 |
|
The Relationship Between Hospital Volume and Outcomes of Hepatic Resection for Hepatocellular Carcinoma
Robert E. Glasgow, MD;
Jonathan A. Showstack, PhD, MPH;
Patricia P. Katz, PhD;
Carlos U. Corvera, MD;
Robert S. Warren, MD;
Sean J. Mulvihill, MD
Arch Surg. 1999;134:30-35.
ABSTRACT
| |
Background Volume-outcome relations have been established for several complex therapies. However, few studies have examined volume-outcome relations for high-risk procedures in general surgery, such as hepatectomy for hepatocellular carcinoma (HCC).
Objective To evaluate the relation between hospital volume and outcome for patients undergoing hepatectomy for HCC.
Design Retrospective cohort study.
Setting All acute-care hospitals in California.
Patients Hospital discharge data were analyzed for each patient in California who underwent major hepatic resection for HCC from January 1, 1990, through December 31, 1994. Hospitals were grouped according to number of hepatectomies performed at each center during the 5-year study.
Main Outcome Measures Outcome measures included operative mortality and length of hospital stay. Regression analyses were used to adjust for differences in patient mix.
Results Five hundred seven patients underwent hepatectomy for HCC during the study. Hepatic resections were performed in 138 hospitals, with an overall in-hospital mortality rate of 14.8%. Three quarters of patients were treated at hospitals that average 3 or fewer hepatic resections for HCC per year. These low-volume providers represent 97.1% of all hospitals treating patients with HCC statewide. Significant reductions in risk-adjusted operative mortality rates (22.7%-9.4%; P=.002, multiple logistic regression) and risk-adjusted length of stay (14.3-11.3 days; P=.03, multiple linear regression) were observed as hospital volume increased.
Conclusions Low operative mortality and length of stay were associated with high-volume centers. These data support regionalization of high-risk procedures in general surgery, such as hepatectomy for HCC.
INTRODUCTION
TODAY'S CHANGING health care environment is being driven, in part, by external pressures on providers to deliver economical, high-quality care. For some medical therapies, quality of care varies little among providers, making cost a primary focus.1-2 For other treatments, however, quality of care is not uniform. Such is the case with coronary angioplasty, coronary surgery, and bone marrow and solid organ transplantation. For these complex therapies, a volume-outcome relationship exists where poor patient outcome, such as in-hospital mortality, is related to low provider volume and inexperience.1, 3-6 These volume-outcome relations serve as the basis for the argument that high-risk procedures should be regionalized to centers of excellence.3, 7-8
In the case of coronary angioplasty, coronary surgery, and transplantation, regionalization is beginning to occur as payers selectively contract with providers for these services. However, this is not the case with other complex therapies. In general surgical practice, standards for the minimum of experience necessary to perform highly complex and risky procedures, ie, major hepatic, pancreatic, or esophageal resection for neoplasia, do not exist. The number of these complex operations performed each year is insufficient for all surgeons and hospitals to have experience. Most of these operations are performed on an elective rather than emergent basis. Thus, if centers with superior patient outcomes could be identified, these procedures could be regionalized as a means of providing the most efficacious and cost-effective care.
A key goal of any reorganization of health care delivery practices in the United States is to preserve or improve quality while reducing costs. Quality of a surgical procedure is measured by operative morbidity and mortality, outcome, effectiveness compared with alternate therapies, and patient satisfaction. It is an open question whether regionalization of high-risk procedures in general surgical practice is desirable or warranted from this standpoint. To help answer this question, we analyzed the relation between hospital volume and postoperative outcome in 1 high-risk, complex general surgical operation, major hepatic resection for hepatocellular carcinoma (HCC). We hypothesized that the risk, as measured by operative mortality, and the cost, as measured by length of hospital stay, are reduced when these patients are cared for in hospitals with greater experience with the procedure.
