The new perspective on public health data

AI🤖 Dec 21, 2020

As the year is folding up, we have seen an increasing demand for AI in the health sector. From detecting Covid-19 symptoms from a simple cough to help accelerate the search for a vaccine, AI is becoming indispensable in some cases. And the need for data on which to apply different models is critical.
The importance of health data is seen with different eyes due to this crisis.
We re-define the meaning of privacy, besides our freedom, but our right to the path of better services.
But this raises a few questions.

Tables of contents:
🧡 🔓 Public health data
💰 🔓 Private + public data
🔓 ✅ Benefits of public health data
🔓 ⚠️ Risks of public health data
📝 🧠 Conclusions

The following article's idea did start with the reading of a journal article on sage about an analysis of public data benefits and risks. // de sters?

🧡 🔓 Public health data

The need for data & the amount of data stored in the last years exploded. This happened because it is so useful to predict, test, understand, and so on. It is also the foundation of all the AI practices the world is so crazy about.

People have a few perspectives regarding technology & the implication of AI practices, and typically they range between a variety of utopias and dystopias. What will AI mean for productivity and living standards? Will it lead to a society of abundance with more leisure time than ever before for the majority? Will we be all controlled by corporations through 5G? How about the distribution of income and wealth, the implications for democracy, and so on?

European Commission describes data as 'the lifeblood of the global economy.'

But besides the economic implications, what would be the health data's benefits & risks to go public? Or from the utopian/dystopian point of view on how to improve or control our lives.  Healthcare is a critical industry that contributes substantially to global data growth (Business Wire, 2018). It has seen the entry of major digital technology companies in recent years seeking to pair health data with their abilities in data analytics.

The best and latest example is the Fitbit acquisition by Google that concerns many entities. Fitbit users give their devices access to sensitive personal health & behavioral details, sleeping data, when & how they work out, and a more exciting type of data like menstrual cycles & alcohol consumption. Also, some users benefited from their wellness program made for companies in exchange for better life insurance. (based on their health data)

The data UK carries through the national health service has a market value estimated at several billion pounds.

💰 🔓 Private + public data

Imagine access to a public data set would enable companies to develop products that may be applied in healthcare markets worldwide. Big medical data is a big treasure for the health system that can provide valuable scientific research information. Researchers can test their ideas and hypothesis using this data and advance discoveries of vaccines and treatments at an impressive speed.
Digital health has witnessed keen commercial interest in recent years with new venture capital investments of billions annually.

Economic activities extend from consumer wearable devices, such as Fitbit, to use AI to develop new pharmaceuticals, to collaborative ventures among big digital tech companies and public health providers.

In essence, it's the same logic as in our digital economy: acquire vast amounts of data and apply analytics to it.

Medicine discovery is an expensive process, on average new drug discovery takes 10 years with 1 billion dollars.
AI is already successfully applied in drug development stages: literature search, identify target molecules, discover effective drugs, speed up clinical trials, and find biomarkers for diagnostics.
AI can be applied in drug development as shown in the below figure, such as target discovery, compound synthesis, screening, crystal structure prediction, toxicity test, patient recruitment, clinical trial design, etc.

China a great illustration of the application of AI methods in healthcare

In the country, where we don't know everything they do about it seems they are pretty advanced with health data and AI application on it, integrating their data in the public medical sector.
In China, the growing aging population and the uneven distribution of medical resources open significant needs for AI in healthcare. Simultaneously, the large population number and the size of the application market provide a reasonable basis for developing AI technologies.

AI plays an essential role in medical services, including clinical assistive decisions, disease prediction, medical assistance, personalized treatment, etc.

Unlike many other developed countries, where family doctors serve as the gateway to specialist hospitals, China doesn't have a hierarchical medical system, which means the patients can visit any hospital at any time they want. The flow of seeing a doctor in a hospital in China is illustrated below. AI can target each step to provide solutions to improve the quality of healthcare service. The administration department also relies on AI to innovate the development of the Chinese medical industry.

The big companies may be interested in health data for 2 reasons:

  • To secure a strategic infrastructure position
  • Potential for product development through the data collected. New products can't be developed immediately for the largest tech companies entering the health sector but are part of a long-term strategy to expand access to data and potentially secure exclusive access to some opportunities

For example, Apple may claim openly that they make no money directly from their freely available ResearchKit tool, 'which provides a platform on Apple's iPhones and watches for medical studies to be conducted' by placing this tool in the public domain. This ensures high-quality research and health-related data is channeling through Apple's proprietary devices and platform.
They are beholding a key strategic position and asset. Another example is Microsoft, which collaborates with Novartis pharmaceutical company to apply AI to all business areas, manufacturing to finance. In late 2019, Google announced a deal with Ascension, which runs 2.600 hospitals in the US, to use Google cloud data storage and it's G Suite business applications, Google can access all Ascension's patient data if they want.

