A New Era of Care (Part 2)

Clinical Decision Support (CDS) tools have the potential to transform healthcare by reimagining patient journeys and addressing critical inefficiencies in health care delivery. These tools create value across the healthcare ecosystem:

• Pharma and MedTech: Optimize drug prescription, treatment efficacy and safety and improve clinical trial efficiency (e.g. speed up patient recruitment)
• Healthcare Providers: Reduce administrative burden, enhance efficiency and improve quality of care
• Payers: Support cost containment and enable preventative care
• Patients: Improve patient outcomes through earlier diagnoses and personalized treatment plans, while delivering a more seamless care experience

Read more about the potential of CDS solutions in part 1 of the series here.

The question remains: How can we fully unlock this transformative potential?

This white paper explores the key considerations for successfully developing and executing a CDS solution if you are a Pharma or a Medtech Company.

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Concept and Strategy Development

The first step in developing a CDS strategy is to define “Where to Play” within your product portfolio. This involves identifying which diseases justify an investment in CDS based on the potential for impact on your product’s commercial success and transformation of the broader patient journey.

Once you have selected target diseases, identify the specific leverage points along the patient journey (e.g. screening, diagnosis, treatment decision and monitoring) where a CDS tool can create the most value. It is critical to ensure that the CDS use case that you target is aligned with your product or brand plan strategy.

Some examples of high value, clinical CDS use cases for Pharma include…

• Patient identification: CDS is relevant for diseases which are asymptomatic in nature, misdiagnosed or underdiagnosed – and can unlock unrealised product demand. These patient ID algorithms should ideally be integrated directly into the point of care to flag potential patients in real time.
  • Example: Focal Segmental Glomerulosclerosis (FSGS) is a rare kidney disease which is underdiagnosed and often misdiagnosed because its symptoms (fatigue, swelling, high blood pressure) overlap with other kidney diseases.
• Treatment Matching: CDS is relevant for diseases with crowded and complex treatment landscapes. They help HCPs match patients to specific drugs or drug combinations based on factors like genetic data, biomarkers, disease stage, prior treatment history, etc…
  • Example: Multiple Myeloma (MM) is one of the most crowded and complex treatment landscapes in oncology. HCPs must navigate multiple drug classes, combination therapies and treatment sequences, and there is no universal algorithm for selecting the optimal next-line therapy.
• Adverse Event (AEs) Monitoring: CDS can support in monitoring AEs associated with high-efficacy but high-risk treatments. By providing real-time alerts, risk stratification, and proactive intervention guidance, CDS empowers both HCPs and patients to use these therapies with greater confidence and safety.
  • Example: Cytokine Release Syndrome is a life threatening adverse event caused by certain high efficacy therapies (e.g. CAR-T, Bispecifics)

Developing a high value, clinical CDS solution will likely be a significant investment and qualify as Software as a Medical Device (SaMD). It is critical to build a business case for the solution. Consider whether the CDS tool be a standalone revenue-generating product, or whether it will be a ´free´ tool designed to enhance drug or product adoption and increase market share – maybe it can be both! A well-defined strategy will ensure that the CDS solution delivers both clinical impact and commercial value.

Building a CDS solution is a multi-stage process that requires strategic planning, cross-functional collaboration, and co-creation with ecosystem stakeholders.

During solution design, it is critical to work closely with clinical and medical teams. They will ensure scientific validity of the solution and help determine which clinical variables (e.g., lab values, genetic markers, comorbidities, treatment history) should be integrated into the decision-making logic. This is also the ideal time to outline a compliance & regulatory roadmap to ensure your solution is designed to meet all regulatory requirements of SaMD.

To maximize the success of your CDS solution, we strongly recommend partnering with a hospital system for co-creation– and taking an iterative agile approach to product development.

Why a Hospital Partner is Critical:

• Access to High-Quality, Real-World Data: Hospital partnerships provide comprehensive, diverse patient datasets, ensuring that your CDS algorithms are built on robust and representative clinical data.
• Improved Algorithm Performance: Developing the CDS within a real-world clinical setting enhances predictive accuracy, validation, and adaptability across patient subpopulations.
• Seamless Workflow Integration: Direct collaboration with HCPs and IT teams ensures that the solution fits naturally into clinical workflows, driving adoption and usability.

Co-creating the solution with your customer will ensure customer centricity is embedded in the solution design.

Many innovative CDS point solutions already exist, but they have fallen short in delivering significant value to healthcare systems. The primary reason these solutions fail to drive meaningful impact is that they either:

1. Lack Seamless Integration into HCP Workflows – If a CDS tool does not fit naturally into clinical decision-making (e.g., requiring extra clicks, logging into a separate platform, or disrupting workflow efficiency), HCPs won’t use it.
2. Face High Costs & Complexity in Scaling – Many CDS tools require labour-intensive, costly Electronic Medical Record (EMR) integrations, making widespread adoption across hospitals financially unsustainable. Different systems (e.g. Cerner, Epic) require custom integrations.

When you are thinking about deploying and scaling your CDS point solution across provider systems, it will be critical to find tech partners and platforms that enable you to integrate quicker and more cost effectively than if you tried to do this alone. We would recommend doing a partnering landscape assessment to determine who can effectively help you achieve your goals.

Examples of Technology Partners:

• Epic – The Epic App Orchard is Epic Systems’ marketplace for third-party applications that integrate with Epic’s EHR system.
• Health Gorilla – A health data interoperability platform that enables secure data exchange between CDS systems and provider networks.
• Redox – A cloud-based API platform that facilitates scalable CDS deployment by connecting to various EHR systems through a single integration.
• Smile CDR – A FHIR-based clinical data repository that supports plug-and-play CDS integration across multiple hospitals.

Developing CDS solution is not a one-time effort - it requires ongoing monitoring, refinement, and adaptation to ensure that it remains reliable, clinically relevant, and impactful for patients and HCPs. Make sure you have a plan to monitor the CDS solution in real-world settings, and track performance, accuracy, and user adoption. Regular evaluation ensures that the system continues to deliver value while adapting to new clinical evidence, regulations, and technology advancements.

CDS solutions have the power to unlock significant value for Pharma and Medtech.

Success requires:

• Aligning CDS strategy with commercial and clinical goals to maximize impact.
• Co-creating with hospital partners and HCPs to ensure clinical validity and seamless workflow integration.
• Leveraging scalable, open-system tech platforms for data connection and cost-efficient deployment.
• Implementing continuous monitoring to maintain relevance, compliance, and real-world performance.

Rebecca Bub, Manager at Intellishore