X-360° Patient and Physician Views — Use Cases

This is the third in a series of three blog posts that discusses how you can achieve Extended 360° (X-360°) views of patients and physicians through big data analytics. Read our first post defining X-360° and our second post discussing the three primary rules of X-360° views and best practices to develop them.

Where to Start

Your health system has a higher chance of success implementing X-360° patient and physician views by taking “baby steps” and identifying a specific use case to start.

Never initiate a project of this scope without a specific use case in mind.

There are examples where some health systems started aggregating data before deciding the real-world objective. These institutions had mixed success. Instead, choose one area of the organization that can benefit most, or look for a part of the organization that is asking for big data and analytics capabilities.

In addition, keep in mind whether you want to start with a tactical goal or a strategic goal. A tactical goal focuses on a single department’s requirements, such as marketing, the physician liaison’s office, or billing. A strategic goal is more closely aligned with the health system’s executive objectives. Population health is one example of a strategic goal.

Whichever alternative you choose, be sure the platform can support multiple teams within your health system. You want to have one analytics platform that other parts of the health system can utilize, including service line leaders tasked with growing the business, strategic planning, and business development that is focused on building the network, investing in new facilities or services, and so on. More

Krishnan Aghoramurthy

Krishnan Aghoramurthy

Krishnan is a Director of Product Management at Evariant and is responsible for the Healthcare Data Hub: Evariant’s big data streaming analytics engine. Krishnan has over 25 years of experience in technology product management and business development in a range of product areas including supercomputers, software, IT infrastructure and semiconductors. For the last 10 years, Krishnan has been focused on healthcare technology working on product lines ranging from from revenue cycle management, to healthcare data analytics, and 3D bioprinting.
Krishnan Aghoramurthy

Best Practices to Develop X-360° Patient and Physician Views

This is the second in a series of three blog posts that discusses how you can achieve Extended 360° (X-360°) views of patients and physicians through big data analytics. Read our first post defining X-360° and why your organization needs X-360° patient and physician views. The third post in the series will discuss how you can achieve Extended 360° (X-360°) views of patients and physicians through big data analytics.

My 360° Views vs. Your 360° Views

There are some “got-yas” with X-360° views:

  • There is no single 360° view. The components of 360° views are different depending upon the use case. For example, a marketer wants data about emails, websites, search terms, behavior on mobile or social media, time of day, and devices used, and to bring that data together with demographics, buying behaviors, life style trends, etc. Physicians want a clinical profile that aggregates and analyzes data about procedures, drugs, family history, physicians, diagnosis, etc. Every department in a hospital can have at least one 360° view of a patient that is always changing based on business rules and the business problem.

More

Krishnan Aghoramurthy

Krishnan Aghoramurthy

Krishnan is a Director of Product Management at Evariant and is responsible for the Healthcare Data Hub: Evariant’s big data streaming analytics engine. Krishnan has over 25 years of experience in technology product management and business development in a range of product areas including supercomputers, software, IT infrastructure and semiconductors. For the last 10 years, Krishnan has been focused on healthcare technology working on product lines ranging from from revenue cycle management, to healthcare data analytics, and 3D bioprinting.
Krishnan Aghoramurthy