Reading Time: 4 minutes
Our choices, whether taking a path to walk home or finding a life partner, have always been based on data in the guise of experience. However, the depths of data collected and its longitudinal impact on decision making has improved dramatically in recent years. We are now collecting more data than ever before and mining those data to make sense of the “known unknown”around us.
So, it is data, if not making the world go around, lubricating the wheels to avoid the creaking noise.
Doctors turning into engineers
Improving the performance of the human body remains the holy grail of medical science. How to upgrade our body to an anti-aging, disease-resistant, self-healing machine. The role of doctors was/is to treat illness and bring our body back to a healthy equilibrium state.
However, with billions of structured data at our disposal and development of technologies like CRISPR and biome, the race is on to upgrade the human body to the next version. Like an engineer who is not only happy to fix a broken camera but strives to find a better way to take photos, it is no longer about just healing the ill, but introducing a next iteration of the human body.
Making data talk
But the challenge is not just about capturing data. It is how to make it talk. The nature of interdependency makes health data unusually complex.To add to the complexity, this dependency changes over time by conditions beyond the human body, such as the environment we grew up in.
For example, we are now finding that the human gut is intricately connected with brain. And this gets impacted by genomics which in turn gets impacted by the environment. So, collecting all these data points and making those data to talk sense is a difficult pursuit, to put it mildly.
Connecting the dots
But there is hope. Moore’s law has transformed the world we live in by doubling the processing power of chips every two years for the last few decades. We are now observing the same analogous exponential technology at work in genome sequencing. We have computers which can analyze billions of data points derived from genome sequencing of millions of people, enabling breakthroughs in medicine not imagined before.
We are using big data to predict the spread of communicable diseases, improving diagnostics by AI and helping machines read pathology reports more accurately than humans. We are using data to train robots to perform surgeries and connect public health records across hospitals to improve allocation of resources, from developing precision medicine to drug discovery.
How are we using data
Tonic is a digital health company which uses data at the core of its operations. We believe prudential use of data generated by millions of members will be what separate us from other companies in the space. We are already using data for improved consultation by our doctors and will soon explore options for an AI based consultation as part of triage by our doctors. We are using data for improved customer experience in health financing and automating the whole process from end to end.
Developing a health service handling personal data always requires attention and care to privacy and information security. At the same time, providing personalised follow-up and being able to access records is a prerequisite to provide efficient and reliable care to patients.
Tonic balances these two prerequisites by making patients’ health data – including historical records and detailed information about exisiting conditions, diagnoses, family situation – available instantly, as doctors handle an incoming call. This enables different doctors to get right down to providing medical advice. However, health records are only available to Tonic doctors, only when patients are calling in, and health records cannot be edited retrospectively. All clinical data are stored on a remote physical server, and back-ups are done separately every day.
Ultimately, we believe, access to quality healthcare should not be limited to a specific geography or people from a certain part of the society. It is a basic right and health justice can only be achieved by digitization of the industry on the foundation of data.