Advances in healthcare are as exciting and critical as they are numerous. Researchers are regularly making new medical breakthroughs for everything, from type 2 diabetes to cancer treatments. Impactful new technologies are also being developed, from neurotechnology that allows for detailed brain imaging to wearable devices through which surgeons can assist with surgery in real time from halfway around the globe.
Whether you are a surgeon, lab technician, or family doctor, the end goal is always the same: providing a meaningful experience while delivering the best possible treatments and outcomes. That requires a more holistic view of the patient, which includes details such as knowing their current health condition, family history, daily activity and lifestyle choices—even their preferred communication methods. There seems to be no limit to the possibilities and the potential, all of which can have a positive impact when it comes to providing better healthcare.
And behind it all lies data. Data helps us determine what the next impactful treatment might be. Data can drive care delivery efficiency, resulting in better patient outcomes. And data can help us get ahead of the next big pandemic.
Saving lives. Saving time. Optimizing clinical and business operations. Data is the foundation for it all and it’s growing rapidly in complexity, speed, and volume, driven by the need for Patient 360, outcome-based care, and continued digital transformation across the industry.
And yet, there can be hesitations and logistical challenges when it comes to gathering data, sharing data, and collaborating on data, both internally and with external organizations. Decision-makers in the healthcare space must continually monitor privacy, regulatory, and security concerns as well as the accuracy of their data. They must ask questions such as how quickly can the data be accessed and by whom? How does the data interface with legacy systems? What are the associated costs? In addition, organizations must evaluate their level of interoperability; that is, their technological ability to share data between different and distinctly separate systems, applications, or platforms.
Data sharing in healthcare is already happening every day to varying degrees, albeit cautiously. But it’s also raising “myths” or misconceptions across the industry about healthcare data, and some of these concerns are outdated or were erroneous to begin with. We’d like to bust five of the biggest ones:
Myth #1: Data sharing is an “all or nothing” proposition
According to Eva Murray, Lead Evangelist, EMEA, at Snowflake, “That’s not true. In fact, as a business model it doesn’t even make any practical sense.”
People in the healthcare industry work with different departments internally, as well as with organizations in a variety of locations outside the organization. A data administrator can choose the level of detail they want to share. It can be an entire data set or individual tables, and access can be limited based on rows, columns, or certain attributes. For example, if somebody worked in a specific department, they would get access to specific data, but if they changed departments, their access would be changed accordingly. Administrators have complete control over who has access to what data, what they can see, and what they can use for their own analysis at all points.
“When you work with a data cloud provider, you have the choice of what you want to share,” says Murray. “You can choose what you share and what level of access you give to individuals. You can decide which teams have access to what data, and also which business partners you share it with.”
Myth #2: Sharing sensitive data is slow and not secure
To debunk this myth, let’s just start with the notion that these days, slowness and a lack of data security are things nobody has the time, patience, or risk tolerance for. Operating that way just doesn’t work in a modern organization, and with today’s strict legislation and regulations both regionally and globally, data security is non-negotiable. “The data cloud provides security and performance out of the box, with a security layer automatically encrypting data built in, for example, and it doesn’t change, no matter what organization you’re with or what things you use the platform for. You will always get the same security and performance,” Murray says.
In this type of data platform, the shared data will perform just as fast as the data you already own and have access to, and that you have introduced into the platform environment. The shared data and your own data is all in the same environment. What usually takes time in the data sharing process is inputting the actual business rules and the processes of deciding who gets access. Once the rules have been established, sharing sensitive data can be fast while the data remains secure.
Myth #3: Accessing external data requires building a new data infrastructure
Traditionally, this might be true. In the past, organizations may have had to design a new data system to ingest their external data, and then combine it with their own data. But it takes extra time, extra effort, extra resources—whether in the cloud or on-prem—which means more data silos, because while you have brought the external data in house, it sits in its own bucket, which is not ideal.
In the data cloud you don’t have to build a whole new infrastructure just to have external data available. All the data is available from the beginning, in a single infrastructure with a separation between storage and compute. This means you can use the data sharing capabilities, and sharing data doesn’t put any burden on the infrastructure you pay for. “That is really helpful for data sharing because it means you don’t have to worry about the kind of queries and analysis that others are doing on the data you are sharing, because that is all their responsibility,” Murray explains. “The compute resources that are required by others are not your responsibility. It’s theirs to look after and to pay for. This all-in-one infrastructure is the same as what you are already using, and the external data becomes available.”
Myth #4: It takes time to get access to external data
Often an organization or a team is doing a lot of data analysis and they want to use third-party data to enrich their analysis. Not all of the data is your own, so you might have to purchase it or access it for free somewhere else. This becomes a time-consuming process because you have to send a request to get access to the data. Or you have to make a purchase, then get access to the data, transform it, bring it into your own environment, and then start figuring out how you can best work with it.
That clunky and time-consuming process is simplified with marketplace solutions, where you can access ready-to-query data from a wide range of providers as well as data services and applications, making it easy for you to find external data sets that are helpful to your analysis.
Myth #5: Patients don’t want to share their data
While it may be true that some patients are reluctant when it comes to sharing their data, the core issue might actually center around trust rather than data. This is where having a 360-degree view of the patient becomes critical. Healthcare providers as well as office technology providers need to build that trust, because good use of shared data can produce better outcomes for everyone.
Patients want their data to be secure at all times. They want their medical records to be reliable and confidential, as they have been promised. But at the same time, they also appreciate being provided seamless care where they don’t need to repeat themselves at every visit.
In many instances, patients might agree to share their data for specific purposes—for example, for medical research. If somebody is suffering from a rare disease, it’s in their interest to have their data shared for research purposes, which could help them as well as others with the same diagnosis.
Additionally, there might not be a lot of data points around a rare disease in one region or one country. So accessing shared data for research purposes across the country immediately gives researchers and doctors more information for their analysis and can help them determine the most effective treatment options.
The perception that nobody wants to share their data may not be entirely accurate. “People should always have the right to not share their data,” says Murray. “But if they want to, then we have to facilitate that process in the most secure and effective way possible. That can then really have a positive impact on the care that is being provided.”
More and more healthcare data is being generated and collected than ever before. Accessing, sharing, managing, and using that data to produce better healthcare outcomes does not have to be a daunting, overwhelming task. Modern data platforms allow healthcare providers to securely share and access data across the organization as well as from partners and vendors, and access live and up-to-date data to enrich patient profiles, all resulting in greater overall efficiency. But in the end it’s about making patients’ lives better, whether thanks to that next big medical breakthrough or by ensuring the next step in patient care is the right one.
Learn more about the Snowflake Healthcare and Life Sciences Data Cloud.