AI in Healthcare: Strategies for Success

AI has incredible potential, but how do you navigate the path to a successful implementation strategy?

By Igor Meltser, VP of Global Technology Solutions and Services

The healthcare industry is undergoing a rapid transformation, and Artificial Intelligence (AI) is a major part of this evolution. One of the main takeaways from the 2023 Becker’s Hospital Review conference lecture, led by prominent technologists from healthcare institutions, is the essence of integrating AI and automation into the broader business context. However, the future isn’t just about the adoption of AI; it’s about ensuring that this adoption directly addresses and mitigates the business challenges faced by healthcare institutions.

08 Nov 2023

Identifying Core Challenges and Aligning AI Solutions in Healthcare

In the healthcare field today, we’re facing two major problems: a shortage of healthcare workers and a rising issue of clinician burnout due to excessive paperwork. Fortunately, AI technology is stepping in as a solution. For instance, healthcare institutions already use AI tools like ChatGPT to automatically create patient messages, cutting down on manual work and making processes smoother. Another major use case is automation of repetitive administrative tasks. Machine learning algorithms can predict which patients need the most care and help. This allows doctors and nurses to manage their time better and concentrate on the patients who need them the most. The list of such examples keeps growing, giving you an opportunity to find a solution that fits your organization the best. 

Another concept that’s gaining momentum in the healthcare industry is the idea of “hospital at home”, emphasizing the increasing importance of remote patient monitoring. With vast amounts of data collected daily, healthcare organizations are turning to AI to decipher and understand this data. This helps identify high-risk patients and optimize costs.

Strategizing AI Implementation: Problem-Solving First

The roadmap to a successful AI strategy starts with identifying a business problem. Institutions can approach this in two ways: either partnering with strategic partners, especially if they offer platforms integral to the organization’s needs, or by investing in co-developing solutions when existing ones don’t fit the bill. This prioritization emphasizes that while AI is the tool, the business challenge remains at the core. Depending on your specific requirements, this can lead to a variety of solutions. You can explore a potential list here.

Choosing the Right Partnerships: A Balance of Investment and Impact

Partnering with others may require a significant investment, but it’s a necessary step. However, when assessing third-party solutions, make sure the investment promises a substantial impact. Considering that hospitals operate within tight budgets, the grading rubric should focus on the problem at hand and the potential solution’s efficacy. Interestingly, smaller healthcare organizations often find more synergy with smaller partners, growing and evolving together. Large software giants, despite their comprehensive solutions, may charge a premium that many providers cannot afford.

Another major deal-breaker is the issue of data ownership. Healthcare institutions are wary of software companies retaining intellectual property rights and ownership of crucial data. What the healthcare sector seeks are long-term partnerships that combine the technical prowess of third-party solutions with the internal healthcare expertise, fostering a harmonious collaboration.

Brilliance in Basics: Laying the Groundwork for Innovation

Before delving into innovation, it’s imperative to master the basics. This means reducing any technology-induced friction and ensuring smooth operations. Once this foundation is in place, the path to innovation becomes clearer and more attainable.

Key to any innovation project is the initial phase of problem identification. What challenge does the institution want to address? And more importantly, how will success be measured? Stakeholder consensus on these parameters is vital before embarking on the innovation journey. Tools to measure Key Performance Indicators (KPIs) play an essential role here, transforming subjective assessments into objective measurements. An underlying consideration should be the quality improvement framework, ensuring that solving one problem doesn’t exacerbate another.

Lastly, healthcare institutions must introspect and assess their operational readiness for change. Embracing change requires a shift from being task-oriented to becoming thought leaders and genuine partners.

Conclusion: AI’s Art of the Possible

The lecture mentioned at the beginning of this piece elucidated the art of the possible, highlighting the shift in digital transformation from IT-centric approach to an operational focus. For healthcare technology executives, the message is clear: AI’s potential is immense, but its success lies in aligning it with core business challenges.

As you navigate this transformative journey, Sphere stands as your beacon. With expertise in healthcare technology, we invite you to collaborate and bring your AI-based solution ideas to life. Reach out to Sphere, and together, let’s redefine the future of healthcare.