Surgical waiting lists and queue management in a Brazilian tertiary public hospital.

BACKGROUND: Centralized management of queues helps to reduce the surgical waiting time in the publicly funded healthcare system, but this is not a reality in the Brazilian Unified Healthcare System (BUHS). We describe the implementation of the "Patients with Surgical Indication" (PSI) in a Brazilian public tertiary hospital, the impact on waiting time, and its use in rationing oncological surgeries during the COVID-19 Pandemic. METHODS: Retrospective observational study of elective surgical requests (2016-2022) in a Brazilian general, public, tertiary university hospital. We recovered information regarding the inflows (indications), outflows and their reasons, the number of patients, and waiting time in queue. RESULTS: We enrolled 82,844 indications in the PSI (2016-2022). The waiting time (median and interquartile range) in days decreased from 98(48;168) in 2016 to 14(3;152) in 2022 (p < 0.01). The same occurred with the backlog that ranged from 6,884 in 2016 to 844 in 2022 (p < 001). During the Pandemic, there was a reduction in the number of non-oncological surgeries per month (95% confidence interval) of -10.9(-18.0;-3.8) during Phase I (January 2019-March 2020), maintenance in Phase II (April 2020-August 2021) 0.1(-10.0;10.4) and increment in Phase III (September 2021-December 2022) of 23.0(15.3;30.8). In the oncological conditions, these numbers were 0.6(-2.1;3.3) for Phase I, an increase of 3.2(0.7;5.6) in Phase II and 3.9(1,4;6,4) in Phase III. CONCLUSION: Implementing a centralized list of surgical indications and developing queue management principles proved feasible, with effective rationing. It unprecedentedly demonstrated the decrease in the median waiting time in Brazil.

Decreasing boarders in the emergency department by reducing clerical work in the discharge process of in-hospital patients in Brazil - an interrupted time-series analysis.

BACKGROUND: Emergency Department (ED) boarding is related to in-hospital patients' discharge since no beds will be available for receiving ED patients if there is a delay for patients in the yard leaving the hospital. New techniques implemented in hospital institutions, such as digital signatures to facilitate clerical work improve these processes. We evaluated the impact of expediting patients' discharge after medical orders with the number of patients with an unplanned hospital admission from the Hospital Out Clinic directed to ED for waiting for an available bed in a public tertiary hospital in Brazil. METHODS: We conducted a quasi-experimental study before and after an intervention. It consisted of an encrypted digital signature to reduce clerical work and expedite the patient's release from the institution after medical discharge. We used an interrupted time-series analysis based on administrative data (number of hospital discharges, bed turnover, the time between medical discharge, and the time the patient effectively left the hospital) from 2011 to 2020. RESULTS: We enrolled 210,496 patients admitted to the hospital from January 2011 to December 2020. Of those, 69,897(33%) composed the group after the intervention. There was no difference between the groups' gender, age distribution, the proportion of surgical patients, or in-hospital stay (≤ 7 or > 7 days). The interrupted time series analysis for the time from medical order to effectively hospital discharge showed an immediate change in level (Coefficient ß2 -3.6 h-95% confidence interval -3.9;-3.4), but no a difference in the slope of the behavior of the post-intervention curve (ß3 0.0005 coefficient-95% confidence interval -0.0040;0.0050). For the number of patients directed to ED, we observed no immediate change in level (Coefficient ß2 -0.84 patients-95% confidence interval -0.33;0.16), but a difference in the slope of the behavior of the post-intervention curve (ß3 0.0005 coefficient-95% confidence interval -0.0040;0.0050). CONCLUSION: Reducing clerical work and expediting patient discharge was associated with decreased potential boarders to ED.

Clinical impact of implementing a rapid-response team based on the Modified Early Warning Score in wards that offer emergency department support.

BACKGROUND: Emergency department (ED) crowding is a frequent situation. To decrease this overload, patients without a life-threating condition are transferred to wards that offer ED support. This study aimed to evaluate if implementing a rapid response team (RRT) triggered by the modified early warning score (MEWS) in high-risk wards offering ED support is associated with decreased in-hospital mortality rate. METHODS: A before-and-after cross-sectional study compared in-hospital mortality rates before and after implementation of an RRT triggered by the MEWS ≥4 in two wards of a tertiary hospital that offer ED support. RESULTS: We included 6863 patients hospitalized in these wards before RRT implementation from July 2015 through June 2017 and 6944 patients hospitalized in these same wards after RRT implementation from July 2018 through June 2020. We observed a statistically significant decrease in the in-hospital mortality rate after intervention, 449 deaths/6944 hospitalizations [6.47% (95% confidence interval (CI) 5.91%- 7.07%)] compared to 534 deaths/6863 hospitalizations [7.78% (95% CI 7.17-8.44)] before intervention; with an absolute risk reduction of -1.31% (95% CI -2.20 --0.50). CONCLUSION: RRT trigged by the MEWS≥4 in high-risk wards that offer ED support was found to be associated with a decreased in-hospital mortality rate. A further cluster-randomized trial should evaluate the impact of this intervention in this setting.