The data-driven revolution in US healthcare: trends and challenges in health data
US healthcare is undergoing a data-driven revolution that will transform the industry. Healthcare data collected from hospitals, insurance companies, and Big Tech can provide valuable insights into disease patterns, and improve public health, patient behaviour, and treatment outcomes.
Data analytics and AI are being used to improve patient outcomes, increase efficiency, and reduce costs, especially during the COVID-19 pandemic; with, for example, the development of track-and-trace apps and sharing information on infection rates and hospital capacity.
However, there are challenges associated with the privacy and security of healthcare data.
The Health Insurance Portability and Accountability Act (HIPAA) and the Health Information Technology for Economic and Clinical Health Act (HITECH Act) are federal US data laws designed to protect patient privacy. However, breaches of healthcare data are still common and can result in harm to patients and damage to healthcare providers' reputations.
What are the current trends in the space?
Big data and the growth of digital health
The increase in remote healthcare providers enables patients to receive care remotely, gives more flexibility in caregiving and eases pressure on hospitals. This provides a more efficient and cost-effective solution.
Digital health services such as mobile health apps and wearable devices are also becoming more prevalent as patients take a more active role in managing their health: tracking their menstrual cycle, health metrics, and more.
Big data is now invaluable to healthcare - from predictive analysis to better-informed patient care. US healthcare providers are making greater use of health data for analytics purposes and, in some cases, using data to train algorithms to help save lives.
AI and machine learning in healthcare
AI and machine learning in healthcare will surpass $20 million in 2023.
Across healthcare, computer vision, pattern recognition systems, and natural language processing systems have proven an enormous cost-effective and time-saving asset as it is adept at medical imagery.
The technology can help with early diagnosis in patients with conditions like Parkinson’s, dementia, diabetes, and mental health issues. It has sped up vaccine developments, by modelling protein and cellular interactions, predicting virus mutation, and aiding in clinical trials.
Predictive AI analytics is also vital in the outcomes of clinical trials and potential side effects of new drugs and vaccines, by providing a better understanding of patient genetics structures. This helps run simulations, identify at-risk patients to provide treatment and further analysis, and better tailor healthcare to specific patients.
The rise of retail healthcare
The rise of retail healthcare has meant retail health clinics growing by 21.5% between 2019 and 2020, with the retail clinic sector in the US valued at $3.49 billion by 2022.
Retail establishments like Walmart, Walgreens, CVS, and Amazon offer basic medical care, health screenings, and vaccinations, providing convenient and accessible healthcare options for consumers, especially those uninsured or from lower-income backgrounds.
As global economic conditions continue to face challenges and budgets for primary care facilities continue to be stretched, retail healthcare has the potential to dramatically transform the US healthcare industry.
The increased need for video and visual data capture
The increased need for video and visual data capture is a notable trend in US healthcare, especially during the pandemic.
Video data capture is optimising operational efficiency in hospitals, supporting telemedicine and remote healthcare services, and monitoring clinical trials. Visual data capture can greatly improve the quality of care in healthcare settings as cameras can monitor medical procedures, patient movements and activity, preventing errors, falls and other accidents.
Healthcare professionals have also come under a lot of pressure: there has been a sharp rise in assaults and violence in hospitals, and many have faced physical and verbal threats from patients and other civilians.
The data privacy angle
However, data privacy remains a concern. Health data is increasingly collected by non-healthcare entities like third-party app providers and Big Tech companies, and this is an issue.
Since the repeal of Roe v Wade, there has been increased scrutiny on how data from health apps and period trackers may be shared with third parties. The lack of federal data protection laws and ambiguity in regulations like HIPAA raise concerns about data privacy and surveillance.
While HIPAA applies to “covered entities”, it fails to address wearable devices, social media, or communication data that can reveal personal health information. There are also no requirements for proportionality and data transparency.
As health data increasingly moves into the hands of private (non-healthcare) companies, the sheer volume of visual data collected poses real-life privacy risks and potential restrictions on people’s freedoms. There need to be systems of accountability and regulation to ensure patient data is safe and secure.
Despite these challenges, the data-driven revolution in healthcare is here to stay. To stay ahead of the curve, healthcare providers should invest in the necessary technology and skills to harness the power of data and ensure their data privacy and security practices are up to date.