The Pennsylvania State University

College of Medicine

Department of Public Health Sciences

IMPACT OF SURGEON AND HOSPITAL VOLUME ON MORTALITY, LENGTH OF

STAY, AND COST OF PANCREATICODUODENECTOMY

A Thesis in

Public Health Sciences

by

Laura M. Enomoto

© 2014 Laura M. Enomoto

Submitted in Partial Fulfillment

of the Requirements

for the Degree of

Master of Science

May 2014

ii

The thesis of Laura M. Enomoto was reviewed and approved* by the following:

Christopher S. Hollenbeak

Professor of Surgery and Public Health Sciences

Thesis Adviser

Niraj J. Gusani

Associate Professor of Surgery, Medicine, and Public Health Sciences

Douglas L. Leslie

Professor of Psychiatry and Public Health Sciences

Director, Master of Science in Public Health Sciences Program

* Signatures are on file in the Graduate School

iii

ABSTRACT

Improved mortality rates following pancreaticoduodenectomy by high volume surgeons and

hospitals have been well documented, but less is known about the impact of such volumes on

length of stay and cost. This study uses data from the Healthcare Cost and Utilization Project

(HCUP) National Inpatient Sample (NIS) to examine the effect of surgeon and hospital volume

on mortality, length of stay, and cost following pancreaticoduodenectomy while controlling for

patient specific factors. Data included 3,137 pancreaticoduodenectomies from the NIS

performed between 2004-2008. Using logistic and generalized linear regression models, the

relationship between surgeon volume, hospital volume, and post-operative mortality, length of

stay, and cost was estimated while accounting for patient factors. Propensity score matching was

used to address potential covariate imbalance. After controlling for patient characteristics,

patients of high volume surgeons at high volume hospitals had a significantly lower risk of

mortality compared to any other group (2.7% vs. 6.0%, p = 0.016). Patients of high volume

surgeons at high volume hospitals also had a five day shorter length of stay (p < 0.001), as well

as significantly lower costs ($12,159, p < 0.001). The results of this study, which simultaneously

accounted for surgeon volume, hospital volume, and potential confounding patient

characteristics, suggest that both surgeon and hospital volume have a significant effect on

outcomes following pancreaticoduodenectomy, affecting not only mortality rates but also lengths

of stay and costs.

iv

TABLE OF CONTENTS

List of Tables ...................................................................................................................................v

List of Figures ................................................................................................................................ vi

Acknowledgements ....................................................................................................................... vii

Introduction ......................................................................................................................................1

Methods............................................................................................................................................2

Data ............................................................................................................................................2

Statistical Analysis .....................................................................................................................5

Results ..............................................................................................................................................7

Patient Characteristics ................................................................................................................7

Mortality ....................................................................................................................................9

Length of Stay ..........................................................................................................................12

Hospital Costs ..........................................................................................................................15

Propensity Score Matching ......................................................................................................18

Discussion ......................................................................................................................................20

References ......................................................................................................................................24

v

LIST OF TABLES

Table 1. Summary statistics of patients undergoing pancreaticoduodenectomy

stratified by surgeon and hospital volume (Low volume, LV; high volume, HV) ..........................8

Table 2. Results of logistic regression model of effect of surgeon and hospital

volume on mortality, controlling for other covariates ...................................................................11

Table 3. Results of generalized linear model of effect of surgeon and hospital

volume on length of stay, controlling for other covariates ............................................................14

Table 4. Results of generalized linear model of effect of surgeon and hospital

volume on cost, controlling for other covariates ...........................................................................17

vi

LIST OF FIGURES

Figure 1. Determination of study cohort ..........................................................................................3

vii

ACKNOWLEDGEMENTS

This work has previously been published in edited form (Enomoto LM, Gusani NJ, Dillon PW,

Hollenbeak CS. Impact of Surgeon and Hospital Volume on Morality, Length of Stay, and Cost

of Pancreaticoduodenectomy. Journal of Gastrointestinal Surgery: Official Journal of the

Society for Surgery of the Alimentary Tract. 2014 April; 18(4): 690-700.). The final publication

is available at http://dx.doi.org/10.1007/s11605-013-2422-z

1

INTRODUCTION

Population studies have demonstrated an association between procedure volume and

patient outcomes for complex surgical procedures including pancreaticoduodenectomy.1-3

