Understanding the Impact of AI in Healthcare

We conjure a force, autonomous but totally compliant, give it a set of instructions, then scramble like mad to stop it once we realise our instructions are imprecise or incomplete—lest we get, in some clever, horrible way, precisely what we asked for. – Brian Christian, The Alignment Problem

This raises an important question: How can we ensure that the technologies we develop truly reflect our goals?

In a world where buzzwords like artificial intelligence and machine learning often promise more than what they deliver, it’s refreshing to find tangible examples where these technologies truly shine. Enter Value Generating AI, wherein, it is not just a flashy add-on but a transformative force driving real-world improvements.

The AI Marvel in Action

At a recent convention in Chicago, attendees witnessed an AI marvel in action. Enabled by GPT-4, this generative AI technology demonstrated how it could turn a clinician’s patient interaction into neatly structured notes within seconds. Imagine a clinician recording a patient visit on a mobile app, with the AI platform adding information in real time, identifying gaps and prompting the clinician to fill them in. Once the visit ends, the clinician reviews the AI-generated notes, edits them if necessary, and submits them to the patient’s electronic health record. This near-instantaneous process transforms the traditionally manual and time-consuming task of note-taking into something almost archaic by comparison.

The Value Proposition: AI For Impact

AI’s promise in healthcare extends far beyond administrative efficiencies. In this regard, the term ‘Value Generating AI’ focuses on three main principles:

• AI For Impact: AI is employed in critical areas such as improving customer experience, supporting diagnostics and determining the best actions for everyone involved.

• Not AI For AI’s Sake: Investments in AI are justified by the tangible returns they bring.

• AI At Scale: Making AI accessible and useful across various applications, both internally and externally.

A global review identified eight central applications for AI in healthcare, including medical imaging, virtual patient care and administrative functions. Another study from Finland found 34 cases ranging from mobile solutions for home care to optimising operating room efficiency. AI’s role in healthcare is not limited to futuristic scenarios but is actively transforming daily operations in diagnosis, chronic disease management and logistics optimisation.

Generative AI: The New Frontier

Generative AI holds the promise of driving significant productivity gains, improving patient and provider experiences, and ultimately leading to better clinical outcomes. This technology can lower administrative costs, speed up biomedical research and drug development, enhance claims management and help develop next-generation diagnostic equipment. Big tech companies are partnering with healthcare organisations to apply generative AI, and investors are channelling capital into nascent companies built around this innovative tool.

The Human Touch: Augmenting, Not Replacing

Bringing generative AI to healthcare organisations will affect not only how work is done but also who does it. Healthcare professionals will see their roles evolve as the technology helps streamline some of their work. A human-in-the-loop approach will be critical: Even though many processes may fundamentally change, people will remain essential in all areas touched by generative AI.

To facilitate these changes, healthcare organisations must learn to use generative AI platforms, evaluate recommendations, and intervene when inevitable errors occur. AI should augment operations rather than replace them. Healthcare leaders need to provide learning resources and guidelines to upskill employees, ensuring that AI-powered applications are easy for frontline staff to use without adding to their workloads or taking time away from patient care.

Strategic Partnerships

Most healthcare organisations will likely need to form strategic partnerships with technology firms to effectively implement generative AI. Leaders should consider potential partners’ adherence to regulatory compliance requirements, such as the Health Insurance Portability and Accountability Act, data privacy and security standards, and the potential for data-sharing to enhance AI outputs.

Value Generating AI in healthcare is not a distant dream but a reality that holds immense promise. By focusing on impactful applications, ensuring a good return on investments and scaling AI to be accessible and useful, organisations can navigate the complexities of AI adoption effectively. As generative AI continues to evolve, it will be crucial to maintain a balance between technological advancements and the indispensable human touch, ultimately leading to better patient care and more efficient healthcare systems.

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