Improving Patient Safety for Surgical Clearance: A PreOp One Stop Shop

Problem: Medical clearance is required for patients scheduled for surgery, also known as “patient optimization.” Ineffective and inefficient patient optimization is a major contributor to surgery postponements, procedure cancellations, and patient dissatisfaction. Context: Ambulatory care clinics often lack resources to medically clear patients prior to scheduled surgery. Poor surgical optimization continues to occur on the same day of surgery, resulting in case cancellation or delay in a suburban, 169 bed community hospital with 9 operating rooms and approximately 500 surgical procedures per month. Interventions: A nurse-led PreOp One Stop Shop (POSS) utilized a standardized checklist to perform preoperative surgical assessment. Measures: System-generated reports assisted in ranking contributing factors that impacted day of surgery cancellations rates, outpatient care experience scores, and staff engagement metrics were reviewed and analyzed weekly between August 2021 to July 2022. Results: A nurse-led POSS decreased the number of same-day surgical cancellations from 10% to 3%, improved the standardized patient care experience measures from 78% to 79%, and increased internal staff engagement scores from 72% to 77% by July 2022. Conclusion: A standardized checklist and associated workflows are recommended for routine presurgical assessment to expedite medical clearance and promote reliable patient optimization. The implementation of a nurse-led PreOp One Stop Shop (POSS) can lead to improved patient safety outcomes and add value for organizational metrics such as patient centered care and staff engagement. Keywords: surgical cancellations; patient optimization; workflows; care experience; medical clearance; safet

Use of location data for the surveillance, analysis, and optimization of clinical processes

Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2006.Includes bibliographical references (leaves 33-35).Location tracking systems in healthcare produce a wealth of data applicable across many aspects of care and management. However, since dedicated location tracking systems, such as the oft mentioned RFID tracking system, are still sparsely deployed, a number of other data sources may be utilized to serve as a proxy for physical location, such as barcodes and manual timestamp entry, and may be better suited to indicate progress through clinical workflows. INCOMING!, a web-based platform that monitors and tracks patient progress from the operating room to the post-anesthesia care unit (PACU), is one such system that utilizes manual timestamps routinely entered as standard process of care in the operating room in order to track a patient's progress through the post-operative period. This integrated real time system facilitates patient flow between the PACU and the surgical ward and eases PACU workload by reducing the effort of discharging patients.(cont.) We have also developed a larger-scale integrated system for perioperative processes that integrates perioperative data from anesthesia and surgical devices and operating room (OR) / hospital information systems, and projects the real-time integrated data as a single, unified, easy to visualize display. The need to optimize perioperative throughput creates a demand for integration of the datastreams and for timely data presentation. The system provides improved context-sensitive information display, improved real-time monitoring of physiological data, real-time access to readiness information, and improved workflow management. These systems provide improved data access and utilization, providing context-aware applications in healthcare that are aware of a user's location, environment, needs, and goals.by Mark A. Meyer.S.M

Measuring performance in healthcare

Hospitals invest in process management and process optimization from an organizational and patient perspective to increase efficiency and simultaneously the quality of their operations. Consequently, the use of process-oriented performance measurement systems gains importance. This study contributes to the development of a dashboard for the process of hip surgery using a case study design. We integrate strategic goals of hospital management and different stakeholders with the analysis of Business Process Management and Hospital Information Systems’ data. Process-oriented KPIs were integrated into the dashboard using a three-step approach. Dashboards enable healthcare organizations to put process-oriented performance measurement into practice

Building a well-balanced culture in the perioperative setting.

Healthcare institutions are currently under enormous financial, political and social pressure. Especially in the perioperative setting, various professional groups with differing agendas, dynamic teams, high-stress levels and diverging stakeholder interests are contributing to tension on a variety of levels. These players ask for guidance that goes beyond defined goals, clear structures or rules for process optimization. The impact of culture, which is influenced by core values, unspoken behaviours and practices, a shared purpose and implicit norms, has been often neglected. However, culture is a key factor in the search for optimal patient outcomes, quality of care, protection and long-time retention of staff, as well as economic success. In this review, we discuss important aspects to consider in building a great perioperative workplace, discuss indispensable adaptations in times of crisis and touch on urgently needed further investigations to optimize the art of developing, protecting, and cultivating a well-balanced culture

Utilizing artificial intelligence in perioperative patient flow:systematic literature review

Abstract. The purpose of this thesis was to map the existing landscape of artificial intelligence (AI) applications used in secondary healthcare, with a focus on perioperative care. The goal was to find out what systems have been developed, and how capable they are at controlling perioperative patient flow. The review was guided by the following research question: How is AI currently utilized in patient flow management in the context of perioperative care? This systematic literature review examined the current evidence regarding the use of AI in perioperative patient flow. A comprehensive search was conducted in four databases, resulting in 33 articles meeting the inclusion criteria. Findings demonstrated that AI technologies, such as machine learning (ML) algorithms and predictive analytics tools, have shown somewhat promising outcomes in optimizing perioperative patient flow. Specifically, AI systems have proven effective in predicting surgical case durations, assessing risks, planning treatments, supporting diagnosis, improving bed utilization, reducing cancellations and delays, and enhancing communication and collaboration among healthcare providers. However, several challenges were identified, including the need for accurate and reliable data sources, ethical considerations, and the potential for biased algorithms. Further research is needed to validate and optimize the application of AI in perioperative patient flow. The contribution of this thesis is summarizing the current state of the characteristics of AI application in perioperative patient flow. This systematic literature review provides information about the features of perioperative patient flow and the clinical tasks of AI applications previously identified