MATERIALS AND METHODS
DATA SOURCES
We retrospectively analyzed standardized patient discharge abstracts obtained from the California Office of Statewide Health Planning and Development (OSHPD), Sacramento. This database contains discharge data abstracts for every patient hospitalization from every acute-care facility in the state of California. Each abstract includes a variety of demographic, clinical, and hospitalization data that characterize a specific hospitalization. Each patient is assigned a principal diagnosis and procedure and up to 16 secondary diagnoses and procedures. The OSHPD database uses diagnostic and procedural codes derived from the International Classification of Diseases, Ninth Revision, Clinical Modification (4th ed) (ICD-9-CM), issued by the US Department of Health and Human Services.9
All discharge abstracts from January 1, 1990, through December 31, 1994, were included in the initial search of the OSHPD database. From these abstracts, all patients who underwent hepatic lobectomy (ICD-9-CM code 50.3) or partial hepatectomy (ICD-9-CM code 50.22) were examined. From this group, a subset of patients undergoing hepatic resection for HCC was selected (ICD-9-CM code 155.0). Hospitals were characterized with regard to the number of acute and intensive care beds, discharges and patient hospital days per year, yearly overall surgical volume and number of hepatic resections for benign and malignant neoplasia, presence of a liver transplantation program and general surgery residency program, university affiliation, and capability for other complex surgery, as determined by the presence of cardiac surgery services. These data were derived, in part, from the Licensed Services and Utilization Profiles: Annual Report of Hospitals for January 11, 1991, through December 31, 1991.10 Frequency distributions for the individual patient characteristics within the data set and hospital characteristics listed above were computed.
DATA ANALYSIS
Patients were grouped according to hospital identification number. Hospitals were then classified into quartile groups based on the number of hepatic resections performed in the study period. Crude operative mortality rate and length of hospital stay were calculated for each volume range. Operative mortality in this study was defined as patient death before hospital discharge. Because length of hospital stay is directly related to events within the postoperative course, patients with long hospital stays are most likely patients in whom significant perioperative complications develop. Thus, the percentage of patients with hospital stays longer than the 75th percentile (14 days) was calculated for each volume group. This measure served as a surrogate for postoperative complications, as other reliable objective measures of postoperative complications were not directly available within this database.4 To characterize a profile of hospitals within each volume group, the distribution of the various hospital characteristics was analyzed.
Regression modeling was used to evaluate the independent associations of patient and hospital characteristics with the primary outcomes of interest (ie, operative mortality and length of hospital stay). The patient was the unit of analysis, with hospital volume group defined as a patient characteristic. This allowed for a volume group effect to be assessed while controlling for the characteristics of individual patients. Multiple logistic regression was used to model the dichotomous outcome, in-hospital mortality, and multiple linear regression was used to model length of hospital stay.
The independent variables in these analyses included hospital volume, age group, sex, year of surgery, source of admission, type of resection (hepatic lobectomy or partial hepatectomy), presence of chronic liver disease, and presence of other preoperative comorbid illnesses. Age was entered into the regression equations as the following sets of dummy variables: 45 to 60 years, 60 to 75 years, and older than 75 years, with younger than 45 years as the reference group. Significant preoperative comorbid illnesses within a given patient abstract were grouped into 1 dichotomous variable to minimize potential colinearities among the various comorbidities. For example, patients with a history of congestive heart failure are likely to also have coronary artery disease. We believed the following comorbidities to have a significant influence on operative risk: coronary artery disease (ICD-9-CM codes 412-414), chronic obstructive pulmonary disease (ICD-9-CM codes 490-496), diabetes mellitus (ICD-9-CM codes 250), congestive heart failure (ICD-9-CM code 428), nutritional deficiencies (ICD-9-CM codes 260-263), and preoperative intra-abdominal hemorrhage (ICD-9-CM code 459). The presence of chronic liver disease, including cirrhosis (ICD-9-CM code 571), was treated as a separate dichotomous variable, as it represents an independent factor associated with poor operative risk. The dependent variables for these analyses were operative mortality or death before discharge and length of hospital stay.
Adjusted means for operative mortality rate and length of hospital stay were calculated from regression equations that included all of the independent variables. A complete description of the process of adjustment is provided by Cohen and Cohen.11 An adjusted mean is an estimate based on the hypothetical situation that all hospital volume groups had the same mean values on each of the independent variables that were entered into the equation. In other words, the adjusted mean represents the estimated operative mortality rate or length of stay if each of the volume groups treated patients with similar patient characteristics. To further evaluate this volume-outcome relation, an additional analysis was performed, where hospital volume was defined by the total number of hepatic resections for benign and malignant neoplasia, including metastatic disease.
