Large tech companies making slow progress in healthcare

Google Health disbands, but giants’ other initiatives make progress in data access, artificial intelligence and cloud computing.

The role of big technology companies in healthcare continues to be in flux, but indications are that they are increasing their footprint in data aggregation, and artificial intelligence and machine learning.

The challenges faced by large technology companies seeking to play a role in healthcare were exemplified by the announcement late this summer that the Google Health division of Alphabet had been dissolved, with its staff reassigned to other parts of Google, working to follow through with the organization’s health-tech initiatives.

Other technology giants – Amazon, Apple and Microsoft, most prominently – continue to pursue advanced computing capabilities to interact with provider or other health organizations, or consumer-facing technologies seeking to improve health data access. Still, the healthcare market generally has continued to be a tough nut to crack for companies that have broadly succeeded with their technologies in other industries.

The changes at Google Health haven’t meant that existing technology efforts have ceased on healthcare solutions. Google’s chief health officer, Karen DeSalvo has indicated in interviews that the company is still continuing efforts in areas where it believes it can use its technology capabilities to improve processes.

In fact, Google has made several announcements in subsequent months to underscore its ongoing healthcare initiatives. For example, In July Google Cloud announced a preview of Healthcare Data Engine, a solution for healthcare and life sciences organizations that harmonizes data from multiple sources, including medical records, claims, clinical trials and research data. It is said its associated API enables an interoperable, longitudinal record of patient data, able to provide clinical insights in formats that interoperate with the Fast Healthcare Interoperability Resources (FHIR) standard.

Also, in September, Google Cloud and C3 AI announced the creation of an alliance to accelerate the application of artificial intelligence solutions across multiple industries, with some solutions developed to improve on the ability of organizations to assess the availability of healthcare equipment via AI-powered asset readiness and preventive maintenance.

And it continues work with individual organizations, for example, announcing in October that it is working with Hackensack Meridian Health to implement productivity through devices and partnering with Google’s cloud segment to deploy artificial intelligence and machine learning in clinical areas, such as screening and detection. Other partnerships it's announced in past years include those with Ascension, Beth Israel Deaconess Medical Center and the Mayo Clinic.

It’s unclear whether the restructuring at Google means it has cold feet about healthcare, “sending bits and pieces of Google Health to other domain leaders,” said John Moore of Chillmark Research in a recent column. Moore said he believes Google and Alphabet “have every intention of staying in healthcare, as represented by its continuing investments via Verily, it’s continuing health-centric efforts with Google Cloud (and their strategic partnership with Meditech)” and the number of open job positions still listed for Google Health.

Other tech giants are continuing to focus efforts in the cloud, and finding ways to support the insertion of artificial intelligence and machine learning into healthcare delivery.

For example, Amazon is featuring its Amazon Web Services unit is hoping to offer machine learning “as a form of service,” said Tasha Kass Hout, MD, chief medical officer and director of artificial intelligence for Amazon Web Services. AWS hopes to offer machine learning on top of “a stack of services,” Hout told attendees at a session during the recent HIMSS conference in Las Vegas.

Machine learning can be offered to organizations to help solve concrete problems. For example, medical images can be analyzed with Amazon Recognition, or a medical note can be used for analysis by running it through Amazon Comprehend Medical, he said. Amazon also has launched Amazon Health Lake, which makes use of index tagging and structure to enable gather and extract medical information, allowing analysis and derived clinical knowledge.

Hout notes that the cloud environments are a key to enabling success with machine learning, and AWS aims to structure capabilities so tools can be used in a modular fashion to meet the needs of medical organizations.

Apple continues to push forward the capabilities of its Health app, with enhanced capabilities to enable consumers to view their electronic health records. The iPhone’s recently upgraded operating system also updates its Health app to make it easier to share a person's health metrics with loved ones or directly with physicians. Devices also can monitor patients for fall detection and walking steadiness.

Advanced computing capabilities, such as those supported by tech giants, can help healthcare organizations grapple with data sharing and analytics, such as were made evident by the COVID-19 pandemic, said Bala Horta, MD, vice president and chief analytics officer at Rush University Medical Center in Chicago, at the session at the recent HIMSS conference.

Analytics supported by cloud processing enabled forecasting at Rush, such as bed needs, based on national and local trends of COVID infections. In addition, cloud computing initiatives with Amazon also are enabling Rush to research and make inroads in dealing with health equity, Horta said. Detailing screening for social determinants of health are helping to support risk adjustment, so “we think it can help us better manage quality,” he said.

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