Race To Grab the Biggest Pie of Gen AI Market in Healthcare Transformations!!.
The Big Software Tech Companies are all jumping into the Generative AI application Game in Healthcare and are making a real big splash!.
Post ChatGPT went viral and since early 2023, there has been a sprout of tech innovations and solutions being developed around Generative AI and associated techs. Be it Process Flows, Language Models, CRM, Chatbots, Avatars, Text to Voice, Text to Image / Video etc., the Tsunami of Apps being developed in GenAI segment and AI ecosystem in general is just gaining momentum month on month. According to some estimates, Start-ups with generative AI solutions in healthcare delivery and life sciences have collectively earned more than $20 billion in funding.
AWS’ s Latest Ace –
Last week, July 2023, AWS announced AWS HealthScribe, a new HIPAA-eligible service that empowers healthcare software providers to build clinical applications that use speech recognition and generative AI to save clinicians time by generating Clinical documentation. HealthScribe makes it easier for Physicians to review clinical notes before entering them into the EHR. Help save Clinicians time by automatically creating transcripts, generating notes, and analyzing Patient-clinician conversations, thus allowing clinicians to easily view the historical context of notes for greater accuracy and transparency. Data security and privacy is also (claimed) managed.
AWS HealthScribe, healthcare software providers can
- RECORD : use a single API to automatically create robust transcripts,
- EXTRACT: extract key details (e.g., medical terms and medications), and
- ANALYZE: Process/ create summaries from doctor-patient discussions that can then be entered into an electronic health record (EHR) system.
Service leverages speech recognition & generative AI to automatically create preliminary clinical documentation from patient-clinician conversations. For Third parties/ Stat-ups – AWS HealthScribe makes it faster and easier for healthcare software providers to integrate generative AI capabilities into their application starting with two popular specialties (i.e., general medicine and orthopedics);
- 3M Health Information Systems, Babylon Health, and ScribeEMR are among AWS customers and partners looking forward to using AWS HealthScribe.
- 3M Health Information Systems (HIS)- 3M Health Information Systems (HIS) is an industry leader whose various Multi-Modal speech understanding, conversational, and ambient AI solutions are currently used by more than 300,000 clinicians (as claimed by 3M).
- Babylon is an integrated digital-first primary care service that manages population health at scale. By harnessing the power of AWS HealthScribe, they can transform the process of healthcare documentation using generative AI. With AWS HealthScribe, It’s advanced processes can now capture and interpret patient visits more effectively and optimize EMR workflows, coding, and reimbursement processes.
HealthScribe is being previewed for two specialties: general medicine and orthopedics. In 2019, AWS launched Transcribe Medical, a voice-to-text technology meant for clinical visits. Unlike HealthScribe, Transcribe Medical does not auto populate relevant information into the EHR.
What Google DeepMind & G-Cloud is Building??
In May 2023 Google DeepMind announced Med-PaLM2, Google’s medical large language model, or LLM. Med-PaLM 2 harnesses the power of Google’s LLMs, aligned to the medical domain to more accurately and safely answer medical questions. It is said to be the First LLM to perform at an “expert” test-taker level performance on the MedQA dataset of US Medical Licensing Examination (USMLE)-style questions, reaching 85%+ accuracy, and it was the first AI system to reach a passing score on the MedMCQA dataset comprising Indian AIIMS and NEET medical examination questions, scoring 72.3%. Earlier last year Google announced Medical Imaging Suite, an AI-assisted diagnosis technology being used by Hologic to improve cervical cancer diagnoses.
- Hackensack Meridian Health to predict metastasis in patients with prostate cancer. Elsewhere, Mayo Clinic and Google have collaborated on an AI algorithm to improve the care of head and neck cancers.
- Google Health recently partnered with iCAD to improve breast cancer screening with AI.
- AI-enabled Claims Acceleration Suite, designed to streamline processes for health insurance prior authorization and claims processing.
Future Capabilities coming to Google Cloud, including Generative AI support in Vertex AI and Generative AI App Builder, which are already being tested by a number of Customers. Developers and businesses already use Vertex AI to build and deploy machine learning models and AI applications at scale, and we recently added Generative AI support in Vertex AI.
Freenome is building the next generation of early cancer detection technology with Google Cloud. Freenome is driven by its mission to develop high-quality diagnostic tests to detect and treat diseases like cancer from a simple blood draw. In 2022, Freenome significantly accelerated its growth on Google Cloud to support the business as it began the clinical trials of its diagnostic blood testing technology.
Google announced a partnership with Mayo Clinic in June to explore generative AI’s applications in the hospital. Several such examples of Google Cloud and ecosystem tools being leveraged by Start-ups and incumbents are now available demonstrating various use cases of AI-ML.
Microsoft Is Taking Lead with It’s OpenAI Collaborations
Microsoft-owned Nuance integrated generative AI into their note-taking products earlier this year. Microsoft recently announced integrations of its generative AI software, which includes Nuance’s note-taking products, with EHR vendor Epic and tele-health provider Teladoc. Microsoft recently unveiled plans to embed generative AI into clinical software from Epic, the biggest hospital EHR vendor in the U.S. Nuance, a documentation company owned by Microsoft, said last month that it had integrated GPT-4 into its clinical note-taking software. This summer, providers using existing Nuance documentation products can apply to beta test the application, called DAX Express. MS also does an important job of using its ecosystems tools, MS Office, MS365 etc. and its reach, to expedite trial of Gen AI.
What Are The Challenges??
While Gen AI has major visible advantages across Healthcare Management to Medical Devices to Life sciences sectors, especially AI to analyze data to help diagnose complex diseases, fill out records or as a concierge for patient portals. AI and particularly Generative AI can also expedite
- R&D, Publications
- Process & Workflow efficiency Management,
- Data Management
- CX and CRM/ Service
However, concerns about data integrity, accuracy of processing & output, bias and oversight due to Tech or Data, have given rise to some safety-focused organizations advocating a slow-down on implementation of Gen AI. One issue with AI is the Uncertainty Problem: How can a result be trusted if it’s not quite clearly understood how the AI got there purely based on input data sets?
Detailed Risk Management and assessment of the failure modes of Gen AI systems (largely still being explored) needs to evolve. Data privacy and information security, including data manipulation, cyber hacks prevention measures are all a cause of concern for many.
There is no doubt that the race for Gen AI applications in Healthcare between the Big tech Cos is heating Up. With so many options available, the Innovators, Developer and Start-up community can leverage these foundational tech, LLM platforms and APIs to build customized next-gen Healthcare solutions. At same time, there is a pressing need for regulations and governance models to understand Risks, Hazards as well as limitations of Gen-AI and AI + Digital ecosystem in Healthcare and evolve themselves to prevent future adverse events.
We are in for some fascinating times ahead in Healthcare Digital Disruption journey, for sure.