The healthcare industry is constantly looking for ways to improve the outcomes for patients — and the focus is often on finding more effective treatments. What new drug or device is available that will improve quality of life or reduce readmissions? But there’s a way that clinicians could have a massive impact on patient outcomes at a fraction of the cost of developing new medication — and that’s by improving medical adherence.
The World Health Organisation has said that adherence to long-term therapies for chronic illnesses, such as hypertension, cancer and HIV in developed countries is only around 50% — and even lower in developing countries.1 That matters. When a patient with a chronic illness doesn’t follow their prescribed treatment regime, they reduce their chances of managing their condition whilst increasing the cost of care.2 It has been estimated that incorrect dosage and non-adherence contributes to 194,500 deaths a year within the European Union.3
Whatever the reason for non-adherence, it has a huge impact on healthcare — in terms of both patient outcomes and the cost of treatment. If an initial treatment is unsuccessful, patients may be prescribed a higher dose — and then possibly a third and fourth treatment. Furthermore, over the long-term, a patient’s condition may deteriorate and require more expensive treatment options. That’s treatment — and costs to payers — that could have been avoided.
So how can adherence be improved? Traditional approaches, like education, interaction and simple reminders, are having an impact. But we now have the technology to make a step change in the measurement and management of adherence. IoT is enabling solutions such as smart packaging and connected drug delivery devices, which can provide an accurate and real-time measure to clinicians of whether patients are following their treatment regimes. This data can then be shared with patients via apps on their smartphones. That can give them a strong impetus to change their behaviour and empower them to self-manage. Research shows that if patients get feedback about their own adherence, their compliance levels increase by nearly 20%.6 With more reliable adherence data, the healthcare industry can also start to understand patient behaviour better and improve dosing recommendations.
The roll out of these IoT solutions has, until recent years, been held back by cost and the complexity of capturing, storing and analysing data from thousands of remote devices. But the technology to make smarter adherence a reality is now here. Providers, like Vodafone, offer managed IoT platforms that provide secure connectivity, storage and compute to handle data from vast numbers of devices.
This technology is making the development of ever-more sophisticated solutions possible. Tools are already available to correlate adherence data with data from other connected devices, like weight scales or fitness trackers, to deliver more individualised treatment. With greater awareness of their own adherence, patients will be in a stronger position to take charge of their own health. With advances in artificial intelligence, it’s possible that this will eventually reach a point where an individual’s prescription could be changed automatically without the need for a clinical appointment. That means better patient outcomes and also lower healthcare costs.
1 Adherence to long-term therapies, WHO, 2003. p XIII ↩
2 Interventional tools to improve medication adherence: a review of literature, Costa et al, Patient Preference and Adherence, 2015, 9, p. 1304 ↩
3 http://cordis.europa.eu/project/rcn/75025_en.html ↩
4 Determinants of patient adherence: a review of systematic reviews, Kardas et al, 2013. p 1 ↩
5 A new taxonomy for describing and defining adherence to medications. British Journal of Clinical Pharmacology, 2012, 73, pp. 696-698 ↩
6 Identification and Assessment of Adherence-Enhancing Interventions in Studies Assessing Medication Adherence Through Electronically Compiled Drug Dosing Histories: A Systematic Literature review and Meta-Analysis, Demonceau et al, Drugs, 2013. p 546 ↩
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