iwatching your health

AUSTRALIA faces a growing burden of chronic diseases, with over $38 billion spent annually on care for conditions like cardiovascular disease, type 2 diabetes, and cancer.

However, the majority of healthcare investment is focused on acute care, while only a small fraction goes towards disease prevention.

This approach is unsustainable, especially considering the strain on healthcare services due to the COVID-19 pandemic and an aging population.

To address this challenge, a predictprevent model of healthcare is needed, leveraging digital health innovations and real-world data.

Smartwatches have gained popularity in Australia, with one in three people owning one.

While they are marketed as lifestyle choices providing real-time health information, their accuracy varies, and they have not been approved for medical use.

Nevertheless, there is growing evidence that patient-generated real-world health data, including smartwatch data, can enhance patients’ understanding of their health and improve trust with care providers.

Smartwatches have the potential to complement the predict-prevent model of healthcare by tracking health metrics and facilitating early detection of deteriorations related to chronic conditions.

They can also provide personalised care and lifestyle recommendations based on user data.

However, challenges such as data accuracy, interoperability, data familiarity, equity, and accessibility need to be addressed before smartwatches can be integrated into existing models of chronic disease prevention.

A roadmap for integrating smartwatches into digitally enabled precision prevention models of care is proposed, focusing on data accuracy, interoperability, data familiarity, equity, and accessibility. Challenges include the variance in data accuracy, proprietary algorithms, lack of clinician training, data ownership and accessibility issues, and the digital divide between socioeconomic groups.

To overcome these challenges, research, digital health investment, and policy changes are necessary.