Healthcare Data Monetization: The Path to Innovation and Increased Revenue
Healthcare data is a powerful asset, with the potential to transform patient care and drive breakthroughs in personalized medicine, drug discovery, and disease prevention. Data monetization offers data custodians (Health Systems, Biobanks, Labs etc.) the opportunity to tap into this potential, generating new revenue streams while supporting advancements in medical research and innovation.
While data monetization holds significant promise, success requires careful strategic planning and addressing complexities ranging from data privacy concerns to technical challenges in data preparation and integration and business model for revenue generation. This blog explores the critical factors that data custodians should evaluate before embarking on this path, emphasizing strategies to overcome challenges and maximize the value of their data.
Key Considerations for Data Monetization
Organizational Readiness
Building a Compelling Business Case
Data monetization requires a well-defined business case outlining potential revenue, resource needs, risks, and alignment with the organization's strategic goals. This case is essential for securing leadership buy-in and necessary investments in data governance, expertise, and potential infrastructure enhancements.
Balancing Privacy and Data Utility
Healthcare data is subject to stringent privacy regulations. Robust data governance practices must be in place to protect patient privacy while still ensuring data utility. Explore solutions that prioritize privacy while preserving the temporal context and granular insights needed for impactful research. Data aggregators can simplify monetization, but consider options that maintain your control over how data is used and ensure you benefit fully from its value generation.
Data Preparation
Data Transformation for Usability
Usable data necessitates a focus on data quality and standardization. Ensuring data is accurate, complete, and follows consistent formats across datasets is critical. Advanced analytics rely on clean data, and lack of consistency can hinder its value.
Unlocking Insights with Unstructured Data
Valuable insights often lie hidden within unstructured notes and documents. Invest in tools and expertise to extract valuable information from clinical notes, physician reports, and imaging results, significantly enriching your datasets.
The Power of Multimodal Data: Datasets integrated across modalities- genomics, pathology, radiology- offer unparalleled depth, enabling more sophisticated analyses and driving higher value for data consumers.
Enhancing Data Utility
Prioritizing Longitudinal Data
Longitudinal data offers a wealth of insights. Datasets that capture a patient’s medical history over time enable analysis of disease patterns and treatment responses across time. By prioritizing solutions that facilitate linking and access to patient history across organizations in a manner that preserves the details necessary for analyzing temporal relationships, data custodians can ensure their data reaches its full value for impactful research.
An example of such a collaboration would be a molecular testing lab partnering with health systems where the in depth genomics data generated during sequencing is augmented with clinical data from the EHR to facilitate clinical trial recruitment and drug discovery use cases
Collaboration in a Competitive Landscape
Expanding the reach of your data through partnerships with other stakeholders can significantly enhance its value. However, the competitive nature of the healthcare landscape can hinder collaboration efforts. Concerns over data ownership, monetization rights, and revealing sensitive business information can create barriers to the seamless integration of data across organizations.
Business Model Selection: Choosing the Right Path to Revenue
Aligning Model with Data and Audience
The ideal revenue model depends on the type of data you have and the target audience.
Budgeting for Customer Acquisition
Accurately factor in costs related to sales, marketing, legal, and compliance efforts to streamline the process of attracting and onboarding data consumers.
Phased Approach for Sustainable Growth
Evaluate a strategy that allows you to generate revenue with your existing data assets while investing in expansion and enhancement for broader monetization opportunities in the future.
Protection, Flexibility, and Scalability
Choose a model that protects your investment, offers flexibility to adapt to market shifts, and enables revenue to grow alongside increasing data utilization.
Conclusion
Data monetization can be a powerful tool for data custodians to achieve their financial goals while fostering innovation and scientific progress. Balancing privacy with utility, ensuring data quality, and navigating the intricacies of collaboration require innovative approaches. By carefully considering the key factors outlined in this blog and seeking guidance when needed, healthcare organizations can successfully navigate this landscape.
Seeking a Solution?
datma understands the importance of preserving the temporal and longitudinal nature of healthcare data while ensuring privacy and compliance. If you are interested in exploring how our innovative approach can help you overcome the challenges of traditional data monetization models, schedule a call or demo at your convenience.
