Real-time analysis for intensive care: development and deployment of the artemis analytic system.

The lives of many thousands of children born premature or ill at term around the world have been saved by those who work within neonatal intensive care units (NICUs). Modern-day neonatologists, together with nursing staff and other specialists within this domain, enjoy modern technologies for activities such as financial transactions, online purchasing, music, and video on demand. Yet, when they move into their workspace, in many cases, they are supported by nearly the same technology they used 20 years ago. Medical devices provide visual displays of vital signs through physiological streams such as electrocardiogram (ECG), heart rate, blood oxygen saturation (SpO(2)), and respiratory rate. Electronic health record initiatives around the world provide an environment for the electronic management of medical records, but they fail to support the high-frequency interpretation of streaming physiological data. We have taken a collaborative research approach to address this need to provide a flexible platform for the real-time online analysis of patients' data streams to detect medically significant conditions that precede the onset of medical complications. The platform supports automated or clinician-driven knowledge discovery to discover new relationships between physiological data stream events and latent medical conditions as well as to refine existing analytics. Patients benefit from the system because earlier detection of signs of the medical conditions may lead to earlier intervention that may potentially lead to improved patient outcomes and reduced length of stays. The clinician benefits from a decision support tool that provides insight into multiple streams of data that are too voluminous to assess with traditional methods. The remainder of this article summarizes the strengths of our research collaboration and the resulting environment known as Artemis, which is currently being piloted within the NICU of The Hospital for Sick Children (SickKids) in Toronto, Ontario, Canada. Although the discussion in this article focuses on a NICU, the technologies can be applied to any intensive care environment.

A method for physiological data transmission and archiving to support the service of critical care using DICOM and HL7.

An increasing amount of physiological monitoring data is displayed on medical devices around the world every day. By and large, much of this data is lost beyond hand written annotations. Opportunities exist to utilize this data for improved care of those patients within the NICU and for clinical research. The service oriented architecture paradigm offers a way of thinking of critical care through the provision of services of critical care provided by clinicians where patients may be located within or outside their intensive care unit. A major inhibitor to this becoming reality is the lack of a standard for the representation of physiological data as HL7, for example, does not include definitions for time series data. This research proposes a method to represent, transmit and archive physiological data using DICOM and HL7. To enable this, a DICOM file writer and viewer for the physiological time-series data is proposed to specifically enable the storage requirement for these data. This research is then tested within the context of Neonatal Intensive Care.

Women in biomedical engineering and health informatics and its impact on gender representation for accepted publications at IEEE EMBC 2007.

The study of women within the professions of Engineering and Computer Science has consistently been found to demonstrate women as a minority within these professions. However none of that previous work has assessed publication behaviours based on gender. This paper presents research findings on gender distribution of authors of accepted papers for the IEEE Engineering and Medicine Society annual conference for 2007 (EMBC '07) held in Lyon, France. This information is used to present a position statement of the current state of gender representation for conference publication within the domain of biomedical engineering and health informatics. Issues in data preparation resulting from the lack of inclusion of gender in information gathered from accepted authors are presented and discussed.