Journal of Vascular Surgery
Volume 49, Issue 5 , Pages 1166-1171, May 2009

Carotid artery stenting: Impact of practitioner specialty and volume on outcomes and resource utilization

Division of Vascular Surgery, The Surgical Outcomes Research Group, University of Medicine and Dentistry, New Jersey–Robert Wood Johnson Medical School, New Brunswick, NJ

Received 23 September 2008; accepted 2 December 2008. published online 23 March 2009.

Article Outline

Objectives

A variety of endovascular specialists perform carotid artery stenting (CAS), but little data exist on outcomes and resource utilization among these specialists. We analyzed differences in outcomes after CAS was performed by radiologists (RAD), cardiologists (CRD), and vascular surgeons (VAS).

Methods

Secondary data analysis of the 2005-2006 State Inpatient Databases for New Jersey were analyzed. Patients with elective admission to the hospital who had CAS procedure ≤2 days after admission were identified. CAS outcomes were analyzed with respect to practitioner specialty and volume, associated complications, and hospital resource utilization.

Results

We identified 625 CAS cases. CRD performed 378 (60.5%), VAS, 199 (31.8%); and RAD, 48 (7.7%). The overall stroke rate was 2.72% and by specialty was CRD, 3.17%; VAS, 2.01%, and RAD, 2.08% (P = .6880). The overall cardiac complication rate was 2.40% (CRD, 2.12%; VAS, 3.02%; RAD, 2.08%; P = .7899). Renal and pulmonary complications were low (0.64% and 0.32%, respectively). Mean hospital length of stay (LOS) in days was significantly shorter for VAS (1.64 ± 1.40) compared with RAD (2.83 ± 5.15; P = .0167) and had the same trend compared with CRD (2.14 ± 3.37; P = .0649). Intensive care unit (ICU) LOS was shorter for VAS (0.52 ± 0.97) and CRD (0.30 ± 0.71) than for RAD (2.12 ± 4.48; P < .0001). The mean total hospital cost was significantly greater for RAD ($20,987 ± $26,603) and CRD ($18,182 ± $16,364) than for VAS ($10,000 ± $4947; P = .0011 and P < .0001, respectively). ICU cost for RAD ($5963 ± $14,551) was also more than for VAS ($864 ± $1514; P < .0001) and CRD ($473 ± $1561; P < .0001). Medical supply costs were significantly greater for CRD ($8772 ± $9546) than for VAS ($3354 ± $2261; P < .0001) and RAD ($4964 ± $2595; P = .0142). Total hospital cost, LOS, and medical supplies were significantly lower for high-volume practitioners vs low-volume practitioners (P < .0001).

Conclusion

Stroke rates after CAS did not vary significantly among practitioner specialties. Hospital resource utilization did vary significantly: Vascular surgeons had the lowest utilization of hospital resources for performing CAS. High practitioner volume was associated with lower hospital resource utilization. Elucidation of factors creating resource utilization disparities among endovascular practitioners may lead to improved patient outcomes and permit significant future cost savings for carotid interventions.

 

Physician specialty training has been associated with the increased utilization of health care services and has also been linked to improved patient outcomes.1, 2 Carotid endarterectomy (CEA) has been established as the gold standard for the management of carotid disease, and CEA use has been shown to be influenced by specialty training.3, 4, 5, 6 At the same time, a dramatic influx of new technology has occurred for the treatment of carotid artery disease with the use of carotid artery stenting (CAS). CAS has been reported as noninferior to CEA and is currently performed by multiple specialties with varied backgrounds and training.7, 8, 9

Most CAS procedures are currently performed by cardiologists, but are also performed by radiologists and vascular surgeons.10 Each of these specialties has very different training processes, credentialing, and experience with patient care. It is possible that variations in training, background, and endovascular skill sets may lead to disparate outcomes. We evaluated CAS procedures performed in New Jersey and identified practitioners performing these procedures for the purpose of examining the influence of physician specialty and volume on outcomes and hospital resource utilization for CAS.

