Social Impact

• Delayed cancer diagnoses alone cost the NHS £150m annually.
• The economic burden of cancer arising out of monetary loss associated with time spent receiving medical care, time lost from work or other usual activities (morbidity costs), low productivity due to premature death (mortality costs), and expenses incurred by caregiver and family (social costs) is often unaccounted. The untold social and emotional impact of cancer can haunt the patient and family members years following treatment. While a lot of effort goes into the calculation of the direct cost of cancer treatment, the indirect loss due to the psychosocial issues surrounding cancer often remains elusive.
• As per the Swedish Institute of Health Economics, findings show the direct cost of cancer to the UK and Europe are 8 billion euro and 88 billion euro, respectively, while the indirect loss amounts to 9 trillion euros and 64 trillion euros respectively annually. Diagnosing cancer in late stages and the inability to provide treatment condemns many people to unnecessary suffering and early death. By taking steps to implement and improve early diagnosis of cancer ensures prompt treatment, especially for breast, cervical, and colorectal cancers. This will result in not only more people surviving cancer, but the treatment will also be less expensive to treat. In other words, an early cancer diagnosis can significantly reduce cancer’s financial and social impact.

Low & medium socio-economic countries
While there are an estimated 8.8 million deaths from cancer every year, 70% of the deaths occur in developing countries who are the most ill-equipped to cope with the cancer burden and provide uniform access to high-quality healthcare. The starkest area of inequalities can be observed in childhood cancers with survival over 80% in high-income countries while as low as 20% in low-income countries.
High socio-economic countries
The disparities in cancer survival are also found in high and middle-income countries, especially in the deprived population such as indigenous, immigrant, refugee, rural, and lower socio-economic groups.
OECD countries’ cancer data shows a vast inter-country difference in the average wait time for cancer treatment with cancer mortality varying more than 2-fold across the nations.

The companies that focus on post-diagnostic or therapeutic support (for example, new drug discovery, a new way of radiation therapy, genomics, proteomics solutions, clinical trial matching, post-diagnosis cancer decision support system etc.) contribute only 5% to the early and timely cancer diagnosis and treatment as these solutions come into pictures only after diagnosis is made. Besides, life gained after such expensive treatments are often limited if the cancer diagnosis is in later stages. In contrast, diagnostic cancer companies can add to 95% of the value to the early cancer diagnosis proposition, given that they act before the diagnosis is made. With their preventive roles, they can reduce the cancer incidences.

AI Healthcare market is full of low technology patient-facing symptom checkers which offer an average diagnostic accuracy around 33%, e.g. Babylon, Ada, Isabel symptom checker, Symptom Checker from WebMD, Your.MD – Health Guide and Self-Care Checker, Bouy Symptom Checker, Aetion, Sensely, mediktor, infermedica symptomate, Mediktor. Lack of accuracy and accountability leaves the patient with a list of probable diagnoses which he or she has to take at his or her own risk. With the lack of a cancer focus and risk-averse approach, they don’t offer much help in terms of early detection of cancer.

On the other hand, radiology artificial intelligence, which has drawn media headlines since the last couple of years and is only focused on diagnosing early cancer should the patient undergo radiological imaging such as a mammogram. This AI is useful only when the patient undergoes a radiological screening test or presents to the hospital with symptoms. A population benefit will arise only when we put the entire population under X-ray machines at a frequent interval (which is not plausible).

The high impact can only be achieved by providing low-cost technologies that can overcome the barriers created by socio-economic status, geography, social, educational, and biological factors. After analysing all types of technologies and options for early diagnosis, we have concluded that big data-driven diagnostic solutions can revolutionise the diagnosis of cancer and bring a paradigm shift to the way we diagnose and treat diseases, especially cancers.

• Both diagnostic and preventive effects – The data-driven diagnostic approach can not only lead to early diagnosis but can also implement the preventive lifestyle changes necessary to reduce the incidence of cancer in the community
• Population empowerment – Early cancer diagnosis can reduce the social and psychological effects of cancer on the population and empower individuals, countries, and government
• Reduce global disparities in cancer care – Widespread implementation of this technology can help to bring global equality in cancer management, standardise the approach to diagnosis and treatments
• Self-sustainability in healthcare models – Early diagnosis of cancer can not only reduce the economic burden on the nation as a whole but also bring financial sustainability to the healthcare systems