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Tuesday, July 30, 2024
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How to adopt healthcare AI in 3 overlapping yet distinct phases

Here’s a factoid you may not have seen coming. By 2030, the six countries of the Gulf Cooperation Council annually purchase more than $23 billion worth of products and services related to generative AI.

The projection comes from the global Big 4 accounting and consulting firm PwC, aka PricewaterhouseCoopers, which has published a report focused on how the intensifying activity will affect healthcare in that part of the world.

(The six countries of the GCC, also called the Cooperation Council for the Arab States of the Gulf, are Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates.)

The conspicuous growth curve ought to interest Westerners with any sort of stake in healthcare AI. And that goes not only for technology suppliers but also healthcare providers, who can learn from their peers on the other side of the world.

More to the point, all can learn by listening in on what PwC has to say to healthcare leaders in the GCC.

“By structuring AI work into three phases, leadership can establish a clear plan from strategy through execution and measurement,” the report reads, in part. “This structured approach aligns teams and maximizes AI’s impact on business operations, customer experiences and technology innovation.” More:

‘To drive this process, an AI Centre of Excellence (CoE) can be established, which will serve as a stepping stone to capture, ideate and develop use cases, and build internal capacity in a responsible and sustainable way.’

The three phases:

Phase 1: Ambition.

Key activities of this first phase include defining AI vision and goals, aligning customer needs and market trends, and establishing clear success criteria for measuring AI’s impact on customer experiences, PwC explains.

This phase “assesses the readiness and investment requirements for AI adoption,” the authors add, “and establishes governance structures and stakeholder engagement mechanisms to ensure alignment and accountability throughout the AI journey.” More:

‘Leadership teams should define quantifiable business goals using key performance indicators (KPIs) to demonstrate AI’s impact, ranging from improving patient outcomes and operational efficiency to driving revenue growth and ensuring regulatory compliance. By setting clear, measurable objectives, leadership can track progress, evaluate efficacy and demonstrate tangible value to stakeholders.’

Phase 2: AI transformation blueprint.  

Here project leaders create a roadmap for balancing value with risk. The formula optimally derives from the KPIs identified in Phase 1 and leads to the development of AI business use cases.

Leadership should identify top opportunities for optimizing existing processes within healthcare workers’ current workflows, PwC advises. “In developing and prioritizing business use cases, leaders must define them in detail, including their objectives, target user groups, data requirements and expected outcomes,” the authors add. “Enabling technology needs are concurrently assessed, and a technology stack is selected or developed to effectively support AI use cases.” More:

‘The rapid advancement of AI technologies can lead to significant changes in risk and feasibility within a few months, necessitating continuous reassessment to ensure alignment with the latest developments and opportunities.’

Phase 3: Monitoring and evaluation.

This phase focuses on evaluating the outcomes of AI initiatives and measuring their impact against the overarching strategy, PwC suggests. These activities entail defining KPIs and metrics to assess the effectiveness, efficiency and ROI of AI programs.

“These metrics may include customer satisfaction scores, revenue growth, cost savings, operational efficiency gains and other relevant indicators,” the authors state. “It also includes conducting regular assessments to track progress, identify improvement areas, and adjust strategies and tactics as needed.” More:

‘Additionally, this phase aims to communicate results and insights to key stakeholders, including senior leadership, business unit, and external partners to recognize successes, address challenges and reinforce the value of AI in transforming customer experiences and driving business outcomes.’

AI is no longer a technology of healthcare’s future, PwC reminds GCC readers: It is in your here and now.

“Healthcare AI holds the promise of empowering healthcare leaders to overcome some of the sector’s most historically daunting challenges,” the authors remind. These include detecting diseases, streamlining care, reducing errors, mitigating burnout, lowering costs and improving outcomes.   

‘It is not a question of whether healthcare will implement AI, but of how the implementation will proceed and evolve.’

Read the whole thing.

 

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Industry Watcher’s Digest

Buzzworthy developments of the past few days.