When

compared with high volume (HV) hospitals, data have shown that low volume (LV) hospitals

have poorer operative outcomes and lower long-term survival.4,5

Previous studies have also

suggested that surgeon volume is related to post-operative mortality following

pancreaticoduodenectomy with HV surgeons demonstrating lower in-hospital mortality.6 As a

result of these studies, there is a growing trend towards referral of patients to HV centers for their

care.7

Patient-related factors also contribute to poor post-operative outcomes. Recent studies

have identified racial minorities and the underinsured as less likely to receive their

pancreaticoduodenectomy at HV institutions, despite efforts to encourage centralization.8,9

Notably, even with the trend toward centralized delivery of complex operations, patients with

more comorbid disease may have worse surgical outcomes, independent of the expertise of the

surgeon.10

Post-operative outcomes arise from a complex interplay between surgeon expertise,

hospital volume, and patient factors.

While the relationship between volume and mortality has been extensively studied, the

relationship between volume and other outcomes, such as length of stay (LOS) and costs, has not

been as well documented. Therefore, the purpose of this study was to examine the effects of

surgeon and hospital volume on outcomes for pancreaticoduodenectomy using data from the

Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS).

2

METHODS

Data

This was a retrospective cohort study that included patients in the NIS data set from 2004

to 2008 who underwent pancreaticoduodenectomy. The NIS is the largest publically available,

all-payer inpatient care database in the United States, constituting 20% of hospital discharges,

and including both academic and specialty hospitals.11

There were 3,290 patients in the NIS

with a primary International Classification of Diseases, 9th

Revision, Clinical Modification (ICD-

9-CM) procedure code for pancreaticoduodenectomy (52.7). After excluding pediatric and

trauma patients as well as 140 patients for missing covariates (Figure 1), 3,137 patients were

included in the final analysis. Due to the large number of patients with a missing race or

admission source variable (N = 559 and N = 507, respectively), the analysis was performed with

missing race and admission source as additional covariates rather than excluding those patients

altogether from the analysis.

3

Figure 1: Determination of study cohort.

4

To evaluate volume, the cohort was categorized into groups for purposes of comparison

before any volume-outcome data analysis was performed. Surgeons were classified as either HV

if they performed ≥5 pancreaticoduodenectomies in a given year or LV if they performed <5

pancreaticoduodenectomies in a given year as previously described.1,6

Using the Leapfrog cut-

off for high-risk surgical procedures, hospitals were defined as HV if a center performed ≥ 11

pancreaticoduodenectomies per year and LV if they performed <11

pancreaticoduodenectomies.12

Analyses controlled for several patient level variables, including demographics (age,

gender, and race/ethnicity), diagnosis of cancer, co-morbidities (history of acute myocardial

infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, chronic

obstructive pulmonary disease, peptic ulcer disease, mild liver disease, moderate or severe liver

disease, diabetes with and without complications, and renal disease), primary payer (Medicare,

Medicaid, commercial, and other), and type of admission (emergent, urgent, and elective). The

analyses also controlled for region of the country (northeast, midwest, south, and west), teaching

hospital status, and year of operation (2004 through 2008). Diagnosis of cancer was determined

using ICD-9-CM diagnosis codes (151.0 – 197.8, 200.00 – 209.30, 230.7 – 258.0). Co-

morbidities were assigned using ICD-9-CM codes as previously described.13

Most hospitals

appeared in the data set in one (64.3%) or two (26.6%) years.

Three outcomes were studied: mortality, LOS, and cost. Mortality was assessed as in-

hospital mortality. LOS was measured as the total length of admission to the hospital where the

pancreaticoduodenectomy was performed. Cost analysis was performed from the perspective of

the hospital and costs were estimated using a cost to charges ratio (CCR) methodology. This is a

standard accounting technique where costs are estimated as a percentage of hospital charges. In

5

this methodology, individual hospital departments calculate a yearly CCR. The next year,

departmental charges are multiplied by the previous year’s CCR and used as an estimate of costs.

