This article, originally published on Government Technology Insider last week, takes a look at how NYC Health + Hospitals has taken control of its data in order to deliver better patient outcomes and streamline operations. By using a data cloud organizations are able to centralize data access and streamline data governance, which makes data ready for use by applications, including AI.
Read on to learn more.
In a recent webinar, Kyle Rourke, Head of Platform Strategy at Snowflake, summarized a large issue facing many agencies today when stating that “the biggest problem in data today is that data is everywhere. It’s stuck in a million different places and it’s really hard to get access to.” This lack of accessibility to data inhibits agencies to gain value from the data that is siloed.
The large amounts of data can simply come from “having different types of applications that are actually creating data. A lot of customers have IoT systems and so that creates data in a different type of format that is typically created by things like ERP systems and CRM tools. So, they end up having to have multiple separate systems for those two and that creates problems,” said Rourke.
Through the use of a Data Cloud, agencies are able to access all of the data both inside and outside the agency in a single place by using agency data (partners, suppliers, customers) and the solution’s data (industry datasets, data services, applications). Additionally, strong governance and controls are important to “understand and classify data across your entire ecosystem,” commented Rourke. The Data Cloud helps to unify security and establish a flexible control over the data. By taking action through the Data Cloud, agencies are able to “safely build datasets and share them with others throughout the network,” said Rourke.
NYC Health + Hospitals, the largest public healthcare system in the nation, uses the Data Cloud to help serve the network of 11 acute care facilities. With an annual visit volume of over 1.4 million visitors and over 42,000 employees, the hospital system faces several challenges when it comes to managing their data.
Kris Komanduri, Head of Enterprise Information Management, Sr. Director at NYC Health + Hospitals, commented that the three main challenges are the absence of enterprise data warehouse, the lack of data and analytics strategy, and the inability to collaborate.
With the absence of enterprise data warehouse, there were “several silos and fragmented data repositories that existed to support basic analytical needs,” but there were issues with data cleansing and consolidation, according to Komanduri. Additionally, “achieving timeliness and completeness of data was very difficult and enforcing data classification was not possible.”
The lack of data and analytics strategy led to the system maintaining “inconsistent adoption of business and technical definitions,” said Komanduri. This inconsistency heavily impacted the data quality throughout the hospital system. Other issues stemming from a lack of strategy included not being able to establish “a visual and advanced predictive analytic framework” and an inability to add “modem capital capability capabilities such as Master Data Management (MDM), artificial intelligence, and machine learning.”
Through the inability to collaborate, the hospital system could not establish a secure connection to “send data from a central repository to external agencies and authorized partners,” commented Komanduri.” This led to unavoidable “multi-step digital footprints of valuable and sensitive healthcare data.” Being unable to collaborate also meant that “data mining to support end-to-end analysis could not be accomplished and data curation from legacy systems and current state systems had challenges and was extremely cumbersome.”
With the use of the Data Cloud, the NYC Health + Hospitals healthcare system was able to find a solution and confront these challenges. By building an enterprise data warehouse, the system to combat the building issues and figure out ways to successfully manage their data.
Vernon Tan, Industry Sales Engineering, commented that “the goal of the data cloud is to eliminate data silos altogether. The Data Cloud is a global network for thousands of organizations mobilized data with near unlimited scale concurrency and performance. It’s about removing barriers between the agency and the data by providing innovative ways to unlock an entirely new frontier of technical and business outcomes.”
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