IDENTIFYING THE OPTIMAL MODEL FOR THE DELIVERY OF PREOPERATIVE REGIONAL ANAESTHESIA IN THE CONTEXT OF THE ONGOING LABOUR CRISIS

Regional anesthesia (RA) is being increasingly utilized in orthopaedic surgery due to its clinical and perioperative efficiency benefits. It allows parallel processing of patients while preceding surgical cases are ongoing. Although several staffing models exist, they broadly fall into two categories: 1) a “back and forth” co-management of patients with allied health professionals such as anesthesia assistants (“back and forth” model) or 2) an extra anesthetist in a block room (“dedicated anesthetist” model). Each configuration has its unique cost-benefit profile and as such, the purpose of this study is to compare the two common models for perioperative RA delivery across key financial and efficiency metrics. A discrete-event simulation (DES) model of daily OR patient flow for arthroplasty procedures at a mid-sized academic-affiliated hospital performing approximately 10,000 procedures per year was developed. Data from the operating room (OR) management software, OR schedule, accounting department, and published literature was used to construct the model. To compare differences in performance across operational and financial outcome metrics, two scenarios were tested against the current state (baseline). Ten thousand simulations were run with common random numbers to reduce output variability. A comparison was made between the two scenarios across key performance metrics as follows: staffing requirements, hours required per day, and labour costs. The configuration of the number of ORs and cases varied from 2 to 6 ORs performing 3 to 5 cases each. These results were then used as the inputs of a Discounted Cash Flow (DCF) model, with additional model input assumptions based on literature and financial data provided by our accounting department. The configuration of the number of ORs and cases selected for the DCF model was three simultaneous ORs with four cases each per day. The difference in profit between no BR and BR represented the Cash Flow (CF) in per annum. Both scenarios resulted in time savings (mean: 68 min, range: 30–80 min) and incremental labour savings ($55,055–56,355 profit/day) over the current state. In the selected configuration (three ORs, four cases per day), the “back and forth” model was more profitable by $1300 per day than the dedicated BR model, and these incremental benefits over the “dedicated anesthetist” model increased by an additional $1930 with the addition of a fourth OR. This study demonstrates that both scenarios of administering RA are profitable to a baseline model without a block room. The “back and forth” model was financially preferable in all scenarios given the higher cost of a dedicated anesthetist. Notably, the DES model also demonstrated that an additional dedicated anesthetist was required with greater than three simultaneous ORs. As such, the incremental profits of the “back and forth” model over the “dedicated anesthetist” model nearly double with four concurrent ORs. Given the granular detail of our models, our methodology can be applied to hospitals irrespective of size or configuration to rapidly determine the ideal model for each individual hospital. In addition, the model can incorporate other proven efficiency strategies such as machine-learning case scheduling, the staggering of OR start times, and utilization of alternative staffing models.