How digital health platforms can improve data management and fuel better insights

December 8, 2022 John Mulcahy

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How digital health platforms can improve data management and fuel better insights

Digital health solutions offer the opportunity to capture a broad range of data that can be used to generate valuable insights. These insights support patients and their care teams at each point in the treatment journey with the aim of improving patient experience, care, adherence, and ultimately, outcomes from therapy.  

With so much data available to collect, collate, and utilize, doing it all from scratch is a huge undertaking; one which can be avoided by using a platform. A digital health platform enables efficient and compliant management of data created from patients’ real-world experience of both the condition and the treatment of that condition. 


Quality of data is key if it is to be used effectively 

A digital health platform should support the fundamental goal of any digital health solution; capturing valuable data and using it to make meaningful impacts on patient experience, care delivery and ultimately healthcare outcomes. This can be broken down into three stages:

1. Collect quality data 

The quality of the data collected will determine its future value and use. Platforms should support the capture of high-quality data by allowing for the integration of medical devices as opposed to limiting device data to unregulated consumer devices. This supports the generation of clinically reliable data.

2. Ensure the data is usable

The structure of the data, how it is hosted, and compliance with legal and regulatory requirements will all determine if the data captured can be used to generate patient and disease insights. As legal and privacy laws evolve and update, and differ from region to region, platforms can manage consent updates, meaning companies can be confident in knowing they have the appropriate compliance and consents in place. 

3. Generate meaning and insight

Once quality data is available and usable, platforms can then support the generation of meaning from the data to drive insights. This starts by comparing each patient’s progress on their care plan. Then, providing patients with the right information, at the right time in the management of their treatment and condition to support them while on therapy. With some platforms, these interventions are personalized to the patient depending on the stage of their treatment journey or the challenges they are currently facing. A platform can identify patients that need follow-up to the PSP or care-team. Platforms often provide the tools to analyze data by facilitating the creation of custom dashboards and reports. Key metrics on adoption, engagement, sustained usage, and treatment adherence can be reported on.  

With so much data potentially available, and how it’s used having such importance, data management is the foundation on which digital health solutions are built. A digital health platform is one of the most effective ways to enable compliant data management which meets the needs of each stakeholder as solutions are deployed at scale and across different jurisdictions.


How platforms manage data to address the challenges faced by pharma 

Digital health platforms are designed to provide scalable, cyber-secure data management that works across multiple jurisdictions to address the following key challenges.

1. Enables the creation of therapy or disease specific information models

Platforms should enable a disease or therapy specific information model to be created for each digital health solution, together with the ability to extend this information model if more therapies or disease areas are added, allowing pharma to leverage the investment in digital health across multiple assets. The model contains the following main elements:

  • Demographics
  • Patient Id: Patient identifiers comprise both an internal system identifier and the Patient National Health Id. External IDs are needed to interface to clinical workflows and support clinical studies and real world evidence generation. 
  • Digital Care Model: Tailored to the solution, this can include medication adherence, data from connected devices, results from digital therapeutics, patient reported outcomes (PRO), biometric data, and clinical outcome assessments 
  • Operational data: Status data from connected devices such as error data, connection status, and battery status that enables technical support of a patient’s devices, fleet management of connected devices, and ultimately, predictive maintenance based on observed patterns of failure 
  • Additional Research Data: To support future real world evidence generation or clinical studies, additional data may be needed to construct matched cohorts of patients (for example related to disease stage, comorbidities, whether the patient is new to treatment or has received other treatments). 

All data is time-stamped so that a longitudinal picture can be created at the patient level. 

2. Manage compliant access and hosting of user data in accordance with consent

Digital health solutions are usually multi-sided, serving different users that may include: patients, their care teams, PSP nurses, clinical research teams, and pharma. Access to data and insights from the digital health solution must be managed in a compliant manner. Platforms achieve this by: 

  • Managing eConsent in a compliant manner across all countries and jurisdictions, and keeping this up-to-date with changes to data protection legislation, and services offered to the patient (for example, if a patient decides to take part in a clinical study)
  • Hosting data in accordance with local health data protection law. Platforms are designed to store personal health information either at a country level. Pseudonymized or de-identified data is stored regionally (so for example de-identified data for US patient populated is stored in the US in compliance with HIPAA, or CPRA regulations, while pseudonymized data for EU patient populations is stored in the EU in accordance with GDPR).
  • Enabling the creation of the necessary data-rights structure that then flows from this, which is typically that: 
    - Patients own their personal health information, and their consent must be given to access and use it
    - The care team treating the patient can view the patient’s personal health information either with patients' consent or invitation
    - PSP nurses can access patient-level information for all the patients in their caseload
    - If a patient consents to take part in research, patient-level information can be exported into clinical study electronic data capture systems
    - If a patient consents to take part in real-world research, patient-level pseudo-anonymized or de-identified patient information is exported to the pharma’s data lake for analysis by the biostats or clinical research teams. 
    - If the solution has a payer interface, payers can only see aggreged anonymized reports showing how the patient population they are paying for has performed
    - Pharma’s commercial teams can only see aggregated anonymized reports and information generated from the data. 


3. Provides state of the art cyber-security and protection 

State of the art, continually up-to-date cyber security is a must-have for any digital health solution. Digital health platforms apply cyber-security across the design, development, deployment, and operation of the platform in accordance with FDA and EU cyber-security regulations.  

These include security risk analysis and mitigation, applying OWASP, NIST and NVD best practice. Data is encrypted at rest (when it is stored in databases) and in-motion (while in transition e.g., between connected drug delivery devices and mobile applications, and between the mobile applications and cloud software). 

Platforms are built on top of leading cloud infrastructure providers to leverage the continual development these make in cyber-security.


The huge range of data that can be derived from digital health solutions throws up the issue of how to capture and manage it. Digital health platforms help capture quality data, ensure appropriate consents are secured, and manage data so it can be used to ultimately make a positive impact on patient experience on therapy, care delivery and healthcare outcomes.

To discuss how digital health platforms can help you with your data management strategy for digital health solutions, get in touch with the team today.