The global demographic population is ageing at a rapid pace. In the UK alone, one-fifth of the population, roughly 11.8 million citizens are more than 65 years of age or older. This ever-growing elderly population suffer from multiple chronic diseases (multimorbidity) such as cardiovascular disease, osteoporosis and dementia. Although there has been an increase in life expectancy, the vast majority tend to live in ill health over the course of their lives. As a result, there is increased need for hospital visits and hospitalisation, placing a huge burden on the healthcare system.
Polypharmacy, the use of multiple drugs or more than medically appropriate, is a burgeoning concern amongst older patients with multimorbidity. The research undertaken by the National Institutes of Health has shown that polypharmacy has become increasingly and alarmingly common in older adults with the highest number of drugs taken by those residing in nursing homes. Nearly 50% of the elderly population take one or more medications that are not medically necessary. The increased use of polypharmacy by doctors and over-prescription of unnecessary medications leads to drug to drug interactions contributing to the increased risk of falls in the elderly population, delirium and other related healthcare complications. Current evidence in medical literature clearly establishes a strong link between polypharmacy and detrimental clinical consequences in later life. Due to this, hospitals see an increased number of hospital admissions and re-admissions. This increased healthcare demand places undue strain on NHS healthcare workforce and infrastructure leading to a supply and demand mismatch.
The advancements in digital health technologies such as Telemedicine and Artificial Intelligence (AI) has contributed to the use remote-monitoring devices in elderly patients. AI technologies and interconnected personal devices has made it possible to audit, analyse and assimilate extensive medical data throughout the elderly population. A research conducted by Professor Arnold Milstein at Stanford University using thermal imaging cameras and AI algorithms has identified patients at risk of falls and injuries in community thereby preventing these by district nurses visiting their homes before an event. The use of thermal imaging and other medical technologies has proven to show the reduction in hospital admissions due to prophylactic interventions beforehand and early treatment of infections such as urinary tract infections. This has also assisted remote monitoring of ageing and vulnerable patients, and has delivered highly targeted and direct diagnostics, healthcare and treatment. The use of technology in healthcare and AI has opened up access to personalised and precision medicine.
The ongoing Covid-19 pandemic has pushed digital technology into the forefront of medicine through virtual clinics and telemonitoring of patients who are unable to visit hospital due to self-isolation and distancing measures. Broader use of this technology in the daily lives of elderly patients will help to identify those patients in need of help before they become unwell and needing hospital care. The use of Artificial Intelligence and remote monitoring of patients using advanced digital health technology will undeniably revolutionize healthcare delivery in the future by taking hospital care to the doorstep of communities.
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