Patient autonomy and its impact on the future of healthcare

Technological advances in healthcare mean that we are all living longer. Whilst a greater human lifespan is beneficial for many reasons, in the UK it is placing a significant and potentially unsustainable burden on the NHS. We consider how technological developments in patient-led care over the next 10 years, could be used to alleviate pressure on the NHS and other healthcare providers and how the healthcare sector can prepare for changes to come.   

What could be the most significant change?

At our recent healthcare law conference in Cambridge, we were joined by renowned futurist Professor Peter Cochrane OBE, who sparked thought and discussion around the provision of future healthcare, particularly regarding developments that could positively change the way patients receive healthcare as well as maximising NHS resourcing. 

It is anticipated that advancements in Artificial Intelligence (AI); machine learning and quantum computing will help the medical profession take significant steps forward in treating cancers; neurological impairments; and chronic illnesses as well as in acute medicine and surgery  over the next 10 years. The use of robotic surgery is also likely to become more prevalent, increasing surgical accuracy and instant collective learning and reducing human error. In addition, advancements in 3D printing are potentially transforming the future of transplant surgery.

The most significant change in healthcare however over the next 10 years, could be a greater shift towards patient autonomy and “DIY” patient-care, made possible by developments in patient centric AI technology. This will create improvements as well as challenges to overall patient safety.

How might this change come about?

Given the wealth of knowledge available online, it is easy to envisage how within 10 years patients may have technology within their own homes to enable accurate diagnosis, prognosis and treatment of their health conditions, along with the technological means to administer treatment - all without speaking to a doctor at any time. The building of “diagnosis trees” by medical professionals who utilise shared knowledge on a global scale to provide patients with electronic access to accurate medical diagnosis and advice, is one means being explored to achieve this.

Within 10 years it is anticipated that AI devices or wearable health technology will be utilised by patients to monitor their health 24 hours a day, and for this data to be linked to healthcare providers like the NHS. The idea is that these devices will amass data that will then be analysed by an algorithm, resulting in personalised healthcare mapping for the individual with the receipt of accurate medical alerts and messages personal to them.  

What is the likely impact of such developments?

Using technological advancements to empower patients who are able to take greater responsibility for the management of their own healthcare could free up precious resources for vulnerable patients needing higher levels of assistance, such as the elderly, children, those suffering with mental illness or those with learning difficulties.

In turn, patients would benefit from a more personalised approach to healthcare, where diagnosis and treatment would be better focussed on an individual’s own needs due to clinical mapping of their data, rather than a “one size fits all” – treating the average approach. This may work to treat disease and illness more effectively from the start, due to medication being specially selected for the individual rather than their condition and how it affects the average patient, in turn reducing medication supply costs.

What issues might the changes raise for healthcare providers?

 For greater patient autonomy to work without there being a negative impact on patient safety, it seems likely that patients would first have to be assessed, trained and properly equipped. Effectively the health service would be acting as a safety net here, providing qualifying patients with the equipment/devices and training needed to take care of their own health in all but the most serious of cases, with oversight by the medical profession only as required.

This change could lead to more work for registered nurses at a primary care level, but could ease the pressure on GPs and secondary care establishments by reducing the number of patient visits for assurances, for less serious, easily diagnosable/treatable conditions, and could also free-up hospital beds.

The accuracy of patient data and clinical mapping will be key. Therefore it seems unlikely that the purchase by patients of their own equipment/devices without some element of NHS/Hospital control, would be encouraged. Patients using own equipment/devices to provide data would need to be given clear advice by their treating practitioner of the possibility of inaccurate readings and to seek medical attention should they experience symptoms that may be indicative of a problem.

The use of such technology and equipment raises the issue of where liability would rest for the maintenance and operation of AI devices, as well as for adverse patient outcomes caused by errors in data analysis. Whilst the purchase, supply and maintenance of such devices by the NHS or private healthcare providers would potentially come with some liability for their functionality and use, it is the option most likely to minimise errors in data collection and protect patient care.

Liability for equipment malfunctions could be limited by contracts agreed with manufacturers and suppliers, ensuring liability is not waived upon purchase. It is also possible that disclaimers/contracts could be signed by patients in which they agree to accept responsibility for the day-to-day care of the equipment, to adhere to the equipment service requirements and to accept liability for any action on their part which leads to inaccurate data capture.

In addition it is worth noting that systems used to send, analyse and store patient data from AI devices will need to be secure in order to ensure compliance with patient confidentiality requirements and with data protection laws.

Whilst there would be an initial cost to healthcare providers for the supply of such equipment to patients, it is hoped that the costs would be offset by the resources saved in reducing patient visits, particularly for minor ailments and check-ups. Costs of equipment purchase may also be driven down by increased global demand.

Comment

Future change in the healthcare sector is inevitable and is undoubtedly required to ensure that resources are appropriately targeted and the standard of patient care improves. AI should not be feared but embraced within a protective cover.

Thinking ahead, if there remains a growing shift towards patient-centric care as predicted, healthcare providers may wish to do the following:-

  1. Conduct an assessment of staff resourcing and individual patient need;
  2. Ensure they have adequate insurance cover for AI technology, seeking to limit their contractual liability for the provision/use of services and products incorporating AI technology;
  3. Assess how their data security systems would fare in the event of AI developments in patient data capture and transmission.
  4. Conduct an assessment of patient populations and how best to train patients to care for themselves.