title: Quantifying the effect of complications on patient flow, costs and surgical throughputs.
abstract: 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.
  
  
  
  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.
  
  
  
  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.
  
  
  
  The study provides evidence supporting the need to incorporate adverse events data in resource planning to improve hospital performance.
authors: Department of Primary Care and Public Health, School of Public Health, Imperial College London, Charing Cross Campus, Reynolds Building, St Dunstans Road, London, W6 8RP, UK. a.almashrafi12@imperial.ac.uk.
authors: Ahmed
authors: 0000-0003-1072-8057
authors: A
authors: Almashrafi
authors: Department of Primary Care and Public Health, School of Public Health, Imperial College London, Charing Cross Campus, Reynolds Building, St Dunstans Road, London, W6 8RP, UK.
authors: Laura
authors: L
authors: Vanderbloemen
mesh_terms: D006348:Cardiac Surgical Procedures / Q000191:economics / Q000706:statistics & numerical data*; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D007902:Length of Stay / Q000191:economics / Q000706:statistics & numerical data*; D009850:Oman; D011183:Postoperative Complications / Q000191:economics
keywords: Cardiothoracic surgery; Complications; Discrete event simulation; Incremental LOS; Oman