pay No Charge Other Missing Comorbidities
Missing Sex
Age category
61e70 years old
13,798
12,251
88.8
1547
11.2
71e80 years old
7,210
6364
88.3
846
11.7
Over 80 years old
2,583
2272
88.0
311
12.0
82
82
100.0
DS
0.0
Missing Mean income based on ZIP code
DS, Data suppressed per HCUP Data User Agreement.
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Table 1. Continued Waiting 3 or Fewer Days (n [ 69,619)
Waiting More Than 3 Days (n [ 8451)
Table 2. Predictors of Prolonged Wait for Aneurysm Clip/Coil OR
95% CI
P Value
Race Total (N)
N
%
N
%
White
Low
19,800
17,449
88.1
2351
11.9
Black
Medium
19,367
17,336
89.5
2031
10.5
High
18,080
16,071
88.9
2009
11.1
Very High
18,417
16,605
90.2
1812
9.8
2405
2158
89.7
247
10.3
Missing Hospital region Northeast
15,960
14,446
90.5
1514
9.5
Midwest
11,424
10,510
92.0
914
8.0
South
32,197
28,508
88.5
3689
11.5
West Missing
18,489
16,155
87.4
2334
12.6
0
0
0.0
0
0.0
Hospital teaching status Nonteaching
10,969
9496
86.6
1473
13.4
Teaching
66,511
59,603
89.6
6908
10.4
591
521
88.2
70
11.8
Missing Hospital bed size Low
1.03 0.86, 1.23
0.7488
Hispanic
1.35 1.12, 1.63
0.0019
Asian Pacific Islander
1.24 0.91, 1.71
0.1790
Native American 0.78 0.25, 2.41
0.6605
Other
0.96 0.72, 1.29
0.7904
Medicare
0.96 0.79, 1.17
0.6899
Medicaid
1.33 1.15, 1.54
0.0001
Payer status
Private Insurance
1.04 0.87, 1.24
0.6532
No charge
0.70 0.39, 1.24
0.4522
Other
0.95 0.72, 1.25
0.7114
Comorbidities No comorbidities
1.03 0.85, 1.26
0.7691
Two or more comorbidities
1.18 1.01, 1.37
0.0377
89.4
273
10.6
Medium
11,041
9686
87.7
1355
12.3
High
63,853
57,100
89.4
6753
10.6
Male
591
521
88.2
70
11.8
Female
Rural
1,223
1120
91.6
103
8.4
Urban
76,256
67,978
89.1
8278
10.9
60 years or younger
591
521
88.2
70
11.8
Missing
Reference
One comorbidity 2312
Hospital location
Reference
Self-pay
2,585
Missing
Reference
Sex Reference 0.80 0.72, 0.89
0.2189
0.77 0.55, 1.08
0.1343
61e70 years old 0.87 0.63, 1.20
0.3982
71e80 years old 0.95 0.69, 1.31
0.7391
Age category
DS, Data suppressed per HCUP Data User Agreement.
Over 80 years old
Reference
Mean income based on ZIP code
joint replacement surgery, leading to increased morbidity. Emergent aneurysm surgery is unlikely to be affected by issues of insurance clearance or selection according to provider as these patients present to emergency departments and warrant urgent admission or transfer. These noted disparities are more likely to result from lack of direct access to tertiary care facilities and specialized health care providers based on geographic disadvantages and routing of emergency services. Influences on health care access and outcome disparities are multifactorial (34). One critical factor is patient access. Ease of
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admission to the types of comprehensive health care facilities equipped to treat aSAH can be challenging for socioeconomically disadvantaged patients and those of minority backgrounds (6, 14, 26, 39). Many communities lack tertiary care facilities or systematic transfer policies designed to efficiently place patients in such centers. Presentation to lowvolume centers can lead to treatment delays and unfavorable outcomes (38). Cultural and socioeconomic factors may also impact an individual’s recognition of symptoms and the need to seek urgent medical attention. Previous studies have suggested that cultural and language barriers among
Low
1.15 0.95, 1.38
0.1476
Medium
1.04 0.90, 1.21
0.5665
High
1.12 0.96, 1.30
0.1451
Very High
Reference
Hospital region Northeast
Reference
Midwest
0.83 0.63, 1.11
0.2138
South
1.18 0.92, 1.52
0.1846
West
1.28 0.86, 1.90
0.2193
Hospital teaching status Continues
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Table 2. Continued OR Nonteaching Teaching
95% CI
P Value
Reference 0.79 0.63, 0.99
0.0362
Hospital bed size Low
Reference
Medium
1.28 0.78, 2.09
0.3361
High
1.03 0.63, 1.69
0.8973
Hospital location Rural Urban
Reference 1.14 0.71, 1.85
0.5872
OR, odds ratio; CI, confidence interval.
