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What will 2021 hold for digital health?

Remote monitoring. Video consultations. Contact tracing. Social distancing.

These coronavirus-inspired terms have become a part of our daily vernacular in the healthcare industry and in the community as we respond to the realities of the pandemic. This new vocabulary is also reflective of more permanent shifts in the delivery of healthcare made possible by the adoption of digital technologies at scale and speed.

Rapid digital transformation was seen in action in 2020. In 2021, healthcare providers will continue at pace to adopt digital systems and services to deliver improved quality of care and patient safety. Building digital workforce competencies will be a priority to help staff to deploy these technologies as part of their clinical service, as well as planning to strengthen overall care delivery including pandemic management preparedness.

In the year ahead, we expect the following trends to impact the success of digital health initiatives.

As witnessed during the pandemic, a large number of patients requiring intensive care can quickly overwhelm local healthcare systems and resources. Clinicians are required to evaluate the quantum of rapidly changing patient data and make critical care decisions in a very short period of time. There is a compelling need for clinical decision support (CDS) tools that can efficiently interrogate enormous amounts of data to improve care quality, avoid errors or adverse events and allow care teams to be more efficient.

In fact, recent research on the use of CDS tools to assist with COVID-19 severity assessment, resource management and care found the technology could empower healthcare providers to save lives. The ability to accurately assess and identify patients at risk of infection or deterioration can help clinicians to prioritise care for patients with elevated risk and manage low-risk patients in home or virtual settings.

The use of mobile technology in healthcare has long been acknowledged but not rapidly adopted. The pandemic has demonstrated its immense potential to give clinical teams’ access to new and relevant information to manage their workloads, monitor patients and action critical events in real-time, wherever they are.

Mobile devices can facilitate more intelligent healthcare applications, by interfacing with electronic medical records or clinical systems to report a patient’s status or alert care teams to changes. This new mobility ecosystem could also expand patient access to care and how care is managed. For example, in a rural context, a doctor could manage an emergency department virtually by reviewing patients’ records, making a diagnosis with the available imaging results and sharing treatment plans via their mobile device.

Social distancing and strained hospital capacity have necessitated the need to provide care to patients at a distance. This was possible through the use of telehealth and remote monitoring dashboards that could integrate data from a patient’s wearable health devices such as heart rate, glucose levels and blood pressure and other diagnostic sources and provide real-time insights to clinicians and care teams.

Healthcare organisations are now looking at how they can support patients to access their own care planning in the community for complex or chronic disease management such as diabetes. This highlights a need for closer integration of primary, community and acute care sectors, as well as digital solutions that can detect and escalate clinical deterioration for safer patient care in virtual or home settings.

Data has the power to save lives, particularly when a healthcare system is under great pressure. However, there are challenges that need to be overcome including interoperability and standardisation where data is stored in multiple formats and various systems, to ensure data can be shared safely and securely.

This will require rigorous integration of data from fragmented sources including patient records, consumer apps and wearables and diagnostic tools, with alignment to reference terminologies. Data will need to be collected on a secure and easily accessible data platform in a coordinated manner, to provide timely and seamless portability of information across the spectrum of care to improve patient outcomes.

The application of artificial intelligence (AI) can also improve the diagnosis, treatment and prevention of diseases by detecting patterns and variations in data and presenting them as meaningful insights to clinicians. However, these AI-approaches are only as good as the data available and AI must be integrated with EHR systems, standardised to a sufficient degree and taught to clinicians for widespread adoption.

Kaye Hocking is General Manager of Marketing and Sales Support at Alcidion