Visit durations were significantly longer for anesthetized and sedated patients. Anesthetized patients incurred the highest costs, followed by sedated patients.

Objective. With aging and obesity trends, the incidence and prevalence of osteoarthritis (OA) is expected to rise in Canada, increasing the demand for health resources. Resource planning to meet this increasing need requires estimates of the anticipated number of OA patients. Using administrative data from Alberta, we estimated OA incidence and prevalence rates and examined their sensitivity to alternative case definitions. Methods. We identified cases in a linked data set spanning 1993 to 2010 (population registry, Discharge Abstract Database, physician claims, Ambulatory Care Classification System, and prescription drug data) using diagnostic codes and drug identification numbers. In the base case, incident cases were captured for patients with an OA diagnostic code for at least 2 physician visits within 2 years or any hospital admission. Seven alternative case definitions were applied and compared. Results. Age-and sex-standardized incidence and prevalence rates were estimated to be 8.6 and 80.3 cases per 1,000 population, respectively, in the base case. Physician claims data alone captured 88% of OA cases. Prevalence rate estimates required 15 years of longitudinal data to plateau. Compared to the base case, estimates are sensitive to alternative case definitions. Conclusion. Administrative databases are a key source for estimating the burden and epidemiologic trends of chronic diseases such as OA in Canada. Despite their limitations, these data provide valuable information for estimating disease burden and planning health services. Estimates of OA are mostly defined through physician claims data and require a long period of longitudinal data.

The objective of this research is to determine whether Systems Dynamics (SD) is a beneficial method for modelling hospital patient flow from a strategic planning perspective. While discrete event simulation has frequently been used as a tool for analysing and improving patient flow in health care settings, the desire to assess and understand patient flow and resource demand from a more strategic, and therefore aggregate, perspective led to the use of SD. To evaluate the suitability of such an approach, a model was developed in collaboration with the General Campus at The Ottawa Hospital with particular attention paid to the delays experienced by patients in the emergency department. The modelling techniques used, model validation and scenarios tested with the model are discussed, accompanied by comments regarding the appropriateness of SD for such a model.

For infants with typical bronchiolitis, omitting radiography is cost saving without compromising diagnostic accuracy of alternate diagnoses and of associated pneumonia.

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