RESUMEN

BACKGROUND: The Operating Theatre (OT) is the largest cost centre as well as the main revenue generator in most hospitals. One of the common problems affecting optimal OT utilization is the cancellation of scheduled surgeries. The goal of this study was to identify factors associated with cancellation within 24 h of scheduled surgeries in a tertiary hospital. METHODS: All elective surgeries performed on adults 18 years and above between June 2015 and December 2016 were included. Cancellations ≤24 h from the scheduled start time of the surgery were recorded, with their reasons for cancellation. Data relating to the patient, surgeon and planned surgery were obtained from the hospital operational database. Univariate analysis and multivariable analysis were conducted using logistic regression. RESULTS: A total of 4060 scheduled surgeries were included, of which 398 (9.8%) were cancelled within 24 h of surgery. On multivariate analysis, cancellation within 24 h of surgery was associated with history of heart failure (Adjusted odds ratio, AOR1.65; 95%CI 1.08-2.50), advanced chronic kidney disease (AOR2.33; 95%CI 1.58-3.39), or a history of hip fracture (AOR2.29; 95%CI 1.33-3.80), low socio-economic status (on Medifund financing, AOR3.16; 95%CI 1.37-6.72), history of ≥4 cancelled surgeries in the past 3 years (AOR2.38; 95%CI 1.30-4.19), and scheduled time in the afternoon (AOR1.83; 95%CI 1.44-2.32) and evening (AOR2.09; 95%CI0.73-5.13), compared to the morning. Attendance at preoperative anaesthesia assessment clinic was associated with reduced likelihood of cancellation (AOR0.55; 95%CI0.43-0.72). CONCLUSIONS: Several patient and system factors can be used to identify scheduled surgeries that are at high likelihood of cancellation within 24 h of surgery, which may inform strategies to improve the efficiency of OT utilization, including having a dedicated preoperative anaesthesia assessment clinic.

Asunto(s)

Centros Médicos Académicos/estadística & datos numéricos , Procedimientos Quirúrgicos Electivos/estadística & datos numéricos , Pacientes no Presentados/estadística & datos numéricos , Quirófanos/estadística & datos numéricos , Adulto , Anestesiología/estadística & datos numéricos , Citas y Horarios , Estudios de Cohortes , Comorbilidad , Femenino , Investigación sobre Servicios de Salud/métodos , Humanos , Masculino , Cuidados Preoperatorios/métodos , Factores de Riesgo , Singapur , Clase Social , Centros de Atención Terciaria/estadística & datos numéricos , Factores de Tiempo

RESUMEN

OBJECTIVES: Emergency Department crowding is a serious and international health care problem that seems to be resistant to most well intended but often reductionist policy approaches. In this study, we examine Emergency Department crowding in Singapore from a systems thinking perspective using causal loop diagramming to visualize the systemic structure underlying this complex phenomenon. Furthermore, we evaluate the relative impact of three different policies in reducing Emergency Department crowding in Singapore: introduction of geriatric emergency medicine, expansion of emergency medicine training, and implementation of enhanced primary care. METHODS: The construction of the qualitative causal loop diagram is based on consultations with Emergency Department experts, direct observation, and a thorough literature review. For the purpose of policy analysis, a novel approach, the path analysis, is applied. RESULTS: The path analysis revealed that both the introduction of geriatric emergency medicine and the expansion of emergency medicine training may be associated with undesirable consequences contributing to Emergency Department crowding. In contrast, enhancing primary care was found to be germane in reducing Emergency Department crowding; in addition, it has apparently no negative side effects, considering the boundary of the model created. CONCLUSION: Causal loop diagramming was a powerful tool for eliciting the systemic structure of Emergency Department crowding in Singapore. Additionally, the developed model was valuable in testing different policy options.