Digital medicine

Graphical Abstract

Leila is an 86-year-old woman with type 2 diabetes and high blood pressure. She lives alone, and, as a result of a recent heart attack, her family doctor and cardiologist want to see her more frequently. She has some moderate arthritis involving her knees and hips and poor vision, but she is committed to maintaining her independence.

Leila represents a typical older patient in many countries. How to care for an ageing population, which is anticipated to double worldwide by 2050, is a question facing individuals, families, health-care systems, and nations. Older patients with multimorbidity, age-associated limitations in mobility, vision, memory, and hearing, plus, all too frequently, social isolation, loneliness, and depression have complex health needs. There are additional difficulties for older people who live on fixed, limited incomes and in low-resource areas. The challenges Leila faces highlight the global need for user-friendly alternatives to hospital and institutionalised care that can support health management and autonomy of living alone for as long as possible.

There is promise for digital health technologies to improve communication, collaboration, and the use of evidence-based guidelines to circumvent barriers to healthy, independent ageing. Today, age remains one of the greatest obstacles to technology adoption. Visual impairment and limitations in dexterity contribute to this, but another hurdle for many older adults is a lack of confidence in using digital health technologies. Intuitive voice-user interfaces on smartphones can help overcome these usability fears. Built around various consumer voice-recognition technologies, developers are creating voice-based applications for management of chronic conditions, care coordination, medication adherence, and even companionship. Beyond aiding in management, early research shows that voice interfaces could have the potential to serve a diagnostic role by recognising vocal biomarkers of change in neurological or mental health status.

Extending and enhancing the ability to monitor and provide prompt help and support for the independent older adult is another capability digital health technologies bring. Widely available consumer devices, such as wearable sensors or patches, smartphones, and watches, can already passively track and alert the wearer of potentially significant arrhythmias. Some can also detect hard falls and automatically connect to emergency services if needed. Unobtrusive activity recognition systems using infrared motion sensors (ie, pyroelectric sensors) and ambient devices with multiple sensors (eg, motion, pressure, video, object contact, and sound sensors), supported by deep learning, could detect a range of routine activities of daily living in real time. This would allow for individualised modelling of daily activities and immediate detection of unusual behaviours.

Social isolation and loneliness are public health issues that have adverse effects on elder health. While existing technologies can provide access to social media, entertainment, education, and counselling for willing users, newer technologies such as socially assistive robots (SAR) could help with physical tasks and provide a partner for social interaction. Early studies of SARs for elder care have found that they might improve cognitive function, companionship, lower blood pressure, and provide an improved overall sense of wellbeing. Although many of the SARs studied so far have been designed as pets, humanoid autonomous robots that are capable of performing tasks similar to human caregivers are also being developed for elder care.

However, if these technologies are poorly integrated into systems of health and social care, technology itself could contribute to even greater isolation for older adults, creating more harm than good. To avoid this hazard, designers must understand the complexity of ageing and incorporate knowledge of age-related changes throughout the design process. Participatory design approaches that include older adults are essential. Design should also focus on how to improve the quality of care and outcomes. Additionally, a rigorous prospective clinical trial assessment will be needed for all these technologies. Only then will digital health technologies help meet the needs of older people.