RESULTS
During the study, 507 patients underwent major hepatic resection for HCC in the state of California. The number of resections performed each year was relatively constant, ranging from 117 in 1990 to 87 in 1993 (Table 1). A total of 138 hospitals reported to the database during the 5 years but, because a hepatic resection was not performed at all hospitals in each year, the yearly average number of hospitals in which a hepatic resection for HCC was performed was 53 (Table 1).
|
|
|
|
Table 1. Distribution of Hospitals and Patients by Year of Surgery
|
|
|
Patient ages were distributed as seen in the following tabulation:
The median age was 60 to 64 years. Men outnumbered women by a ratio of nearly 3:2 (293 [57.8%] vs 214 [42.2%], respectively). The most common race of treated patients was white (263 [51.9%] of the study population), followed by Asian (135 [26.6%]), Hispanic (68 [13.4%]), other (21 [4.1%]), and African American (20 [3.9%]). Payer source is presented in the following tabulation:
Source of admission and presence of comorbid medical illnesses were analyzed as indicators of severity of illness. Patients transferred from other acute-care hospitals and those admitted on an elective basis for surgery far outnumbered patients admitted from the emergency department (453 [89.3%] vs 54 [10.6%]). Preoperative comorbidities included diabetes mellitus (46 [9.1%]), coronary artery disease (37 [7.3%]), chronic obstructive pulmonary disease (36 [7.1%]), chronic nutritional deficiencies (17 [3.4%]), congestive heart failure (9 [1.8%]), and chronic renal insufficiency (6 [1.2%]). Eight patients, or 1.6% of the total, presented emergently with a diagnosis of intra-abdominal hemorrhage. Six (11.1%) of the 54 patients admitted through the emergency department had a diagnosis of intra-abdominal hemorrhage, compared with 2 (0.4%) of the 453 patients admitted on a routine basis or transferred from another acute-care facility. The median number of significant comorbidities per patient was 0, with a mean±SE of 0.70±0.04.
Chronic liver disease, including cirrhosis, was present in 192 (37.9%) of patients overall. For patients with chronic liver disease, the crude operative mortality rate was 27.1% compared with 7.3% in patients without chronic liver disease (P<.001 by  2 analysis). Likewise, increasing number of comorbidities correlated with increased crude operative mortality. For patients with no comorbidities, the operative mortality was 5.0%. This rate increased significantly with increasing number of secondary diagnoses (P<.001 by linear regression analysis). For patients with 4 or more comorbidities, the operative mortality was 50.0%. Partial hepatectomy (ICD-9-CM code 50.22) was performed in 299 patients compared with 208 patients who underwent hepatic lobectomy (ICD-9-CM code 50.3).
Each of the 4 volume groups included approximately 127 patients (25.0% of the total number of patients). One half of all patients were treated at centers where 6 or fewer resections were performed during the study (Table 2). These centers accounted for 88.4% of all reporting hospitals. In contrast, the highest-volume centers averaged 37 patients each during the 5 years and accounted for only 2.9% of the reporting hospitals statewide.
|
|
|
|
Table 2. Hospital Volume Group Assignments
|
|
|
Hospital volume groups varied widely with regard to hospital characteristics (Table 3). The highest-volume providers were larger, with more acute and intensive care unit beds and more discharges and patient days per year. They also were more likely to be university hospitals with a general surgery residency training program. In addition to a higher overall surgical volume per year, the highest-volume providers were more likely to perform other complex operations (ie, coronary artery bypass) and to have a higher overall volume of hepatic resections for benign and malignant neoplasia. Three of the 4 highest-volume providers had a liver transplantation program, indicating an institutional interest in hepatology and hepatic surgery. In contrast, none of the lowest-volume providers performed liver transplantation.
|
|
|
|
Table 3. Hospital Characteristics by Hospital Volume Groups
|
|
|
The overall mortality rate for the study population was 14.8%. Crude operative mortality rates decreased with increasing hospital volume, from 24.4% in the lowest-volume centers to 6.2% in the highest-volume centers (Table 4). This inverse relationship between decreasing operative mortality rate and increasing hospital volume is summarized in Figure 1. This relationship was highly significant (P<.001 by logistic regression analysis). When the crude mortality rates for each volume group were adjusted to account for differences in patient characteristics, this highly significant volume-outcome relationship persisted (Table 4).
|
|
|
|
Table 4. Crude and Adjusted Operative Mortality Rates by Hospital Volume Groups
|
|
|
|
|
|
|
Scatterplot diagram of hospital volume plotted against operative mortality rate.
