Evaluation of a Smart Alarm for Intensive Care Using Clinical Data

We describe and report the results of an evaluation of a smart alarm algorithm for post coronary artery bypass graft (CABG) patients. The algorithm (CABG-SA) was applied to vital sign data streams recorded in a surgical intensive care unit (SICU) at a hospital in the University of Pennsylvania Health System. In order to determine the specificity of CABGSA, the alarms generated by CABG-SA were compared against the actual interventions performed by the staff of the critical care unit. Overall, CABG-SA alarmed for 55% of the time relative to traditional alarms while still generating alarms for 12 of the 13 recorded interventions

Evaluation and Enhancement of an Intraoperative Insulin Infusion Protocol via In-Silico Simulation

Intraoperative glycemic control, particularly in cardiac surgical patients, remains challenging. Patients with impaired insulin sensitivity and/or secretion (i.e., type 1 diabetes mellitus) often manifest extremely labile blood glucose measurements during periods of stress and inflammation. Most current insulin infusion protocols are developed based on clinical experiences and consensus among a local group of physicians. Recent advances in human glucose metabolism modeling have established a computer model that invokes algorithms representing many of the pathways involved in glucose dysregulation for patients with diabetes. In this study, we used an FDA approved glucose metabolism model to evaluate an existing institutional intraoperative insulin infusion protocol via closedloop simulation on the virtual diabetic population that comes with the computer model. A comparison of simulated responses to actual retrospective clinical data from 57 type 1 diabetic patients undergoing cardiac surgery managed by the institutional protocol was performed. We then designed a proportional-derivative controller that overcomes the weaknesses exhibited by our old protocol while preserving its strengths. In-silico evaluation results show that our proportional-derivative controller more effectively manages intraoperative hyperglycemia while simultaneously reducing hypoglycemia and glycemic variability. By performing insilico simulation on intraoperative glucose and insulin responses, robust and seemingly efficacious algorithms can be generated that warrant prospective evaluation in human subjects

Smart Alarms: Multivariate Medical Alarm Integration for Post CABG Surgery Patients

In order to monitor patients in the Intensive Care Unit, healthcare practitioners set threshold alarms on each of many individual vital sign monitors. The current alarm algorithms elicit numerous false positive alarms producing an inefficient healthcare system, where nurses habitually ignore low level alarms due to their overabundance. In this paper, we describe an algorithm that considers multiple vital signs when monitoring a post coronary artery bypass graft (post-CABG) surgery patient. The algorithm employs a Fuzzy Expert System to mimic the decision processes of nurses. In addition, it includes a Clinical Decision Support tool that uses Bayesian theory to display the possible CABG-related complications the patient might be undergoing at any point in time, as well as the most relevant risk factors. As a result, this multivariate approach decreases clinical alarms by an average of 59% with a standard deviation of 17% (Sample of 32 patients, 1,451 hours of vital sign data). Interviews comparing our proposed system with the approach currently used in hospitals have also confirmed the potential efficiency gains from this approach

Clinician-in-the-Loop Annotation of ICU Bedside Alarm Data

In this work, we describe the state of clinical monitoring in the intensive care unit and operating room, where patients are at their most fragile and thus monitoring is most heightened. We describe how large amounts of data generated by monitoring patients’ physiologic signals, along with the ubiquitous aspecific threshold alarms in use today, cause dangerous alarm fatigue for medical caregivers. In order to build more specific, more useful alarms, we gathered a novel data set that would allow us to assess the number, types, and utility of alarms currently in use in the intensive care unit. To do this, we developed a system to collect physiologic monitor data, alarms, and annotations of those alarms provided electronically by clinicians. We describe the collection process for this novel data set and provide a preliminary description of the data

The Medical Device Dongle: An Open-Source Standards-Based Platform for Interoperable Medical Device Connectivity

Emerging medical applications require device coordination, increasing the need to connect devices in an interoperable manner. However, many of the existing health devices in use were not originally developed for network connectivity and those devices with networking capabilities either use proprietary protocols or implementations of standard protocols that are unavailable to the end user. The first set of devices are unsuitable for device coordination applications and the second set are unsuitable for research in medical device interoperability. We propose the Medical Device Dongle (MDD), a low-cost, open-source platform that addresses both issues

Challenges and Research Directions in Medical Cyber-Physical Systems

Medical cyber-physical systems (MCPS) are lifecritical, context-aware, networked systems of medical devices. These systems are increasingly used in hospitals to provide highquality continuous care for patients. The need to design complex MCPS that are both safe and effective has presented numerous challenges, including achieving high assurance in system software, intoperability, context-aware intelligence, autonomy, security and privacy, and device certifiability. In this paper, we discuss these challenges in developing MCPS, some of our work in addressing them, and several open research issue

GSA: A Framework for Rapid Prototyping of Smart Alarm Systems

We describe the Generic Smart Alarm, an architectural framework for the development of decision support modules for a variety of clinical applications. The need to quickly process patient vital signs and detect patient health events arises in many clinical scenarios, from clinical decision support to tele-health systems to home-care applications. The events detected during monitoring can be used as caregiver alarms, as triggers for further downstream processing or logging, or as discrete inputs to decision support systems or physiological closed-loop applications. We believe that all of these scenarios are similar, and share a common framework of design. In attempting to solve a particular instance of the problem, that of device alarm fatigue due to numerous false alarms, we devised a modular system based around this framework. This modular design allows us to easily customize the framework to address the specific needs of the various applications, and at the same time enables us to perform checking of consistency of the system. In the paper we discuss potential specific clinical applications of a generic smart alarm framework, present the proposed architecture of such a framework, and motivate the benefits of a generic framework for the development of new smart alarm or clinical decision support systems

Partnership for a healthy work environment: tele-ICU/ICU collaborative.

The tele-intensive care unit (ICU) provides a remote monitoring system that adds an additional layer of support for critically ill patients. However, to optimize contributions, the bedside team must incorporate this resource into the patient\u27s plan of care. Using the American Association of Critical-Care Nurses\u27 Healthy Work Environment Standards as a platform, we can create and nurture a new partnership model. Strategies that embrace the standards of skilled communication, true collaboration, and effective decision making become mutual goals for improving patient safety and outcomes. Joint communication guidelines facilitate timely and meaningful communication. Trust and the desire to cooperate encourage provider engagement to strengthen collaboration. The use of tele-ICU technology can assist in the interpretation and transformation of data to affect decision making at all levels to influence patient care. Through the lens of the healthy work environment, the tele-ICU/ICU partnership provides enhanced opportunities for improved patient care and team satisfaction