Make robust patient consent management and data protection as key features
As the owners of their own Personal Health Information (PHI), patients have the right to approve or deny the retention and use of their data by organizations. Patients need assurance that their PHI is protected both within the organization and in trusted networks outside of it. Data protection measures should include data access controls and encryption during storage and transport between organizations.
Data safety and patient consent management should be integral features of digital health solutions by design, and patients should be informed accordingly. Ensuring the protection of patient data, along with the capability to manage consent within the application, will help generate the necessary trust for patients to use digital health applications, thereby alleviating privacy concerns.
Suggested actions: assess and implement cloud services that offer strong and robust data privacy and consent management features.
Implement effective cybersecurity measures
Digital Health actors need to invest in state-of-the-art cybersecurity to protect connected and personal devices, Digital Health applications, data and networks from cyberattacks. Once the required level of security has been established, organizations could become certified from security associations (e.g. ISC2) or governmental organizations (e.g. EU’s ENISA) and display the certifications in Digital Health applications. These certifications will help to reassure patients that their PHI would remain safe.
Suggested actions: establish cybersecurity processes; regularly execute cybersecurity procedures such as vulnerability testing and infrastructure monitoring; enforce security aspects within organizational policies.
Prepare data in a meaningful way to ensure organizational interoperability
Business and technical benefits could be accrued as result of information exchange through organizational interoperability. These benefits in turn come from syntactic interoperability (i.e. preparing data with a common data structure and format) as well as semantic interoperability (i.e. corroborating data with unambiguous definitions and information). The organizational interoperability ensures that the data to be processed are easy to work with across organizations and current as well as future AI technologies would be able to extract information and interpret accordingly.
Suggested actions: enforce adherence to industry standards; appoint interoperability champions/ POCs within each organization.
Develop unified view of patients’ health within an organization
Data silos in Life Sciences and Healthcare organizations may arise from patient data being dispersed across different departments (e.g. laboratory, clinic, billing), which results in fragmented view of patient health data. Consolidation of data from disparate databases results in unified view of patient that allow healthcare providers to take informed decisions about patients. These decisions would also be based on historical patient data within a hospital or healthcare provider from various departments. Electronic health records (EHR) of patients based on data standards would bring together data available within the healthcare organization that could be analyzed further. Analytic tools based on AI could further help to better diagnose and predict diseases of patients. Getting a unified view of patients within an organization will be the first step to providing personalized healthcare solutions to patients.
Suggested actions: adopt global interoperability standards; leverage Master Data Management (MDM) solutions; adopt cloud services with powerful AI environments and tools.
Develop integrated view of patients’ Health across organizations
Once a unified view of patients has been created within an organization, different patient views across organizations could be combined to provide an integrated view of patients. This is a challenging phase as it involves agreement between organizations regarding standards for data transport (e.g. HL7 FHIR) and data security (e.g. HIPAA, GDPR, OAuth). Accessing data using an integrated data view from various organizations would provide a holistic picture of patients’ health. This integration involves the creation and implementation of application programming interfaces (API) between involved organizations that would exchange information using standardized data taxonomy.
Suggested actions: design and establish a holistic view of patient’s health data based on common technical protocols; adopt AI tools to leverage data potential of patient data.
Modernize legacy systems for cross-organizational integration
Legacy applications such as Laboratory Information Systems (LIM), Radiology Information Systems (RIM), Hospital Information Systems (HIS) and claims processing systems could experience interoperability issues because of incompatibility with new technologies. Other possible issues include data security vulnerabilities, limited scalability, and high operational costs. There are several ways to upgrade data infrastructure from rebuilding applications to migrating data to a state-of-the-art platform, creating APIs and integrating using middleware. Modernized data infrastructure allows improved accessibility for digital health data and efficient integration of data within an organization.
Suggested actions: run a feasibility assessment to check interoperability in the current technology environment; migrate from on-premise systems to cloud platforms within the context of an overall IT strategy review at organizational level.
Implement digital health enterprise platform to manage digital devices
Implementing a digital health enterprise platform (DHEP) within life sciences and healthcare organizations allows the central management of data assets using a single repository. Real-world data (RWD) from EHR, patients’ data from mobile and IoT devices are becoming more relevant in the pharma industry, especially for clinical trials. DHEP could help healthcare organizations to leapfrog many legacy system issues and allow data from digital devices and services within the organization to be stored in a single platform. Several vendors offer GxP-relevant platform services from the cloud that could be an efficient solution for many organizations to manage data efficiently.
Suggested actions: assess and implement a DHEP platform within the context of an overall IT strategy review at organizational level.
Get Buy-in from internal stakeholders to embrace interoperability concept and benefits
Organizational silos hinder digital health actors to leverage the intrinsic value of data spread across the organization. Each department or team typically thinks of its own benefits and has little incentive to collaborate to extract the full potential of data. Key stakeholders in each healthcare department need to be made aware of the holistic benefits of patient-centric digital solutions by the leadership team and encouraged to collaborate. The change management activities to promote collaboration and commitment among involved departments require top-down approach to enable interoperability within the organization.
Suggested actions: secure leadership support and define a change management strategy to socialize and adopt interoperability.
Agree on business case for cross-organizational collaboration among life sciences and healthcare organization
As each organization is driven by its goals, it is imperative that the actors in digital health services come together to define a common business case. Cross-organizational collaborations need to be based on a shared vision to establish patient-centric digital healthcare, leveraging AI technologies such as Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI). The ecosystem actors should define their mission and develop a business case that includes a cost-benefit analysis. Once the revenue potential of the collaboration becomes clear, the leaders in each organization need to commit to the success of the digital health solution.
This collaboration between organizations needs to be strategically planned and based on partnerships, as the execution of a patient-centric business case requires a longer time frame. As the initial success of the digital health application becomes evident in the market, more actors will join, making the digital health ecosystem even more successful.
Suggested actions: collaborate with involved organizations to develop bespoke use cases leveraging AI tools having business impacts and implement the business case.
Looking ahead
Today’s social and technological advancements provide the foundation for a new patient-centric approach with enormous potential to improve patient healthcare and transform the life sciences and healthcare industry. This paradigm shift, which places patients at the center of care, requires bringing together all actors in the digital health ecosystem to enable cross-organizational data interoperability. Addressing the current challenges will accelerate the realization of this paradigm shift for everyone’s benefit.
