The healthcare industry has been affected uniquely by the COVID-19 pandemic. Not only did those working in the industry have to shift overnight to working remotely and care for those who needed it because of the virus, but the changes to the way data was handled in order to support both the care and the research needed placed an incredible strain on the industry's IT departments. Pandemic healthcare required rapid data handling across the spectrum from R&D to patient testing, while sharing data had to be both improved technically and legally.
The digital transformation in the healthcare industry was already underway when the pandemic hit. However, the response to COVID accelerated this trend. The impact of the outbreak touched on current issues in healthcare data, such as privacy, and COVID-19 provided the first serious stress-test of Europe's GDPR regulation. Problems such as data incompatability across healthcare providers made health information sharing difficult. Some controversy surrounds the U.S. government's United States Core Data for Interoperability (USCDI) implementation, as interoperability requirements laid out by the government in 2020 and 2021 fail to acceptably account for the types of data that needs to be shared due to COVID. However, the requirements, under the Fast Healthcare Interoperability Resources (FHIR) are a step in the right direction, according to some. Dr. Steve Labkoff sees that registry science has moved forward with the introduction of FHIR and USCDI in that, "FHIR helps the data move from place to place, and USCDI helps define how it should be named and stored."
Moreover, the organization of research and analytics, especially in terms of interoperability, has been pushed into the forefront of concern in the healthcare industry.
"If the COVID pandemic has taught us anything in healthcare, it’s that being able to rapidly aggregate data into registries can be a critically important capability for both the health and wellbeing of individuals, our nation, and the world,"— Dr. Steve Labkoff, Global Head of Clinical and Healthcare Informatics at Quantori.
New Healthcare Industry Data
Healthcare has been data driven since the days of the medical chart. However, the changes in the way data is created and shared is part of the shift in the healthcare industry. The electronic health record market alone is expected to reach USD 31.5 billion by 2030. The U.S. USCDI is only one set of regulations shaping the industry. GPRD in the EU as well as the My Health Record platform in Australia are also creating regulatory pressure that is helping the market grow.
In many cases, the pandemic itself drove the adoption of data analytics. In an article for TechRepublic in October 2021, Transworld Data president Mary Shacklett posited that the pandemic might be seen as a turning point for analytics, as the field is no longer a helpful adjunct, but an essential part of an incident response kit for an institution.
Shacklett notes that across many industries, adapting to the pandemic included redefining and retraining AI models.
"In some cases, existing data models that had been so reliable suddenly began to underperform to the point that they needed tweaking. In other cases, companies lacked data and applications altogether to deal with the COVID crisis, and they had to find new ways to obtain the data they needed and develop new analytics models quickly… In some instances, new types of analytics data and applications had to rapidly be created to deal with the COVID crisis."
— Mary Shacklett, Transworld Data President.
The response to the pandemic has broken new ground within data science. At the same time, the rising awareness of the importance of data science in the general public should make its application in healthcare easier to accept. However, while the role of data science in healthcare is now more clearly seen, its job just got more complicated.
Big Data in Healthcare
The Healthcare Information and Management Systems Society (HIMSS) sees how big data is used in healthcare in terms of five 'V's, instead of the traditional three of Volume, Variety, and Velocity. Data volume increased tremendously due to the pandemic, but so did the need to ensure Veracity, that data authenticity and quality of patient data is high. This includes not only keeping health records secure but also that data from devices such as heartbeat monitors is as high-quality as possible. With the rise of home-based devices collecting data, big data and health will intersect at the 'variety' of the five 'V's as well.
The fifth V, for the healthcare data analytics market in particular, is Value, which HIMSS writes, "means the end result of all the data, or what it brings to the industry or organization."
Regarding Value, before COVID, there had been a growing emphasis on protecting personal data, which led the European Union to create General Data Protection Regulation (GDPR) in 2016. Then, just as the impact of GDPR on data engineering was being absorbed by the industry, the effort required to fight the pandemic forced a reconsideration of the relationship between personal data privacy and social needs.
Privacy and Healthcare in the Pandemic:
In Digital Solutions to Fight COVID-19, the Council of Europe's 2020 data protection report, the CE pointed directly to the fact that,
"The use of emerging technologies providing distance communication in lieu of human contacts, and algorithms replacing human intervention has simply exploded."
— Council of Europe. Digital Solutions to Fight COVID-19.
The CE also called for governments implementing emergency measures that affect the right to privacy and data protection to ensure that those measures:
- respect the general principles of law
- remain proportional to the threat they address
- be limited in time.
The CE saw no conflict between the measures required and the overall principles of privacy and data protection rights, as "they are the guarantee that such responses will be taken in full consideration of human dignity and integrity."
Data and Analytics
Implementing the Council of Europe's vision for using privacy and data protection as a guarantee for the humane use of data is, like the pandemic itself, not limited to a single geography. The effects of GDPR are felt around the world, especially in terms of data collection and research, as the data source and/or the researcher might be in Europe, even if the bulk of the project's workers are not. Data engineering firms with experience in analytics for the health care industry and GDPR will need a firm grasp of GDPR and similar efforts worldwide.
Just as companies working with data had to be flexible and ready to retrain AI meet new conditions, those working with health-related data will need to adapt to changing rules regarding data which might change rapidly. Time limits, purpose limitations, the proportionality of data-related measures to the seriousness of the issue and the ability to end the measure based on a lack of benefit, and the involvement of government protection authorities at various stages of a project's lifecycle all need to be taken into account.
“The continued impact of the COVID-19 pandemic will keep driving changes in the way the healthcare industry uses data. From studying and tracking the virus itself to facilitating home-based care, especially for vulnerable segments of the populace, the variety and velocity of demand for data engineering is expanding rapidly. Technological partners with applicable experience are going to be in demand for years to come.”— Vlad Medvedovsky, CEO at Proxet (ex - Rails Reactor) - a custom software development company.
Medical data companies are finding that the ability to simultaneously navigate a pandemic, shifting regulations, technological change and societal stress has its rewards. Venture backing of biotech and health care startups reached over $107 billion in 2021 through end-October, according to Crunchbase. That's up from the over $82 million raised for the whole year of 2020.
Spending might change, though, as new healthcare companies sort out possible post-COVID landscapes. Testing has been transformed since January 2020, but it might be set to change again as demand rises and falls. As of the time of writing, new mutations of COVID-19 are expected to suddenly and unexpectedly sweep the world, and medical data companies will be needed just as swiftly.
On the other hand, telemedicine and hand-held devices that were exoteric in 2019 are commonplace now and are unlikely to go away. Despite the volatility in the field, the healthcare analytics market is set to grow at a CAGR of 12.5% annually worldwide over 2021-2026, Research and Markets reports.
In this case study, the translation model called seq2seq model or encoder decoder neural network was built in TensorFlow. The objective of the model is to translate English sentences into French sentences. You can see the process of developing the model to answer the questions to define the encoder model.
Data analytics in the healthcare industry will continue to drive change as well as being affected by the changes brought on by the pandemic. Being flexible enough to adapt quickly will require partners with experience in both the technical and regulatory aspects of medical data engineering. At Proxet, data engineering is a large part of our day. From caremarket software to setting up a bespoke data engineering stack, our experience with data from the smallest heartbeats to medical research portals for 10,000+ users can help your company navigate the COVID-era environment.
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