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Methods 

Data source 

Our data were derived from the publicly available New Jersey State Inpatient Database (NJ SID) for the years 2005 and 2006, developed as part of the Healthcare Cost and Utilization Project (HCUP) and sponsored by the Agency for Health Care Research and Quality (AHRQ).11 The NJ SID includes inpatient discharge abstracts from all acute care community hospitals in the state and contains >200 various data elements. Among them, we used for the analysis variables recognizing patient demographics (age, gender, and race), admission type, principal and secondary diagnoses, principal and secondary procedures, discharge status, physician (surgeon) identifier, number of days from admission to procedure, hospital length of stay (LOS), hospital charges and costs, and Elixhauser comorbidities. We also calculated the Elixhauser score as a sum of comorbidities presented for each observation. The HCUP Cost-to-Charge Ratio Files were used to convert charges to cost from the data.12

The Elixhauser Index13, 14, 15 was used to identify and adjust for comorbidities in the study cohort. Included in NJ SID data are 29 AHRQ comorbidity measures reported by Elixhauser et al.14 To identify these comorbidities, we used the Comorbidity Software developed as part of the HCUP.16 The performance of the Elixhauser comorbidity measures in predicting patient outcomes are well validated and have been established in the prediction of in-hospital and 1-year mortality among patients with congestive heart failure, diabetes mellitus, chronic renal failure, stroke, and patients undergoing coronary artery bypass grafting.15

Study population 

All patients who underwent CAS ≤2 days after elective admission to the hospital were analyzed. To identify these patients, we used the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) procedure code 00.63 in any of eight procedure positions in the data. Using the information about the number of days from admission to procedure, we selected only those cases where CAS was performed ≤2 days after admission to the hospital. This approach was used to increase the likelihood that elective cases, without a preexisting diagnosis of stroke, were selected for the study. Selecting only elective admissions and a short time to intervention decreases the likelihood of including patients with a pre-existing stroke.

To identify complications, we used the following ICD-9-CM diagnosis codes in the secondary diagnoses positions:

•For stroke: 997.00, 997.01, 997.02, 997.09, 433.11, 434.01, 434.11, and 434.91 (Table I);
Table I. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) stroke codes used
ICD-9 codesDescription of codes
997.01Central nervous system complication with cerebral hypoxia.
997.02Iatrogenic cerebrovascular infarction or hemorrhage; postoperative stroke.
997.00Nervous system complication, unspecified.
997.09Other nervous system complications.
433.11Occlusion and stenosis of the carotid artery with cerebral infarction.
434.01Cerebral thrombosis with infarction.
434.11Cerebral embolism with infarction.
434.91Cerebral artery occlusion, unspecified with infarction.

•For cardiac complications, including myocardial infarction: 997.1, 410.00-410.02, 410.10-410.12, 410.20-410.22, 410.30-410.32, 410.40-410.42, 410.50-410.52, 410.60-410.62, 410.70-410.72, 410.80-410.82, and 410.90-410.92;

•For pulmonary complications: 997.3, 518.4, and 518.5;

•For renal complications: 997.5.

To identify practitioner specialty, we used a variable in the NJ SID that identified operating physician. We then divided practitioners into three groups of physicians who perform CAS: radiologists, cardiologists, and vascular surgeons. The first step established procedures relevant to each of these specialties, and the ICD-9-CM codes for these procedures were identified as outlined in Table II. We subsequently analyzed the frequency and distribution of these procedures among practitioners from the data and then identified practitioner specialty by procedure types performed. Physicians had ≥80% of the codes in a specialty before they were classified. The six practitioners not identified using this approach were excluded from the analysis.

Table II. International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes used to determine specialist
ICD-9 codesDescription
Interventional cardiologist
37.21Right heart cardiac catheterization
37.22Left heart cardiac catheterization
Interventional radiologist
55.04Percutaneous nephrostomy with fragmentation
51.98Other percutaneous procedures on biliary tract
99.25Injection or infusion of cancer chemotherapeutic substance
44.44Transcatheter embolization for gastric or duodenal bleeding
Vascular surgeon
39.25Aorta-iliac-femoral bypass
38.44Resection of vessel with replacement aorta, abdominal
38.42Resection of vessel with replacement of other vessels of head and neck
38.12Carotid endarterectomy

To identify symptomatic patients, we used the following ICD-9-CM diagnosis codes: 435 (transient cerebral ischemia) and all subcodes, 437.1 (other generalized ischemic cerebrovascular disease), 781.4 (transient paralysis of limb), 362.34 (transient arterial occlusion, amaurosis fugax), and 368.12 (transient visual loss).

According to the number of CAS performed by each practitioner, we classified all operating physicians as high-volume, middle-volume, and low-volume specialists. The distribution of practitioners by CAS volume was highly skewed to the low levels; therefore, stratification by quartiles for the analysis was not used. Providers were ranked in order of increasing estimated total volume to create categoric variables for volume. Cutoff points were selected that approximated the experience and credentialing criteria of the lead-in for the Carotid Revascularization Endarterectomy vs. Stent Trial (CREST) to select a volume number of 20 as a high-volume specialist.17 The techniques used to develop volume thresholds are consistent with previous state and national investigations of the volume-outcomes effect for CEA and other surgical procedures.18, 19

The high-volume specialists (≥20 CAS procedures) represented the top 10% of practitioners and accounted for 51% of all CAS procedures. Physicians who performed 10 to 19 CAS were classified as middle-volume (10% practitioners, 19% of CAS procedures), and physicians with <10 procedures were recognized as low-volume (80% practitioners, 30% of CAS procedures).

