AI has the potential to revolutionise healthcare by personalising treatment plans, improving clinical studies, and streamlining administrative tasks
Artificial intelligence (AI) can transform healthcare as we know it dramatically. This opportunity goes further beyond the complex algorithms and massive datasets in critical cases. It’s also about automating mundane administrative tasks and lessening the load for those delivering healthcare services on the front lines. For example, generative AI can be a game-changer when planning and achieving fast diagnoses in critical situations. It holds the potential to personalise treatment plans for a range of conditions and diseases.
For the first time, healthcare providers don’t need to rely solely on the generic criteria of age and sex when considering how to treat a patient. Instead, AI can be used to evaluate a patient’s clinical profile fully and to fuse that information with complex insights from similar clinical cases—all at machine speed. In the long term, this powerful capability will support clinicians in tailoring treatment plans to individual patients and offering better treatments.
Similarly, AI improvements are being utilised to improve clinical studies. For example, AI will make it easier to spot patterns in existing data, identifying participants likely to react favourably to the treatment and those with adverse reactions. This will allow researchers to perform preliminary experiments utilising the data models of specific patients, or digital twins, before investing in a trial involving real participants.
Drug trials occasionally need to catch up to their goals. This technological development will help researchers assess real participants’ responses to medication in greater detail, reducing the time and money required to create new medicines. Ultimately, this will improve the financial viability of additional interventions that enhance the quality of life and the targeting of these medicines towards those who will benefit from them the most.
Powering the move towards AI
With the world moving away from manual, labour-intensive processes, healthcare organisations increasingly turn to AI to improve efficiency. AI capabilities have advanced significantly over the past few years, offering the potential to revolutionise planning, remote patient monitoring, and decision-making with better, faster, and more effective outcomes.
Yet, adopting AI can take time and be a costly investment. Over 30 years of productivity-enhancing technology have proved that there’s a difference between successfully implementing new technology to the specifications, time, and budget and delivering capabilities that patients and clinicians want to use. Also, with this buy-in, AI-enabled capabilities can deliver on the promise of better, faster, and more effective healthcare.
In a way, this is the same as the issues that healthcare organisations experienced with the introduction of IT self-service capabilities like check-in kiosks or digital monitoring apps that allow patients to play a bigger role in managing their care. The introduction of new technologies usually affects the ways of delivering patient care and the people receiving care, which means there can be some resistance to overcome. This is why organisational change management tools and techniques are needed to facilitate AI success.
Considerations for AI Adoption
In an e-book compiled by ManageEngine, Service Management Strategies for the next 3 Years from 10 ITSM leaders and experts, two key areas are highlighted:
- Addressing people-related issues
- Making process-related improvements
These two areas are key to adopting any new technology, like AI, in any organisation. Identifying business opportunities, making purchase decisions wherever needed, and optimising technology usage to successfully implement any new technology are important. With proper contributions from the key stakeholders, these processes might be possible. Also, the right business use cases and the appropriate existing practices must be adapted to the new AI implementations rather than replaced.
A one-size-fits-all approach is unlikely to work with AI. Instead, individual healthcare providers must start by deciding which areas or ways of working will benefit the most from AI technologies. By identifying the opportunities for AI and understanding how the technology can best be used to improve patient care, organisations can make informed decisions about where to apply the technology and how to drive adoption levels slowly.
To ensure that AI delivers the value their organisations expect, healthcare providers must also support employee upskilling and invest in AI training. By giving clinicians a better understanding of AI technology, clearly outlining AI policies, communicating the risks and opportunities, and ensuring compliance are built into AI processes, gaining employees’ trust and boosting long-term adoption levels will be easier.
Finally, healthcare providers need to be alert to the constraints and biases that come with the growing use of AI. The very nature of AI means that it requires a large amount of data to work efficiently. An algorithm’s output grows increasingly precise and individualised as more data is fed. As healthcare providers rely more on AI, they must also be mindful of the latest data protection laws, algorithmic accountability, ethical AI guidelines, and advice from regulatory bodies. These measures are intended to ensure that patients’ privacy rights are safeguarded and that organisations utilising AI are held accountable for the data they collect and utilise. Generative AI could transform healthcare, but it needs to be used wisely and cautiously.
AI: Navigating the next frontier in healthcare
For healthcare providers, AI is revolutionising everything from clinical decision-making and pandemic risk assessments to individualised care and drug research. Amid a shortage of medical professionals, AI’s additional clarity could help answer complex resourcing challenges in the long term. Also, with a market opportunity estimated at $6 trillion, AI could hold vast benefits for the industry. It could continue to boost economic growth and healthcare outcomes, benefitting society as a whole and individual patients in years to come.
Yet, for the adoption of AI to be successful, the healthcare industry must undergo a cultural change. Energy should be focused on creating value and nurturing an environment of collaboration between patients, clinicians, and other departments like IT. Continual learning will be essential to ensure the skills of those working within healthcare remain current, supporting the long-term capabilities of their teams and equipping them with the necessary knowledge to assist patients. Above all, it’s important to view this change as an iterative journey as new strategies, plans, and operating methods unite so that healthcare organisations can operate with greater agility in a rapidly changing world and ultimately deliver better patient outcomes.
This piece was written and provided by Kumaravel Ramakrishnan, technology director, ManageEngine
