The Clinia Resource Management

The Clinia Platform consists of two main functions based on the specific use case: Data Management and Search Experience. Due to its modular design, organizations have the flexibility to utilize specific infrastructure module(s) necessary to meet their unique needs and support their intended use case.

Clinia Data Management

Clinia Data Management helps your organization to ingest multiple sources of data, each with its unique schema, automate the reconciliation or deduplication of similar records to create a master view, and make an entire record or defined view available for access via API or search using the Clinia Health-grade Search.

Incoming Data

Data Sources

A Clinia Workspace requires at least one Data Source - a link to an external data store connected to the Clinia ingestion pipeline. Supported Data Sources include a database, a server, or a file (eg JSON, XML or CSV). Each Data Source is individually configurable, based on the type.

How to create a Data Source

How to send data in a Data Source

Data Augmentation

Incoming data can be augmented and enriched at the time of ingestion. A typical configuration for Profile data might include address validation or geocoding of an address.

(Coming Soon) How to configure Data Augmentation

Managing Data

Once the system has ingested data, it is ready for processing and matching with existing records. For implementations which use the MDM, importantly from the view of a User, the data is not yet accepted and accessible in the system until it has been processed by the MDM and the rules defined by Record Reconciliation.

Record Reconciliation

Reconciliation rules allow your team to define criteria to link records together, under a Unified Record. Those rules are defined by a set of matching criteria, applied to every record. Matching criteria can include one or more match rules, like an EXACT MATCH of Property A (eg Matching two providers with the same Practice Number and Practice Province Code).

If a Record successfully completes Reconciliation, it is accepted by the system and is linked under a Unified Record. This is now available in a Data Partition.

If a Record does not complete Reconciliation (for example, only a partial match or some other rule) it will be included as an Item in a Queue for manual review.

Queues

Queues are a list of records or resources that require manual intervention or processing, typically by a data steward. Each queue is defined by either Reconciliation Rules (incoming data to the system), or data management rules (from data already accepted in the system).

Viewing a Resource

Once a record is accepted by the system, it can now be viewed as a Resource.

Views of Data

Now that you have a Unified Record, you can create unique or proprietary views of each Record based on the Data Source or a specific attribute, through a Data Partition. If an implementation does not use the MDM, incoming data from a data source is accessible directly in a Data Partition.

Data Partition

The Data Partition is responsible for the storage and making accessible a virtual subset of data coming from a single Data Source, or multiple ones once the reconciliation rules are applied. This is where any Resource can be queried via Clinia Search.

How to create a Data Partition

The Clinia Search Experience

Clinia Search Experience allows your organization to surface the most relevant resources contained in your environment, and create seamless user experiences.

How to use the Search

Impacting Search Results

Relevance

Clinia's search engine's primary objective is to identify all records, in a given Data Partition, that correspond to a given query and subsequently arrange them in order of relevance, with the most suitable ones appearing at the top of the search results.

Depending if you are using the Standard Search our Clinia's Health Grade Search, the criteria to define every record relevancy will change to adapt to the given use-case.

Personalization

Clinia also allows search results to be influenced by given rules to enhance the relevancy of results for users by allowing the use of:

Business rules: Higher scoring relevancy depending on specific record criteria
User signals: Preferences, characteristics, location, ...