Who Receives Their Complex Cancer Surgery at Low-Volume Hospitals?
Minnesota Surgical Outcomes Research Center, Department of Surgery, University of Minnesota and Minneapolis Veterans Affairs Medical Center, Minneapolis, MN 55455, USA. Journal of the American College of Surgeons
(Impact Factor: 5.12).
11/2011; 214(1):81-7. DOI: 10.1016/j.jamcollsurg.2011.10.003
Previous literature has consistently shown worse operative outcomes at low-volume hospitals (LVH) after complex cancer surgery. Whether patient-related factors impact this association remains unknown. We hypothesize that patient-related factors contribute to receipt of complex cancer surgery at LVH.
Using the 2003-2008 National Inpatient Sample, we identified 59,841 patients who underwent cancer operations for lung, esophagus, and pancreas tumors. Logistic regression models were used to examine the impact of sociodemographic factors on receipt of complex cancer surgery at LVH.
Overall, 38.4% received their cancer surgery at LVH. A higher proportion of esophagectomies were performed at LVH (70.3%), followed by pancreatectomy (38.2%) and lung resection (33.8%). Patients who were non-white, with non-private insurance, and had more comorbidities were all more likely to receive their cancer surgery at LVH (for all, p < 0.05). Multivariate analyses continued to demonstrate that non-white race, insurance status, increased comorbidities, region, and nonelective admission predicted receipt of cancer surgery at LVH across all 3 procedures.
In this large national study, non-white race and increased comorbidities contributed to receipt of cancer surgery at LVH. Patient selection and access to high-volume hospitals are likely reasons worthy of additional investigation. This study provides additional insight into the volume-outcomes relationship. Given the demonstrated outcomes disparity between high-volume hospitals and LVH, future policy and research should encourage mechanisms for referral of patients with cancer to high-volume hospitals for their surgical care.
Available from: PubMed Central
- "And there is a negative association between SES and cancer survival rate ,,. A study from the United States also revealed that patients who underwent cancer operations for lung, esophagus, and pancreas tumors with more comorbidities were more likely to receive their cancer surgery at low-volume hospitals . Although these trends were also seen in this current study, several of these variables were associated with increased short-term mortality and were entered into the multivariate analysis. "
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ABSTRACT: The influence of different hospital and surgeon volumes on short-term survival after hepatic resection is not clearly clarified. By taking the known prognostic factors into account, the purpose of this study is to assess the combined effects of hospital and surgeon volume on short-term survival after hepatic resection.
13,159 patients who underwent hepatic resection between 2002 and 2006 were identified in the Taiwan National Health Insurance Research Database. Data were extracted from it and short-term survivals were confirmed through 2006. The Cox proportional hazards model was used to assess the relationship between survival and different hospital, surgeon volume and caseload combinations.
High-volume surgeons in high-volume hospitals had the highest short-term survivals, following by high-volume surgeons in low-volume hospitals, low-volume surgeons in high-volume hospitals and low-volume surgeons in low-volume hospitals. Based on Cox proportional hazard models, although high-volume hospitals and surgeons both showed significant lower risks of short-term mortality at hospital and surgeon level analysis, after combining hospital and surgeon volume into account, high-volume surgeons in high-volume hospitals had significantly better outcomes; the hazard ratio of other three caseload combinations ranging from 1.66 to 2.08 (p<0.001) in 3-month mortality, and 1.28 to 1.58 (p<0.01) in 1-year mortality.
The combined effects of hospital and surgeon volume influenced the short-term survival after hepatic resection largely. After adjusting for the prognostic factors in the case mix, high-volume surgeons in high-volume hospitals had better short-term survivals. Centralization of hepatic resection to few surgeons and hospitals might improve patients' prognosis.
PLoS ONE 01/2014; 9(1):e86444. DOI:10.1371/journal.pone.0086444 · 3.23 Impact Factor
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ABSTRACT: Inadequate access has contributed to widespread racial disparities in cancer care in the United States. However, the outcomes for racial minorities at quality-seeking hospitals, such as those participating in the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP), remain unknown. We hypothesized that operative outcomes for racial and ethnic minority patients after cancer surgery at ACS NSQIP hospitals are comparable with those for white patients.
Using the 2005-2008 ACS NSQIP data, we identified 38,926 patients who underwent thoracic, abdominal, or pelvic cancer surgery. We used multivariate logistic regression to examine the association between race and ethnicity and short-term (30-day) operative outcomes after cancer surgery. Sensitivity analyses were performed to ensure the relationship remained consistent after stratification by procedure.
Nonwhite patients constituted 16.9% of patients treated for cancer surgery in ACS NSQIP hospitals. Although nonwhite patients were more likely to have higher levels of comorbidities and undergo more complex resections (p < 0.05 for all), multivariate analyses demonstrated that these patients were as likely as white patients to have adverse short-term operative outcomes develop after cancer surgery. These results persisted after stratification by extent of surgical procedure. However, black, Hispanic, and American-Indian/Alaskan-Native patients were more likely to experience prolonged length of stay (odds ratio for black vs white patients = 1.33; p < 0.001).
Racial and ethnic minority patients who undergo their cancer surgery at ACS NSQIP hospitals have short-term operative outcomes similar to white patients, but they remain hospitalized longer. These findings suggest that access to quality-driven hospitals might ameliorate racial disparities in cancer care and outcomes. Future policies should focus on expanding access to quality-driven surgical facilities as a step toward timely and optimal cancer care.
Journal of the American College of Surgeons 02/2012; 214(4):539-47; discussion 547-9. DOI:10.1016/j.jamcollsurg.2011.12.024 · 5.12 Impact Factor
Available from: Yu-Chieh Su
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ABSTRACT: Positive results between caseloads and outcomes have been validated in several procedures and cancer treatments. However, there is limited information available on the combined effects of surgeon and hospital caseloads. We used nationwide population-based data to explore the association between surgeon and hospital caseloads and survival rates for major cancers.
A total of 11,677 patients with incident cancer diagnosed in 2002 were identified from the Taiwan National Health Insurance Research Database. Survival analysis, the Cox proportional hazards model, and propensity scores were used to assess the relationship between 5-year survival rates and different caseload combinations.
Based on the Cox proportional hazard model, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer survival rates, and hazard ratios ranged from 1.3 in head and neck cancer to 1.8 in lung cancer after adjusting for patients' demographic variables, co-morbidities, and treatment modality. When analyzed using the propensity scores, the adjusted 5-year survival rates were poorer for patients treated by low-volume surgeons in low-volume hospitals, compared to those treated by high-volume surgeons in high-volume hospitals (P<0.005).
After adjusting for differences in the case mix, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer 5-year survival rates. Payers may implement quality care improvement in low-volume surgeons.
PLoS ONE 07/2012; 7(7):e40590. DOI:10.1371/journal.pone.0040590 · 3.23 Impact Factor
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