Has Amazon Brought Something New To Healthcare Data Analytics?

Posted on November 29, 2018 I Written By

Anne Zieger is a healthcare journalist who has written about the industry for 30 years. Her work has appeared in all of the leading healthcare industry publications, and she's served as editor in chief of several healthcare B2B sites.

Amazon’s announcement that it was getting into healthcare data analytics didn’t come as a major surprise. It was just a matter of time.

After all, the retail giant has been making noises about its health IT ambitions for a while now, and its super-sneaky 1492 team’s healthcare feints have become common knowledge.

Now, news has broken that its massive hosting division, Amazon Web Services, is offering its Comprehend Medical platform to the healthcare world. And at the risk of being a bit too flip, my reaction is “so?” I think we should all take a breath before we look at this in apocalyptic terms.

First, what does Amazon say we’re looking at here?

Like similar products targeting niches like travel booking and supply-chain management, the company reports, Comprehend Medical uses natural language processing and machine learning to pull together relevant information from unstructured text.

Amazon says Comprehend Medical can pull needed information from physician notes, patient health records and clinical trial reports, tapping into data on patient conditions and medication dosage, strength and frequency.

The e-retailer says that users can access the platform through a straightforward API call, accessing Amazon’s machine learning expertise without having to do their own development or train models of their own. Use cases it suggests include medical cohort analysis, clinical decision support and improving medical coding to tighten up revenue cycle management.

Comprehend Medical customers will be charged a fee each month based on the amount of text they process each month, either $0.01 per 100-character unit for the NERe API, which extracts entities, entity relationships, entity traits and PHI, or $0.0014 per unit if they use its PHId API, which only supports identifying PHI for data protection.

All good. All fine. Making machine learning capabilities available in a one-off hosting deal — with a vendor many providers already use — can’t be wrong.

Now, let’s look coldly at what Amazon can realistically deliver.

Make no mistake, I understand why people are excited about this announcement. As with Microsoft, Google, Apple and other top tech influencers, Amazon is potentially in the position to change the way things work in the health IT sector. It has all-star brainpower, the experience with diving into new industries and enough capital to buy a second planet for its headquarters. In other words, it could in theory change the healthcare world.

On the other hand, there’s a reason why even IBM’s Watson Health stumbled when it attempted to solve the data analytics puzzle for oncologist. Remember, we’re talking IBM here, the last bastion of corporate power. Also, bear in mind that other insanely well-capitalized, globally-recognized Silicon Valley firms are still biding their time when it comes to this stuff.

Finally, consider that many researchers think NLP is only just beginning to find its place in healthcare, and an uncertain one at that, and that machine learning models are still in their early stages, and you see where I’m headed.

Bottom line, if Google or Microsoft or Epic or Salesforce or Cerner haven’t been able to pull this off yet, I’m skeptical that Amazon has somehow pole-vaulted to the front of the line when it comes to NLP-based mining of medical text. My guess is that this product launch announcement is genuine, but was really issued more as a stake in the ground. Definitely something I would do if I worked there.