In this thesis, I chose to identify and evaluate different monitoring methods on surgeon specific outcomes in colorectal surgery. An initial literature search identified different methods that were applied to a cohort of colorectal patients operated on by general surgeons using an electronic hospital database. Surgeon specific complications were validated with a chart review. General surgeons at The Ottawa Hospital were surveyed on their opinions regarding monitoring outcomes. We can conclude that different methods may be needed as they are dependent heavily on specified target limits. With our derived cohort, we had adequate risk adjustment using a modified Escobar model for 30 day mortality and morbidity. These complications were derived from electronic algorithms and had excellent specificity and sensitivity. General surgeons at The Ottawa Hospital have different opinions regarding monitoring their outcomes and surgeon engagement is necessary to make monitoring fruitful for patients, public, hospital administration, and surgeons.

In this thesis, I chose to identify and evaluate different monitoring methods on surgeon specific outcomes in colorectal surgery. An initial literature search identified different methods that were applied to a cohort of colorectal patients operated on by general surgeons using an electronic hospital database. Surgeon specific complications were validated with a chart review. General surgeons at The Ottawa Hospital were surveyed on their opinions regarding monitoring outcomes. We can conclude that different methods may be needed as they are dependent heavily on specified target limits. With our derived cohort, we had adequate risk adjustment using a modified Escobar model for 30 day mortality and morbidity. These complications were derived from electronic algorithms and had excellent specificity and sensitivity. General surgeons at The Ottawa Hospital have different opinions regarding monitoring their outcomes and surgeon engagement is necessary to make monitoring fruitful for patients, public, hospital administration, and surgeons.

Publication bias is one threat to validity that researchers conducting meta-analysis studies confront. Two primary goals of this research were to examine the degree to which publication bias impacts the results of a random effects meta-analysis and to investigate the performance of five statistical methods for detecting publication bias in random effects meta-analysis. Specifically, the difference between the population effect size and the estimated meta-analysis effect size, as well as the difference between the population effect size variance and the meta-analysis effect size variance, provided an indication of the impact of publication bias. In addition, the performance of five statistical methods for detecting publication bias (Begg Rank Correlation with sample size, Begg Rank Correlation with variance, Egger Regression, Funnel Plot Regression, and Trim and Fill) were estimated with Type I error rates and statistical power. The overall findings indicate that publication bias notably impacts the meta-analysis effect size and variance estimates. Poor FTSe I error control was exhibited in many conditions by most of the statistical methods. Even when Type I error rates were adequate the power was small, even with larger samples and greater numbers of studies in the meta-analysis.

Background The Swedish Association of local authorities and regions in collaboration with the national board of health and welfare produces the yearly “Swedish Health Care Report” in order to provide evaluations of the hospitals and counties in Sweden for both the politicians and the general public. Method We describe several standard methods which have been used to present the performance of each hospital or county: Forest plot (FL), League Table (LT), League Plot (LP) and Funnel Plot (FP). Using simulation technique to produce the League Plot of rank is also presented in order to illustrate the unreliable of the ranking principle. Results The league plot with confidence interval is easily understood by people, but it should provide the total number of operations (sample size) as well. The resulting multiple-indicators system gives a clear overview of the whole system, but the cut-off points used in the traffic light method is not the best choice. Several possible improved methodologies are: A league plot traffic light method and a standard funnel plot traffic light method is recommended when aiming at finding the outliers; A p=0.67 funnel plot traffic light method is suggested when wishing to divide the units into approximately equally large groups; A one-side traffic light method seems to be a wonderful choice when focusing on the bad performance units.