Rosane Goldwasser

Desmame e interrupção da ventilação mecânica

A retirada da ventilacao mecânica e uma medida impor-tante na terapia intensiva. A utilizacao de diversos termos para definir este processo pode dificultar a avaliacao de sua duracao, dos diferentes modos e protocolos e do prognos-tico. Por esse motivo, e importante a definicao precisa dos termos, como se segue:

A prova prática no processo de seleção do concurso de residência médica

A structured questionnaire regarding the use of hands-on tests in the selection of medical residents was applied to the participants of an interactive workshop on this issue, held during the XLIII Brazilian Congress of Medical Education in Natal, in October 2005. The skills considered important in this testing and different models of hands-on tests applied in the selection process of medical residents by some institutions were discussed. A SWOT analysis (Strengths, Weaknesses, Opportunities, and Threats) was performed for evaluating the models (strengths and weaknesses) and their applicability to the external environment, considering all institutions offering residency programs (opportunities and threats). The medical students considered knowledge and qualification the most important skills while the teachers opted for attitude and ethical behavior. The majorit y realized that the evaluation model would have to be customized to each region of the countr y although this would be in disagreement with the Brazilian curricular guidelines. Among all hands-on models analyzed, the practical test performed with patients and the model using multimedia resources were considered the easiest to be reproduced. One concludes that, although being an excellent method for the selection of medical residents, hands-on testing still shows weak points and calls for a broader discussion.

Difficulties in access and estimates of public beds in intensive care units in the state of Rio de Janeiro

ABSTRACT OBJECTIVE To estimate the required number of public beds for adults in intensive care units in the state of Rio de Janeiro to meet the existing demand and compare results with recommendations by the Brazilian Ministry of Health. METHODS The study uses a hybrid model combining time series and queuing theory to predict the demand and estimate the number of required beds. Four patient flow scenarios were considered according to bed requests, percentage of abandonments and average length of stay in intensive care unit beds. The results were plotted against Ministry of Health parameters. Data were obtained from the State Regulation Center from 2010 to 2011. RESULTS There were 33,101 medical requests for 268 regulated intensive care unit beds in Rio de Janeiro. With an average length of stay in regulated ICUs of 11.3 days, there would be a need for 595 active beds to ensure system stability and 628 beds to ensure a maximum waiting time of six hours. Deducting current abandonment rates due to clinical improvement (25.8%), these figures fall to 441 and 417. With an average length of stay of 6.5 days, the number of required beds would be 342 and 366, respectively; deducting abandonment rates, 254 and 275. The Brazilian Ministry of Health establishes a parameter of 118 to 353 beds. Although the number of regulated beds is within the recommended range, an increase in beds of 122.0% is required to guarantee system stability and of 134.0% for a maximum waiting time of six hours. CONCLUSIONS Adequate bed estimation must consider reasons for limited timely access and patient flow management in a scenario that associates prioritization of requests with the lowest average length of stay.

DEMAND FORECAST AND OPTIMAL PLANNING OF INTENSIVE CARE UNIT (ICU) CAPACITY

Critical Care is a medical specialty which addresses the life-saving and lifesustaining management of patients at risk of imminent death. The number of Intensive Care Unit (ICU) beds has an impact on patient’s prognosis. This paper aims to determine the optimal number of ICU beds to reduce patient’s waiting time. Time series was applied to predict demand making use of information on the daily patient’s requests for ICU beds to obtain a demand forecast by means of exponential smoothing and Box-Jenkins models, which provided the input of a Queuing model. The outputs were the optimal number of ICU beds, in different scenarios, based on demand rate and patient’s length of stay (LOS). A maximum waiting time in the queue of 6 hours was proposed and compared to government recommendation (118-353 beds). The need for ICU beds varied from 345 to 592 for a 6-hour waiting time (for a LOS of 6.5 to 11.2 days, respectively). The results show that managing demand and discharge timing could control the queue. Moreover, they also suggest that the current recommendation is inadequate for the demand.