Dr. Bill Kerr, CEO and cofounder of Avalon Healthcare Solutions
Photo: Avalon Healthcare Solutions
Dr. Bill Kerr, CEO and cofounder of Avalon Healthcare Solutions, works in what his company calls "diagnostic intelligence" – using real-time diagnostic data, advanced analytics and clear clinical policies to guide more precise and proactive decisions.
Diagnostics are no longer just static lab results, he explains, but dynamic signals that reveal how a patient's condition is changing in real time.
The next phase of value-based care, he predicts, will rely on diagnostic intelligence.
"With the rapid growth of genetic testing, biomarkers and other advanced diagnostics – thousands of new tests appear each year – we now have a deeper understanding of disease risk, progression and treatment response," said Kerr.
Patterns traditional methods miss
"These tools reveal patterns that traditional methods often miss, helping us better understand each patient's needs and enabling more personalized care," Kerr continued. "They also integrate insights from imaging and laboratory data, enhancing the ability to monitor disease progression with greater clarity and precision."
Diagnostic intelligence improves value-based care by aligning care with earlier detection and better treatment options, he added.
"When clinicians use tools like polygenic risk scores, liquid biopsies or Alzheimer's blood tests to understand a patient's biology, they can intervene sooner, select therapies with a higher likelihood of success, and avoid the costly trial-and-error that has long defined complex care," Kerr said.
"This supports VBC's primary goal: better outcomes with fewer unnecessary costs," he continued. "It also helps prevent mismatches between targeted therapies and the patients receiving them – an increasingly important safeguard as precision medicines become more common."
Eliminating operational barriers
And diagnostic intelligence can help eliminate operational barriers that have slowed the adoption of more personalized care within value-based care models, Kerr added.
"Issues such as inconsistent test use, delays with certain biopsy types and uneven guideline adherence contribute to clinical variation and higher costs," he noted. "By layering analytics on top of diagnostic data, health plans and providers can identify these gaps in real time and implement more consistent, evidence-based practices.
"As a result, diagnostics shift from a back-end cost to a frontline strategic asset – one capable of improving equity, reducing waste and ensuring the right care reaches the right patient at the right time," he added.
Diagnostic data this year will become healthcare's most powerful IT asset, fueling earlier detection, smarter treatment choices and truly personalized care at scale, Kerr said.
Healthcare's most valuable IT resource
"Diagnostic data is poised to become healthcare's most valuable IT resource, offering the earliest and most personalized insights into a patient's health journey," Kerr stated. "Unlike claims or EHR data, which document what has already happened, diagnostic data reveals what is occurring biologically in real time, often before symptoms emerge.
"With the rapid growth of genomic testing, early multi-cancer detection assays, polygenic risk scoring and blood-based neurodegenerative markers, healthcare now accesses clinical signals that enable much earlier intervention than ever before," he continued. "These tools shift the focus from reactive treatment to proactive prevention and early detection."
When combined with advanced analytics and AI, diagnostic data also supports smarter treatment decisions, he added.
"Diagnostics help identify which patients need expensive specialty therapies, require more precise interventions, or might benefit from preventive or lower-intensity options," Kerr explained. "As costs continue to increase – especially in fields like oncology, metabolic diseases and neurology – this precision becomes crucial.
"By integrating diagnostic data across laboratory systems, provider workflows and payer decision-making tools, stakeholders can decrease unnecessary usage, align with evidence-based guidelines and achieve better outcomes more consistently," he added.
Personalized care at scale
Finally, diagnostic data enables truly personalized care at scale by building a constantly evolving ecosystem, he said.
"As more patients undergo testing and data grows, predictive models improve and clinical guidelines become more precise," he noted. "This feedback cycle broadens precision insights from high-acuity groups to primary care, chronic disease management and population health initiatives.
"It also helps make personalized care fairer by identifying disparities in testing and treatment, allowing targeted efforts to address those gaps," he concluded. "Although adoption will keep progressing gradually and unevenly, the current infrastructure positions diagnostic data as a key driver for a more predictive, personalized and efficient healthcare system."
Follow Bill's health IT coverage on LinkedIn: Bill Siwicki
Email him: bsiwicki@himss.org
Healthcare IT News is a HIMSS Media publication.
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