Dominic Cushnan & Kevin Wyke
The modern day is characterised by a constant evolution in the technological industry. Technology has brought about increased efficiency and effectiveness in multiple different fields. The concept of Artificial Intelligence has also evolved extensively with the perception that technology can replace human expertise due to its ability to process huge amounts of data, it’s speed, large storage capacity, ease of access and accuracy. In the field of medicine, most technological developments have been introduced to aid and support longevity of human life as well as assist in the diagnosis of patient conditions. Recent demographic changes mean, demand for healthcare has increased significantly and as a result even getting an appointment with any general practitioner has become quite difficult (Curtis, 2013). However, technology is trying to provide an alternative. Several mobile applications have been created that hope to offer some of the general practitioner’s services. For instance, the creation of MD, which makes use of Artificial Intelligence to mimic a consultation with a general practitioner, has been found quite useful. It works by taking a user’s symptoms and providing a list of what , what the person’s illness might be. The mobile application has brought out an effortless way to make an initial check on an individual’s health without the cost and inconvenience of an appointment with a GP. With the increased demand for healthcare services, automated mobile solutions powered by big data and increasing use of Artificial Intelligence are becoming a more attractive solution than visiting a practitioner.
The MD application has been created from a collection of various knowledge databases pooled into one big system. But databases are fairly static, and this system is dynamic, it has an additional distinct element that is; it learns from every consultation. Every interaction with a user increases its knowledge base and its accuracy (Murgia, 2017). This is the real power that mobile applications have, harnessing the social capital that comes from being on the phones of tens or hundreds of thousands of users, learning and improving with every interaction. MD has around 90+ million users per month to learn from, even the most productive individual GP would struggle to see 1000 patients per month.
There are also interesting developments in the management of chronic and complex conditions with applications that can monitor heart condition atrial fibrillation or diabetes also being developed. This marks an increase in support for the self-management of patients conditions with access to diagnostic information previously the preserve of specialist labs; it is a potential shift in the power relationship between patients and medical practitioners with increased expertise being available to the patient. Applications are enabling patients to monitor their physiological responses with increased accuracy and convenience, Data such as blood pressure, blood oxygen levels can be collected easily and sent to the medical specialists reducing the amount of time that an individual spends at a specialist and also simplifying the practitioner’s work. One benefit of these applications is the vital role they can play in assisting the doctors by handling the simpler queries, providing them more time to concentrate on the more complicated conditions and patients who require more time, more care, more compassion, more of a human.
Applications like Babylon Health are streamlining the whole consultation process, reducing the waiting time to meet a practitioner, by providing their users with an option to hold a phone or video phone consultation with a doctor at short notice (Thomas, 2016). This service is made available seven days a week resulting in a reduction in the demand for a face to face consultation and so a reduction in waiting times.
Miniaturisation of biosensors which allow regular measurement of health-associated physiological signals and responses has also had an impact on what is possible with mobile health apps. The ability to monitor human physiological changes in real time during different activities has moved from a specialist laboratory function to an app found on your smart watch. As a result of this real-time data, right at the user’s fingertips (or wrist), with the ability to record and analyse the data and advise on diagnosis and manage conditions the expertise in managing a condition gets a meteoric shift towards the patient. These devices can monitor an individual’s physiological changes in real time in different environments., Perhaps most importantly, studies show that the combination of the biosensor information with regular medical measurements can recognise early symptoms of conditions as obscure as inflammatory reactions and Lyme disease, and can provide a distinction between physiological differences of insulin-resistant and insulin-sensitive people. Affordable, miniature mobile biosensors provide the user with levels of complex physiological data that were previously the preserve of university laboratories, the data and AI infrastructures behind the apps convert this date into useful information for self-management of anything from lifestyle changes to complex conditions. This is truly democratic, providing the tools to enable disadvantaged communities to access sophisticated diagnostic information and affordable health care tools which may have been denied them by geography or socioeconomic reasons or by privilege of birth in the previous centuries (Li et al., 2017).
These diagnostic devices would have been the stuff of science fiction 10 years ago but there are now a plethora of wrist-based diagnostic tools available to us, Apple, with its aspirational brand and image, continues to lead the use of technology to influence and manage every aspect of our lifestyle And whilst its Apple Watch is far from cheap it is a lot more affordable than a personal EGC technician. Apple has perfected the trick of getting us to willingly participate in physiological experiments and diagnostic investigations that we would have avoided a GP in fear of generations past. The smart watch that knows where you are, how fast you are moving, how many steps you are taking, what your heart rate is, how steep the hill you are climbing that watch exists today.
