An Open-Source, Interoperable Architecture for Generating Real-Time Surgical Team Cognitive Alerts from Heart-Rate Variability Monitoring.

Clinical alarm and decision support systems that lack clinical context may create non-actionable nuisance alarms that are not clinically relevant and can cause distractions during the most difficult moments of a surgery. We present a novel, interoperable, real-time system for adding contextual awareness to clinical systems by monitoring the heart-rate variability (HRV) of clinical team members. We designed an architecture for real-time capture, analysis, and presentation of HRV data from multiple clinicians and implemented this architecture as an application and device interfaces on the open-source OpenICE interoperability platform. In this work, we extend OpenICE with new capabilities to support the needs of the context-aware OR including a modularized data pipeline for simultaneously processing real-time electrocardiographic (ECG) waveforms from multiple clinicians to create estimates of their individual cognitive load. The system is built with standardized interfaces that allow for free interchange of software and hardware components including sensor devices, ECG filtering and beat detection algorithms, HRV metric calculations, and individual and team alerts based on changes in metrics. By integrating contextual cues and team member state into a unified process model, we believe future clinical applications will be able to emulate some of these behaviors to provide context-aware information to improve the safety and quality of surgical interventions.

The Launch of the iCoDE Standard Project.

INTRODUCTION: The first meeting of the Integration of Continuous Glucose Monitor Data into the Electronic Health Record (iCoDE) project, organized by Diabetes Technology Society, took place virtually on January 27, 2022. METHODS: Clinicians, government officials, data aggregators, attorneys, and standards experts spoke in panels and breakout groups. Three themes were covered: 1) why digital health data integration into the electronic health record (EHR) is needed, 2) what integrated continuously monitored glucose data will look like, and 3) how this process can be achieved in a way that will satisfy clinicians, healthcare organizations, and regulatory experts. RESULTS: The meeting themes were addressed within eight sessions: 1) What Do Inpatient Clinicians Want to See With Integration of CGM Data into the EHR?, 2) What Do Outpatient Clinicians Want to See With Integration of CGM Data into the EHR?, 3) Why Are Data Standards and Guidances Useful?, 4) What Value Can Data Integration Services Add?, 5) What Are Examples of Successful Integration?, 6) Which Privacy, Security, and Regulatory Issues Must Be Addressed to Integrate CGM Data into the EHR?, 7) Breakout Group Discussions, and 8) Presentation of Breakout Group Ideas. CONCLUSIONS: Creation of data standards and workflow guidance are necessary components of the Integration of Continuous Glucose Monitor Data into the Electronic Health Record (iCoDE) standard project. This meeting, which launched iCoDE, will be followed by a set of working group meetings intended to create the needed standard.

Design Implementation and Evaluation of a Mobile Continuous Blood Oxygen Saturation Monitoring System.

OBJECTIVE: In this study, we built a mobile continuous Blood Oxygen Saturation (SpO2) monitor, and for the first time, explored key design principles towards daily applications. METHODS: We firstly built a customized wearable computer that can sense two-channel photoplethysmogram (PPG) signals, and transmit the signals wirelessly to smartphone. Afterwards, we explored many SpO2 model building principles, focusing on linear/nonlinear models, different PPG parameter calculation methods, and different finger types. Moreover, we further compared PPG sensor placement principles by comparing different hand configurations and different finger configurations. Finally, a dataset collected from eleven human subjects was used to evaluate the mobile health monitor and explore all of the above design principles. RESULTS: The experimental results show that the root mean square error of the SpO2 estimation is only 1.8, indicating the effectiveness of the system. CONCLUSION: These results indicate the effectiveness of the customized mobile SpO2 monitor and the selected design principles. SIGNIFICANCE: This research is expected to facilitate the continuous SpO2 monitoring of patients with clinical indications.

Applying Medical Device Informatics to Enable Safe and Secure Interoperable Systems: Medical Device Interface Data Sheets.

This article describes the concept of Medical Device Interface Data Sheets (MDIDSs) to document and characterize medical device interface data requirements, the processes for creating MDIDSs, and its role in supporting patient safety and cybersecurity of current systems while enabling innovation in the area of next-generation medical Internet of Things (IoT) platforms for integrating sensors, actuators, and applications (apps).

Establishing a Ventilator-Heart Lung Machine Communication Bridge to Mitigate Errors when Weaning from Bypass.

If a perfusionist weans a patient off the heart lung machine (HLM) and the anesthesiologist has not re-started the ventilator, the patient will become hypoxic. The objective of this project was to create a redundant safety system of verbal and electronic communication to prevent failure to ventilate errors after cardiopulmonary bypass. This objective could be realized by building an electronic communication bridge directly between the HLM and ventilator. A software application was created to retrieve and interpret data from the pump and ventilator and trigger a programmed smart alarm. The software is able to interpret data from the pump and ventilator. When both are off simultaneously (defined as a pump flow of 0 L/min with a respiratory rate of 0 breaths/min), the application will raies an alarm. Communication between a pump and ventilator is possible, enabling the deployment of a safety system that could exist in the operating room (OR) as a standalone alarm. A device dataset can be used to optimize clinical performance of the alarm. The application could also be integrated into smart checklists and computer-assisted OR process models that are currently in development.