Improving surgical patient flow in a congested recovery area

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 63).The recent movement in healthcare reform requires hospitals to care for more patients while simultaneously reducing costs. Medical institutions can no longer afford to simply add beds and hire staff to increase capacity. They must use existing resources more effectively and develop innovative solutions to increase capacity. This project focuses on the redesign of surgical patient flow through multiple Post-Anesthesia Care Units (PACUs) at Massachusetts General Hospital (MGH). The PACU is where surgical patients recover following their procedure that takes place in the Operating Room (OR) suite. Some patients experience delays when leaving the OR due to the lack of a staffed PACU bed. These patients begin the recovery process in the OR which causes delays for to-follow cases. In addition, the OR nursing staff rather than a PACU nurse must monitor recovery, which drives higher costs and frustrates staff members. Therefore this study examined the sources of delay and sought to redesign the flow of surgical patients through the PACUs. Our main recommendation is to incorporate a "Fast Track" for the outpatient population that eliminates delays and expedites outpatient processing in the PACU. Segregating the outpatients and implementing the one-stop "Fast Track" recovery process will reduce average outpatient PACU length of stay (length of stay) by 27%, the equivalent of adding 1.8 beds of capacity. Through the application of operations management techniques, we can decrease the patient processing time or length of stay in the PACU, which in turn increases throughput and creates additional capacity.by Trevor A. Schwartz.S.M.M.B.A

Developing a data-driven approach for improving operating room scheduling processes

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 52).In the current healthcare environment, the cost of delivering patient care is an important concern for hospitals. As a result, healthcare organizations are being driven to maximize their existing resources, both in terms of infrastructure and human capital. Using a data-driven approach with analytical techniques from operations management can contribute towards this goal. More specifically, this thesis shows, drawing from a recent project at Beth Israel Deaconess Medical Center (BIDMC), that predictive modeling can be applied to operating room (OR) scheduling in order to effectively increase capacity. By examining the current usage of the existing block schedule system at BIDMC and developing a linear regression model, OR time that is expected to go unused can be instead identified in advance and freed for use. Sample model results show that it is expected to be operationally effective by capturing a large enough portion of OR time for a pooled set of blocks to be useful for advanced scheduling purposes. This analytically determined free time represents an improvement in how the current block system is employed, especially in terms of the nominal block release time. This thesis makes the argument that such a model can integrate into a scheduling system with more efficient and flexible processes, ultimately resulting in more effective usage of existing resources.by Gregory C. Sham.S.M.M.B.A

Continuous roadmapping in liver TACE procedures using 2D–3D catheter-based registration

PURPOSE: Fusion of pre/perioperative images and intra-operative images may add relevant information during image-guided procedures. In abdominal procedures, respiratory motion changes the position of organs, and thus accurate image guidance requires a continuous update of the spatial alignment of the (pre/perioperative) information with the organ position during the intervention. METHODS: In this paper, we propose a method to register in real time perioperative 3D rotational angiography images (3DRA) to intra-operative single-plane 2D fluoroscopic images for improved guidance in TACE interventions. The method uses the shape of 3D vessels extracted from the 3DRA and the 2D catheter shape extracted from fluoroscopy. First, the appropriate 3D vessel is selected from the complete vascular tree using a shape similarity metric. Subsequently, the catheter is registered to this vessel, and the 3DRA is visualized based on the registration results. The method is evaluated on simulated data and clinical data. RESULTS: The first selected vessel, ranked with the shape similarity metric, is used more than 39 % in the final registration and the second more than 21 %. The median of the closest corresponding points distance between 2D angiography vessels and projected 3D vessels is 4.7–5.4 mm when using the brute force optimizer and 5.2–6.6 mm when using the Powell optimizer. CONCLUSION: We present a catheter-based registration method to continuously fuse a 3DRA roadmap arterial tree onto 2D fluoroscopic images with an efficient shape similarity

Perioperative Care

Perioperative care practices worldwide are in the midst of a seeing change with the implementation of multidisciplinary processes that improve surgical outcomes through (1) better patient education, engagement, and participation; (2) enhanced pre-operative, intra-operative, and post-operative care bundles; and (3) interactive audit programs that provide feedback to the surgical team. These improved outcomes include reductions in the frequency and severity of complications and improved throughput, which ultimately reduce operative stress. Practices in theatre as well as ward are becoming more collaborative and evidence-driven.This book is best utilized by perioperative care team members engaged in quality improvement, collaborative practice, and application of innovations in surgical care