IntroductionPatient progress, the movement of patients through a hospital system from admission to discharge, is a foundational component of operational effectiveness in healthcare institutions. Optimal patient progress is a key to delivering safe, high-quality and high-value clinical care. The Baystate Patient Progress Initiative (BPPI), a cross-disciplinary, multifaceted quality and process improvement project, was launched on March 1, 2014, with the primary goal of optimizing patient progress for adult patients.MethodsThe BPPI was implemented at our system’s tertiary care, academic medical center, a high-volume, high-acuity hospital that serves as a regional referral center for western Massachusetts. The BPPI was structured as a 24-month initiative with an oversight group that ensured collaborative goal alignment and communication of operational teams. It was organized to address critical aspects of a patient’s progress through his hospital stay and to create additional inpatient capacity. The specific goal of the BPPI was to decrease length of stay (LOS) on the inpatient adult Hospital Medicine service by optimizing an interdisciplinary plan of care and promoting earlier departure of discharged patients. Concurrently, we measured the effects on emergency department (ED) boarding hours per patient and walkout rates.ResultsThe BPPI engaged over 300 employed clinicians and non-clinicians in the work. We created increased inpatient capacity by implementing daily interdisciplinary bedside rounds to proactively address patient progress; during the 24 months, this resulted in a sustained rate of discharge orders written before noon of more than 50% and a decrease in inpatient LOS of 0.30 days (coefficient: −0.014, 95% CI [−0.023, −0.005] P< 0.005). Despite the increase in ED patient volumes and severity of illness over the same time period, ED boarding hours per patient decreased by approximately 2.1 hours (coefficient: −0.09; 95% CI [−0.15, −0.02] P = 0.007). Concurrently, ED walkout rates decreased by nearly 32% to a monthly mean of 0.4 patients (coefficient: 0.4; 95% CI [−0.7, −0.1] P= 0.01).ConclusionThe BPPI realized significant gains in patient progress for adult patients by promoting earlier discharges before noon and decreasing overall inpatient LOS. Concurrently, ED boarding hours per patient and walkout rates decreased.
Diagnostic errors comprise a critical subset of medical errors and often stem from errors in individual cognition. While traditional patient safety methods for dissecting medical errors focus on faulty systems, such methods are often less useful in cases of diagnostic error, and a broader cognitive framework is needed to ensure a comprehensive analysis of these complex events. The fishbone diagram is a widely utilized patient safety tool that helps to facilitate root cause analysis discussions. This tool was expanded by the authors to reflect the contributions of both systems and individual cognitive errors to diagnostic errors. We describe how two medical centers have applied this modified fishbone diagram to approach diagnostic errors in a way that better meets the patient safety and educational needs of their respective institutions.
Background Initial recommendations discouraged high flow nasal cannula (HFNC) in COVID-19 patients, driven by concern for healthcare worker (HCW) exposure. Noting high morbidity and mortality from early invasive mechanical ventilation, we implemented a COVID-19 respiratory protocol employing HFNC in severe COVID-19 and HCW exposed to COVID-19 patients on HFNC wore N95/KN95 masks. Utilization of HFNC increased significantly but questions remained regarding HCW infection rate. Methods We performed a retrospective evaluation of employee infections in our healthcare system using the Employee Health Services database and unit records of employees tested between March 15, 2020 and May 23, 2020. We assessed the incidence of infections before and after the implementation of the protocol, stratifying by clinical or non-clinical role as well as inpatient COVID-19 unit. Results During the study period, 13.9% (228/1635) of employees tested for COVID-19 were positive. Forty-six percent of infections were in non-clinical staff. After implementation of the respiratory protocol, the proportion of positive tests in clinical staff (41.5%) was not higher than that in non-clinical staff (43.8%). Of the clinicians working in the high-risk COVID-19 unit, there was no increase in infections after protocol implementation compared with clinicians working in COVID-19 units that did not use HFNC. Conclusion We found no evidence of increased COVID-19 infections in HCW after the implementation of a respiratory protocol that increased use of HFNC in patients with COVID-19; however, these results are hypothesis generating.
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