The complications of a digitalised healthcare system are growing ever more complex. Overcoming challenges such as data privacy, payment models, trust, ease of use and interoperability remains essential to realise the full potential of digital health solutions in transforming the healthcare sector. We speak to Shameem C Hameed, Founder and CEO of blueBriX, an advanced digital health tool, who discusses the key challenges preventing innovation in the industry.
Now more than ever, the healthcare sector is under pressure to curb rising costs, increase accessibility, alleviate issues caused by worker shortages and improve both clinician and patient outcomes.
In addition, there is a rising demand for remote patient monitoring services, such as medical IoT and wearable devices, as well as the rapid growth of digital healthcare infrastructure across developed nations.
Added to this are additional demographic factors, with the total size and relative proportion of older people growing worldwide. For example, in 2019, 703 million people were aged 65 and over, who make up nine percent of the total world population. This is predicted to reach 16% (1.5 billion) by 2050. These demographic trends are causing shifts within the healthcare sector and resulting in increased expenditure associated with the costs of treatment and prevention in old age.
Artificial Intelligence, digital health apps and virtual care platforms, among other technologies, provide solutions which are both cost and labour effective and seek to reduce the pressures being placed on the healthcare sector. In fact, the global digital health model is huge – valued at $211 billion in 2022 and set to get bigger, with a projected growth of 18.6% from 2023 to 2030.
However, there are certain challenges that must be surmounted if the full potential of these digital solutions is yet to be realised and successfully integrated into current healthcare settings.
Data privacy and security
Within pharmaceutical, hospital, clinic and other healthcare settings, there is a call for a balance between the requirements of data protection and security as well as a need for innovation such as real-time alerting, predictive analysis and telemedicine. While the digitisation of patient health records and data has been around for the last several decades, the unprecedented acceleration of digital solutions within healthcare settings has bought an increased need to ensure sensitive patient information is kept private and secure.
When we consider that approximately 30% of the world’s data volume is generated by the healthcare industry and this is projected to increase to 36% by 2025, this is a huge, complex and often expensive undertaking. Added to this complexity, regulations around the privacy and security of information, such as the Health Insurance Portability and Accountability Act [HIPAA] in the US and GDPR throughout the EU must be adhered to.
As well as privacy compliance, sensitive data must also be secured against possible breaches and malicious attackers, with over 22.6 million patients affected by data breaches in 2021 alone.
Payment and reimbursement models
With technology having lagged in healthcare for decades, communication between patients and providers has become convoluted, with services unnecessarily complex and difficult to navigate. Increasingly, there is a challenge of transparency in reimbursement models within healthcare. Traditional transactional models prioritise neither patient outcomes nor the incentivisation of cost-savings from a clinical perspective.
This has led to a misalignment of incentives for patients and clinicians, as well as insurance companies and has ultimately led to patients being disconnected from the treatments they receive, with costs remaining opaque.
The increased interest in digital healthcare solutions offers a way to accelerate the conversation, underpinning traditional payment and reimbursement models with the data and digital infrastructure to place value-based care at the forefront, with digital tools able to generate useful data that can establish useful metrics for measuring value-based contracts. With better data, better models can be established that provide an incentive for clinicians to adopt them.
Trust and regulation
When it comes to certain digital solutions, especially those that implement AI and Machine Learning, there is hesitancy on the part of both healthcare professionals and patients to fully trust the technology, particularly when it comes to critical decision-making processes. While public opinion is slowly warming to the capabilities and positive potential of AI, particularly with the rise in popularity of AI platforms like ChatGPT, many are still sceptical of AI-based solutions within healthcare.
Compounding this challenge, the regulatory landscape around artificial intelligence and its integration into digital healthcare has somewhat lagged behind the developments within the field, stifling further innovation and doing little to build public trust.
There is an undeniable friction between the proper regulation of such technologies that will prioritise the safety and efficacy of patient outcomes while assuaging public concerns and the need to create a regulatory framework that does not unduly stifle innovation.
While we are seeing nations around the world begin work on implementing the necessary regulatory guidelines, such as the AI Act in the EU, or the recent Action Plan released by the FDA in the US, this does place a burden on those developing AI-driven solutions, as obtaining the necessary regulatory approval can be a long and costly process.
Ease of use
Digital solutions like AI and Machine Learning have so much to offer the healthcare sector, but to be truly effective, they must provide a positive user experience to both healthcare professionals and patients. The majority of healthcare providers simply do not have the technical expertise or resources needed to develop, implement and integrate complex digital solutions into their existing working landscape.
To increase both engagement and uptake, digital health solutions must be user-friendly and intuitive, with clinicians and other healthcare professionals given effective training to adapt to these new systems. Both a lack of clinical engagement and inadequate resources are two often-cited areas that prevent better integration of otherwise promising digital solutions. These are important challenges to address, as they can have a large impact on patient safety, as well as data quality and governance.
From a patient perspective, ease of use is also of utmost importance, especially in regard to creating better health equity. If powerful digital solutions are to be adopted patient-side, the healthcare sector must tackle the challenges of technological literacy, unequal access to the internet and issues around language dependence. Issues of equity must be woven into the core design of digital healthcare solutions.
Interoperability
Healthcare is a complex area, involving multiple entities from clinics and hospitals to laboratories and pharmacies, each with its own data formats and systems. For digital solutions to be effective on a larger scale, they must be able to be seamlessly integrated across multiple systems and smoothly interface with each of them.
Known as interoperability, the seamless exchange of information across core clinical systems is key to improving the safety and efficiency of digital healthcare solutions and more easily integrating products and solutions into the existing healthcare infrastructure. Not only can this be a challenge to achieve, but the adoption of standard healthcare data systems and models is necessary for further innovation and development of digital health solutions.
Developers of such solutions must address the issues surrounding interoperability and the need to adhere to healthcare and regulatory standards, or risk ending up with patient data that simply cannot be used or requires extensive cleaning up. In short, they must find a suitable balance between interoperability and the security concerns that come with vast amounts of confidential clinical data. There is a clear need for pioneering players within the digital health space, who will continue setting standards that address both interoperability and regulatory concerns.
Conclusion
Digital solutions have huge scope for applications within healthcare that can improve patient outcomes, accuracy and treatments, as well as clinician experience and cost-efficiency. However, their successful implementation requires careful regulation and evaluation of both the technical and ethical aspects of these promising technologies.