One of the industries that have benefited most from the upgraded modern data architecture is healthcare and life sciences. Whether it’s new HealthTechs aiming to improve health in a disruptive way, or traditional healthcare companies and organizations.
There is a tremendous amount of data within the Healthcare and Life sciences industries. The growth and availability of data and the ability to store this data have led to opportunities that are both financially important, and even more importantly could save lives or improve quality of life.
Data Access Challenges
Most organizations who use cloud-based data storage struggle with securing data access and governance. This is further compounded and increasingly more difficult for healthcare and life science companies.
We outline some of the general issues for data governance in the cloud here. In summary, there are a number of difficulties with cloud-based data governance such as tracking data that changes rapidly, continuously masking sensitive PHI and PII data, pinpointing data ownership, serving a large number of data users, and the complexity of keeping the data secure and compliant.
The healthcare industry was one of the most impacted industries from the great data evolution over the last several years. This advancement has come in the form of data storage, processing and analytics.
This is because there are a lot of use-cases where having a large amount of data (from different monitoring devices, tests, etc) over time can add significant value.
The growth of databases, warehouses, and lakes have increased the variety of cheap and elastic cloud data storage. Since healthcare data is so valuable, the ability to store it cheaply and easily has led to the significant growth of the available healthcare data, spurring on massive technological innovations within the industry.
This data is easily accessible, maybe too much so, as the BI and machine analytics tools have simultaneously advanced, providing analytical mechanisms through which to gain value from the wealth of data collected. The benefits of this data is that healthcare professionals, organizations, and analysts can use this information to improve the quality and quantity of health care.
Despite the tremendous value in adopting modern data technologies, these are not “low-hanging fruits”. As most healthcare companies are handling a lot of sensitive data, adoption of cloud computing for data analytics can encounter objections and delays. These delays are primarily concerning the highly vulnerable security risks, as well as stringent compliance hurdles.
Let’s look at some of these obstacles:
Given the highly private and sensitive nature of healthcare and life science data there are strict regulations regarding its collection, use, and storage. HIPAA or HITRUST strictly governs the use and collection of healthcare data.
In addition to ensuring compliance with HIPAA and HITRUST regulations, there are also compliance and privacy issues related to the use of healthcare data by data partners. This is due to the processes surrounding the handing of PII which are also strictly governed. The sharing of this information must also be highly protected.
Healthcare data tends to be highly fragmented across multiple data warehouses, stores, and lakes. For healthcare and life science professionals and their partners to make effective use of this data requires that it is shared between a highly distributed network of data consumers. This can be very difficult to achieve based on the different access controls and the necessary masking of PII. In these cases there are no easy ways to control which employees have access to what data. This not only opens the company up to significant data risks but also places a tremendous burden on the data engineering team to navigate the labyrinth of compliance and regulations, grant and revoke access, and continuously locate and mask sensitive data.
For more information on this topic take a look at our blog post about why cloud data governance is difficult.
The data is not only valuable to the companies. Healthcare data is highly valuable leaving it exposed to high-risk threats and breaches. The average cost of a healthcare breach increased by $1 million to a record high of $10.1 million in 2022 (IBM and HIPAA journal)
In other words, the security, data, governance, and privacy teams have to balance the need to be innovative and competitive with all these obstacles and risks.
How Satori Helps
Some of our customers are coming from such industries and are facing the same problems. Satori solves these problems for data accessed in databases, data warehouses and data lakes. Here are some of the ways in which Satori helps:
- Satori continuously discovers and classifies sensitive data, and allows companies to place security policies that will automatically be enforced even when sensitive data is found in new locations.
- Security policies can be applied from a single location to all data platforms.
- Satori allows differential data masking, where different teams will get different (redacted, hashed or masked) versions of the data, across all data platforms.
- Satori provides full visibility into sensitive data in the organization with a continuously updated data inventory, and a data access audit across all data platforms.
For more information, and a personalized demo, please set a meeting with one of our experts.