The rise of technological medical treatmentPosted on: September 15, 2023
by Ben Nancholas
Global health systems are under increasing pressure – from budget cuts to widespread public health crises and insufficient staffing levels. As such, many healthcare providers are searching for increasingly innovative ways of offering and managing treatment and care – and observing highly positive results.
While medical technology has been steadily developing over the centuries, a specific step-change has recently occurred – one that has been gaining in sophistication and momentum for some time: digital healthcare technology. The widespread adoption and roll-out of both existing and new technologies we’re now witnessing have further revolutionised how we manage the scale, challenge and diversity of public health.
The NHS Long Term Plan states the importance of technology in its future, flagging the critical priority of supporting digital transformation to improve patient health and wellbeing.
What types of technology are used in medicine and healthcare?
Technological advancements are transforming modern healthcare environments. Alongside more traditional information technology systems, artificial intelligence (AI), machine learning (ML), virtual reality (VR), blockchain and big data analytics are overhauling the range, scope and accessibility of treatment options.
The benefits of information technology in healthcare settings are profound. They include:
- improving patient care and patient experience
- real-time information exchange
- greater flexibility for patients and clinicians.
Common examples and use cases include:
- e-prescribing. Prescribers can send electronic prescriptions to pharmacies – of a patient’s choosing – making the prescribing-dispensing process quicker and more convenient. Patients can also request repeat prescriptions via e-prescribing software.
- electronic medical records (EMRs). EMRs contain a patient’s medical treatment history in digital form. Digitising this data helps clinicians to track data over time, identify those who require check-ups or preventative screenings, assess patients by specific parameters – such as vaccination status, interventions or health markers – and monitor and enhance overall care within a clinic or practice.
- electronic health records (EHRs). EHRs build on the data of EMRs and enable the wider reach and collaboration between other health services, clinics and providers. This sharing of critical health information supports an interconnected, multidisciplinary approach to a patient’s care.
- mobile health apps. Made possible by the prevalence and number of smartphones and mobile devices, health-related mobile apps are an easy, cheap way to connect the public with a huge variety of health services. Text messaging, for example, is a simple way to remind patients to attend appointments and spread awareness of clinical trials.
- personalised medicine. Utilising AI and ML technologies, medicines and treatment plans can now be individually tailored to patients, providing customised care that takes into account medical histories, calculations of future implications, genetic data and disease behaviour. The possibilities of personalised medicine are vast, with everything from personalised pacemakers to computerised hearts now available.
- wearable medical devices. Data-driven ML enables huge swathes of the population to monitor and manage their health autonomously, through the use of wearable tech that connects to mobile devices and other equipment. Common examples include continuous glucose monitors (CGMs), implantable cardioverter defibrillators (ICD), and pulse oximeters. In addition to supporting patients to manage their health conditions day-to-day, many devices are also linked with clinics so health workers can monitor patient progress.
- telehealth. Tele-based methods are used widely to support a number of clinics and services, such as remote GP consultations. They have proved particularly beneficial in the mental health services sphere, supporting remote psychiatry and psychotherapy consultations and follow-ups, cognitive behavioural therapy (CBT) sessions and other integrated mental health treatments to help patients with a variety of mental health conditions who face barriers to in-person therapy.
Digital health technologies have numerous applications within medical contexts, from the VR environments that enable trainee surgeons and specialists to practise procedures to big data analytics that pinpoints demographics and geographical populations who may require certain types of healthcare support. These applications and initiatives will only continue to advance: the digital health sector is rapidly growing, and expected to be worth $6.2 trillion this year alone.
The role of telemedicine and telehealth
One particular innovation was thrown into specific focus during the COVID-19 pandemic: telemedicine. Against a backdrop of spiralling waiting lists, enforced social distancing and chronic cancellations, the pressure to provide ongoing, high-quality healthcare services was extreme – and a fresh approach was required.
Telemedicine (also known as telehealth) is a branch of e-health that refers to the provision of remote clinical services and consultations. It enables two-way, real-time communication – via devices, video conferencing and other telecommunications technologies – between healthcare professionals and their patients. In recent years, it’s grown in popularity; it’s estimated that 20% of emergency room visits and 24% of office and outpatient visits could be shifted to virtual care delivery overall.
What are the limitations of technology in healthcare?
Strict regulations govern the management of digital healthcare technologies. They exist for good reason, such as avoiding unintended harm, but rigorous testing and caution means that adoption for many technologies is gradual and, as a result, time-consuming.
Digital literacy can also prove a barrier to progress. Evidence suggests that not only do digital skills gaps exist within healthcare settings – meaning healthcare professionals themselves must receive sufficient training and support – but issues can also exist on the patient side. Many are using these technologies for the first time, and others may even prove resistant, which can impact the feasibility of widespread roll-out.
Technology and data hold the keys to much of the progress and innovation in this sphere. That itself can cause issues in both the short-term and long-term, from an insufficiency of data – while data sources scale and build over time – to questions regarding data protection and ownership.
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