Efficiency of Ontario primary care physicians across payment models : a stochastic frontier analysis

Objective The study examines the relationship between the primary care model that a physician belongs to and the efficiency of the primary care physician in Ontario, Canada. Methods Survey data were collected from 183 self-selected physicians and linked to administrative databases to capture the provision of services to the patients served for the 12 month period ending June 30, 2013, and the characteristics of the patients at the beginning of the study period. Two stochastic frontier regression models were used to estimate efficiency scores and parameters for two separate outputs: the number of distinct patients seen and the number of visits. Results Because of missing data, only 165 physicians were included in the analyses. The average efficiency was 0.72 for both outputs with scores varying from 4 % to 93 % for the visits and 5 % to 94 % for the number of patients seen. We observed that there were both very low and very high efficiency scores within each model. These variations were larger than variations in average scores across models

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Passenger Travel-Time and Path Choice Implications of Real-Time Transit Information

This paper considers information systems in public transit in which the passenger receives information in real time regarding projected vehicle travel times. To provide a preliminary assessment of these systems, an analytic framework is presented to evaluate path choices and travel time benefits resulting from real-time information. A behavioral model of transit path choice is presented that frames the choice in terms of a decision whether to board a departing vehicle. Furthermore, this path choice model accommodates network travel times that are both stochastic and time-dependent, two elements that have been neglected in previous studies but are critical to evaluating real-time information systems. The results suggest that real-time information yields only very modest improvements in passenger service measures such as the origin-to-destination travel times and the variability of trip times

The impact of scheduling on service reliability: Trip-time determination and holding points in long-headway services

This paper presents research on optimizing service reliability of longheadway services in urban public transport. Setting the driving time, and thus the departure time at stops, is an important decision when optimizing reliability in urban public transport. The choice of the percentile out of historical data determines the probability of being late or early, while the scheduled departure time determines the arrival pattern for travelers. A hypothetical line and a case study are used to determine the optimal percentile value for long-headway services without and with holding points. If no holding points are applied, it is shown that the 35-percentile value minimizes the additional travel time to 25 % of the reference situation. In the case of holding, two holding points combined with a 30–60-percentile value yield the best performance: a further reduction of the additional travel time with 60 %.Transport en PlanningCivil Engineering and Geoscience