The total cost for an admission is the sum of all departmental costs. Although this only provides

an estimate of costs, previous research has shown that CCR’s are an acceptable approach for

estimating costs across hospitals for patients with a common diagnosis-related group.14

Costs

were inflation adjusted to 2008 US dollar values using the medical care component of the

consumer price index.

Statistical Analysis

Statistical analysis was performed primarily to determine whether surgeon and hospital

volume were significantly associated with outcomes after controlling for important covariates.

Univariate analysis using 2 tests for binary and categorical variables was performed to

determine whether there were differences in patient characteristics across surgeon and hospital

volume groups. Although weights are available to produce nationally representative descriptive

statistics, our interest was not in producing nationally representative estimates. Therefore, in our

descriptive statistics and in our multivariate models described subsequently, we did not apply

national or regional weights.

Logistic regression was used to model the effects of surgeon and hospital volume on in-

hospital mortality after controlling for patient, procedure, and provider characteristics. LOS and

costs were fit to generalized linear regression models assuming a gamma family of distributions

and log link function. These models were chosen because LOS and cost data were highly skewed

and did not meet the normality assumption of the classical linear model. We report the marginal

6

effects from the generalized linear models, which show the effect of a one-unit change in the

independent variable on the outcome.

If a significant imbalance in patient covariates existed between different surgeon and

hospital volumes, then a regression model may not adequately control for covariates. Therefore,

a propensity score matching analysis that dealt with potential covariate imbalance was

performed. The propensity score models for mortality, LOS, and cost were estimated using

logistic regression with HV surgeons at HV hospitals as the dependent variable and covariates as

previously described. Using the estimated propensity scores from this model, patients in the HV

surgeon, HV hospital group were matched 1:1 to patients in the other groups using a k-nearest

neighbor match with a max-min common support restriction.

The primary metric for the propensity score analysis was the average effect of treatment

on the treated (ATT). For all three outcomes, this is the difference between the outcome for the

patient treated by a HV surgeon in a HV hospital and the outcome for the patients in the three

remaining groups. To deal with the uncertainty induced by both the selection process and the

data, a standard bootstrapping algorithm was used to compute 95% confidence intervals. All

reported inferences for the ATT were based on 1000 bootstrap replicates. All statistical analyses

were performed using STATA (version 12.1, StataCorp LLP, College Station, TX) and the

psmatch2 routines.15

Statistical significance for all analyses was defined as a p-value < 0.05.

7

RESULTS

Patient Characteristics

There were 3,137 pancreaticoduodenectomies recorded in the NIS database between

2004 and 2008 after excluding 153 patients. Data from all participating institutions in the

database were included. Of these procedures, 866 were performed by LV surgeons at LV

hospitals, 451 were performed by LV surgeons at HV hospitals, 179 were performed by HV

surgeons at LV hospitals, and 1,641 were performed by HV surgeons at HV hospitals.

Demographic characteristics of patients who underwent pancreaticoduodenectomy stratified by

surgeon and hospital volume and are shown in Table 1. Compared with other groups, patients

who underwent pancreaticoduodenectomy by HV surgeons at HV hospitals were more likely to

be diagnosed with a disease other than cancer (p = 0.036), elective admissions (p < 0.001), and

treated in a teaching hospital (p < 0.001).

8

Table 1: Summary statistics of patients undergoing pancreaticoduodenectomy stratified by

surgeon and hospital volume. (Low volume, LV; high volume, HV)

