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Healthcare AI Could Generate $150B In Savings By 2025

Posted on September 27, 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.

Is the buzz around healthcare AI solutions largely hype, or can they deliver measurable benefits? Lest you think it’s too soon to tell, check out the following.

According to a new report from market analyst firm Frost & Sullivan, AI and cognitive computing will generate $150 billion in savings for the healthcare business by 2025.  Frost researchers expect the total AI market to grow to $6.16 billion between 2018 and 2022.

The analyst firm estimates that at present, only 15% to 20% of payers, providers and pharmaceutical companies have been using AI actively to change healthcare delivery. However, its researchers seem to think that this will change rapidly over the next few years.

One of the most interesting applications for healthcare AI that Frost cites is the use of AI in precision medicine, an area which clearly has a tremendous upside potential for both patients and institutions.

In this scenario, the AI integrates a patient’s genomic, clinical, financial and behavioral data, then cross-references the data with the latest academic research evidence and regulatory guidelines. Ultimately, the AI would create personalized treatment pathways for high-risk, high-cost patient populations, according to Koustav Chatterjee, an industry analyst focused on transformational health.

In addition, researchers could use AI to expedite the process of clinical trial eligibility assessment and generate prophylaxis plans that suggest evidence-based drugs, Chatterjee suggests.

The report also lists several other AI-enabled solutions that might be worth implementing, including automated disease prediction, intuitive claims management and real-time supply chain management.

Frost predicts that the following will be particularly hot AI markets:

  • Using AI in imaging to drive differential diagnosis
  • Combining patient-generated data with academic research to generate personalized treatment possibilities
  • Performing clinical documentation improvement to reduce clinician and coder stress and reduce claims denials
  • Using AI-powered revenue cycle management platforms that auto-adjust claims content based on payer’s coding and reimbursement criteria

Now, it’s worth noting that it may be a while before any of these potential applications become practical.

As we’ve noted elsewhere, getting rolling with an AI solution is likely to be tougher than it sounds for a number of reasons.

For example, integrating AI-based functions with providers’ clinical processes could be tricky, and what’s more, clinicians certainly won’t be happy if such integration disrupts the EHR workflow already in existence.

Another problem is that you can’t deploy an AI-based solution without ”training” it on a cache of existing data. While this shouldn’t be an issue, in theory, the reality is that much of the data providers generate is still difficult to filter and mine.

Not only that, while AI might generate interesting and effective solutions to clinical problems, it may not be clear how it arrived at the solution. Physicians are unlikely to trust clinical ideas that come from a black box, e.g. an opaque system that doesn’t explain itself.

Don’t get me wrong, I’m a huge fan of healthcare AI and excited by its power. One can argue over which solutions are the most practical, and whether AI is the best possible tool to solve a given problem, but most health IT pros seem to believe that there’s a lot of potential here.

However, it’s still far from clear how healthcare AI applications will evolve. Let’s see where they turn up next and how that works out.

Company Supports Patient Data Sharing Via Blockchain

Posted on July 23, 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.

After a year in development, a tech startup has released a platform using blockchain to help patients share personal health records. The company, which was founded by former IMS Health exec Robert Chu, plans to sell their information to pharmaceutical companies without involving a third-party data broker.

Embleema, which built its software on the Ethereum smart-contract platform, is focused on delivering what it calls “real world evidence” to drug researchers.

Its blockchain-based app, which is known as PatientTruth, allows patients to pull provider CCDs and Fitbit data together in a single location. The idea here is that blockchain will permit patients to manage data sharing permissions far more securely and effectively than with other approaches.

When patients agree to share their data, they get crypto-tokens. Embleema, for its part, generates income by selling an anonymized version of that data to clinical researchers.

The company contends that its data offers significant advantages over traditional data sources include that it offers in individual rather than aggregate data. Having access to individual data allows drugmakers to monitor a given patient over time, which helps to improve research and drug development, it says.

On the whole, Embleema seems to have a smart business model and seems to address some well-defined needs. Bringing together health data users and sellers directly probably offers some advantages. And it will probably be very profitable to give drugmakers access to real-time patient data structured as individual records.

That being said, I’m not sure how the company will get, much less maintain, patients’ interest. Other than people in this industry, few of my acquaintances or family members have the slightest idea of how to upload their health records. In fact, some of them would be quite intimidated by the prospect.

Also, it’s is a little weird that patients who share their data with Embleema are paid in tokens rather than actual publicly-negotiable money. I know I’d find cash incentives to be a lot more motivating than tokens. My guess is that either way, patients aren’t going to get much of the income generated by their data, and I have little doubt that competitors will point this out.

Of course, clinical researchers always face some form of obstacle in getting the data they need. No matter what approach they take, the data they choose seems to have some significant limitations.

I can’t tell whether Embleema has solved this problem completely, and if so, whether its solution is scalable and if it’s really any better than companies like IMS Health, but it does seem to be focused on a sector with deep pockets and a bottomless need for patient data. In fact, I’m sure its competitors will show up soon.