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Background: Postoperative adverse events are known to increase length of stay and cost. However, research on how adverse events affect patient flow and operational performance has been relatively limited to date. Moreover, there is paucity of studies on the use of simulation in understanding the effect of complications on care processes and resources. In hospitals with scarcity of resources, postoperative complications can exert a substantial influence on hospital throughputs., Methods: This paper describes an evaluation method for assessing the effect of complications on patient flow within a cardiac surgical department. The method is illustrated by a case study where actual patient-level data are incorporated into a discrete event simulation (DES) model. The DES model uses patient data obtained from a large hospital in Oman to quantify the effect of complications on patient flow, costs and surgical throughputs. We evaluated the incremental increase in resources due to treatment of complications using Poisson regression. Several types of complications were examined such as cardiac complications, pulmonary complications, infection complications and neurological complications., Results: 48 % of the patients in our dataset experienced one or more complications. The most common types of complications were ventricular arrhythmia (16 %) followed by new atrial arrhythmia (15.5 %) and prolonged ventilation longer than 24 h (12.5 %). The total number of additional days associated with infections was the highest, while cardiac complications have resulted in the lowest number of incremental days of hospital stay. Complications had a significant effect on perioperative operational performance such as surgery cancellations and waiting time. The effect was profound when complications occurred in the Cardiac Intensive Care (CICU) where a limited capacity was observed., Conclusions: The study provides evidence supporting the need to incorporate adverse events data in resource planning to improve hospital performance.

Background: Intensive care unit (ICU) care is associated with costly and often scarce resources. In many parts of the world, ICUs are being perceived as major bottlenecks limiting downstream services such as operating theatres. There are many clinical, surgical and contextual factors that influence length of stay. Knowing these factors can facilitate resource planning. However, the extent at which this knowledge is put into practice remains unclear. The aim of this systematic review was to identify factors that impact the duration of ICU stay after cardiac surgery and to explore evidence on the link between understanding these factors and patient and resource management., Methods: We conducted electronic searches of Embase, PubMed, ISI Web of Knowledge, Medline and Google Scholar, and reference lists for eligible studies., Results: Twenty-nine papers fulfilled inclusion criteria. We recognised two types of objectives for identifying influential factors of ICU length of stay (LOS) among the reviewed studies. These were general descriptions of predictors and prediction of prolonged ICU stay through statistical models. Among studies with prediction models, only two studies have reported their implementation. Factors most commonly associated with increased ICU LOS included increased age, atrial fibrillation/ arrhythmia, chronic obstructive pulmonary disease (COPD), low ejection fraction, renal failure/ dysfunction and non-elective surgery status., Conclusion: Cardiac ICUs are major bottlenecks in many hospitals around the world. Efforts to optimise resources should be linked to patient and surgical characteristics. More research is needed to integrate patient and surgical factors into ICU resource planning.

Objectives: Two objectives were set for this study. The first was to identify factors influencing prolonged postoperative length of stay (LOS) following cardiac surgery. The second was to devise a predictive model for prolonged LOS in the cardiac intensive care unit (CICU) based on preoperative factors available at admission and to compare it against two existing cardiac stratification systems., Design: Observational retrospective study., Settings: A tertiary hospital in Oman., Participants: All adult patients who underwent cardiac surgery at a major referral hospital in Oman between 2009 and 2013., Results: 30.5% of the patients had prolonged LOS (≥11 days) after surgery, while 17% experienced prolonged ICU LOS (≥5 days). Factors that were identified to prolong CICU LOS were non-elective surgery, current congestive heart failure (CHF), renal failure, combined coronary artery bypass graft (CABG) and valve surgery, and other non-isolated valve or CABG surgery. Patients were divided into three groups based on their scores. The probabilities of prolonged CICU LOS were 11%, 26% and 28% for group 1, 2 and 3, respectively. The predictive model had an area under the curve of 0.75. Factors associated with prolonged overall postoperative LOS included the body mass index, the type of surgery, cardiopulmonary bypass machine use, packed red blood cells use, non-elective surgery and number of complications. The latter was the most important determinant of postoperative LOS., Conclusions: Patient management can be tailored for individual patient based on their treatments and personal attributes to optimise resource allocation. Moreover, a simple predictive score system to enable identification of patients at risk of prolonged CICU stay can be developed using data that are routinely collected by most hospitals., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)