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Analytics is the Driver for Useful Health Services at Philips

Shared by Radhika Narayanan | 0 103 2 | about 3 years ago

Although pioneer health care organizations jumped into risk sharing and fee-for-value without a good grounding in data, they have come to recognize the critical role analytics play over the past few years. Results of a 2015 survey of ACOs show that, “Nearly 85 percent of respondents report they have in place advanced analytics software to analyze disparate data sets.” The data tends to be limited (mostly claims and EHR data) and data sharing is still rare between organizations, but basic practices such as identifying high-risk patients are becoming more widely seen.

Philips has been in health care informatics for a long time, gradually building a data platform with analytics capabilities and basing more and more services on this platform. I talked to Dr. ck Andrade, Director of Product Management of Philips’ HealthSuite Digital Platform, to find how their basic analytics drive their services.

Like the ACOs mentioned earlier, Philips allows a single organization to combine and mine data of different types. Philips does not combine data from different unrelated organizations–in fact, to respect privacy, they don’t peek at user data at all. The platform is intended to aid institutions with precisely the types of data integration that are now so difficult. Now it is being incorporated by Philips into their own high-level services, showing how analytics can be a platform for building businesses.

Philips’s HealthSuite digital platform offers FHIR APIs. EHR data is read in through the vendors’ APIs when they’re available, by using the platform’s other interoperability capabilities, or through the CCD-A format. Imaging support was announced on February 18. Genomics is being pursued. Finally, device data can be taken in through several sources. Philips Device Cloud manages 8 million connected devices today, and a recently announced integration with Validic connects to data from 130 different device vendors over a wide range of protocols.

Clearly, all these data sets are interdependent. For instance, an image is of no value without the patient history that comes from an EHR.

Read More On www.emrandehr.com

Categories Data Science Predictive Analytics



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