The watch of tomorrow will do all this and more, it will measure electrical signals and secretions on your skin to capture data about your level of excitement or nervousness (Marks, 2014). It will be able to measure glucose levels, lactic acid thresholds and more.
This points to future applications of mobile-based health applications that can have an influence and impact well beyond the individual to a population level. Already a mobile phone diagnostic tool exists that can instantly detect bacteria and viruses at different geographical locations in the world. This device is created through re-engineering of the existing technology responsible for basic blood glucose monitoring of diabetes. From this technology, a biosensor that can track deadly diseases like influenza, HIV or Zika virus by use of a DNA swab has been designed. All the patients are required to do is to put saliva or blood sample onto a stick-like sensor, then put it in a module which is entered into a mobile phone analysis and diagnosis. This method is more portable and economical than laboratory tests, making it particularly appropriate for infectious diseases in the developing nations. The gear can be used in the monitoring of stress levels and other common illnesses. Therefore, these devices are a proper means of controlling the spread and management of infectious ailments and effective in self-diagnosis.
Combine this with the miniaturisation of physiological monitors, add them to watches, distribute widely and you have a population-based live public health monitoring system, based on mobile phones and watches.
However, despite the growth of technology-based diagnostics and the continued advancement of technology, the use of smartphones has not yet replaced the human General Practitioners. Nevertheless, the potential of artificial intelligence, big data, self-management and the democratisation of health expertise does give hope for a different future where algorithms replace the general practitioners, at least in part.(Mellor, 2016).
The continued advancement in technology has brought about more efficient and effective ways to tranquil operations in various fields. However, in the sector of medicine, this growth has been quite significant. Currently, most mobile applications have been designed to monitor an individual’s wellness as well as their fitness. Other gears have also been created to offer a self-diagnosis hence, saving time and costs of visiting a general practitioner. This technology is reliable given the increase in the number of serious illnesses facing people across the world. Also, there has been a development of a device that can immediately detect any presence of bacteria or viruses at any region. Such an invention can help in the management of the spread of infectious illnesses. Moreover, there are other mobile applications which can monitor physiology and personal activities. However, despite that technology has brought about cost-effective and portable means of diagnosis and health management, the smartphones applications have not been able to replace an individual general practitioner.
The development of more and more sophisticated technological mobile tools that are aimed at helping us to manage our lifestyle and our health has the opportunity to radically change how health care is delivered. The old power relationship between medical expert and patient is being disrupted. Patients now have potential access to some of the most powerful physiological measurement and diagnostic tools on their phone or wrist. This should allow us to build models of healthcare where patients are experts at self-management of their conditions and can access the medical expertise only when that human input is needed. It should also allow clinicians to become the experts in the human bit of health care.
With the demographic led increase in demand for healthcare leading an inevitable capacity crisis, this might not be just the stuff of science fiction; it may be our only hope.
- Curtis, M. (2013). Your phone will know you’re sick before you do. CNN. Retrieved 5 March 2017, from http://edition.cnn.com/2013/02/26/tech/opinion-health-mobile-curtis/
- Li, X., Dunn, J., Salins, D., Zhou, G., Zhou, W., &MiryamSchüssler-Fiorenza Rose, S. et al. (2017). Digital Health: Tracking Physiome and Activity Using Wearable Biosensors Reveals Useful Health-Related Information.
- Marks, P. (2014). Apple’s smart watch could have us all self-monitoring. New Scientist. Retrieved 5 March 2017, from https://www.newscientist.com/article/mg22329874-500-apples-smart-watch-could-have-us-all-self-monitoring/
- Mellor, L. (2016). Mobile phone diagnostic tool to immediately detect viruses. ABC News. Retrieved 5 March 2017, from http://www.abc.net.au/news/2016-08-23/mobile-phone-diagnostic-tool-to-immediately-detect-viruses/7778590
- Murgia, M. (2017). How smartphones are transforming healthcare. Ft.com. Retrieved 5 March 2017, from https://www.ft.com/content/1efb95ba-d852-11e6-944b-e7eb37a6aa8e
- Thomas, K. (2016). Will mobile health apps make GPs redundant? The Guardian. Retrieved 5 March 2017, from https://www.theguardian.com/sustainable-business/2016/apr/16/mobile-health-apps-gps-nhs-doctors