Hispanic patients lead to treatment delays, which can result in adverse outcomes (26). Correlations between treatment delays and inferior patient outcomes for individuals of Hispanic background and those insured by Medicaid are supported in studies of other neurosurgical procedures (9, 27). El-Sayed et al. (9) demonstrated that Medicaid patients had more postoperative complications and longer stays in the intensive care unit/hospital after neurosurgical procedures than privately insured patients. Similarly, Curry et al. (7) found that Medicaid patients endured the greatest inhospital mortality rates after craniotomy. Disease-specific determinants may vary according to ethnicity and/or socioeconomic background. When measuring clinical outcome as a primary end point, comorbidities and disease susceptibility can profoundly impact surgical results. These factors, however, are unlikely to confound measurements of latency to an emergent procedure. Delays in definitive treatment of acute, life-threatening conditions reflect deficiencies in systems of care. That these delays are associated with ethnic and socioeconomic determinants is concerning. There are limitations to this study, principally associated with the use of a large national discharge database. Residual bias and confounding may persist despite thorough adjustment in multivariable regression analyses. Coding inaccuracies can affect large, administrative databases. These imprecisions, however, have been shown to be minor (36). Not all US hospitals
are included in the database during the time period of study. Variations in geography, size, and academic status of the sample institutions could potentially affect results. However, the large scope and diversity of hospitals included in the database limit such an impact. The NIS does not provide clinical admission details, such as disease severity or Hunt and Hess grade. This limits the ability to control for such potentially confounding factors in a multivariable analysis. Furthermore, although it is unlikely that significant differences exist in time to presentation, the NIS lacks data regarding this variable. Finally, the use of mean income of zip code as a proxy for socioeconomic status may suffer from potential variation in status among inhabitants of a given region. CONCLUSION Our study suggests racial and socioeconomic disparities in times to treatment of aSAH. Notably, Hispanic patients and those insured with Medicaid experience prolonged times to clip ligation and coil embolization procedures. Future studies are necessary to identify the potential root causes of these inequalities. Ultimately, identifying the factors contributing to these delays could help standardize systems of care so that patients with aSAH experience more uniform treatment regardless of socioeconomic status and race to provide improved patient care and clinical outcomes. REFERENCES 1. Ackerman IN, Graves SE, Wicks IP, Bennell KL, Osborne RH: Severely compromised quality of life in women and those of lower socioeconomic status waiting for joint replacement surgery. Arthritis Reum 53:653-658, 2005. 2. Angeja BG, Gibson CM, Chin R, Frederick PD, Every NR, Ross AM, Stone GW, Barron HV: Predictors of door-to-balloon delay in primary angioplasty. Am J Cardiol 89:1156-1161, 2002. 3. Baskaya MK, Kelley R, Nanda A, Vannemreddy P: Delayed diagnosis of intracranial aneurysms: confounding factors in clinical presentation and the influence of misdiagnosis on outcome. South Med J 94:1108-1111, 2001. 4. Bazarian JJ, Pope C, McClung J, Cheng YT, Flesher W: Ethnic and racial disparities in emergency department care for mild traumatic brain injury. Acad Emerg Med 10:1209-1217, 2003. 5. Bekelis K, Missios S, Labropoulos N: Regional and socioeconomic disparities in the treatment of
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subarachnoid hemorrhage: clinical J Neurosurg 119:1627-1632, 2013.
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Conflict of interest statement: The authors declare that the article content was composed in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Received 21 February 2014; accepted 27 August 2014; published online 29 August 2014
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Citation: World Neurosurg. (2014) 82, 6:1071-1076. http://dx.doi.org/10.1016/j.wneu.2014.08.053
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