The progressive growth of utilizing data analytics solutions in healthcare settings has facilitated clinical and operational use cases. With that said, large healthcare systems still face significant challenges when trying to understand their complex multi-vendor technology networks. Although there is an abundance of application performance monitoring solutions being used in healthcare settings, there are gaps when trying to make connections between performance monitoring and monitoring system health.
Paragon Consulting Partners’ one-of-a-kind data analytics, Strings by Paragon, is a data analytics platform that helps healthcare IT administrators to better understand the data related to their clinical workflows, the applications being used, and the equipment that supports them. By dynamically collecting and analyzing data from disparate sources, Strings can simplify the management of intricate multi-vendor technology ecosystems. From there, it can analyze and establish relationships and correlations across sources. Enrichment algorithms can be implemented to further analyze data, thereby providing increasingly valuable insights. This enriched data can also be used to make predictions on future trends which can be monitored for any inconsistencies, ultimately helping clients take a more actionable approach to optimizing system, application and clinical workflows. So, how exactly are all these unique features achieved?
What Makes Strings Unique and Special?
Data Collection and Banding
Strings by Paragon is purpose-built to monitor system health and operations. To accomplish this, Strings can pull data across disparate systems and applications, making it easier for users to obtain a more complete picture of their applications, clinical workflows, and operations. To effectively collect data across a multi-vendor healthcare system, Strings has leveraged an advanced graphing database, which applies graph theory, a mathematical structure that is used to model complex relationships between objects that belong to dynamic systems that have many moving parts.
In comparison to traditional relational database management systems, graphing databases do not require a pre-defined schema. Data elements within them can be defined with any number of attributes. This makes it much easier to update attributes and create new relationships between data elements. This means that not only can Strings collect data from multiple systems and applications, but it can also dynamically band these data elements together to form meaningful relationships. As data elements are being banded across systems and applications, we can begin to gain a better understanding of the end-user experiences as they interact with various application systems. Additionally, data banding helps to evaluate the impact any infrastructure bottlenecks have on the end-user’s ability to deliver patient care.
Data Enrichment and Discovery
Strings by Paragon goes beyond simply modeling data. It has applied enrichment algorithms to help answer questions and gain insights about the complexity of multi-vendor technology ecosystems. Through these algorithms, Strings can analyze and enrich the data to understand more about the data elements themselves and how they interact with each other. For example, it can create procedure attributes to enhance the monitoring of archived medical imaging studies. Various event log entries being tracked across applications and web servers can be categorized by event type and then monitored. With these new data attributes, new connections and relationships can be made. By being knowledgeable about the relationships and data structures that comprise the complex infrastructure, decision-making is greatly improved.
String takes it a step further by applying predictive graph algorithms to discover even more. For example, algorithms can be applied to identify communities where data entities have substantial interactions that can further reveal tight node clusters or isolated node groups. More specifically, relevant interactions and behaviours made by application end-users can be grouped together to predict future behaviours and preferences. By exploring these interactions and relationships, predictions can be made about future trends. These predictive trends and data enrichments can be continuously monitored which provides our clients the ability to track system performance and take proactive measures towards preventing adverse system events before clinical workflows are negatively impacted.
Tying it All Together
With these unique features, Strings by Paragon brings together data on clinical and system performance to monitor and measure the possible positive or negative impacts on each other. Not only does Strings leverage advanced software capabilities, but Paragon subject matter experts can also help evaluate the unique challenges healthcare organizations face to add more customization for Strings.
Interested in how Strings by Paragon actually does it? Subscribe to our blog to learn more about what’s under the hood in our next instalment: The How: The Magic Behind Strings by Paragon.