Is theatre utilization a valid performance marker for NHS theatres?

Background Utilization is used as the principal marker of theatre performance in the NHS. This study investigated its validity as: a managerial tool, an inter-Trust indicator of efficient theatre use and as a marker of service performance for surgeons. Methods A multivariate linear regression model was constructed using theatre data comprising all elective general surgical operating lists performed at a NHS Teaching hospital over a seven-year period. The model investigated the influence of: operating list size, individual surgeons and anaesthetists, late-starts, overruns, session type and theatre suite on utilization (%). Results 7,283 inpatient and 8,314 day case operations were performed on 3,234 and 2,092 lists respectively. Multivariate analysis demonstrated that the strongest independent predictors of list utilization were the size of the operating list (p < 0.01) and whether the list overran (p < 0.01). Surgeons differed in their ability to influence utilization. Their overall influence upon utilization was however small. Conclusion Theatre utilization broadly reflects the surgical volume successfully admitted and operated on elective lists. At extreme values it can expose administrative process failure within individual Trusts but probably lacks specificity for meaningful use as an inter-Trust theatre performance indicator. Unadjusted utilization rates fail to reflect the service performance of surgeons, as their ability to influence it is small

Computer-aided detection in full-field digital mammography in a clinical population: performance of radiologist and technologists

International audienceThe purpose of the study was to evaluate the impact of a computer-aided detection (CAD) system on the performance of mammogram readers in interpreting digital mammograms in a clinical population. Furthermore, the ability of a CAD system to detect breast cancer in digital mammography was studied in comparison to the performance of radiologists and technologists as mammogram readers. Digital mammograms of 1,048 consecutive patients were evaluated by a radiologist and three technologists. Abnormalities were recorded and an imaging conclusion was given as a BI-RADS score before and after CAD analysis. Pathology results during 12 months follow up were used as a reference standard for breast cancer. Fifty-one malignancies were found in 50 patients. Sensitivity and specificity were computed before and after CAD analysis and provided with 95% CIs. In order to assess the detection rate of malignancies by CAD and the observers, the pathological locations of these 51 breast cancers were matched with the locations of the CAD marks and the mammographic locations that were considered to be suspicious by the observers. For all observers, the sensitivity rates did not change after application of CAD. A mean sensitivity of 92% was found for all technologists and 84% for the radiologist. For two technologists, the specificity decreased (from 84 to 83% and from 77 to 75%). For the radiologist and one technologist, the application of CAD did not have any impact on the specificity rates (95 and 83%, respectively). CAD detected 78% of all malignancies. Five malignancies were indicated by CAD without being noticed as suspicious by the observers. In conclusion, the results show that systematic application of CAD in a clinical patient population failed to improve the overall sensitivity of mammogram interpretation by the readers and was associated with an increase in false-positive results. However, CAD marked five malignancies that were missed by the different readers