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BackgroundTo increase operating room (OR) efficiency, a new resource allocation strategy, a new policy for patient urgency classification, and a new system for OR booking was implemented at a tertiary referral hospital. We investigated the impact of these interventions.MethodsWe carried out a before-and-after study using OR data. A total of 23 515 elective (planned) and non-elective (unplanned) orthopaedic and general surgeries were conducted during calendar year 2007 (period 1) and July 2008 to July 2009 (period 2). The Wilcoxon–Mann–Whitney test was used to calculate statistical significance.ResultsAn increased amount of case time (7.1%, p < 0.05) was conducted without any increase in out-of-hours case time. Despite having three fewer ORs for electives, slightly more elective case time was handled with 26% less use of overtime (p < 0.05). Mean OR utilization was 56% for the 17 mixed ORs, 60% for the 14 elective ORs, and 62% for the 3 dedicated ORs. A 20% growth (p < 0.05) of non-elective case time was primarily absorbed through enhanced daytime surgery, which increased over 48% (p < 0.05). As a result, the proportions of case time on evenings and nights decreased. Specifically, case time at night decreased by 26% (p < 0.05), and the number of nights without surgery increased from 55 to 112 (out of 315 and 316, respectively). Median waiting time for the middle urgencies increased with 1.2 hours, but over 90% received treatment within maximum acceptable waiting time (MAWT) in both periods. Median waiting time for the lowest urgencies was reduced with 12 hours, and the proportion of cases treated within MAWT increased from 70% to 89%. The proportion of high urgency patients (as a proportion of the total) was reduced from 20% to 12%. Consequently, almost 90% of the operations could be planned at least 24 hours in advance.ConclusionsThe redesign facilitated effective daytime surgery and a more selective use of the ORs for high urgency patients out of hours. The synergistic effect probably exceeded the sum of the individual effects of the changes, because the effects of each intervention facilitated the successful implementation of others.

Intrazonal trips are not always included in model estimation because they do not appear on a network in centroid-to-centroid travel. It is also presumed that their exclusion does not affect model results. This paper tests the above presumption by examining the assumptions of ignorable missingness. The results indicate that omitting intrazonal trips in model estimation result in biased sample. Consequently parameter estimates get biased. The paper also compares the results of travel mode choice models by excluding and including the intrazonal trips in model estimation.

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______________________________________________________________________ AbstractModeling travel demand is a vital part of transportation planning and management. Level of service (LOS) attributes representing the performance of transportation system and characteristics of travelers including their households are major factors determining the travel demand. Information on actual choice and characteristics of travelers is obtained from a travel survey at an individual level. Since accurate measurement of LOS attributes such as travel time and cost components for different travel modes at an individual level is critical, they are normally obtained from network models. The network-based LOS attributes introduce measurement errors to individual trips thereby causing errors in variables problem in a disaggregate model of travel demand. This paper investigates the possible structure and magnitude of biases introduced to the coefficients of a multinomial logit model of travel mode choice due to random measurement errors in two variables, namely, access/egress time for public transport and walking and cycling distance to work. A model was set up that satisfies the standard assumptions of a multinomial logit model. This model was estimated on a data set from a travel survey on the assumption of without measurement errors. Subsequently random measurement errors were introduced and the mean values of the parameters from 200 estimations were presented and compared with the original estimates. The key finding in this paper is that errors in variables result in biased parameter estimates of a multinomial logit model and consequently leading to poor policy decisions if the models having biased parameters are applied in policy and planning purposes. In addition, the paper discusses some potential remedial measures and identifies research topics that deserve a detailed investigation to overcome the problem. The paper therefore significantly contributes to bridge the gap between theory and practice in transport.

This study investigates potential port users' surplus and terminal operators' profits due to transforming port governance from the 'tool port' model to the 'landlord port' model. Although the landlord port model is one of the most adopted and successful port governance models, many ports still operate under other models. Chittagong Port, the largest port in Bangladesh, currently operates under the tool port model, while the country's second-largest port, Mongla Port, operates under the service port model. Chittagong Port is currently facing many challenges, including capacity expansion and renovation of port facilities. Therefore, we form four hypothetical situations for port governance model transformation, assuming that Chittagong Port will transform to the landlord port model but that Mongla Port will run under the existing governance model. Estimating a Bertrand game model, we present a cost-benefit analysis for port users and terminal operators (or port authorities) in hypothetical game situations. The results reveal that privatising one of the container terminals under a landlord setting is the most profitable scenario for Chittagong Port Authority, but privatising all terminals of Chittagong Port yields the highest users' surplus. However, privatising two of the terminals while they cooperate yields the lowest users' surplus.

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