HB - Gestão Operacional
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- A comparison of methods for forecasting emergency department crowdingPublication . Carvalho da Silva, M; Monteiro, MT; Sá-Soares, S; Dória-Nóbrega, S
- Combined tools for Surgical Case Packages contents and cost optimization: a preliminary studyPublication . Alves, AC; Gonçalves, AM; Fernandes, JM; Vaz, I; Teixeira, S; Sousa, I; Pereira, JJ; Dória-Nóbrega, SThis paper presents a solution proposal based on mathematical and statistical tools to optimize Surgical Case Packages of an Operating Room (OR) in a Portuguese public hospital that it is the most complex environment in a hospital. In this particular hospital, more than 27000 surgeries/year are performed, employing, sometimes, misadjusted composition of standard surgical packages and non-optimized grouping of surgical instruments. Problem consequences are, among others, high transport of various surgical cases packages; high number of open cases and delays in surgical times following surgery. These type of problems are waste that do not add value to the service in the context of Lean Healthcare and must be eliminated using the most suitable tools. After the analysis, different tools were used: combinatorial analysis to optimize surgical cases composition and statistical analysis to identify the instruments usage and surgical basic case patterns. An optimization model was developed which produced a sterilizing initial solution of 135.24€. By identifying the most commonly employed instruments, it was concluded that some instruments have never been used and others rarely and some patterns were identified. The results achieved were based on minor sample and in a form of data collection that needs some adjustments
- Assessment of forecasting models for patients arrival at Emergency DepartmentPublication . Carvalho-Silva, M; Monteiro, MT; Sá-Soares, F; Dória-Nóbrega, SThe unpredictability of arrivals to the Emergency Department (ED) of a hospital is a great concern of the management. The existence of more complex pathologies and the increase in life expectancy originate a higher rate of hospitalization. The hospitalization of patients via ED upsets previously programmed services and some cancellations may occur. The Hospital’s ability to predict turnout variations in the arrivals to the ED is fundamental to the management of the human resources and the required number of beds. Braga Hospital, in Portugal, is the subject of this work. Data for ED arrivals in 2 years (2012–2013), the test period, was studied and forecasting models based on time series were built. The models were then tested against the real data from the evaluation period (2014). These models are of ARIMA (AutoRegressive-Integrated-Moving Average) type, used software was the Forecast Pro.