The healthcare sector has always been closely related to innovation. In 2023 alone, the global digital health market was estimated at 180.2 billion dollars. In Europe alone, countries spend around 312 euros on medical technology per capita.
The potential is immense. Especially with recent developments in AI, which have impacted everything from promising improvements in administrative operations to speeding up the diagnosis process.
On the flip side, our reliance on technology raises important questions about data privacy in health tech. It’s easy to see why some people may be cautious or even sceptical.
So, how do we balance innovation with risks? How can we protect sensitive patient information when healthcare organisations are increasingly targeted by malicious actors?
We’ll answer all of these questions and more.
With increased reliance on health tech comes great responsibility. Specifically, healthcare providers need to balance risks and opportunities and make informed decisions. Growing concerns are related to the use of patient data, whether it can be sold to a third party or used for unethical purposes.
Understandably, patients want control over their data. For example, they are concerned about workplace discrimination should their doctor's office mismanage a data leak.
Another aspect is bias which can fly under the radar when using tools such as AI. Biases now spread much faster than ever before, leading to more inequality or medical errors.
However, nobody can deny that patient data, when used ethically, can help further scientific research and innovation. It leads to better health tech, personalised care and even improved healthcare systems.
Patient privacy is a sensitive issue and it will only grow in importance in the coming years. Significant risks include:
Healthcare technology needs data to function optimally. For instance, an app that identifies skin conditions such as melanoma relies on actual patient images. However, results can be vastly improved with access to a person's health records and risk factors. And some applications collect more than they need, raising important ethical questions.
While some platforms only need the basics, there are many types of data already stored in health platforms:
Currently, many frameworks govern health data. The US has HIPAA, GDPR is in effect in the EU, Canada has PIPEDA, etc.
GDPR considers health data as a special category. It's defined as “personal data related to the physical or mental health of a natural person, including the provision of health care services, which reveal information about that person's health status” (Article 4(15), GDPR).
The framework has introduced some innovative aspects or principles that directly impact health tech, including:
At the same time, healthcare organisations need to take particular care when it comes to processing health information, and genetic or biometric data.
The use of these types of data without explicit consent is forbidden. Furthermore, it can only be used for preventative or occupational medicine, diagnoses and public health reasons. Non-compliance penalties include fines (up to 4% of the organisation's annual revenue), lawsuits, and reputational damage.
The stakes are high in healthcare. Data loss or breach damage can’t be easily repaired. At the same time, the numbers are alarming. In the US, a record high of 116 million people were affected by large data breaches in 2023.
The European Union Agency for Cybersecurity (ENISA) observed that 53% of all reported incidents happened at healthcare institutions, particularly hospitals.
Common threats include:
However, insider threats and unintentional data exposure should be particularly worrying for healthcare providers.
Insider threats define persons in the system who lead to data breaches, which can be intentional, negligent, or accidental. Negligent and accidental breaches are widespread and easily preventable with the right measures. For example, staff can be made aware of security policies, receive proper training, or learn how to do their due diligence to protect data around unauthorised persons.
Aside from the human factor, certain organisational factors must be considered when using healthcare technology.
While this isn’t an exhaustive list, there are certain things that any healthcare provider can do to protect their patients’ data.
Encryption protocols can become vulnerable over time because of technological advancements and new attack methods. That’s why it’s best to update them regularly and work with a provider that can maintain best practices over time.
For example, Transport Layer Security (TLS) is used to secure communication over the internet, ensuring the confidentiality and integrity of data exchanged between applications. AES (Advanced Encryption Standard) is a symmetric encryption algorithm widely used for encrypting data. The advantage is that it can be used in various applications and protocols. Other notable examples are RSA (Rivest–Shamir–Adleman) and Blowfish.
Intentional and unintentional data misuse can be prevented by controlling who can access and modify data. Here, the best practice is to rely on authentication mechanisms rather than manual permissions.
Of course, multifactor authentication plays an essential role, adding another layer of protection. However, this is just touching the surface. As organisations rely on more medical devices for everyday tasks, the need for more sophisticated security measures increases. For example, while strong passwords will always be relevant, adding layers such as biometric authentication is a game-changer.
Common standard procedures are implementing monitoring and auditing tools to track access to sensitive data. Or regularly reviewing logs and auditing trails to identify and respond to suspicious activities.
However, since everything changes quickly and attacks get more sophisticated, you also need to conduct regular privacy policy assessments to identify potential risks and vulnerabilities. In this way, it's easier to find recommendations for managing, minimising or eliminating them.
