Scaling digital health integration to improve patient care

• Data-rich healthcare systems can benefit greatly from digital transformation 
• Although much progress has been made, challenges exist to the widespread implementation of digital solutions 
• MIT Technology Review surveyed healthcare executives to determine the potential and appropriate use of digital technologies across healthcare organizations

Aging populations, growing rates of chronic disease, and workforce shortages around the world present huge challenges for health care systems. At the same time, digital technology is progressing rapidly and could enhance the efficiency and effectiveness of health care, easing the burden on stretched systems. The World Health Organization (WHO) believes the scope of application for digital health is “immense”, estimating that spending an additional $USD 0.24 per patient per year on digital health interventions could save more than two million lives from non-communicable diseases over the next decade.¹

However, despite the promise of digital health to improve care, widespread adoption is slow, and the path to scaling solutions remains complex. A recent survey by MIT Technology Review explored healthcare executive attitudes towards the potential and appropriate use of digital technologies. The report concluded that to work most effectively, digital solutions need to be scaled and embedded in an ecosystem that ensures a high degree of interoperability, data security, and governance.

The healthcare sector is data-rich, producing an estimated one-third of the world’s data. It is therefore primed for digital transformation to increase organizations' abilities to exchange, interpret, and use data effectively. Systems can also be innovative when necessary. This has been clear since the COVID-19 pandemic, when health systems rapidly deployed digital solutions.² Since then, there has been an expansion of digital technologies across organizations:³

Digital diagnosis: Advances in AI have enabled powerful tools for patient care that offer personalized and predictive capabilities. Today, human-designed algorithms have advanced to become software as a medical device (SaMD), meaning the software functions as a standalone medical tool. Operating as digital co-pilots, these systems support healthcare providers by minimizing errors, improving diagnostic precision, and tailoring care to individual patients.⁴

Resource optimization: AI has provided the tools to handle the large amounts of data seen in healthcare systems. In laboratories, scientists are able to analyze vast data sets, extract insights, and make recommendations for next steps more efficiently than ever. Hospitals are also seeing efficiency gains through tools that connect different data and IT systems, and are also benefitting from solutions designed to streamline processes and enhance logistics through automation.⁴

Workforce augmentation: Digital tools have the potential to ease pressure on over-stretched workforces, which is particularly important as the WHO predicts a shortfall of 11 million workers by 2030.⁵ For example, transcription tools can help reduce the time it takes a physician to write up notes, algorithms can review genetic profiles to personalize treatment plans, and remote digital tools can enable more patients to be treated at home, alleviating pressure on hospitals. A critical consideration flagged by the report is that digital solutions should not be viewed as a replacement for workers, but should augment the workforce and free up time for more complex tasks. 

For technologies to support the digital transformation of health care most effectively, the report concludes they must be scaled up and embedded in ecosystems with robust data governance, interoperability, and security.

Data quality and interoperability are essential to the effectiveness of digital health systems, but something that organizations often struggle with. To run effectively, systems should be able to exchange, interpret, and use data like electronic medical records with ease. However, much of the data is trapped, and only a small percentage can be used for physician or population health administrators’ use, thus limiting the delivery of connected care. In large countries with fragmented systems and disparate income levels between clinics, the universal adoption of technologies remains challenging.⁴ To help tackle this problem, there are a number of standards being developed that create a common language for data exchange, including Health Level Seven International (HL7) and Fast Healthcare Interoperability Resources (FHIR).⁶

The sharing of data across clinics, and potentially with third parties, brings with it privacy and security challenges, and the risks are high. The report notes high-profile data breaches that affected 8.9 million patients at a US health care provider, and the theft of 78.8 million records from a major health insurance company.⁷ Almost 40% of MIT survey respondents agreed that balancing security with system performance and usability is the primary challenge for secure digital health solutions.⁴ Countries and organizations are working together to find ways to share data safely, and emerging technologies hold promise for strengthening data governance. Blockchain, a decentralized distributed database, stores data across multiple computers, making it resistant to tampering and enhancing the security of medical data. Homomorphic encryption also helps ensure privacy when third-party access is needed by allowing computations to be performed directly on encrypted data without the need for decryption.⁸ Cloud storage solutions can also help strengthen governance and security by providing guardrails for hospitals that enforce policy requirements, such as ensuring all data is encrypted for upload.

Another requirement for integrating new technologies is a careful balance of innovation while remaining compliant with regulatory guidance.⁹ This is an area that organizations can struggle with as regulations try to keep pace with technological change and are often unclear. Reimbursement can also be inconsistent, meaning organizations can be reluctant to invest in innovation. Some progress has been made in the regulatory space; the EU AI Act (2024) provides a framework with the aim of balancing innovation with ethical considerations, while the FDA’s Predetermined Change Control Plan (PCCP) aims to support innovation by allowing minor updates to evolving AI systems without repeated regulatory applications.^10,11 The report notes that regulators also have a role to play by encouraging organizations to share data through open data ecosystems. This philosophy is based on open finance, where governments dictate that banks must let customers share data with other providers.¹²

Overall, the report found that nearly 75% of organizations believe they are ready, or very ready, to implement and use digital health solutions effectively.⁴ Despite this, implementing tools with existing infrastructure and ensuring interoperability are continued obstacles to delivering secure connected health at scale. By prioritizing building resilient, secure, and scalable infrastructure, organizations can support current needs and future innovations. Success depends not just on individual digital solutions but on the right platforms to balance data innovation, interoperability, usability, and security.