LV Surgeon HV Surgeon

LV Hospital HV Hospital LV Hospital HV Hospital

Variable (N=866) (N=451) (N=179) (N=1,641) P-Value

Age

0.374

18-55 26.0% 22.4% 17.9% 24.0%

56-65 25.8% 26.6% 31.3% 27.0%

66-75 29.9% 28.6% 31.3% 30.0%

76+ 18.4% 22.4% 19.6% 19.0%

Female 48.6% 46.3% 45.8% 50.9% 0.226

Race/Ethnicity

< 0.001

White 55.8% 62.3% 68.7% 66.0%

Black 10.0% 8.2% 14.5% 5.0%

Hispanic 7.4% 10.9% 1.1% 6.9%

Other 5.7% 6.9% 2.8% 3.8%

Missing 21.1% 11.8% 12.8% 18.3%

Any Diagnosis of Cancer 86.7% 86.0% 85.5% 82.6% 0.036

Co-morbidities

Acute Myocardial Infarction 4.0% 4.9% 5.6% 4.3% 0.764

Congestive Heart Failure 3.7% 3.8% 4.5% 2.4% 0.159

Peripheral Vascular Disease 2.4% 0.9% 2.2% 1.7% 0.238

Cerebrovascular Disease 1.8% 0.9% 0.6% 1.2% 0.300

COPD 16.2% 10.0% 10.6% 11.3% 0.001

Peptic Ulcer Disease 4.5% 3.3% 1.1% 1.6% < 0.001

Mild Liver Disease 1.5% 1.8% 0.6% 1.5% 0.726

Moderate/Severe Liver Disease 0.8% 1.3% 1.1% 0.6% 0.459

Diabetes 23.9% 24.2% 27.4% 19.4% 0.007

Diabetes with Complications 1.6% 0.9% 0.0% 1.2% 0.289

Renal Disease 1.8% 2.9% 0.6% 0.7% 0.002

Payer

0.005

Medicare 47.9% 51.9% 48.0% 49.5%

Medicaid 7.9% 7.3% 3.4% 5.7%

Commercial 37.6% 34.1% 46.4% 40.0%

Other 6.6% 6.7% 2.2% 4.8%

9

Table 1 (continued): Summary statistics of patients undergoing pancreaticoduodenectomy.

LV Surgeon HV Surgeon

LV Hospital HV Hospital LV Hospital HV Hospital

Variable (N=866) (N=451) (N=179) (N=1,641) P-Value

Admission Source

< 0.001

ER 18.9% 13.3% 3.9% 2.8%

Other hospital 1.8% 5.1% 2.2% 2.4%

Long term care 0.7% 0.4% 0.0% 0.5%

Other 68.2% 65.2% 74.3% 75.3%

Missing 10.3% 16.0% 19.6% 19.0%

Admission Type

< 0.001

Elective 67.3% 66.5% 86.0% 87.6%

Urgent 10.4% 14.2% 9.5% 7.5%

Emergent 22.3% 19.3% 4.5% 4.9%

Teaching hospital 56.7% 91.4% 73.7% 93.4% < 0.001

Region

< 0.001

Northeast 29.0% 28.8% 24.6% 29.5%

Midwest 8.0% 20.6% 17.9% 9.6%

South 42.7% 27.5% 38.0% 25.9%

West 20.3% 23.1% 19.6% 35.0%

Year

< 0.001

2004 21.6% 29.9% 25.1% 18.3%

2005 17.6% 19.1% 10.6% 18.3%

2006 21.7% 12.9% 24.0% 15.1%

2007 18.4% 17.3% 20.7% 24.3%

2008 20.8% 20.8% 19.6% 24.1%

Mortality

Table 2 provides the results of the logistic regression model of in-hospital mortality

controlling for covariates. There was a significant difference in mortality between LV surgeons

at LV hospitals and LV surgeons at HV hospitals, as well as HV surgeons at HV hospitals (OR

0.54, p = 0.018; and OR 0.32, p < 0.001; respectively). Additionally, several other patient

characteristics were associated with increased mortality. Patients who were 76 years of age or

older had an almost three times higher odds of mortality compared to those of younger age (OR

10

2.76, p = 0.003). Several comorbidities were significantly associated with greater risk of

mortality, including a history of acute myocardial infarction, congestive heart failure, and

cerebrovascular disease. Diabetes and PVD were significantly associated with a lower risk of

mortality. Urgent and emergent admissions had significantly higher odds of mortality compared

to patients who were admitted electively (OR 1.77, p = 0.033; and OR 2.07, p = 0.04;

respectively). Other covariates were not significantly associated with risk of mortality.

11

Table 2: Results of logistic regression model of effect of surgeon and hospital volume on

mortality, controlling for other covariates.