  • HHS has begun doing healthcare AI differently. For one thing, it’s meshing AI strategy and policy functions with cybersecurity and data duties. For another, to reflect this and other “streamlining” changes, it has rebadged the ONC the ASTP/ONC (for Assistant Secretary for Technology Policy and Office of the National Coordinator for Health Information Technology). Adding more letters to a bowl of alphabet soup seems a counterintuitive way to streamline anything, but let’s give them a chance before judging. “For decades, HHS has worked across the organization to ensure appropriate and safe use of technology, data and AI to advance the health and well-being of the American people,” says HHS Secretary Xavier Becerra. “This reorganization builds on that success and prepares the Department for the challenges that lie ahead.”
     
  • This seems counterintuitive too. A strong majority of Baby Boomers, 84%, believe AI can help keep health data accurate. Yet Gen Z, which grew up with techie devices in hand, is the most likely generation to have to deal with inaccuracies. And often those are handled manually, as in over the phone. Meanwhile all generations, but especially Boomers, blame human error for inaccurate healthcare records. The findings are from a national online survey of 1,006 consumers commissioned by Carta Healthcare.
     
  • AI for claims denials? Two can play at that game. Doctors are using AI to fight back against health insurers who use AI to get out of paying, according to an article filed by Computerworld reporter Lucas Mearian. He speaks with subject matter expert Ashish Jha, MD, MPH, dean of the School of Public Health at Brown University. “In my mind, this is just round one of the AI-vs-AI battle,” Jha says. “There will be escalation here.”
     
  • This is not Timothy Leary’s Hallucination Index. It’s Galileo’s. That’s Galileo, the GenAI supplier. The company’s resource ranks 22 large language models. The latest list, posted July 29, shows Anthropic’s Claude 3.5 Sonnet as the best performer, Google’s Gemini 1.5 Flash as the best on cost and Alibaba’s Qwen2-72B-Instruct as the best open-sourcer. (Brush up on Timothy Leary’s legacy in hallucinogenic history here.)
     
  • The healthcare system with a quantum computer in a public lobby has hired its first chief AI officer. The institution is the Cleveland Clinic. The new member of its C-suite is Ben Shahshahani, PhD, whose immediate previous post was senior VP of science, machine learning and product analytics at SiriusXM and Pandora. Announcement here.
     
  • Two tech concerns that are both kind of a big deal are combining forces over healthcare AI. You might have heard of these players—GE HealthCare and Amazon Web Services. In announcing the team-up, GE technology honcho Taha Kass-Hout, MD, comments on the state of healthcare technology in the GenAI era. “We haven’t seen progress like this,” Kass-Hout says, “since the emergence of the internet.”
     
  • China snaps back at Sam Altman. Last week the OpenAI CEO wrote a high-profile opinion piece warning of “authoritarian” things to come should China win the AI arms race. The Washington Post ran it. This week a spokesperson for the Chinese Embassy in the U.S. tells Altman to kiss off. Not in those exact words, of course. “China has consistently advocated that the development of artificial intelligence should adhere to principles that are human-centered and promote benevolence,” the spokesperson tells Newsweek. “China believes that AI development should be fair and inclusive, ensuring that all countries equally enjoy the benefits brought by AI, and has no intention of seeking dominance in this field.”
     
  • Google gently responds to Elon Musk. The tech tycoon and others had accused the search monster of messing with results when users tried to search for “assassination attempt on Trump” and similar terms. The main mischief seemed to occur in the engine’s auto-complete field. Some users found they couldn’t get the auto-fill to suggest “Trump.” Instead they kept getting “Truman.” Or Donald Trump became Donald Duck. That sort of thing. In any case, Google tells Fortune it did not take “manual action” on the auto-complete predictions, and will be “working on improvements” to its auto-complete feature. Meanwhile the New York Post covers the kerfuffle as only it can.
     
  • That’s not legendary sports broadcaster Al Michaels commentating at the Paris Olympics. It’s AI Al Michaels. The real one is sitting this one out. And it turns out he’s just as impressed with the impersonation as you would be. “Frankly, it was astonishing,” Michaels tells The Sporting News of the first time he heard his digital double. “It was amazing, and it was a little bit frightening.”
     
  • Recent research in the news:
     
  • AI funding news of note:
     
  • From AIin.Healthcare’s news partners:
     

 

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