|
|
|
A similar volume-outcome relationship was observed when length of hospital stay was analyzed. The mean hospital stay was 12.9 days. The lowest-volume providers had a mean length of stay of 14.7 days compared with 10.8 days in the highest-volume providers (Table 5). When the length of hospital stay for each volume group was adjusted to account for differences in patient characteristics, this significant volume-outcome relationship persisted (Table 5). In addition, lowest-volume providers were more likely to have patients with hospital stays beyond the 75th percentile (Table 5). This implies that patients treated at lowest-volume providers were twice as likely to have complicated postoperative courses than patients treated at highest-volume providers. The mean (±SEM) length of stay for patients who died was longer than that for patients who survived (18.4±2.24 vs 12.0±0.42 days). When patients who died were excluded from the length-of-stay analysis, a significant volume outcome relationship persisted.
|
|
|
|
Table 5. Crude and Adjusted Operative Length of Hospital Stay by Hospital Volume Group
|
|
|
When hospital volume was defined as total number of hepatic resections for benign and malignant neoplasia, these significant volume-outcome relations persisted. In 2004 patients, the overall operative mortality rate was 6.9%, ranging from 9.3% in the lowest-volume providers to 4.1% in the highest-volume providers.
COMMENT
In an era of limited resources, increased attention is being paid in the United States to the most efficient delivery of health care services. The desired goal is to provide the highest quality of care while using the fewest resources. Volume-outcome analyses have shown that for certain complex surgical procedures, including heart transplantation and coronary artery bypass, the results of treatment are directly linked to experience. These observations have led to the suggestion that these complex, high-risk procedures should be regionalized to high-volume centers of excellence. To determine if similar volume-outcome relations exist in general surgical practice, we examined the relation between hospital volume and operative outcome in 1 complex, high-risk procedure, hepatic resection for HCC.
Hepatic resection was selected for this analysis because it represents a technically challenging, resource-intensive procedure. Hepatic resection may be performed at any hospital, as there are no certificate-of-need requirements or other measures in place to regulate where such operations are performed. Similar to other complex, high-risk operations in general surgery, most hepatic resections are performed on an elective basis, making it possible for such cases to be regionalized to high-volume centers of excellence. Furthermore, hepatectomy for HCC is an infrequently performed procedure for which the average surgeon or hospital is not likely to have substantial experience. Hepatocellular carcinoma was selected as a model in this study, because it is a diagnosis for which major hepatic resection would be considered and represents a disease entity associated with significantly higher rates of operative morbidity and mortality compared with hepatic resection for other indications.12-14
Our main finding was a highly significant relationship between hospital volume and operative outcome for patients undergoing hepatic resection for HCC in California during the 5-year study. The sample size was large, encompassing 507 patients treated at 138 hospitals. The effect of hospital volume on operative mortality was substantial, with a 4-fold difference in mortality between the lowest- and highest-volume groups. In addition to reduced operative mortality rates, high-volume centers were found to have shorter average lengths of hospital stay. These findings suggest that the highest-volume hospitals not only treat patients undergoing hepatic resection for HCC with substantially lower operative mortality, but also accomplish this by using fewer resources.
There are 3 possible explanations for these results. First, the data may have been flawed, and systematic reporting or coding errors may have favored the highest-volume providers. In previous studies of population database reliability, a 10% to 30% error rate in diagnosis and procedure coding has been reported.15-17 In our study, concordance between diagnosis and procedure codes was required for each patient as part of the inclusion criteria, thereby reducing the number of erroneously coded patient discharge abstracts from further analysis. An error rate of only 1% has been identified in the reporting of the end point of patient mortality when the OSHPD database has been reconciled to primary data from individual patient medical records.15 This error rate is not sufficiently large to explain the differences in operative mortality found between low- and high-volume hospitals in this study.
Second, differences in patient characteristics could account for the observed variations in patient outcome. We controlled for these differences in 2 ways. First, the data were pooled by hospital volume such that the number of patients in each volume group was sufficiently large to offset small differences in patient mix at any one hospital. Second, we used multivariate statistical techniques to adjust mortality rates and length of hospital stay for differences in patient characteristics. This risk adjustment did not alter the primary finding of a highly significant association between hospital volume and patient outcome. Additional risks may have been present but not identifiable in the OSHPD database, and the distribution of patients with these unknown risk factors may have been skewed toward hospitals with low volume, but this seems unlikely.
Finally, our findings probably represent true differences in outcome related to variations in patient care in hospitals of various volume groups. Supporting evidence suggests that this interpretation of the data is correct. First, the overall operative mortality rate of 14.8% and the rates for the lower-volume hospital groups in this study are comparable with previously reported operative mortality rates for this procedure in other large-population studies, including the nationwide Veterans Administration experience.14 Second, the operative mortality rates of the highest-volume centers in our study mirror the recently published results of other high-volume centers around the world.12, 18-21 Therefore, the recently cited improvements in operative outcome in patients undergoing hepatectomy for HCC may apply only to high-volume centers and not more generally to the medical community. Finally, when the analysis in our study was extended to hepatic resection for all benign and malignant neoplasia, the volume-outcome relation persisted.