95% Confidence Interval

Variable Odds Ratio Lower Upper P-value

Surgeon and Hospital Volume

Low/Low Reference

Low/High 0.54 0.33 0.90 0.018

High/Low 0.56 0.27 1.19 0.130

High/High 0.32 0.20 0.49 < 0.001

Age

18-55 Reference

56-65 1.07 0.60 1.89 0.825

66-75 1.24 0.64 2.41 0.524

76+ 2.76 1.41 5.37 0.003

Female 1.01 0.73 1.40 0.958

Race/Ethnicity

White Reference

Black 1.39 0.79 2.45 0.250

Hispanic 1.26 0.69 2.30 0.444

Other 0.52 0.20 1.38 0.187

Missing 0.76 0.45 1.28 0.300

Any Diagnosis of Cancer 1.68 0.95 2.98 0.074

Co-morbidities

Acute Myocardial Infarction 2.35 1.29 4.26 0.005

Congestive Heart Failure 3.35 1.84 6.08 < 0.001

Peripheral Vascular Disease 0.12 0.02 0.97 0.047

Cerebrovascular Disease 3.89 1.58 9.62 0.003

COPD 1.21 0.77 1.91 0.401

Peptic Ulcer Disease 1.73 0.82 3.68 0.152

Mild Liver Disease 2.40 0.95 6.11 0.066

Moderate/Severe Liver Disease 2.88 0.76 10.90 0.120

Diabetes 0.57 0.37 0.88 0.012

Diabetes with Complications 0.98 0.26 3.67 0.977

Renal Disease 1.79 0.65 4.96 0.262

Payer

Medicare Reference

Medicaid 1.28 0.60 2.75 0.525

Commercial 0.65 0.38 1.11 0.118

Other 1.11 0.49 2.48 0.808

12

Table 2 (continued): Results of logistic regression model of effect of surgeon and hospital

volume on mortality, controlling for other covariates.

95% Confidence Interval

Variable Odds Ratio Lower Upper P-value

Admission Source

ER Reference

Other hospital 1.41 0.50 3.97 0.517

Long term care 0.99 0.11 8.96 0.995

Other 1.04 0.50 2.17 0.908

Missing 1.04 0.45 2.43 0.924

Admission Type

Elective Reference

Urgent 1.77 1.05 2.98 0.033

Emergent 2.07 1.04 4.12 0.040

Teaching hospital 0.71 0.48 1.06 0.096

Region

Northeast Reference

Midwest 1.00 0.53 1.88 0.993

South 0.97 0.63 1.48 0.880

West 0.88 0.53 1.47 0.633

Year 0.95 0.83 1.09 0.459

Length of Stay

The results of a generalized linear regression model of LOS controlling for covariates are

shown in Table 3. Patients treated by LV surgeons at HV hospitals, HV surgeons at LV

hospitals, and HV surgeons at HV hospitals had a significantly shorter LOS relative to patients

treated by LV surgeons at LV hospitals (-2.44 days, p < 0.001; -2.97 days, p < 0.001; and -5.65

days, p < 0.001; respectively). A significantly increased LOS was found in patients between 66

and 75 years of age and over 76 years of age compared to those of younger age (1.54 days, p =

0.032; and 2.85 days, p = 0.001; respectively). Race/ethnicity was significantly associated with

LOS, with Hispanic and other race/ethnicity groups having significantly longer stays relative to

13

patients of white race (2.53 days, p = 0.004; and 4.25 days, p < 0.001; respectively). Patients

with congestive heart failure had significantly increased LOS (2.93 days, p = 0.024) while

patients with diabetes had significantly decreased stays compared to those without those co-

morbidities (-1.67 days, p < 0.001). Urgent and emergent admissions were associated with a

longer LOS relative to elective admissions (4.91 days, p < 0.001; and 7.47 days, p < 0.001;

respectively). Patients treated at teaching hospitals had slightly longer stays than patients treated

at non-teaching hospitals (1.19 days, p = 0.024). Gender, cancer diagnosis, payer, admission

source, and region of the country were not significantly associated with LOS.

14

Table 3: Results of generalized linear model of effect of surgeon and hospital volume on length

of stay, controlling for other covariates.

