Transcript: James’s blog post (text-only version)
From Chatbots to VR: How Health Technologies are Advancing Sustainable Healthcare
I’ve recently taken on a role helping to organise and run a community festival in my hometown, Salty Creek. The festival’s focuses are sustainability, local talent, and the future of our town. As readers of this blog will know, ‘the future’ is my favourite thing to write about, especially when it comes to new developments in health tech. The festival role has given me a chance to think about the ways health technology innovation is supporting global sustainability efforts.
Sustainability in health isn’t just about clean air, safe drinking water, and responsible disposal of waste, though all these things are vital to human health and healthy societies. Sustainability in health is also about ensuring that expertise is shared globally, research and services are resourced, patients can afford quality care, and medical professionals are given what they need to do their job well.
The United Nations Sustainable Development Goal 3 (SDG 3) aims to ensure healthy lives and promote wellbeing for all ages. It seeks to end preventable deaths, fight diseases, promote mental health, reduce road deaths and those caused by pollution, prevent and treat substance abuse, and strengthen the capacity of all countries to provide affordable and safe access to quality healthcare, family planning and education, medicines, and vaccines.
Read the targets and methods of SDG 3
3.1: Reduce global maternal mortality (deaths due to pregnancy-related causes)
3.2: End all preventable deaths under 5 years of age
3.3: Fight communicable diseases (such as HIV, tuberculosis, and malaria)
3.4: Reduce mortality from non-communicable diseases (such as heart disease, diabetes, and cancer) and promote mental health and wellbeing
3.5: Strengthen the prevention and treatment of substance abuse (such as narcotic drugs and alcohol)
3.6: Reduce the global number of injuries and deaths caused by traffic accidents
3.7: Ensure universal access to sexual and reproductive care, family planning and education
3.8: Achieve universal health coverage (affordable access to quality medical care for all)
3.9: Reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contamination
- Strengthen the implementation of the World Health Organization Framework Convention on Tobacco Control in all countries
- Support the research and development of vaccines and medicines for the communicable and non-communicable diseases that primarily affect developing countries, provide access to affordable essential medicines and vaccines
- Substantially increase health financing and the recruitment, development, training and retention of the health workforce, especially in least developed countries
- Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risks
SDG Tracker (2023) Good health and well-being, SDG-Tracker website, accessed 20 February 2023. https://sdg-tracker.org/good-health.
Joint SDG Fund (2023) Goal 3: Good health and well-being, Joint SDG Fund website, accessed 20 February 2023. https://jointsdgfund.org/sustainable-development-goals/goal-3-good-health-and-well-being.
The global pandemic showed us that healthcare systems in both developing and developed countries can be pushed to breaking point by unexpected circumstances. Many systems have been shown to be unsustainable, meaning that they are not able to continue functioning properly under pressure. Many hospitals are understaffed because there aren’t enough qualified specialists, and existing employees spend a lot of time doing paperwork, all of which places a large burden on the system. These issues limit the quality of treatment options and attention patients receive.
Health tech can make healthcare more sustainable by supporting these systems and removing the burden on medical practitioners and hospitals. There are so many fascinating ways health technologies are contributing to SDG 3 and plenty of opportunities for greater improvement and innovation. Like with many new technologies, there are ethical issues to consider when it comes to health tech, and we must remember that things like AI aren’t a fix-all. That said, this post is about the ideal ways tech innovations can help make healthcare sustainable.
AI research and diagnostic tools
AI-based tools are computer programs that use artificial intelligence to analyse images, videos, sound recordings, and other health data to detect and predict medical issues. The part that excites me the most about AI in healthcare is the great strides that are being made and will be made in health research.
AI can scan data at a much faster rate than we can. It can be used to review large amounts of data to identify new relationships and patterns, speeding up the process of medical discovery. It can also be used to generate detailed models of diseases and drug interactions to help develop more precise treatments. Research programs in these areas can help make discoveries to fight communicable and non-communicable diseases and increase the global quality of healthcare services.
AI can also help ease the burden on medical professionals and bridge the skills gap in places where there are shortages of training opportunities and specialised medical practitioners. It can also be used to help diagnose patients quickly and accurately, as well as offer guidance and quality control.
- Powerful machines and AI programs can analyse scans 150 times faster than radiologists and can work 24 hours a day.
- AI can be an excellent support tool in the diagnosis of melanoma, especially in areas without specialists, and smartphone applications will soon be able to accurately diagnose a photo of a skin lesion.
- AI can be utilised to help screen patients for eye conditions in areas with a critical shortage of health practitioners and facilities. Check out the case study below to learn more. You might be interested to know that I actually used an AI program to help me draft and format it!
CASE STUDY: Using AI to reduce blindness in Zambia
Diabetic retinopathy (a condition that affects the eyes of people who have diabetes) is a major cause of blindness in many developing countries. This includes Zambia, where the shortage of ophthalmologists and eye care professionals has made it difficult to provide adequate screening and treatment for patients with the condition. Artificial intelligence (AI) technology offers a potential solution and a way to work towards sustainability in healthcare.
The program was implemented in partnership with a local health clinic in Zambia and an AI technology provider. The AI algorithm was trained using a diverse set of retinal scans. The algorithm was then integrated into the clinic’s existing screening process, with patients’ retinal images being captured using a portable camera (often by non-medically trained technicians) and passed through the AI system for analysis and diagnosis.
The AI-based screening program was effective in detecting diabetic retinopathy and other eye health issues. Compared to traditional screening methods, the program was able to screen a larger number of patients in a shorter amount of time and at a lower cost. Patients with cases of diabetic retinopathy were referred to an ophthalmologist.
