Glassbeam for medical analytics – part 2

VIVEK SUNDARAM
Friday, February 7, 2014

In PART ONE of the Glassbeam for Medical blog, we explored how Glassbeam helps customer support save turnaround time and avoid unnecessary replacement costs. Support is one use case that benefits from machine data analytics. But the benefits of such a solution can span across the enterprise from customer support to engineering to sales and marketing.

Glassbeam, with the expressive power of SPL, helps model machine data in a way that abstracts all the complexity inherent in the log file. A complex piece of machinery can be modeled as a composition of several parts, each part logically mapped to different areas in the log file. This allows product managers, engineering, sales and field organizations to glean real world insights from their install base by using an easy to understand logical model. Since we are dealing with near real time data directly from the machines, the information is up to date and represents the true current configuration and state of systems worldwide, something a traditional CRM solution cannot provide.

Following are some examples of the use cases from the medical industry:

Glassbeam for high precision electrosurgical equipment

A company manufacturing high precision power generators used for electrosurgery, such as tissue sealing, is interested in understanding the typical power setting used and the duration of procedures across their installed base. Aggregating this information helps them understand the battery capacity required to perform a number of procedures without interruption. It also helps them identify the different SKUs that are tuned for specific categories of surgical procedures. This information is invaluable for sales and account managers, who are keen to know a specific hospital’s usage profile in order to provide better customer service, as well as identify up-sell opportunities.

Glassbeam for MRI and CAT scanners

When the engineering team is faced with a deluge of customer complaints escalated to them, they need to identify the underlying root cause to fix the issue. By performing pattern search across the install base using Glassbeam Explorer, the team is able to quickly isolate the cause. Identifying affected firmware versions, serial numbers, machine models etc. are some more of the features that enable users to quickly drill down to the root cause of the problem. Similarly, complex medical equipment contain several field replaceable units, such as tubes, power adapters, gantry, patient table, motors, pumps, generators etc. Ability to track replacement rates across the install base is essential to understanding failure rates, as well as trigger a deeper investigation if the numbers are above the norm.

Glassbeam for molecular diagnostics

Molecular testing and diagnostic systems have advanced in leaps and bounds and are now capable of performing dozens of test runs simultaneously, as well as provide on-demand capability. Time is extremely critical in many of these tests, since the results determine the next course of action for an ailing patient. Getting visibility into the kind of tests being performed (with sensitive information appropriately sanitized) can help the manufacturer optimize device features for more accurate and faster results. In addition, Glassbeam could become a global knowledge base that helps hospitals ‘discover’ tests performed around the world. This ties into our “powered by Glassbeam” program that allows manufacturers to gain a competitive advantage by offering Glassbeam solutions as a white-label value added service.

To conclude, using machine data analytics as a “decision support system” across the enterprise enables companies to achieve phenomenal ROI. When companies recognize the hidden value in machine logs, the potential benefits are limitless.