Marginal 95% Confidence Interval

Variable Effect Lower Upper P-value

Surgeon and Hospital Volume

Low/Low Reference

Low/High -2.44 -3.59 -1.30 < 0.001

High/Low -2.97 -4.42 -1.51 < 0.001

High/High -5.65 -6.70 -4.60 < 0.001

Age

18-55 Reference

56-65 0.93 -0.17 2.04 0.098

66-75 1.54 0.13 2.95 0.032

76+ 2.85 1.21 4.50 0.001

Female -0.38 -1.12 0.36 0.313

Race/Ethnicity

White Reference

Black 0.86 -0.69 2.41 0.278

Hispanic 2.53 0.81 4.24 0.004

Other 4.25 2.00 6.49 < 0.001

Missing 0.09 -0.97 1.14 0.873

Any Diagnosis of Cancer -0.47 -1.54 0.60 0.387

Co-morbidities

Acute Myocardial Infarction 0.70 -1.20 2.60 0.469

Congestive Heart Failure 2.93 0.38 5.47 0.024

Peripheral Vascular Disease -0.94 -3.59 1.70 0.486

Cerebrovascular Disease 2.66 -1.20 6.52 0.177

COPD 0.43 -0.74 1.60 0.469

Peptic Ulcer Disease 1.89 -0.71 4.49 0.154

Mild Liver Disease 2.83 -0.75 6.42 0.122

Moderate/Severe Liver Disease 0.27 -3.97 4.50 0.902

Diabetes -1.67 -2.53 -0.82 < 0.001

Diabetes with Complications -1.56 -4.67 1.56 0.327

Renal Disease 0.84 -2.63 4.31 0.635

Payer

Medicare Reference

Medicaid -0.92 -2.64 0.81 0.297

Commercial -0.73 -1.84 0.38 0.195

Other -0.49 -2.32 1.34 0.600

15

Table 3 (continued): Results of generalized linear model of effect of surgeon and hospital

volume on length of stay, controlling for other covariates.

Marginal 95% Confidence Interval

Variable Effect Lower Upper P-value

Admission Source

ER Reference

Other hospital -0.40 -3.32 2.53 0.791

Long term care 0.94 -4.92 6.80 0.753

Other -1.74 -4.03 0.56 0.139

Missing -0.89 -3.15 1.36 0.438

Admission Type

Elective Reference

Urgent 4.91 3.18 6.64 < 0.001

Emergent 7.47 4.77 10.18 < 0.001

Teaching hospital 1.19 0.16 2.22 0.024

Region

Northeast Reference

Midwest -1.16 -2.46 0.14 0.080

South -0.61 -1.60 0.37 0.222

West 0.81 -0.27 1.89 0.141

Year -0.54 -0.86 -0.23 0.001

Hospital costs

Results of a generalized linear regression model of cost are presented in Table 4. Patients

treated by LV surgeons at LV hospitals showed a significant increase in cost compared to

patients treated by LV surgeons at HV hospitals, HV surgeons at LV hospitals, and HV surgeons

at HV hospitals (-$4,800, p = 0.009; -$9,087, p < 0.001; and -$12,275, p < 0.001; respectively).

A significantly increased cost was associated with patients over 76 years of age relative to those

of younger age ($5,630, p = 0.023). Women had a significantly lower cost compared to men (-

$3,406, p = 0.003). Similar to the trends observed with LOS, Hispanic and other race/ethnicity

groups had significantly higher costs of $8,853 and $16,100, respectively compared to white race

16

(p = 0.001 and p < 0.001, respectively). Patients with a history of acute myocardial infarction

and congestive heart failure had increased costs ($7,650, p = 0.021; and $11,346, p = 0.007;

respectively) while diabetic patients had lower costs relative to patients without those co-

morbidities (-$5,870, p < 0.001). Urgent and emergent cases had higher costs than elective cases

($8,421, p = 0.001; and $18,223, p < 0.001; respectively), as did teaching hospitals and hospitals

in the Midwest and South. Diagnosis of cancer, payer, admission source, and year of operation

were not significant predictors of costs.

17

Table 4: Results of generalized linear model of effect of surgeon and hospital volume on cost,

controlling for other covariates.

