Estudo sobre a taxa de cancelamento de cirurgias eletivas em um hospital terciário de ensino e construção de um checklist pré-operatório

Abstract

BACKGROUND: Same day surgery cancellations cause great distress in SUS hospitals in Brazil. The impacts caused by the cancellation of surgeries stress the patient, have a negative economic impact on the hospital and reduces operating room performance´s. Several factors contribute to the cancellation of surgeries: user absenteeism, unfavorable clinical conditions, lack of preoperative clinical examinations, delayed operating room turn-over and lack of available hospital beds. OBJECTIVE: Build a preoperative checklist template to reduce the possibility of canceling elective surgeries. SPECIFIC OBJECTIVES: Estimate the causes of cancellation of elective surgeries and which specialties have the highest cancellation rate; Evaluate the cancellation rate of elective surgeries at the Hospital Universitário Getúlio Vargas; Prepare a management report for the Superintendent of the Hospital Universitário Getúlio Vargas with the data collected on the hospital's surgery cancellations. METHOD: Qualitative, descriptive, exploratory study using the Design-Thinking methodology. RESULTS: Between 2019 and 2021, a positive evolution was observed in the cancellation rate of elective surgeries at the HUGV, which went from 25.4%, a rate above the national average, to 18.2%. The current cancellation rate is within the Brazilian average for public hospitals. The creation of the Checklist aims to improve the surgical scheduling process, reducing the chances of setbacks with the patient, medical team and institution. CONCLUSION: Between 2019 and 2021, a positive evolution was observed in the cancellation rate of elective surgeries at the HUGV, which went from 25.4%, a rate above the national average, to 18.2%. The main cause of cancellation of surgeries was related to the patient, the main one being the lack of clinical conditions. A checklist was created, bringing a proposal for organization, data filtering and collection of important information for a surgical appointment with lower chances of cancellation, which must be applied in the pre-scheduling period up to two days before the procedure.