As mentioned before, human error is a common threat. Healthcare staff is particularly vulnerable since they work with sensitive data every day. They're also not data protection specialists.
With things changing quickly, staff may be behind on the latest data protection measures. For example, not leaving devices unattended, taking extra care when working remotely or controlling physical access to unauthorised areas. This means that regular awareness training is key for all staff members, no matter how closely (or not) they work with patients.
Data ownership is a fundamental right. This means that healthcare professionals, such as doctors, nurses, receptionists, etc., should know how data is used and processed and answer patients’ questions.
Moreover, all platforms and websites should have the necessary consent functions and offer accurate information regarding patient data sharing.
The numerous attacks on healthcare organisations mean they will be less resilient and exposed in the future. This doesn't have to be the case. They can recover much more quickly if they have an incident response plan.
Moving from a cyber security perspective to a cyber resilience one, incident response means having well-defined procedures to cushion a data breach's impact.
Conducting regular testing, detecting anomalies early and limiting access to sensitive information are just a few of the basics of a good strategy.
Medical providers, especially hospitals and clinics, often rely on many third-party vendors. They can be medical suppliers, consultants, software services, janitorial services, etc. This means that they should have a vendor risk management plan to cover all the potential scenarios. This includes an assessment of security risks, compliance requirements and certifications.
Additionally, a best practice is to do vendor tiering, which is putting vendors into categories based on their risk security level.
For example, a medical equipment supplier has more access to an organisation’s critical systems than a vending machine supplier. In this way, you’re paying more attention to the ones who can have the most negative impact while having the appropriate rules for low-impact third-party vendors.
Health tech adoption shows no signs of slowing down, and security must keep up with it. The good news is that there is a lot to look forward to regarding safeguarding patient privacy:
On the one hand, hackers can use AI and ML to convince staff to give them information or access. On the other hand, developments in AI and ML replace tedious and outdated manual work:
Of course, this approach has its challenges. In using ML/AI for patient privacy, you need datasets, which conflicts with the data minimisation principle (collecting and storing only necessary data). The risks can be lowered by creating a model of the organisation and teaching it to work according to specific rules before launching it in the real environment.
Major advantages of blockchain include transparency, flexibility, tracking data provenance and enhanced privacy. Just like with economic transactions, the blockchain is a ledger keeping track of each dataset and modification, making it difficult to tamper with healthcare data.
When it comes to security, traditional data management systems rely on a centralised architecture or a centralised server/cluster. In other words, a single point of failure leaves organisations very vulnerable. Blockchain, on the other hand, ensures a decentralised architecture, in which data is harder to access by outsiders.
Additionally, it’s an effective way to manage patient identity since the blockchain doesn’t store personal identifiable information. Instead, it uses cryptography to verify credentials. In this way, both providers and patients can easily and safely access health records.
Healthcare organisations need a reliable custom health tech provider, who understands and implements regulatory frameworks such as GDPR.
Qubiz is a trusted technological partner for many healthcare organisations. With more than 15 years of experience, we PLAN, BUILD and MAINTAIN software solutions that put medical professionals and patients first.
Health tech relies on patient data to ensure optimal functioning and relevance. Take for instance apps that detect conditions such as melanoma. Or clinical trials that collect vast amounts of data to advance science in general and the technology behind it. Another good example is AI or ML in which models can be designed for diagnosis, health monitoring, etc.
The largest challenge with maintaining privacy in health care is outdated, legacy health tech systems that are vulnerable to attacks. Maintaining electronic health records means that sensitive information, including conditions and personal identifiable information.
Healthcare organisations are attractive targets for malicious actors. Common threats include ransomware, data leaks, DDoS and phishing attacks. Insider threats such as accidental data leaks are also important threats to consider.
Patient data encryption, regular audits, security training and incident response plans are just some of the ways to safeguard patient data privacy. Vendor management gets a special mention since healthcare institutions work with many third-party companies with various access levels to data.
Health tech makes huge leaps each year. On the downside, cyber attacks also get more sophisticated, so staying current with healthcare technology is important for offering better patient care and ensuring that their data is protected.
While there are many exciting developments to watch out for, AI and blockchain technology should be at the top of the list. AI offers real-time detection, automated responses and recommendations for securing your systems. Blockchain functions as a secure electronic ledger, so patient data is much easier to manage.
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