Marginal 95% Confidence Interval

Variable Effect Lower Upper P-value

Surgeon and Hospital Volume

Low/Low Reference

Low/High -4,800 -8,382 -1,217 0.009

High/Low -9,087 -13,355 -4,820 < 0.001

High/High -12,275 -15,444 -9,107 < 0.001

Age

18-55 Reference

56-65 1,780 -1,550 5,110 0.295

66-75 3,112 -1,131 7,354 0.151

76+ 5,630 774 10,486 0.023

Female -3,406 -5,656 -1,156 0.003

Race/Ethnicity

White Reference

Black 3,062 -1,729 7,852 0.210

Hispanic 8,853 3,429 14,276 0.001

Other 16,100 8,667 23,534 < 0.001

Missing 4,057 624 7,490 0.021

Any Diagnosis of Cancer -1,192 -4,451 2,067 0.473

Co-morbidities

Acute Myocardial Infarction 7,650 1,162 14,138 0.021

Congestive Heart Failure 11,346 3,055 19,636 0.007

Peripheral Vascular Disease -163 -8,667 8,340 0.970

Cerebrovascular Disease 7,059 -4,677 18,795 0.238

COPD 2,486 -1,144 6,116 0.180

Peptic Ulcer Disease 3,147 -4,456 10,750 0.417

Mild Liver Disease 9,803 -1,635 21,242 0.093

Moderate/Severe Liver Disease 12,330 -4,062 28,722 0.140

Diabetes -5,870 -8,411 -3,329 < 0.001

Diabetes with Complications 738 -10,005 11,481 0.893

Renal Disease 2,704 -7,991 13,400 0.620

Payer

Medicare Reference

Medicaid 291 -5,288 5,870 0.919

Commercial -1,763 -5,145 1,620 0.307

Other -1,765 -7,296 3,765 0.532

18

Table 4 (continued): Results of generalized linear model of effect of surgeon and hospital

volume on cost, controlling for other covariates.

Marginal 95% Confidence Interval

Variable Effect Lower Upper P-value

Admission Source

ER Reference

Other hospital -973 -9,858 7,912 0.830

Long term care 6,590 -12,746 25,926 0.504

Other -3,067 -10,004 3,870 0.386

Missing -3,704 -10,425 3,016 0.280

Admission Type

Elective Reference

Urgent 8,421 3,525 13,316 0.001

Emergent 18,223 10,072 26,374 < 0.001

Teaching hospital 4,869 1,795 7,943 0.002

Region

Northeast Reference

Midwest -4,638 -8,475 -801 0.018

South -3,170 -6,117 -223 0.035

West -904 -4,122 2,314 0.582

Year -600 -1,543 344 0.213

Propensity score matching

The results from multivariate models were confirmed by the propensity score analysis.

Among propensity score matched groups, patients treated by HV surgeons at HV hospitals (N =

1,641) had a mortality rate of 2.7%, as compared to the three other groups’ (N = 1,496) rate of

6.0%, which is a significant difference (ATT) of 3.3% (p = 0.016). Patients treated by HV

surgeons at HV hospitals had a significantly lower LOS among the propensity score matched

groups. LOS of patients treated by HV surgeons at HV hospitals was 13.6 days, as compared to

18.8 days for the remaining three groups. This 5.2 day difference (ATT) was significant (p <

0.001). Finally, costs for patients treated by HV surgeons at HV hospitals were $36,919

19

compared to $49,078 for the three other groups. This difference (ATT) in cost of $12,159 was

statistically significant (p < 0.001).

20

DISCUSSION

Post-operative outcomes of pancreaticoduodenectomy have been widely studied, and like

other complex surgical procedures, correlated with both surgeon and hospital volume. Single

institution studies as well as studies incorporating large, national databases have demonstrated

significantly higher mortality rates in patients undergoing pancreaticoduodenectomy by LV

surgeons as compared to HV surgeons.1,2,6,16

Studies have also shown longer lengths of stay and

cost differences greater than $5,000 associated with patients treated by LV surgeons.17

Even after

controlling for patient related factors, the benefits of treatment by HV surgeons remain evident.

