Heterogeneous data sharing in healthcare
June 03, 2019

Heterogeneous Data Sharing in Healthcare Is Vital to Personalized Care

In this Q&A, Life Image CTO Janak Joshi talks about heterogeneous data sets and their importance to healthcare AI companies, and makes a pitch for imaging data to ONC.

A seamless exchange of health data is a win for patients, but it would also be a win for researchers and clinicians who’d have better access to heterogeneous data sets.

Unlike homogeneous data sets, heterogeneous data sets are highly variable. That kind of variability is necessary to build robust data models that can provide more precise and more personalized care, according to Janak Joshi, CTO at Life Image Inc.

In this interview, Joshi discusses why heterogeneous data sets are so important to healthcare companies — especially those building AI products, and why Life Image, one of the largest networks for exchanging image and clinical data, hopes CMS and ONC will look to the company as a blueprint toward interoperability.

Why is interoperability in healthcare such a big topic right now?

Janak Joshi: Interoperability is not a new topic. However, more recently, some of the regulations from ONC and CMS have been cross industry as far as being able to share the data, being able to manage the patient consent if you’re recruiting patients for a clinical trial. And, oh by the way, you have to include a lot more than just claims data for running trials if a pharma company is partnering with a network of hospitals or if a pharma company is either considering an acquisition of a healthcare IT company or partnering with a healthcare IT company.

Essentially, it’s a continuation of the maturity of the industry in the interop space in lieu of Roche Pharmaceuticals buying Flatiron Health and Foundation Medicine [in 2018] and the growing interest from pharma companies to either partner with or absolutely acquire a company like AthenaHealth and Allscripts.

The question remains: How does the convergence of broader industry constituents work together in a way that addresses the governance, the management, and the overall access component of the information flow coming from various instrumentation data sets and various healthcare IT systems?

At the end of the day, you don’t really care if information is coming from Epic or Cerner or Allscripts or GE or Siemens. You care about, for example: What are the different clinical pathways? What are the most effective ways to address an intervention for the best outcomes? What is the variability in treatment patterns across different institutions for patients with similar conditions?

You can’t really answer any of those questions unless you have a heterogeneous data set.

Read the complete article here. Written by Nicole Laskowski for Search Health IT in May 2019.