Srinivasan Sundararajan

360 Degree View of Patient

With rising demands for quality and cost-effective patient care, healthcare providers are focusing on data-driven diagnostics while continuing to utilize their hard-earned human intelligence. In other words, data-driven healthcare is augmenting human intelligence.

360 Degree View of Patient, as it is called, plays a major role in delivering the required information to the providers. It is a unified view of all the available information about a patient. It could include but is not limited to the following information:

  • Appointments made by the patients
  • Interaction with different doctors
  • Medications prescribed by the doctors
  • Patient’s relationship to other patients within the eco-systems specially to identify the family history related risks
  • Patient’s admission to hospitals or other healthcare facilities
  • Discharge and ongoing care
  • Patient personal wellness activities
  • Patient billing and insurance information
  • Linkages to the same patient in multiple disparate databases within the same hospital
  • Information about a patient’s involvement in various seminars, medical-related conferences, and other events

Limitations of Current Methods

As evident in most hospitals, these information are usually scattered across multiple data sources/databases. Hospitals typically create a data warehouse by consolidating information from multiple resources and try to create a unified database. However, this approach is done using relational databases and the relational databases rely on joining tables across entities to arrive at a complete picture. The RDBMS is not meant to handle relationships which extend to multiple hops and require drilling down to many levels.

Role of Graph Technology & Graph Databases

A graph database is a collection of nodes (or entities typically) and edges (or relationships). A node represents an entity (for example, a person or an organization) and an edge represents a relationship between the two nodes that it connects (for example, friends). Both nodes and edges may have properties associated with them.

While there are multiple graph databases in the market today like, Neo4J, JanusGraph, TigerGraph, the following technical discussions pertain to graph database that is part of SQL server 2019. The main advantage of this approach is that it helps utilize the best RDBMS features wherever applicable, while keeping the graph database options for complex relationships like 360 degree view of patients, making it a true polyglot persistence architecture.

As mentioned above, in SQL Server 2019 a graph database is a collection of node tables and edge tables. A node table represents an entity in a graph schema. An edge table represents a relationship in a graph. Edges are always directed and connect two nodes. An edge table enables users to model many-to-many relationships in the graph. Normal SQL Insert statements are used to create records into both node and edge tables.

While the node tables and edge tables represent the storage of graph data there are some specialized commands which act as extension of SQL and help with traversing between the nodes to get the full details like patient 360 degree data.

MATCH statement

MATCH statement links two node tables through a link table, such that complex relationships can be retrieved. An example,

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SHORTEST_PATH statement

It finds the relationship path between two node tables by performing multiple hops recursively. It is one of the useful statements to find the 360 degree of a patient.

There are more options and statements as part of graph processing. Together it will help identify complex relationships across business entities and retrieve them.

GRAPH processing In Rhodium  

As mentioned in my earlier articles (Healthcare Data Sharing & Zero Knowledge Proofs in Healthcare Data Sharing), GAVS Rhodium framework enables Patient and Data Management and Patient Data Sharing and graph databases play a major part in providing patient 360 as well as for provider (doctor) credentialing data. The below screen shots show the samples from reference implementation.

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Patient Journey Mapping

Typically, a patient’s interaction with the healthcare service provider goes through a cycle of events. The goal of the provider organization is to make this journey smooth and provide the best care to the patients. It should be noted that not all patients go through this journey in a sequential manner, some may start the journey at a particular point and may skip some intermediate journey points. Proper data collection of events behind patient journey mapping will also help with the future prediction of events which will ultimately help with patient care.

Patient 360 data collection plays a major role in building the patient journey mapping. While there could be multiple definitions, the following is one of the examples of mapping between patient 360-degree events and patient journey mapping.

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The below diagram shows an example of a patient journey mapping information.

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Understanding patients better is essential for improving patient outcomes. 360 degree of patients and patient journey mapping are key components for providing such insights. While traditional technologies lack the need of providing those links, graph databases and graph processing will play a major role in patient data management.

About the Author –

Srini is the Technology Advisor for GAVS. He is currently focused on Data Management Solutions for new-age enterprises using the combination of Multi Modal databases, Blockchain and Data Mining. The solutions aim at data sharing within enterprises as well as with external stakeholders.