Using Real-Time Locating Systems to Optimize Endoscope Use at a Large Academic Medical Center.

Massachusetts General Hospital (MGH) manages a large inventory of surgical equipment which must be delivered to operating rooms on-time, efficiently, and according to a set of quality standards and regulatory guidelines. In recent years, flexible scope management has become a topic of interest for many hospitals, as they face pressure to reduce costs, prevent infections that can result from mismanagement, and are under increased regulatory oversight. This work conducted at MGH proposes a novel method for surgical equipment management in a hospital. The proposed solution uses a real-time locating system to track flexible scopes, a semantic reasoning engine to determine the state of each scope, and a user interface to inform staff about necessary interventions to avoid scope expirations while maximizing efficiency. This study aimed to accomplish three primary goals. First, the study sought to improve the hospital's compliance to quality standards in order to reduce risks of infection due to expired scopes. Second, the study aimed to improve the cost-efficiency of scope disinfecting processes through more efficient inventory management. Finally, the study served as an opportunity for the hospital to establish best practices for working with the newly installed real-time locating system. The system proposed in this work was implemented at MGH on a subset of the hospital's flexible scopes. The study results demonstrated a quality compliance increase from 88.9% to 94.5%. The study also showed an estimated $17,350 annual cost savings due to more efficient scope management. Finally, the study demonstrated the feasibility, increase in regulatory compliance, and cost savings that would make this technology valuable when scaled across the hospital to other types of scopes and medical devices.

Optimizing Endoscope Reprocessing Resources Via Process Flow Queuing Analysis.

The Massachusetts General Hospital (MGH) is merging its older endoscope processing facilities into a single new facility that will enable high-level disinfection of endoscopes for both the ORs and Endoscopy Suite, leveraging economies of scale for improved patient care and optimal use of resources. Finalized resource planning was necessary for the merging of facilities to optimize staffing and make final equipment selections to support the nearly 33,000 annual endoscopy cases. To accomplish this, we employed operations management methodologies, analyzing the physical process flow of scopes throughout the existing Endoscopy Suite and ORs and mapping the future state capacity of the new reprocessing facility. Further, our analysis required the incorporation of historical case and reprocessing volumes in a multi-server queuing model to identify any potential wait times as a result of the new reprocessing cycle. We also performed sensitivity analysis to understand the impact of future case volume growth. We found that our future-state reprocessing facility, given planned capital expenditures for automated endoscope reprocessors (AERs) and pre-processing sinks, could easily accommodate current scope volume well within the necessary pre-cleaning-to-sink reprocessing time limit recommended by manufacturers. Further, in its current planned state, our model suggested that the future endoscope reprocessing suite at MGH could support an increase in volume of at least 90% over the next several years. Our work suggests that with simple mathematical analysis of historic case data, significant changes to a complex perioperative environment can be made with ease while keeping patient safety as the top priority.

Gastrointestinal tuberculosis following renal transplantation accompanied with septic shock and acute respiratory distress syndrome: a survival case presentation.

BACKGROUND: Post-transplant tuberculosis (PTTB) is a serious opportunistic infection in renal graft recipients with a 30-70 fold higher incidence compared to the general population. PTTB occurs most frequently within the first years after transplantation, manifesting as pulmonary or disseminated TB. Gastrointestinal TB (GITB) is a rare and potentially lethal manifestation of PTTB and may show delayed onset in renal transplant recipients due to the use of lower doses of immunosuppressants. Further, non-specificity of symptoms and the common occurrence of GI disorders in transplant recipients may delay diagnosis of GITB. CASE PRESENTATION: Here we report a rare survival case of isolated GITB in a renal transplant recipient, occurring seven years after transplantation. The patient's condition was complicated by severe sepsis with positive blood culture Staphylococcus haemolyticus, septic shock, multiple organ failure including acute respiratory distress syndrome (ARDS) and acute renal failure, requiring mechanical ventilation, vasopressor circulatory support and intermittent hemodialysis. Furthermore, nosocomial infections such as invasive aspergillosis and Pseudomonas aeruginosa occurred during hospitalization. Antituberculosis therapy (rifampicin, isoniazid, ethambutol and pyrazinamide) was initiated upon Mycobacterium confirmation. Moreover, treatment with voriconazole due to the Aspergillus flavus and meropenem due to the Pseudomonas aeruginosa was initiated, the former necessitating discontinuation of rifampicin. After 34 days, the patient was weaned from mechanical ventilation and was discharged to the pulmonary ward, followed by complete recovery. CONCLUSION: This case offers a guideline for the clinical management towards survival of GITB in transplant patients, complicated by septic shock and multiple organ failure, including acute renal injury and ARDS.

Direct admission to improve timely access to care for patients requiring transfer to a level 1 trauma center.

