The healthcare and pharmaceutical industries are witnessing a surge in digital data generation thanks to wearable sensors, electronic health records, and clinical and genetic data. Simultaneously, the emergence of data-centric decision-making is set to benefit healthcare services in several areas.
These areas include:
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Genomics and precision medicine. This will enable targeted treatments for specific patient groups, potentially enhancing efficacy and leading to novel therapeutic avenues.
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Remote care. This will enhance healthcare accessibility, leading to patient needs being addressed earlier and the healthcare system potentially becoming more efficient.
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Technology-supported self-management. Patients will be able to better understand their condition(s), helping them more effectively manage their health and fostering improved behavioral and clinical outcomes.
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Data. This will serve as a catalyst for improving national healthcare systems’ research and decision-making.
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AI. This could augment analytical capabilities for patient diagnoses, leading to more efficient triage and patient logistics management.
The continued development of healthcare-related technologies, including AI, is transforming healthcare business processes, especially in medium-sized and large pharmaceutical firms, resulting in faster, more efficient decision-making. Other advantages include diminished human error and accelerated product development cycles, ultimately resulting in faster product launches.
Meaningful Metrics
In recent years (and in large part because of the pandemic), governments stepped up pressure on the healthcare and pharmaceutical sectors, asking them to develop a more aligned, cohesive approach to the use of digital technologies and data management in decision-making to deliver greater value to stakeholders.
Aligning healthcare interventions with outcomes that matter to patients is of paramount importance. Significant challenges arise when healthcare systems prioritize activity and inputs over outcomes, hindering adoption. For example, researchers found payer uncertainty about the value of investment in mental health treatments and showed the potential for this to impede the adoption of new treatments.
Two other research groups demonstrated the criticality of aligning on outcome metrics to achieve value-based healthcare (VBHC). Meaningful metrics and measurements serve as a guiding condition for innovation implementation, informed decision-making, quality improvement, and reduced costs.
A recent initiative spearheaded by the Welsh Government demonstrates the critical role of robust digital infrastructure in driving innovation adoption and realizing tangible outcomes. The Ibex Galen AI platform’s analysis of prostate biopsies resulted in a remarkable 13% increase in cancer detection, and the platform is now being used at Betsi Cadwaladr University Health Board to examine suspected breast cancer cases.
Funded through the Welsh Government’s innovation fund and supported by the Small Business Research Initiative (SBRI) Centre of Excellence, the AI tool uses a traffic-light system to classify digital images of pathology samples to indicate the likelihood of cancer, helping clinicians prioritize urgent cases. This is leading to faster diagnoses and is expected to reduce the need for additional biopsies and tests.
[For more from the authors on this topic, see: “Using Data Technology Platforms to Deliver Stakeholder Value in Healthcare.”]
