Does high surgeon and hospital surgical volume raise the five-year survival rate for breast cancer? A population-based study.
ABSTRACT This study sets out to examine the relationship between both surgeon and hospital volume and five-year survival rates for breast cancer patients. We performed Cox proportional hazard regressions on a pooled population-based database linking the Taiwan National Health Insurance Research Database with the 'cause of death' data file, covering the three-year period from January 1997 to December 1999. Of the 13,360 breast cancer resection patients in our study sample, the five-year survival rates, by surgeon volume, were 77.3% in the high-volume group (>201 cases), 76.9% in the medium-volume group (45-200), and 69.5% in the low-volume group (<or=44). The five-year survival rates, by hospital volume, were 77.3% for high-volume hospitals (>585 cases), 74.5% for medium-volume hospitals (259-585) and 72.1% for low-volume hospitals (<or=258). Cox regression analyses show that the risk of death for patients treated by low-volume surgeons was up to 1.305 times (P < 0.001) as high as the risk for those treated by high-volume surgeons. Similarly, the risk of death for patients whose resections had been performed in low-volume hospitals was 1.484 times (P < 0.001) as high as the risk for those whose resections had been performed in high-volume hospitals. High surgeon or hospital volume contributes significantly to patient outcomes and may be regarded as an overall indicator of high treatment quality; we therefore strongly recommend that the healthcare authorities reveal to the public all of the relevant information on provider performance and caseloads in order to assist them to make the optimum choice when surgery becomes necessary.
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ABSTRACT: Volume has been suggested as a surrogate quality indicator for breast cancer surgeries by several researchers. It is crucial to understand the underlying reasons as to why there is a disparity in utilization of high volume hospitals. However, the studies that investigated the mechanism underlying the disparity in high volume hospital utilization are very limited. The objectives of this study include: 1) examine the relationship between geographic differential distance and utilization of high volume hospitals; 2) investigate other demographic, socioeconomic and clinical factors that may affect patients' utilization of high volume hospitals. Multivariate logistic regressions were used to evaluate factors that impact patients' utilization of high volume hospitals. The study results showed that geographic distance is a significant factor that impedes patients' utilization of high volume hospitals, independent of patients' clinical, demographic, and socioeconomic characteristics. It was also found that white, non-Hispanic women, patients with higher education level are more likely to be admitted in high volume hospitals compared to low volume hospitals. These factors are also significant to patients' choice of medium vs. low volume hospitals. Geographic proximity is an important factor that affects patients' choice of hospital, and directing more patients to high volume hospitals should anticipate negative effects, such as increasing the cost of seeking care at high volume hospitals. Alternative strategies need to be developed to improve surgical outcomes without increasing patients' traveling related cost, such as enhancing the network between high volume hospitals and low volume hospitals, establishing radiation centers in rural areas.
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ABSTRACT: Many superscalar processors support out-of-order instruction execution and executes multiple instructions per cycle. One of the hazards of executing instructions out of order occurs when a prior instruction store is at the same memory location as a later instruction load, but the execution of the load occurs before the store is complete. Dynamic prediction about a store instruction involved in a load/store hazard can be used to delay a load instruction execution that is later in program order. The load/store conflict-prediction mechanism consists of a two-way set associative, 32-entry, two-ported SRAM cache used to contain information on store instructions involved in load/store conflictsSolid-State Circuits Conference, 1997. Digest of Technical Papers. 43rd ISSCC., 1997 IEEE International; 03/1997
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ABSTRACT: Studies suggest that institutional case volume and teaching status significantly affect patient survival. We sought to compare outcomes of surgical resection for lung cancer at teaching facilities (TF) and at high-volume centers (HVC). Patients undergoing lung cancer resection with curative intent were examined using a linked dataset from 1998 to 2002 between the Florida Cancer Data System and the Florida Agency for Health Care Administration. A total of 13,469 patients were analyzed and outcomes adjusted for comorbidities. Median survival time (MST) was superior for patients treated at TF versus nonteaching facilities (NTF) (47.1 versus 40.5 months, P < 0.001). Mortality rates at NTF were higher at 30 days (2.6% versus 1.1%, P < 0.001), 90 days (6.8% versus 3.8%, P < 0.001), and at 5 years (63.9% versus 59.2%, P = 0.005). Similarly, MST was superior in the cohort treated at HVC versus low-volume center (LVC) (45.1 versus 39.8 months, P < 0.001). Mortality was observed to be higher in LVC than HVC at 30 days (2.7% versus 1.6%, P < 0.001), 90 days (7.5% versus 4.0%, P < 0.001), and at 5 years (63.5% versus 59.3%, P = 0.002). Significant preoperative, independent predictors of survival include age, sex, smoking status, and the existence of certain comorbidities. Treatment at a TF or HVC were independent predictors of better outcome. Race, use of chemotherapy or radiation did not affect outcomes. Surgical treatment for lung cancer at TF or HVC results in significantly better short- and long-term patient outcomes.Annals of Surgical Oncology 07/2008; 16(1):3-13. DOI:10.1245/s10434-008-0025-9 · 3.94 Impact Factor