Statistical analysis 

Analysis of the database and all statistics was done with SAS 9.1 software (SAS Institute, Cary, NC). To test the difference between groups, we used chi-square analysis with calculating odds ratio (OR) and 95% confidence interval (95% CI) for categorical variables, t test and analysis of variance (ANOVA) for continuous variables, and test for difference between two independent proportions when results were presented as percentage. All means are presented with standard deviations. A value of P < .05 was considered significant for all analyses.

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Results 

We identified 625 cases for CAS, of which cardiologists performed 378 (60.5%), followed by vascular surgeons with 199 (31.8%) and radiologists with 48 (7.7%). The mean age of those who were operated on by vascular surgeons (71.7 ± 8.98 years) was similar to the age of patients operated on by cardiologists (72.0 ± 9.51) and radiologists (71.3 ± 7.9; P = .8411). However, the mean Elixhauser score for the cardiologists' patients (2.3 ± 1.17) was greater than for those of vascular surgeons (1.8 ± 1.18; P < .001) and radiologists (1.5 ± 1.35; P < .0001); the last two groups did not differ significantly.

The overall stroke rate was 2.72% for all CAS performed, with no significant variation among specialties (cardiologists, 3.17%; vascular surgeons, 2.01%; radiologists, 2.08%; P = .6880). The overall cardiac complication rate after CAS was 2.40%, and we also did not find significant differences among physicians (cardiologists, 2.12%; vascular surgeons, 3.02%; radiologists, 2.08%; P = .7899). Renal and pulmonary complications were low in the study cohort (0.64% and 0.32%, respectively). Of the 625 CAS patients identified, only 22 (3.52%) were symptomatic. Because of the low incidence found and concerns about coding within the data set, subset analysis of symptomatic patients was not performed. Mean Elixhauser comorbidity scores were calculated for the three practitioner specialties. The patients were at 2.27 ± 1.17 for cardiologists, 1.78 ± 1.18 for vascular surgeons, and 1.47 ± 1.35 for radiologists. The cardiologists had patients with higher comorbidity scores (P < .001) compared with the other specialties.

Resource utilization differences are summarized in Table III. Mean hospital length of stay (LOS) in days was significantly shorter for vascular surgeons (1.64 ± 1.40) compared with radiologists (2.83 ± 5.15; P = .0167) and had the same trend compared with cardiologists (2.14 ± 3.37; P = .0649). ICU LOS was also shorter for vascular surgeons (0.52 ± 0.97) and cardiologists (0.30 ± 0.71) than for radiologists (2.12 ± 4.48; P < .0001). Mean total hospital cost was significantly greater for radiologists ($20,987 ± $26,603) and cardiologists ($18,182 ± $16,364, P = .0011) than for vascular surgeons ($10,000 ± $4947; P < .0001). ICU cost for radiologists ($5963 ± $14,551) was also larger than for vascular surgeons ($864 ± $1514; P < .0001) and cardiologists ($473 ± $1561; P < .0001). No differences were noted in the operating room costs among the three specialties. However, medical supply costs were significantly greater for cardiologists ($8772 ± $9546) than for vascular surgeons ($3354 ± $2261; P < .0001) and radiologists ($4964 ± $2595; P = .0142).

Table III. Hospital resource utilization for patients with carotid artery stenting performed by various specialists
VariableaPhysician specialty
Vascular surgeonCardiologistRadiologist
LOS, days
Hospital1.64±1.402.14±3.372.83±5.15
ICU0.52±0.970.30±0.712.12±4.48
Cost, $
Hospital10,000±494718,182±16,36420,987±26,603
ICU864±1514473±15615963±14,551
Operation room2837±26862781±24892461±2276
Medical supplies3354±22618772±95464964±2595

ICU, Intensive care unit; LOS, length of stay.

aData are presented as the mean ± standard deviation.

A subset analysis of this study failed to demonstrate significant differences for stroke by volume, although high-volume specialists appeared to have a lower stroke rate overall. Physicians who performed 20 to 35 procedures had a stroke rate of 1.92% compared with the 3.80% (P = 0.641) stroke rate for those who performed fewer than five procedures. This did not reach statistical significance and is likely based on the small sample size and lack of power for this type of analysis.

