Dave Wessinger, Cofounder & CEO of PointClickCare, a leading healthcare technology platform enabling meaningful collaboration.
As healthcare data becomes increasingly digitized, clinicians are finding themselves navigating an ever-increasing volume of data. Yet in my time working with healthcare technology, I’ve found that what truly matters isn’t the amount of information; it’s whether or not organizations and care teams can synthesize and draw insights from complex datasets at the point of care.
Healthcare doesn’t need just “artificial” intelligence, but “actionable” intelligence—technology that helps organizations optimize resources and improve outcomes.
The Real Data Challenges In Healthcare
I believe unlocking AI’s true potential starts with a clear, honest understanding of the real healthcare data challenges that exist today. Too often, conversations about AI center on the exciting possibilities while overlooking the core issue: whether or not the data feeding the systems is incomplete or poorly integrated. This often leads to AI solutions falling short of expectations.
AI’s impact depends entirely on the quality and comprehensiveness of the data it processes. Yet a great deal of vital healthcare information remains trapped in paper records or scattered across disjointed digital systems, creating a major barrier to quality care. Even digital records are often incomplete or inaccessible when needed most, limiting AI’s ability to deliver reliable insights.
If we don’t start by tackling inaccuracies and gaps, we risk building AI models on an unreliable foundation. What’s more, these risks can be further compounded when data is pulled and served up elsewhere, such as by vendors whose standards for security or quality are inconsistent. I’ve seen numerous cases where fragmented data delivered by less-secure sources undermined trust and ultimately jeopardized patient outcomes.
That’s why building and maintaining a unified system of record within your organization is important for making AI actionable. This allows AI to operate at its best and provide trustworthy insights that drive better care.
Unlocking Data To Power Transformative Care
I believe AI’s true power in healthcare lies in fine-tuning models to deliver reliable results. The more structured data that is available to be analyzed, the sharper healthcare AI models can become, and the more capable they are of adapting to the shifting realities of patient populations and emerging trends in care delivery.
This feedback loop can help ensure that intelligence is not static but evolves in response to the lived experiences of patients and care teams. Being able to transform your data into actionable intelligence can equip your clinicians to anticipate needs, respond with agility, and deliver truly personalized care. Without this foundation of structured data, however, AI will likely remain just a tool—unable to provide the clear guidance clinicians need and lacking the power to truly drive change.
Transforming Raw Data Into Meaningful Intelligence
If you’re looking to integrate AI systems into your healthcare organization, the first step is understanding how you can convert raw data into meaningful, actionable intelligence. Start by connecting your organization’s clinical, financial and operational data so that care teams have a complete view of each patient.
Clinicians should also be essential participants in the decision-making process, so ensure they have access to concise, intelligent summaries that highlight the most relevant, immediate details at the point of care. I’ve found that when care teams can surface the most important information as it happens, they can act swiftly and decisively, becoming more efficient and effective. Rich, actionable data—distilled for clarity—can empower your clinicians to make timely decisions and deliver targeted, personalized care when it matters most.
Final Thoughts
True intelligence in healthcare goes far beyond data aggregation—it can elevate your data and deliver timely, relevant insights directly into clinical workflows. In my experience, this shift from a reactive model of care to one that is preventive and forward-looking can not only streamline operations and reduce administrative burdens but also redefine patient outcomes for the better.
Turning information into intelligence, and intelligence into action, enables more efficient and effective care. Put simply, AI alone can’t transform healthcare. Rather, it’s having your clinicians in the loop and supporting their ability to act on intelligence that can make all the difference.
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