The pioneering developments in digital technology and healthcare in recent years have helped improve client-patient relations by assisting in the provision of better diagnoses through data, as well as enabling people to manage their symptoms post-diagnosis and gain a better understanding of their condition. Together, this combination of touchpoints has made it easier (and more cost-effective) to take a patient from first referral to ongoing treatment and close the knowledge gaps of how a patient’s condition is progressing or regressing when they are outside of the clinic. Gathering big data (large volumes of rapidly-generated and complex data sets) from patients regarding their condition is also a critical step toward preventative care and the treatment of disease, with research suggesting that the cure for cancer may lie in big data.
With so much extra patient data being collected and made available to different stakeholders throughout the patient’s healthcare journey, the important issue of privacy and security is often brought up due to the nature of the data being collected as it must be compliant with the relevant regional laws and standards such GDPR (in the UK and Europe) and HIPAA (in America). The processing and sharing of data are extremely important when patients are referred to outside clinics or when they require a change from one healthcare provider to another, so compliance standards must also be met during the transfer process as well as in individual institutions (in fact, in a survey by Accenture, 38% of patients had concerns around data security in relation to technology).
Automating this compliance process and ensuring big data is stored securely is a huge challenge for the medical industry as a whole with over $14.7 billion spent on cybersecurity in 2019, which is projected to increase to $58.4 billion by 2030. Research company, Gartner, additionally predict a 5% year-on-year increase in artificial-intelligence-powered privacy compliance technology across all sectors by 2023 (taking figures to 40% globally).
In many ways, the COVID-19 pandemic accelerated the medical industry’s technological uptake, yet the industry still remains a top target for data breaches. In the 2021 Healthcare Cybersecurity Breach Report by Infoblox and the CyberRisk Alliance, it was revealed that over a 12-month period since the beginning of the pandemic, 53% of healthcare providers experienced data breaches (as well as a range of other cloud networking attacks such as malware, denial of service and distributed denial of service attacks, and even insider attacks). Healthcare providers also revealed the attacks resulted in the loss of data and customer data breaches 51% of the time, alongside financial loss and general operational disruption.
Artificial intelligence encapsulates a very broad range of opportunities and can be used by healthcare providers to not only preempt data breaches but also manage a breach and minimise damage. AI technology can use current and historical data to analyse “normal” traffic across a network and flag suspicious activity and unusual, subtle patterns that may otherwise go unnoticed. AI can also scan systems to expose vulnerabilities to improve systems long-term, as well as being a powerful tool in fighting against breaches in real-time to prevent data corruption or loss. This is incredibly important as medical data breaches that go undetected can be detrimental to patients, especially as many may not know they’ve been affected for many years and the poor adoption of cybersecurity technology by healthcare providers (alongside lack of sufficient training) has been cited as one of the main reasons for the aggressive targeting of the industry by hackers.
As software developers in this industry, we’ve worked on a number of health tech projects, including the QIoT Connected Asthma project (which was shortlisted in the Herald Digital Transformation Awards 2022 for Best Use of Technology in Healthcare). During the development of this platform, we wanted to mitigate the risk of data breaches with a solution that encrypted data and anonymised each data set depending on the account permissions of the user accessing the system. For example, the connected inhalers used by patients are identifiable by a reference code that cannot be traced back to any one individual user of the app, so admin users are not able to see the patient’s name or other personal details but can access their inhaler statistics. The patient, on the other hand, can log into the app and share new data for the admin to see, as well as access their own data at any time (both online and offline).
Find out more about how Zudu can help you create a modern, secure, and compliant digital health system or upgrade your existing software by contacting our team. We also provide digital transformation consultancy, software design, and full training and support to help you adapt to the changing digital landscape.
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