A solution for not offering control over the big private companies may seem to develop digital health divisions that are part of the National Health Systems, Canada & UK are already following this trend. This way, data may be secure from "commercialization."

🔓 ✅ Benefits of public health data

The collection of data, personal data, is the core of today's digital economy's operations. Consumers engage in a rational, kind off, cost-benefit/trade-off when they give up their data in exchange for benefits such as discounts and online services ' personalization, and so on'. Regard the previous 'kind off,' it's not always a rational decision, sometimes you are forced or tricked into it. This may increase friction in the future when a good cost-benefit/trade-off is presenting itself. Perfect ported in the song Kelis - Trick Me, actually could be a perfect song to resume today's relationship between tech giants and consumers.

Unlike other types of big data around us, health data is acknowledged as having the potential to benefit wider society if researchers can share, link, and reuse them in data analytics. The WHO's chief scientist has claimed that health data itself is a public good. All of this data can be applied to the following use cases:

AI-assisted diagnostic

  • Includes medical imaging, electronic medical records, medical service robots, virtual assistant
  • A virtual assistant can provide real-time support to doctors, triage, filtering patients. For example, patients need to know the necessary information about the disease when they go offline for consultation, and these highly overlapping contents take up a lot of doctors’ time. AI technology can help doctors respond to inquiries based on a large amount of historical information, saving time and energy.

AI drug development

  • As I already mention, medicine discovery is an expensive and lengthy process that can benefit from the use of AI.
  • AI can be applied in drug development as shown in the below figure, such as target discovery, compound synthesis, screening, crystal structure prediction, toxicity test, patient recruitment, clinical trial design, etc.

AI health management

  • AI health management is a way to change from passive disease treatment into proactive self-monitoring, and the main products are wearable devices. Yeah, exactly the previous Fitbit example

AI diseases prediction

  • AI technology in disease prediction is mainly used for gene sequencing to forecast disease occurrence

🔓 ⚠️ Risks of public health data

Regarding the risks, could there be public data with no commercial implications? Maybe yes, but as history has shown us, most of the innovation is happening in the private sector. In 2015 the British Medical Association found that patients saw the benefits of giving consent of their health data for analysis, supporting research, and improving care and public health. But patients had 2 significant concerns, the potential use by private companies outside the NHS and privatizations. In Canada, there was a mixed and more negative reaction when there is private sector involvement.

There may be the private sector that is driving the innovation, but companies were never so big and had so much control. Maybe there's a need for more government input alone or with the private sector's help.

In 2016 Ipsos MORI's report presents the premise of public aversion to sharing personal data for research, especially private companies. In its introduction, the report cites a 2014 ONS/ESRC-funded study, which found the public felt a lack of control over their data and a feeling that data reuse was an invasion of privacy. A 2014 study by the Royal Statistical Society found that, in principle, most people feel that sharing of health records with private companies should not happen.
The 2016 Wellcome Trust, Ipsos MORI study highlights that 54% of people supported sharing of health data with commercial organizations for the specific purposes of health research; and that, faced with the prospect of losing out on research that otherwise could not happen, 61% of people will opt for commercial involvement, vis-à-vis these earlier studies by the ONS/ESRC and Royal Statistical Society.
However, within the report, it acknowledges, ‘in principle, people would prefer the NHS to retain all its functions in-house rather than allowing private sector involvement.’
But we can deny that sharing, linking, and reusing public health data is equal to efficiencies in healthcare.

📝 🧠 Conclusions

The new wave of wellbeing products that can track various health data may be a good opportunity for new start-ups or tech giants, with transparency as one of the main traits that could guide them to success.
People may seem more interested and looking to enhance their health through data, either by tracking their fitness life or sleep.
The need for health-enhancing consumer products is already booming, after the covid new norm needs: on fitness, eating, work-life balance, mood tracking, and so on.

This type of data can have application furthermore even to psychology & behavior research.
Cross these types of data with ones from the general public sector and discover valuable findings.
Transparency is the MVP of the game and the cornerstone of a sustainable eco-system built around healthcare data.
As we eventually manage to move beyond the current pandemic, the potential for further economic and social disruption is undoubtedly vast. The health sector may see an increase of attention, either as an individual or part of society as a whole.
After the access to the internet, reducing the bridge between peoples, and people and information, the next big thing has to be an increase in life quality and improvement.

Recommended further readings State of AI 2020, an annual report going in-depth of the latest news and practice in AI and a great in-depth article about Weaponizing Digital Health Intelligence

Illustrations from UnDraw
China AI Healthcare downloadable here


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