Significant differences existed in hospital resource utilization among specialists with different volumes (Table IV). A similar hospital LOS was found in patients from the high-volume (1.7 ± 1.4 days) and medium-volume (1.7 ± 1.2 days), which was significantly lower than the LOS in low-volume specialists (2.4 ± 4.1 days; P = .0182 and P = .0422, respectively). Total hospital costs for high-volume specialists ($13,193 ± $9095) did not differ significantly from costs for medium-volume specialists ($8442 ± $3983; P = .0971) but were significantly lower than for low-volume specialists ($19,325 ± $19,236; P = .004 and P < .0001, respectively). Similar to total hospital cost, costs of medical supplies in high- and medium-volume specialists ($4496 ± $5692 and $3060 ± $2372, respectively; P = .3056) were significantly lower than in low-volume specialists ($8800 ± $9043; P < .0001 for both).

Table IV. Hospital resource utilization for patients with carotid artery stenting by specialist volume
VariableaPhysician volume
High (≥20)Medium (10-19)Low (<10)
Hospital LOS, days1.7±1.41.7±1.22.4±4.1
Cost, $
Hospital13,193±90958442±398319,235±19,236
Medical supplies4496±56923060±23728800±9043

LOS, Length of stay.

aData are presented as the mean ± standard deviation.

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Discussion 

Multiple trials and registries evaluating CAS and CEA have demonstrated noninferiority of CAS as well as inferior results.7, 8, 20 Explanations for these variations in outcomes for CAS may include differences in practice patterns, experience or training of the operator, patient selection, and the learning curve associated with CAS. This study has evaluated the influence of specialty (cardiology, radiology, and vascular surgery) and procedure volume on outcomes for CAS in New Jersey.

Within vascular surgery, surgeon volume and specialization have been correlated with improved outcomes for patients undergoing CEA and abdominal aortic aneurysm repair.6 The influence of volume has been further evaluated for CEA, using population data and statistical modeling, and a significant volume effect for death has been demonstrated.21 Surgical mortality has varied significantly across hospitals and surgeons, more so than would be predicted by chance alone or differences in case-mix.18 Rosenthal et al1 concluded that patients undergoing abdominal aortic aneurysm repair performed by a specialized team have significantly better outcomes than those whose surgery is done by general surgeons.

Other areas within medicine have also evaluated the differences between practitioners and their associated outcomes. Greenfield et al22 evaluated resource utilization for medical specialties for the management of general medical patients and demonstrated that increased usage was independently related to specialty.22 Additional analyses have demonstrated that subspecialists use more resources than generalists, whereas other authors suggest that practice organization may also have a significant influence on physician resource utilization.23, 24 Although a large body of research has suggested the importance of specialty training, the true clinical mechanisms underlying variation in surgical mortality remain largely unknown.25

This study has demonstrated no significant difference in the rate of stroke or complications after CAS by physician specialty. Other authors have suggested a significant learning curve is associated with performing CAS. Mas et al20 referred to the “learning curve” for CAS as a reason for the inferior results associated with CAS by the Endarterectomy Versus Angioplasty in Patients With Symptomatic Severe Carotid Stenosis (EVA-3S) investigators. However, a subanalysis of that study demonstrated that most of the strokes in CAS patients occurred with the interventionalists who had the most experience doing CAS. We did not find this trend. As well, it has been well established that the risk associated with CEA varies among surgeons,6, 18 and it is likely that CAS has similar risks associated with the operator.

Others have demonstrated the center's experience is associated with peri-interventional stroke and death. Theiss et al26 demonstrated that neurologic complications or death, or both, occurred 1.76 times more often in the first 50 interventions of an institution. Their findings support the need for dedicated training and strict credentialing rules for CAS.26 As well, the CREST trial found that 94 operators who had performed <15 CAS procedures had a stroke/death rate of 7.1% compared with 3.7% for the nine operators who had performed ≥15 CAS procedures.17

Our analysis was unable to demonstrate a significant difference for stroke rates based on practitioner volume, although this finding may be biased by the relatively small sample size and the rare event of stroke. No differences were noted for stroke or other complications, but we did find an association between experience and specialty with resource utilization for CAS.