Only a limited insight into potential differences in patient care leading to lower operative mortality in the high-volume centers could be gleaned from the available data. High-volume centers were larger hospitals with higher overall surgical volume and university and residency program affiliation. They were more likely to perform other complex operations, such as cardiac surgery. The highest-volume providers performed a greater overall number of hepatic resections per year, and 3 of 4 had active liver transplantation programs, compared with none of the lowest-volume providers. Furthermore, a greater percentage of patients treated at low-volume providers had extended hospital stays, suggesting complicated postoperative courses. Patients treated at high-volume centers were less likely to have postoperative complications, or these centers have developed the means to better manage these complications should they arise. Thus, the improved in-hospital mortality rates and shorter lengths of hospital stay for patients with HCC at high-volume centers likely represent not only increased volume or experience, but an institutional interest and expertise in the treatment of patients undergoing liver surgery.
In today's health care environment, quality of care is measured not only in terms of patients' clinical outcome, but also cost-effectiveness. In California, most patients undergoing hepatic resection for HCC are treated at hospitals with limited experience. This study demonstrates a strong relationship between hospital volume and outcome in these patients. The standard of patient care for hepatic resection for HCC is not uniform across California. If the adjusted outcomes estimated for the highest-volume hospitals were applied statewide in 1990 through 1994, 44 additional patients would have survived their operation, with a savings of 1067 hospital days. Our results support the regionalization of high-risk general surgical procedures, such as hepatic resection for HCC, as a means of providing the most efficacious and cost-effective care.
AUTHOR INFORMATION
Corresponding author: Sean J. Mulvihill, MD, Department of Surgery, Room U-122, University of California–San Francisco Medical Center, San Francisco, CA 94143-0788 (e-mail: sjm{at}itsa.ucsf.edu).
From the Departments of Surgery (Drs Glasgow, Corvera, Warren, and Mulvihill) and Medicine (Drs Showstack and Katz) and the Institute for Health Policy Studies (Drs Showstack and Katz), University of California, San Francisco.
REFERENCES
| |
1. Hannan EL, O'Donnell JF, Kilburn H Jr, Bernard HR, Yazici A. Investigation of the relationship between volume and mortality for surgical procedures performed in New York State hospitals. JAMA. 1989;262:503-510.
FREE FULL TEXT
2. Rosenthal GE, Harper DL, Quinn LM, Cooper GS. Severity-adjusted mortality and length of stay in teaching and nonteaching hospitals. JAMA. 1997;278:485-490.
FREE FULL TEXT
3. Luft HS, Bunker JP, Enthoven AC. Should operations be regionalized? N Engl J Med. 1979;301:1364-1369.
ABSTRACT
4. Showstack JA, Rosenfeld KE, Garnick DW, Luft HS, Schaffarzick RW, Fowles J. Association of volume with outcome of coronary artery bypass graft surgery: scheduled vs nonscheduled operations. JAMA. 1987;257:785-789.
FREE FULL TEXT
5. Laffel G, Barnett A, Finkelstein S, Kaye M. The relation between experience and outcome in heart transplantation. N Engl J Med. 1992;327:1220-1225.
ABSTRACT
6. Hannan EL, Racz M, Ryan TJ, et al. Coronary angioplasty volume-outcome relationships for hospitals and cardiologists. JAMA. 1997;279:892-898.
7. Bunker JP, Luft HS, Enthoven A. Should surgery be regionalized? Surg Clin North Am. 1982;62:657-668.
ISI
| PUBMED
8. Gordon T, Burleyson G, Tielsch J, Cameron J. The effects of regionalization on cost and outcome for one general high-risk surgical procedure. Ann Surg. 1995;221:43-49.
ISI
| PUBMED
9. Jones M, Brouch K, Hall D, Aaron W. St Anthony's Compact ICD-9-CM: Code Book for Physician Payment, 1995. Reston, Va: St Anthony's Publishing Inc; 1994:1-2.
10. Office of Statewide Health Planning and Development. Licensed Services and Utilization Profiles: Annual Report of Hospitals. Sacramento, Calif: Office of Statewide Health Planning and Development; 1991.