Development of an Interactive Dashboard to Analyze Cognitive Workload of Surgical Teams During Complex Procedural Care.

In the surgical setting, team members constantly deal with a high-demand operative environment that requires simultaneously processing a large amount of information. In certain situations, high demands imposed by surgical tasks and other sources may exceed team member's cognitive capacity, leading to cognitive overload which may place patient safety at risk. In the present study, we describe a novel approach to integrate an objective measure of team member's cognitive load with procedural, behavioral and contextual data from real-life cardiac surgeries. We used heart rate variability analysis, capturing data simultaneously from multiple team members (surgeon, anesthesiologist and perfusionist) in a real-time and unobtrusive manner. Using audio-video recordings, behavioral coding and a hierarchical surgical process model, we integrated multiple data sources to create an interactive surgical dashboard, enabling the analysis of the cognitive load imposed by specific steps, substeps and/or tasks. The described approach enables us to detect cognitive load fluctuations over time, under specific conditions (e.g. emergencies, teaching) and in situations that are prone to errors. This in-depth understanding of the relationship between cognitive load, task demands and error occurrence is essential for the development of cognitive support systems to recognize and mitigate errors during complex surgical care in the operating room.

Intelligent Interruption Management System to Enhance Safety and Performance in Complex Surgical and Robotic Procedures.

Procedural flow disruptions secondary to interruptions play a key role in error occurrence during complex medical procedures, mainly because they increase mental workload among team members, negatively impacting team performance and patient safety. Since certain types of interruptions are unavoidable, and consequently the need for multitasking is inherent to complex procedural care, this field can benefit from an intelligent system capable of identifying in which moment flow interference is appropriate without generating disruptions. In the present study we describe a novel approach for the identification of tasks imposing low cognitive load and tasks that demand high cognitive effort during real-life cardiac surgeries. We used heart rate variability analysis as an objective measure of cognitive load, capturing data in a real-time and unobtrusive manner from multiple team members (surgeon, anesthesiologist and perfusionist) simultaneously. Using audio-video recordings, behavioral coding and a hierarchical surgical process model, we integrated multiple data sources to create an interactive surgical dashboard, enabling the identification of specific steps, substeps and tasks that impose low cognitive load. An interruption management system can use these low demand situations to guide the surgical team in terms of the appropriateness of flow interruptions. The described approach also enables us to detect cognitive load fluctuations over time, under specific conditions (e.g. emergencies) or in situations that are prone to errors. An in-depth understanding of the relationship between cognitive overload states, task demands, and error occurrence will drive the development of cognitive supporting systems that recognize and mitigate errors efficiently and proactively during high complex procedures.

Toward Improving Surgical Outcomes by Incorporating Cognitive Load Measurement into Process-Driven Guidance.

This paper summarizes the accomplishments and recent directions of our medical safety project. Our process-based approach uses a detailed, rigorously-defined, and carefully validated process model to provide a dynamically updated, context-aware and thus, "Smart" Checklist to help process performers understand and manage their pending tasks [7]. This paper focuses on support for teams of performers, working independently as well as in close collaboration, in stressful situations that are life critical. Our recent work has three main thrusts: provide effective real-time guidance for closely collaborating teams; develop and evaluate techniques for measuring cognitive load based on biometric observations and human surveys; and, using these measurements plus analysis and discrete event process simulation, predict cognitive load throughout the process model and propose process modifications to help performers better manage high cognitive load situations. This project is a collaboration among software engineers, surgical team members, human factors researchers, and medical equipment instrumentation experts. Experimental prototype capabilities are being built and evaluated based upon process models of two cardiovascular surgery processes, Aortic Valve Replacement (AVR) and Coronary Artery Bypass Grafting (CABG). In this paper we describe our approach for each of the three research thrusts by illustrating our work for heparinization, a common subprocess of both AVR and CABG. Heparinization is a high-risk error-prone procedure that involves complex team interactions and thus highlights the importance of this work for improving patient outcomes.

OpenICE medical device interoperability platform overview and requirement analysis.

We give an overview of OpenICE, an open source implementation of the ASTM standard F2761 for the Integrated Clinical Environment (ICE) that leverages medical device interoperability, together with an analysis of the clinical and non-functional requirements and community process that inspired its design.

A Novel Interoperable Safety System for Improved Coordination and Communication in Cardiac Surgery.

During cardiac surgery there is an unmet need for safe transfer of responsibility for patient oxygenation back and forth from the anesthesia to the perfusion teams. Prior to cardiopulmonary bypass (CPB), lung ventilation is performed by the anesthesia machine ventilator and is the responsibility of the anesthesia team. During CPB, lung ventilation is halted and oxygenation is performed by the CPB oxygenator and perfusion team This recurrent transfer throughout the procedure introduces the rare but serious possibility of a "never event", resulting in the patient's lungs not being ventilated upon stopping the CPB and potentially leading to catastrophic hypoxemia. Monitors and alarms on the anesthesia and bypass machines would not be useful when the other device is operating so they are routinely put into a standby mode until needed. Consequently, in the event that the handoff is missed, there are no alarms to catch the situation. To solve this unmet need, we propose a novel interoperable, context-aware system capable of detecting and acting if this rare situation occurs. Our system is built on the open-source OpenICE framework, allowing it to seamlessly work with a variety of ventilator and bypass machines.

