Drinking from the Data Fire Hose, Integrating Medical Device Data
e-Health ePoster Library. Frede D. Jun 6, 2017; 167131; EP07.05
Doug Frede
Doug Frede
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Abstract
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Purpose/Objectives: We are still in the early days of a clinical data revolution. While medical devices generate an enormous amount of clinical data, most of this data goes unused, siloed in proprietary device formats and systems that are nearly impossible to access. However, this data is essential to realizing the promise of improved healthcare by the emerging advances in predictive analytics and retroactive data analysis systems. Exactly what does it take to get this data and then what can you do with it? What does it take to get a data acquisition project rolling and how can you empower your clinicians, researchers, and innovators to make breakthrough discoveries?

Methodology/Approach: Using a variety of systems and methods, we have developed techniques and methods for collecting large amounts of data for customers such as Sick Kids in Toronto. In addition, we have 12 years of experience connecting medical devices for companies such as Hospira, Baxter, and Smiths Medical. This data is sometimes placed in the medical record, but is now being placed into systems from IBM, Google, Hitachi, GE, and others to perform real time predictive analytics.

Finding/Results: Having implemented/integrated and developed software for device integration at hospitals across the US and Canada, we have taken years of expertise and put it into our own products and solutions for data acquisition and storage. This has resulted in some of the most reliable, high quality data that researchers have been able to use from devices that generate huge amounts of data such as patient monitoring systems. Medical record systems are not device data warehouses. Data is generated at a high rate from some devices, both numeric and waveform data, that cannot be stored at the resolution necessary for research, or simply not at all.

Conclusion/Implications/Recommendations: Although standards exist and are being further developed, there are still a large number of devices that need connectivity that will be around for years and don't utilize standards. We have helped customers sort through these systems to provide data that can be used for more than just the medical record, it is stored and can be used for research for as long as is needed. When most people think of ""big data"" in healthcare, they think of the analysis of the data and systems that perform it (such as IBM Watson). What they miss is that the most difficult part is still the link from the device to those systems.

140 Character Summary: We will bring our expertise of the task of connecting medical devices and device data for hospitals, researchers, and technologists alike.
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