Outcomes for CAS were similar for all practitioners, but resource utilization varied significantly. Reasons for this variation may be predicated on discrepancies in training, medical background, in-hospital work up, and endovascular skill sets. Kilaru et al27 demonstrated CEA was cost-saving compared to CAS owing to the higher rate of stroke with CAS and the high cost of stents. We have demonstrated that CAS cost can also vary significantly based on the practitioner. Medical supply costs were significantly greater for cardiologists compared with the other groups. Reasons for this may include the number of catheters and the types of equipment used by cardiologists. Beyond supply costs, hospital resource utilization also varied by specialty. Vascular surgeons as a whole had the shortest LOS after CAS intervention and the lowest ICU costs. Previous studies looking at specialties in medicine found different utilization, and increased utilization was also independently related to specialty.22

It is also possible that the disparities noted for CAS may be influenced by volume, experience, and credentialing. Studies of multiple procedures have demonstrated that surgeons with higher volumes demonstrated consistently lower mortality and morbidity rates than surgeons with low volumes.6, 28, 29 It has also been demonstrated that vascular surgeons with basic catheter and guidewire skills can become credentialed to perform CAS with 10 to 30 procedures.17 A subset analysis of this study failed to demonstrate significant differences for outcomes based on volume, but this may be secondary to the sample size and power required for this type of analysis.

A subset analysis of resource utilization according to practitioner volume, regardless of specialty, did demonstrate significant differences in resource utilization between high- and low-volume practitioners. High-volume practitioners used significantly fewer medical supplies and significantly less hospital resources overall. These data suggest that practitioners with greater experience and larger procedural volume may have more efficient use of resources to streamline and accomplish the same procedure.

Further analysis to elucidate disparities between practitioner specialties was performed. Elixhauser comorbidities were analyzed on patients treated by the three specialties. Significant differences in comorbidities were found among the patients of cardiologists, vascular surgeons, and radiologists. This analysis indicates that the cardiology cohort had a greater number of comorbidities, which may explain variations in greater length of stay but fails to fully elucidate the medical supply utilization variation of the CAS procedure itself.

To further evaluate higher utilization by cardiologists, secondary procedures, including cardiac catheterization and percutaneous transluminal angioplasty, were analyzed. There was not a significant increase in secondary procedures performed by cardiologists compared with the other specialties. Cardiac interventions were the lowest in the vascular surgery group at 1.1% and highest in the cardiology group at 5.1%. To discern if secondary cardiac interventional cases affected our results, we excluded them from the data set and performed a subset analysis. The new results were similar to the previous ones, and no significant changes in utilization were noted. Thus, reasons for variation among providers with different specialties and volume still remains unclear.

Limitations for this study include that the NJ SID database does not contain patients from military hospitals or Veterans Affairs medical centers. The potential for inclusion bias based on limited coding schemes for the many clinical entities cannot be entirely excluded nor can confounding by indication of the procedures. Classification as elective vs nonelective was based on the HCUP variable for admission type.

Another study limitation is the coding used for the diagnosis of stroke. The NJ SID is an administrative discharge data set based on billing. The data contained in the NJ SID and other discharge data sets are limited by the coding schemes created by AHRQ and ICD-9-CM codes. It is possible that the definition of stroke and coding may vary within the data set and may vary between institutions and hospital coders. We expanded the stroke codes used in this study with the rational that stroke is an acute diagnosis code and by selecting elective carotid interventions ≤2 days of admission, patients were unlikely to carry an acute stroke codes in their administrative discharge data unless this event occurred during that hospitalization and likely in association with a carotid intervention. Our group has previously reported this methodology for the evaluation of stroke after carotid interventions.30

Also possible is a type II error in evaluating the rates of stroke for different practitioners due to the relativity small sample size for the evaluation of a rare complication. Finally, we were not able to discern symptomatic patients within the data set due to coding limitations. We acknowledge that there is a trade-off in using administrative data compared with smaller cohorts with more refined clinical information. Both types of studies have drawbacks and strengths, but we believe that administrative databases provide valuable population-based information on carotid procedures, outcomes, and resource utilization.

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Conclusions 

Physician specialty did not significantly influence patient outcomes or complications. We have demonstrated that hospital resource utilization did vary significantly by specialty, with vascular surgeons having the lowest utilization of hospital resources for CAS. As well, we have demonstrated that high-volume practitioners used significantly fewer medical supplies and had lower hospital resource utilization for performing CAS regardless of specialty. The reasons for these disparities remain unclear, and further analyses examining possible explanations for these discrepancies may offer future cost savings and increased standardization of CAS.

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Author contributions 


Conception and design: TV

Analysis and interpretation: TV, VD

Data collection: VD

Writing the article: TV

Critical revision of the article: TV, PH, AG

Final approval of the article: TV

Statistical analysis: TV, VD

Obtained funding: Not applicable

Overall responsibility: TV

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 Competition of interest: none.

PII: S0741-5214(08)02130-7

doi:10.1016/j.jvs.2008.12.006

Journal of Vascular Surgery
Volume 49, Issue 5 , Pages 1166-1171, May 2009

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