How Better DataOps is Driving Healthcare Innovation
How Better DataOps is Driving Healthcare Innovation
IT Data Solutions
Early successes from Data Management projects deliver speed, agility and scale.
As the current pandemic continues to spread, and the worldwide number of cases crosses the four million mark, public, private, and government organizations are using big data and analytics in new ways to help with prevention and treatment. From using location data to manage exposure tracking, to using supply chain data to manage testing resources, to aggregating trial data in the race to develop a vaccine, virtually every COVID-19 approach is harnessing big data analytics to solve a broad array of testing, treatment, and containment challenges.
Because the data involved is often massive, housed in a variety of companies, and changing by the minute, the success of each effort requires data that is easily ingested into an analytic platform, scalable storage and compute environments, and an accelerated data pipeline capable of processing near real-time information. In addition, these data operations must maintain a level of data security and compliance in order to meet HIPAA and other regulatory requirements.
The past several weeks have shown the increasingly critical need for companies taking on ambitious COVID-19 efforts to optimize their data supply chain. The following are several examples where Data Management and operations optimization increases the efficiency, governance, and rapid scalability of current pandemic efforts.
Eradication
Open Research Data Set: Data is driving the race for a cure. Initiatives like the COVID-19 Open Research Dataset (CORD-19) aim to create central repositories for a wide range of projects. Clinicians, researchers, and other healthcare professionals can contribute, query, and analyze data. Collaboration, unifying observations, and validating findings will accelerate pandemic cure timelines.
Vaccine Partnerships: Even as countries succeed in flattening the curve, virus resurgence will happen, and a vaccine remains the best eradication solution. The traditional vaccine development timeline, even in a best-case scenario, is too slow, and big data projects are discovering inefficiencies that will compress the clinical trial timeline. Unique, often global, partnerships, such as the one between GSK and Innovax, accelerate meaningful analytics using real-time data across larger data sets.
Treatment
Predictive Analytics for Hospital Bed Capacity: While the world’s largest technology companies have proven well-equipped to create repositories for research and data, the logistics and manufacturing industries are less agile. Test kit production and distribution continues to be a challenge with the dependence on the global supply chain being a primary factor. One area where Data Management and analytics are succeeding is predicting the number of hospital beds needed by region and timeline. For states dealing with a high case volume, such as New York, having advanced data for hospital demand results in better supply distribution, staffing decisions, and, ultimately, fewer fatalities.
