The spread of wearable digital technologies in healthcare generating big data entailed the appearance of a new type of medical information. They produce actionable insights into the biological state of individuals, just as "general" biomarkers, but are collected through digital tools. Here's my summary of what digital biomarkers mean and how they will be used in the near future. In the last couple of years, Fitbit, Misfit, Jawbone, Apple Health, Sleep as Android, WIWE, MocaCare, Skeeper – in other words, fitness trackers, step counters, health apps, sleep sensors, pocket ECG, blood pressure or other health parameter measuring devices appeared out of nowhere. By now, they constitute significant players on the health, wellness and fitness market; generating an astounding amount of data about patients and individuals not getting patient care.
As the wearable technology ecosystem advances, we are headed towards a future where we will be able to choose whether to have a device in our hand or an implant in our brain. It is a destiny recognised for its possibilities by various industries who continue to observe the importance of investment in this space. With rapid change taking place, we are seeing quite a lot of changes in the medical, wellness, and fitness markets, where the exploration of wearable devices, applications, and services is taking us in the direction where we will be able to take control of our health so we can become a better version of ourselves. The report recognised an increase in demand for improving supply factors that include developments in electronics miniaturisation and innovation. Confirming the fact that we are headed towards a tomorrow where we will be able to turn to wearable healthcare devices to enhance our functionality.
First and foremost is the value challenge that all countries across the globe are facing – there is escalating demand from long-term, chronic disease, rising costs, often with an ageing population and limited resources. Yet we are continuing to invest in facilities and equipment that were built to solve a completely different set needs. A hospital-centric system deals well with serious health episodes that require days or weeks of acute care for very ill people. But it was never intended to deal with large numbers of people whose conditions are chronic, complex and require treatment for the longer term. The past decade has seen an explosion in the amount of health data that is now available to us.
We are a country of a billion people. However, at one doctor for 1,681 patients, we have one of the lowest doctor-to-patient ratios in the world. In rural areas, the numbers are even more skewed. In the US and Japan, this ratio is around 1:400. One way to improve this ratio is, of course, to produce more doctors.
Artificial Intelligence (AI) and Machine Learning (ML) have already started making inroads into various industries. Healthcare is emerging as one of the biggest beneficiaries of the AI revolution. The technology is capable of facilitating easy and secure access to patient medical data, understanding and analysing their conditions. This ultimately helps improve accuracy and efficiency in the diagnosis and modernisation of health care practices. An example of an elementary implementation of AI is the use of chatbots and virtual assistants that can take care of basic yet tedious tasks like registering medical records, clinical workflows and monitoring lab results – all in an automated and secure process.