Cognitive Support During High-Consequence Episodes of Care in Cardiovascular Surgery.

Despite significant efforts to reduce preventable adverse events in medical processes, such events continue to occur at unacceptable rates. This paper describes a computer science approach that uses formal process modeling to provide situationally aware monitoring and management support to medical professionals performing complex processes. These process models represent both normative and non-normative situations, and are validated by rigorous automated techniques such as model checking and fault tree analysis, in addition to careful review by experts. Context-aware Smart Checklists are then generated from the models, providing cognitive support during high-consequence surgical episodes. The approach is illustrated with a case study in cardiovascular surgery.

Capturing Essential Information to Achieve Safe Interoperability.

In this article, we describe the role of "clinical scenario" information to assure the safety of interoperable systems, as well as the system's ability to deliver the requisite clinical functionality to improve clinical care. Described are methods and rationale for capturing the clinical needs, workflow, hazards, and device interactions in the clinical environment. Key user (clinician and clinical engineer) needs and system requirements can be derived from this information, therefore, improving the communication from clinicians to medical device and information technology system developers. This methodology is intended to assist the health care community, including researchers, standards developers, regulators, and manufacturers, by providing clinical definition to support requirements in the systems engineering process, particularly those focusing on development of Integrated Clinical Environments described in standard ASTM F2761. Our focus is on identifying and documenting relevant interactions and medical device capabilities within the system using a documentation tool called medical device interface data sheets and mitigating hazardous situations related to workflow, product usability, data integration, and the lack of effective medical device-health information technology system integration to achieve safe interoperability. Portions of the analysis of a clinical scenario for a "patient-controlled analgesia safety interlock" are provided to illustrate the method. Collecting better clinical adverse event information and proposed solutions can help identify opportunities to improve current device capabilities and interoperability and support a learning health system to improve health care delivery. Developing and analyzing clinical scenarios are the first steps in creating solutions to address vexing patient safety problems and enable clinical innovation. A Web-based research tool for implementing a means of acquiring and managing this information, the Clinical Scenario Repository™ (MD PnP Program), is described.

The Need to Apply Medical Device Informatics in Developing Standards for Safe Interoperable Medical Systems.

Medical device and health information technology systems are increasingly interdependent with users demanding increased interoperability. Related safety standards must be developed taking into account these systems' perspective. In this article, we describe the current development of medical device standards and the need for these standards to address medical device informatics. Medical device information should be gathered from a broad range of clinical scenarios to lay the foundation for safe medical device interoperability. Five clinical examples show how medical device informatics principles, if applied in the development of medical device standards, could help facilitate the development of safe interoperable medical device systems. These examples illustrate the clinical implications of the failure to capture important signals and device attributes. We provide recommendations relating to the coordination between historically separate standards development groups, some of which focus on safety and effectiveness and others focus on health informatics. We identify the need for a shared understanding among stakeholders and describe organizational structures to promote cooperation such that device-to-device interactions and related safety information are considered during standards development.

The Importance of State and Context in Safe Interoperable Medical Systems.

This paper describes why "device state" and "patient context" information are necessary components of device models for safe interoperability. This paper includes a discussion of the importance of describing the roles of devices with respect to interactions (including human user workflows involving devices, and device to device communication) within a system, particularly those intended for use at the point-of-care, and how this role information is communicated. In addition, it describes the importance of clinical scenarios in creating device models for interoperable devices.

The Design of Safe Networked Supervisory Medical Systems Using Organ-Centric Hierarchical Control Architecture.

There are growing demands to leverage network connectivity and interoperability of medical devices in order to improve patient safety and the effectiveness of medical services. However, if not properly designed, the integration of medical devices through networking could significantly increase the complexity of the system and make the system more vulnerable to potential errors, jeopardizing patient safety. The system must be designed and verified to guarantee the safety of patients and the effectiveness of medical services in the face of potential problems such as network failures. In this paper, we propose organ-centric hierarchical control architecture as a viable solution that reduces the complexity in system design and verification. In our approach, medical devices are grouped into clusters according to organ-specific human physiology. Each cluster captures common patterns arising out of medical device interactions and becomes a survivable semiautonomous unit during network failures. Further, safety verification and runtime enforcement can be modularized along organ-centric hierarchical control structure. We show the feasibility of the proposed approach under Simulink's model-based development framework. A simplified scenario for airway laser surgery is used as a case study.

Design of an x-ray / ventilator synchronization system in an integrated clinical environment.

Patients in an ICU may receive daily chest x-rays. These x-rays are taken manually and may be at different phases of respiration, which limits their clinical usefulness. We examine design issues around automatically synchronizing an x-ray and ventilator in an interoperable manner, including requirements on the individual devices and new safety hazards introduced by connecting them into a system.