The implementation of the AI-based screening program shows the potential for several positive impacts on the sustainability of the local healthcare system. By reducing the workload of ophthalmologists and eye care professionals, the program helped to address the shortage of these professionals in the community. Additionally, the program contributed to reducing the environmental impact of the healthcare system by minimizing the number of in-person visits required for screening and follow-up. The program also had a positive impact on the health and wellbeing of the local population by improving access to eye care.
The use of AI technology in healthcare offers a promising solution to many of the sustainability challenges faced by healthcare systems in developing countries. This case study demonstrates the potential of AI-based screening programs to improve access to eye care for patients with diabetic retinopathy, while also addressing the shortage of eye care professionals. With further development and implementation of programs like these, it is possible to achieve a more sustainable and equitable healthcare system for all.
Summarised and formatted by OpenAI’s ChatGPT, personal communication, 27 February 2023.
Bellemo, V., Lim, Z. W., Lim, G., Nguyen, Q. D., Xie, Y., Yip, M. Y. T., et al. (2019) ‘Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study’, The Lancet Digital Health, 1(4), doi:10.1016/S2589-7500(19)30004.
Virtual Reality devices can be used to create immersive learning environments and simulate medical procedures, allowing doctors to practice before performing the actual procedure. VR programs can also be created to train medical professionals in areas where there may be a skill shortage. Of course, this technology has limitations, as it requires good internet infrastructure, meaning developing areas may not be able to use it.
VR is also a promising tool for treating addiction. It can be used to simulate real-life situations that may trigger cravings or other addictive behaviours. This allows the user to practice coping strategies in a safe environment. Putting on a headset and being immersed in different environments can act as therapeutic support for hospitalised patients, and those suffering from mental health issues such as anxiety, depression, and phobias, as well as drug and alcohol addiction.
A chatbot is a computer program that uses AI to simulate conversations with humans through text, audio, or video. You might have seen basic versions pop up in the corner of websites asking if they can help you. They’re getting more sophisticated and knowledgeable by the day.
Chatbots can help support patients while also making medical professionals’ workloads more sustainable. They are now being used to respond to patients’ queries and give basic health advice, reducing the workload of medical staff in hospitals. There are also chatbots that can help users with depression and anxiety by giving them a safe space to talk through topics. This is extremely useful where there might be a lack of affordable mental health care and/or in-person therapists. Chatbots can also resolve language barriers, and provide 24/7 support.
Wearable devices are tech gadgets designed to be worn on the body. They capture and monitor data, such as fitness and health information.Some well-known examples include smartwatches and fitness trackers. They can help track patients’ health conditions and collect health data that can be used with a personalised treatment plan. These devices can also give users reminders to take medication or make an appointment, and users can choose to have information sent to their care providers. Devices like these can empower people to take charge of their own health before illnesses develop, tackling non-communicable diseases and easing the strain on healthcare providers.
People using tech and taking charge of their health leads to better public health and more early detection and treatment of illnesses, which leads to fewer people having long-term treatment in hospitals. This means less pressure on medical professionals and hospitals, which in turn leads to better care for the patients in hospitals. The ultimate outcome is a more sustainable healthcare system.
DID YOU KNOW?
People aged 80 years and over are part of the fastest-growing age group. The number of people in this demographic is projected to triple between 2018 and 2050, reaching 426 million.
Sustainable healthcare systems will only become more important with the aging of the global population. Reducing the number of elderly patients who require expensive long-term hospital treatment is crucial. Wearable devices, VR, and AI make patients more aware of their health and how to maintain their wellbeing. These improvements mean in the future, more patients can find answers to their questions and receive support without going to the hospital. They can also be treated at home, which will reduce medical wait times, prevent the spread of hospital-acquired diseases, and therefore reduce the burden on hospitals.
Population Division of the United Nations (UN) Department of Economic and Social Affairs (2019) World Population Prospects 2019: Highlights, UN website, accessed 15 February 2023. https://population.un.org/wpp/Publications/Files/WPP2019_10KeyFindings.pdf
Health tech is an evolving field and a thrilling frontier – and I’ve only included a few examples in this post (next time I’ll delve into AR, robotics, and 3D printing as well). I hope you find these innovations as exciting as I do and can see the many ways they can contribute to global healthcare and sustainability. They offer more sophisticated remote care and training and give medical professionals more time to focus on quality health care. They make it easier to sift through information, find answers faster, and give accurate diagnoses.
I think it’s vital for healthcare specialists to keep up to date with new developments in the sector, and we should also be building our knowledge of sustainability. The need to protect our planet and patients through sustainable innovation won’t be going away, and an understanding of the SDGs can give us a more complete view of the many ways sustainability, health, and technology are interconnected.
United Nations (2015) Goal 3: Good Health and Well-being [graphic], United Nations SDGs website, accessed 30 January 2023. https://www.un.org/sustainabledevelopment/news/communications-material/
The Economist (2019) ‘Is this the future of health?’ (video), The Economist, YouTube, accessed 15 February 2023. https://www.youtube.com/watch?v=jZg5QhL3Ckc
Sweeney, C., Potts, C., Ennis, E., et al. (2021). ‘Can Chatbots Help Support a Person’s Mental Health? Perceptions and Views from Mental Healthcare Professionals and Experts’, ACM Transactions on Computational Healthcare, 2(3):1-15, doi:10.1145/3453175.
Mar, V.J. and Soyer, H.P. (2018) ‘Artificial intelligence for melanoma diagnosis: how can we deliver on the promise?’, Annals of Oncology, Elsevier, doi:10.1093/annonc/mdy193.