11. Cohen J, Cohen P. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, NJ: Lawrence Eribaum Associates Inc; 1983.
12. Tsao JI, Loftus JP, Nagorney DM, Adson MA, Ilstrup DM. Trends in morbidity and mortality of hepatic resection for malignancy. Ann Surg. 1994;220:199-205.
ISI
| PUBMED
13. Doci R, Gennanri L, Bignami P, et al. Morbidity and mortality after hepatic resection of metastatic colorectal carcinoma. Br J Surg. 1995;82:377-381.
ISI
| PUBMED
14. Nadig DE, Wade TP, Fairchild RB, Virgo KS, Johnson FE. Major hepatic resection: indications and results in a national hospital system from 1988 to 1992. Arch Surg. 1997;132:115-119.
FREE FULL TEXT
15. Chen A, Meux E, Cox G. Report of the Results From the OSHPD Reabstracting Project: An Evaluation of the Reliability of Selected Patient Discharge Data July Through December 1990. Sacramento, Calif: Office of Statewide Health Planning and Development; 1993.
16. How good are the data? Am J Kidney Dis. 1992;46:675-683.
17. Lloyd SS, Rissing JP. Physician and coding errors in patient records. JAMA. 1985;254:1330-1336.
FREE FULL TEXT
18. Segawa T, Tsuchiya R, Furui J, Isawa K, Tsunoda T, Kanematsu T. Operative results in 143 patients with hepatocellular carcinoma. World J Surg. 1993;17:663-668.
PUBMED
19. Vauthey J, Klimstra D, Franceschi D, et al. Factors affecting long-term outcome after hepatic resection for hepatocellular carcinoma. Am J Surg. 1995;169:28-35.
FULL TEXT
|
ISI
| PUBMED
20. Bismuth H, Chiche L, Castaing D. Surgical treatment of hepatocellular carcinoma in noncirrhotic liver. World J Surg. 1995;19:35-41.
FULL TEXT
|
ISI
| PUBMED
21. Lai EC, Fan S-T, Lo C-M, Chu K-M, Liu C-L, Wong J. Hepatic resection for hepatocellular carcinoma. Ann Surg. 1995;221:291-298.
ISI
| PUBMED
 CiteULike  Connotea  Del.icio.us  Digg  Reddit  Technorati  Twitter
What's this?
RELATED ARTICLE
Invited Critique: The Relationship Between Hospital Volume and Outcomes of Hepatic Resection for Hepatocellular Carcinoma
Christian Herfarth and Peter Kienle
Arch Surg. 1999;134(1):35.
EXTRACT
| FULL TEXT
THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES
|
Long-term Survival After Surgery for Primary Hepatic Sarcoma in Adults
Matthaei et al.
Arch Surg 2009;144:339-344.
ABSTRACT
| FULL TEXT
Patient characteristics and hospital quality for colorectal cancer surgery
Zhang et al.
Int J Qual Health Care 2007;19:11-20.
ABSTRACT
| FULL TEXT
The Relationship Between Surgeon and Hospital Volume and Outcomes for Shoulder Arthroplasty
Jain et al.
JBJS 2004;86:496-505.
ABSTRACT
| FULL TEXT
The Effect of Clustering of Outcomes on the Association of Procedure Volume and Surgical Outcomes
Panageas et al.
ANN INTERN MED 2003;139:658-665.
ABSTRACT
| FULL TEXT
Hospital Volume and Operative Mortality in Cancer Surgery: A National Study
Finlayson et al.
Arch Surg 2003;138:721-725.
ABSTRACT
| FULL TEXT
Hepatic Resection in the United States: Indications, Outcomes, and Hospital Procedural Volumes From a Nationally Representative Database
Dimick et al.
Arch Surg 2003;138:185-191.
ABSTRACT
| FULL TEXT
Postoperative Complication Rates After Hepatic Resection in Maryland Hospitals
Dimick et al.
Arch Surg 2003;138:41-46.
ABSTRACT
| FULL TEXT
Implementation of a Voluntary Hospitalist Service at a Community Teaching Hospital: Improved Clinical Efficiency and Patient Outcomes
Auerbach et al.
ANN INTERN MED 2002;137:859-865.
ABSTRACT
| FULL TEXT
The Effect of ICU Physician Staffing and Hospital Volume on Outcomes After Hepatic Resection
Dimick et al.
J Intensive Care Med 2002;17:41-47.
ABSTRACT
Surgical volume was not related to 30 day mortality in 8 common operations
Birkmeyer
Evid. Based Med. 2000;5:62-62.
FULL TEXT
|