However, as Birkmeyer et al. noted, outcomes from complex surgical procedures may

depend not only on how well the operation is performed but also on the available resources at the

hospital itself.1 Not surprisingly, several studies of hospital volume and surgical outcome have

demonstrated significantly higher mortality rates in patients undergoing pancreatic resection at

LV hospitals as compared to HV hospitals.2,18

By their nature, HV hospitals may tend to provide

more resources to specialty care, and may benefit from the availability of other specialists,

consistent post-operative care processes, and established intensive care unit protocols. Likewise,

LOS and cost of pancreaticoduodenectomy has been compared between low and high volume

hospitals. Glasgow et al. showed that length of hospital stay did not vary significantly based on

hospital volume, but that total hospital charges were significantly higher at LV centers.19

This

observation is in contrast, however, to the findings by Ho and Aloia who found no significant

cost differences by hospital volume.17

Because of these findings, there has been a growing trend to centralize care by

concentrating select operations in HV hospitals. The Leapfrog group has advocated for improved

outcomes through regionalization and volume based referral.12,20

As a result, many studies have

21

described increasing centralization of care,21,22

with subsequent improvement in outcomes.

Although factors other than hospital volume were responsible for the observed decrease in

mortality for pancreatic resection between 1999-2008, Finks et al. demonstrated that 67% of the

overall decrease in mortality for pancreatectomy was attributable to increased hospital volume.21

While better outcomes are associated with high surgeon volume and high hospital

volume, it is generally observed that HV surgeons operate at HV centers while LV surgeons

operate at LV centers. Complexities arise when HV surgeons operate at LV hospitals and LV

surgeons operate at HV hospitals. This confounds whether the surgeon or hospital volume effect

is the driving force behind improved surgical outcomes following pancreaticoduodenectomy.

The results of our study, which simultaneously account for surgeon volume, hospital

volume, and potential confounding patient characteristics in the analysis, suggest that both

surgeon and hospital volume have a significant effect on outcomes following

pancreaticoduodenectomy. In this cohort of the NIS, patients treated by LV surgeons at LV

hospitals had a mortality rate more than three times as high as patients of HV surgeons at HV

hospitals. Additionally, LV surgeons at HV hospitals had significantly lower mortality rates than

LV surgeons at LV hospitals. This supports previous studies which demonstrated that patients at

HV centers had lower mortality rates than those at LV centers, regardless of surgeon volume.1

Patients of HV surgeons at LV centers, however, did not have significantly lower mortality rates

compared to patients of LV surgeons at LV hospitals suggesting that the protective effect of HV

surgeons on patient outcomes demonstrated in previous studies was not enough to overcome the

poorer patient outcomes found in LV hospitals.6

Our results also demonstrate significant differences in LOS and cost following pancreatic

resection when stratified by surgeon and hospital volume. LOS of patients treated by HV

22

surgeons at HV centers was two days shorter than the LOS of patients of any other group. These

results are similar to the findings of Kennedy et al. who demonstrated that average hospital stays

for patients of HV surgeons were significantly shorter than the LOS for patients of LV

surgeons.23

In our study, patients of HV surgeons at HV centers also had significantly lower

costs associated with their stay. Compared to LV surgeons at LV hospitals, the difference in cost

of patients of HV surgeons at HV hospitals was $12,275 less. This finding is consistent with

previous studies that demonstrated cost differences between high and lower volume

surgeons.17,23

There are limitations to any study involving administrative data. Although the NIS

database is the largest all-payer database in the United States, it does not ensure that our cohort is

representative of all pancreaticoduodenectomies being performed in this country. Additionally,

outcomes were only collected in the hospital setting during the index admission, and thus only

in-hospital mortalities were captured. Lengths of admission to acute care nursing or

rehabilitation facilities were not included in the data set so we could not study whether shorter

lengths of in-hospital stay were associated with longer lengths of stay at sub-acute facilities.

Similarly, we also could not address whether cost results were influenced by early discharge to

nursing or rehabilitation facilities. The number of patients treated by HV surgeons at LV

institutions was relatively low compared to the rest of the groups. Lastly, despite the strengths of

propensity score matching, it cannot account for selection bias related to unmeasured

confounders.

In conclusion, our study confirms previous findings of improved post-operative outcomes

following pancreaticoduodenectomy in patients treated by HV surgeons at HV centers and also

highlights the complex interplay between surgeon and hospital volume while adding additional

23

information about the relationship between volume and resource use. With growing trends

toward centralization, care must be taken to ensure that both surgeon and hospital volume are

optimized at centers providing pancreaticoduodenectomy.

24

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