BACKGROUND: Emergency departments (EDs) at level 1 trauma centers are often overcrowded and deny ED-to-ED transfers from lower-tiered centers. Lack of access to timely level 1 care is associated with increased mortality. We evaluated the feasibility of a direct admission (DA) protocol as a method to increase timely access to a level 1 trauma center during periods of ED overcrowding. METHODS: During periods of ED overcrowding between 1 May and 31 December 2019, we admitted patients from referring EDs directly to the intensive care unit (ICU) or inpatient ward using the DA protocol. In a prospective comparative study design, we compared their outcomes to patients during the same period who were admitted through the ED when the ED was not overcrowded. RESULTS: During periods of ED overcrowding, transfer was requested and clinically accepted for 28 patients, of which 23 (82.1%, age 63±20.3 years, men 52.2% men) were successfully admitted via the DA protocol. Five (17.9%) were not successfully transferred due to lack of available inpatient beds. During periods when the ED was not overcrowded, 106 patients (age 62.8±23.1 years, men 52.8%) were admitted via the ED. There were no morbidity or mortality events attributed to the DA process. Time to patient arrival was 2.7 hours (95% CI 2.3 to 3.1) in the DA cohort and 1.9 hours (95% CI 1.5 to 2.4) in the ED-to-ED cohort (p=0.104). Up-triage to the ICU within 24 hours was performed in only one patient (4.3%). In-hospital mortality did not differ (3 (13%) vs. 8 (7.6%), p=0.392). DISCUSSION: The DA pathway is a feasible method to safely transfer patients from a referring ED to a higher-care trauma center when its ED is overcrowded. LEVEL OF EVIDENCE: Level III, care management.

Development and Validation of a Machine Learning Model to Aid Discharge Processes for Inpatient Surgical Care.

Importance: Inpatient overcrowding is associated with delays in care, including the deferral of surgical care until beds are available to accommodate postoperative patients. Timely patient discharge is critical to address inpatient overcrowding and requires coordination among surgeons, nurses, case managers, and others. This is difficult to achieve without early identification and systemwide transparency of discharge candidates and their respective barriers to discharge. Objective: To validate the performance of a clinically interpretable feedforward neural network model that could improve the discharge process by predicting which patients would be discharged within 24 hours and their clinical and nonclinical barriers. Design, Setting, and Participants: This prognostic study included adult patients discharged from inpatient surgical care from May 1, 2016, to August 31, 2017, at a quaternary care teaching hospital. Model performance was assessed with standard cross-validation techniques. The model's performance was compared with a baseline model using historical procedure median length of stay to predict discharges. In prospective cohort analysis, the feedforward neural network model was used to make predictions on general surgical care floors with 63 beds. If patients were not discharged when predicted, the causes of delay were recorded. Main Outcomes and Measures: The primary outcome was the out-of-sample area under the receiver operating characteristic curve of the model. Secondary outcomes included the causes of discharge delay and the number of avoidable bed-days. Results: The model was trained on 15 201 patients (median [interquartile range] age, 60 [46-70] years; 7623 [50.1%] men) discharged from inpatient surgical care. The estimated out-of-sample area under the receiver operating characteristic curve of the model was 0.840 (SD, 0.008; 95% CI, 0.839-0.844). Compared with the baseline model, the neural network model had higher sensitivity (52.5% vs 56.6%) and specificity (51.7% vs 82.6%). The neural network model identified 65 barriers to discharge. In the prospective study of 605 patients, causes of delays included clinical barriers (41 patients [30.1%]), variation in clinical practice (30 patients [22.1%]), and nonclinical reasons (65 patients [47.8%]). Summing patients who were not discharged owing to variation in clinical practice and nonclinical reasons, 128 bed-days, or 1.2 beds per day, were classified as avoidable. Conclusions and Relevance: This cohort study found that a neural network model could predict daily inpatient surgical care discharges and their barriers. The model identified systemic causes of discharge delays. Such models should be studied for their ability to increase the timeliness of discharges.

A case of severe chlorite poisoning successfully treated with early administration of methylene blue, renal replacement therapy, and red blood cell transfusion: case report.

The case of a 55-year-old man who attempted suicide by ingesting <100 mL of 28% sodium chlorite solution is presented. On arrival in the intensive care unit, the patient appeared cyanotic with lowered consciousness and displayed anuria and chocolate brown serum.Initial laboratory tests revealed 40% of methemoglobin. The formation of methemoglobin was effectively treated with methylene blue (10% after 29 hours).To remove the toxin, and because of the anuric acute renal failure, the patient received renal replacement therapy. Despite these therapeutic measures, the patient developed hemolytic anemia and disseminated intravascular coagulation, which were treated with red blood cell transfusion and intermittent hemodialysis. These interventions led to the improvement of his condition and the patient eventually fully recovered. Patient gave written informed consent.This is the third known case of chlorite poisoning that has been reported. Based upon this case, we suggest the management of sodium chlorite poisoning to comprise the early administration of methylene blue, in addition to renal replacement therapy and transfusion of red blood cells.