The Time is Right
Medical Data Doesn't Have To Be Kept In Silos
Personalized predictive medicine is a possibility right now but, despite technological advancements and increased computing power, medical and clinical research data is kept in silos. This impedes a "personalized" medicine approach to healthcare and discovery.
But it does not have to be this way ...
People - you, me, all of us together - have the power to influence the government and the healthcare industry to open up all their medical data for research in a safe and privacy-mindful way.
If there is a will, there is a way!
Nobody will make this happen for us. This is one of those situations where it's up to us to make things happen, as we all will benefit from it.
Spending On Healthcare Is Unsustainable Across The World
Canada
- Total health expenditure in Canada In 2015 was about $219.1 billion
- Total health expenditure in Canada In 2015 was ~ $219.1 billion
- U.S. spends over $2.6 trillion on healthcare each year; more than any other industrialized nation in the world
- $600 billion of those costs include treatments that either do not help or actually cause harm.
- 75% of healthcare spending in US is for largely preventable chronic illnesses, such as Type 2 diabetes & heart disease
- Despite spending, US citizens are not the healthiest. US ranks 37th in life expectancy and other measures of health
- Spending is set to increase from 6% of GDP to 9% of GDP in 2030, and as much as 14% by 2060.
The Technology Is There
The latest innovations in technology help engineers and scientists capture, analyze and store data at rates faster than ever before.
A number of recently improved algorithms and software tools using super fast computers can derive valuable information from masses of data.
We can now use natural language processing and machine learning (ML) to reveal insights from large amounts of unstructured data.
There are tools available that analyze medical imaging, genomics data and even voice recordings.
Smart sensors and wearable devices add value when their data are analyzed together and pooled with other data sets.
P4 Medicine Is Possible Now
P4 medicine describes a holestic approach to healthcare: predictive, personalized, preventive and participatory.
The premise is that P4 medicine will lead to powerful new diagnostics and therapeutics for treatment and prevention. This will be based on each person’s unique genomic and biologic characteristics (e.g., inherited variation to drug response). This also includes behavioural, social and environmental factors as well as any government healthcare policies that can influence availability and access to expert care.
Ten years ago, the proposition of P4 was regarded as highly speculative. Today, the core elements of the P4 vision are widely accepted by healthcare professionals.
There is even a P4 Medicine institute (P4Mi) in Seattle founded by the scientist that coined the term P4 Medicine, Dr. Leeroy Hood.
Artificial Intelligence To The Rescue
Artificial intelligence (AI) has an unimaginable potential. It is already transforming every industry, including healthcare.
AI can help with better diagnoses by providing information that is both predictive and actionable, either before disease occurs or in its early stages.
How?
AI can help with better diagnoses by providing information that is both predictive and actionable, either before disease occurs or in its early stages.
AI can learn faster - and access information faster - than humans can.
Matched with human insight, there is unlimited potential to discover cures and eliminate disease.
We could have access to more than enough data for meaningful insights
There is a lot of data collected on patients at hospitals, clinics, labs.
There are now thousands of mobile healthcare apps and wearable devices that can track nearly everything, from physical activity to sleep, heart rate, mood and exposure to sunlight.
Many governments now have open data policies releasing public health data, environmental, nutritional and other data.
All this data pooled together provides big data that's essential to power predictive, preventive and personalized health solutions.
Finding the right data for analyses is not a problem anymore. It's the willingness from the organizations that's sitting on it, to share it for research, that's the problem.