Tech challenges facing digital health start-ups and SMEs and how to solve them. Part 1 – Personalised Healthcare
Part 1 – Personalised healthcare
When it comes to personalised healthcare, innovation can conflict with responsibility. Improving patient outcomes is marked by both promise and challenge. As we look at the complex but transformative digital healthcare industry, it’s essential to consider the concerns surrounding patient data while empowering tech start-ups and SMEs to drive innovation forward.
Is personalised healthcare the answer?
The UK’s NHS is struggling. Personalised healthcare could be the answer. Removing the strain by promising tailored treatment suggestions and enhancing patient experiences, could reduce the burden facing our healthcare system. Driven by advancements in technology and data analytics, this shift in healthcare delivery holds immense potential to change the way we diagnose, treat, and manage diseases. From AI-driven diagnostics to wearable health trackers and telemedicine platforms, digital healthcare innovations could reshape the patient care landscape.
But there are challenges.
Protecting patients should be a priority
To make personalised healthcare work, you need vast amounts of patient data. But being in possession of such sensitive information demands the highest levels of protection. Patient history, including medical records, diagnostic tests, treatment plans, and outcomes, forms the backbone of clinical decision-making. And, with the influx of digital health technologies, the scope of data has expanded exponentially, encompassing wearable device data, genomic sequences, and even social causes of health.
As a tech start up working in the digital healthcare industry, morally and legally, it’s your duty to keep this information safe.
Addressing security concerns
Healthcare organisations, including tech start-ups and SMEs, must take a multi-faceted approach to data security and consider including:
Encryption - safeguard patient data from unauthorised access by encoding it into an unreadable format.
Access controls - restrict system entry to trusted people only, ensuring patient data confidentiality and integrity.
Regular audits - maintain compliance, seek out vulnerabilities, and enhance security measures to protect sensitive patient info.
Employee training programs - educate staff on cybersecurity best practices, reducing the risk of human error and potential data breaches.
Penetration testing - proactively identify weaknesses in systems and applications, strengthening defences against cyber threats.
Our partners – NAQ and CT Defense are experts helping you become compliant. Speak to us to see if you can take advantage of our partnerships.
By combining these five areas you can mitigate the risk of data breaches and protect patient privacy.
The question is, how can you do it?
Practical steps for data security
Introduce encryption and access controls
Start-ups and SMEs should use encryption protocols to secure patient data both in transit and at rest. At Scryla, we recommend a zero-trust approach. This might sound extreme but if it works for the big organisations, it will work for growing startups and SMEs, like you.
In a nutshell, here’s how zero trust works:
No one is automatically trusted, regardless of whether they’re inside or outside the company network. Every person and device must be verified before being allowed to access any resource.
Users are only given the minimum level of access they need to perform their specific tasks or roles. This reduces potential damage if any user or device is compromised.
User behaviour, devices, and access patterns are continuously monitored for any suspicious activity, even after they’ve been granted access. Access can be revoked immediately if a threat is detected.
The network is divided into small, secure segments, making it harder for an attacker to infiltrate the system.
The goal of zero trust is to assume that threats can come from both inside and outside your business, and to use layers of security checks and controls to protect valuable assets and data.
Secure cloud infrastructure
Cloud computing offers scalability and flexibility for digital healthcare tech, but it also introduces security challenges. Our advice would be to choose cloud providers with robust security measures and adhere to best practices for data encryption, network segmentation, and incident response.
We recommend providers like AWS, MS Azure who comply with HIPAA laws and rules. However, if you don’t have the skills in house to set this up, you can use systems like Apitble who take care of the heavy lifing but at a price.
Keep up to date on regulatory requirements
Compliance with regulations such as GDPR and HIPAA is essential for start-ups and SMEs handling patient data. Investing in regulatory compliance frameworks and seeking guidance from legal experts can help you get to grips with complex data protection laws.
Get clever with cash
While introducing robust data security measures can be financially daunting for start-ups and SMEs with a limited budget, there are cost-effective solutions that mitigate risks without breaking the bank.
Open-source security tools. Using open-source security tools and frameworks can provide you with cost-effective solutions for data encryption, intrusion detection, and vulnerability scanning. Look at SNORT, OpenVAS, OWASP ZAP. You must keep in mind that to set up and monitor these systems requires expert knowledge. Get the right skills in place first because leaving systems to fend for themselves won’t work.
Collaborative partnerships. Partnering with established healthcare organisations or technology providers can offer access to infrastructure, expertise, and resources that might otherwise be out of reach. Collaboration can also encourage sharing data security knowledge and best practice.
Challenges facing start-ups and SMEs when using AI in digital healthcare
While the potential of AI in changing the face of personalised healthcare is immense, you face unique challenges if you to use want to use this technology. Digital healthcare businesses often deal with highly sensitive patient data, making it difficult to use pre-trained language models such as OpenAI due to strict data controls. They also face ethical implications of using patient data and data bias, plus legal ramifications if they don’t adhere to regulations like GDPR. And, training a large language model from scratch comes with a hefty price tag, posing financial barriers for resource-constrained start-ups and SMEs.
Data sharing
Explore the option of collaborative data sharing with healthcare institutions and research organisations. By pooling anonymised patient data from multiple sources, you might be able to create diverse datasets for AI model training while adhering to data privacy regulations.
Optimised resource allocation
To reduce the financial burden of training large language models, start-ups and SMEs can prioritise resource allocation and seek cost-effective alternatives. This may involve using cloud-based AI services, using specialised hardware accelerators, or exploring federated learning approaches to distribute model training across multiple devices.
Algorithm bias and interpretability
AI algorithms can develop biases present in the data they’re trained on, leading to disparities. Employing techniques such as bias detection, fairness-aware learning, and interpretable AI models can help reduce bias and enhance transparency.
Regulatory and ethical considerations
Regulatory frameworks must evolve to address the unique challenges posed by AI in personalised healthcare, including data privacy, liability, and patient consent. Working closely with regulatory agencies, policymakers, and ethicists can help establish guidelines and standards that promote innovation while safeguarding patient rights and safety.
Finger on the pulse
Personalised digital healthcare is a relatively new concept with new pathways to be explored. By prioritising data security, embracing cost-effective solutions, and embracing the power of emerging technologies, tech start-ups and SMEs can play a pivotal role in shaping the future of healthcare delivery.
If your start up or SME is operating in this space and you’d like a tech check-up, contact us. We can work together to make sure your business is using tech correctly to grow and scale in this market.
Next month, we’ll look at digital healthcare and the price tech start-ups pay for overspending on data storage.