Bulletin: Composed Classifiers

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Introduction

All Emergency Department Registration data coming into EpiCenter is automatically classified by the system. Classifications are categories or tags associated with each healthcare interaction that are used by EpiCenter’s Syndromic Surveillance and other analyses. Classifiers are groupings of conceptually similar classifications. 

Classifications for Acute Care Interactions are based on an individual data field. Most commonly this is the “chief complaint” field, but others such as diagnosis code can be considered as well. Health Monitoring also supports the definition of “composed classifiers”, which combine evidence across multiple classifications. This bulletin provides more detail about composed classifiers and how they work.

Details of Clarification

Evidence Classifications

EpiCenter’s system classifications for acute care interactions are based on individual, discrete pieces of evidence. Many classifications are based on chief complaint, medical notes, or observations, all of which are free-text fields. Classifications based on free-text fields are defined by the inclusion of one or more words or phrases and an optional list of negative words or phrases. If an interaction’s text field matches the definition of the classification, the classification will be tagged to the interaction. An interaction can have multiple classifications from multiple classifiers applied to it. 

To use a simplified example, the “Suicidal Ideation” chief complaint evidence classification searches for chief complaints that include the word “suicide” but not the phrases “denies self-harm” or “accident.”

Other classifications are based on diagnosis code. Instead of parsing a free-text field, these classifications simply search for a specific diagnosis code or codes. For example, the “Flu Diagnosis” evidence classification looks for ICD9 or ICD10 codes corresponding to influenza.

Composed Classifiers

Composed classifiers are based on multiple pieces of evidence, using combinations of classifications. Composed classifiers can use the logical operations AND, OR, and NOT.

For example, the “Suicidal Ideation” composed classifier looks for interactions tagged with either the “Suicidal Ideation” chief complaint evidence classification described above, OR the “Suicidal Ideation” classification based on diagnosis code OR the “Suicidal Ideation” classification based on text evidence found in medical notes.

Figure 1 – Suicidal Ideation Composed Classifier Flow Chart

 

As another (simplified) example, the “COVID-19 Symptoms (Broad)” composed classifier looks for interactions tagged with EITHER the “COVID-19” diagnosis evidence classification OR a “Fever” classification from chief complaints, medical notes, or vital signs AND at least one of a “Cough” or “Dyspnea” classification from chief complaints or medical notes AND NOT an “Influenza” diagnosis classification.

Figure 2 – Simplified COVID-19 Symptoms (Broad) Composed Classifier Flow Chart

 

Impact

No changes are planned to existing system classifiers or classifications. Development of new composed classifiers can be supported as a customization.

Bulletin: Data Flow from Facilities to EpiCenter

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Introduction

EpiCenter uses healthcare data as the input for Syndromic Surveillance, Visit Monitoring, Treatment Monitoring, and custom reports.. This bulletin provides specifics around how data flows from facilities to EpiCenter.

Figure 1 – Data Flow from Hospital to EpiCenter

Clarification on Data Flow

Hospital Systems

Facilities send electronic healthcare data to EpiCenter according to Health Monitoring’s Data Transmission Guidelines. The primary data format supported is the Health Level Seven (HL7) standard, with limited support available for CSV, TXT, CDA, and XML formats. The HL7 standard defines the language, structure, and data types for packaging and sending electronic health information and is platform-independent. Health Monitoring captures a limited patient-specific dataset for use in EpiCenter and supports transmission of facility data that accords with The Public Health Information Network (PHIN) Messaging Guide for Syndromic Surveillance.

Because HL7 is already used in virtually all healthcare facilities, there is minimal effort required from facility personnel to set up a connection with Health Monitoring Systems via VPN. The VPN provides a dedicated, secure network tunnel for a facility, enabling a one-to-one, encrypted connection to Health Monitoring servers.

Mergence and Health Central Databases

After being sent from a facility, encrypted HL7 messages are stored in Health Monitoring’s Mergence database. Mergence is a high-performance data processing system that is resilient to failure, supporting hundreds of simultaneous data connections. From Mergence, EpiCenter’s sender configuration assigns each HL7 message to a “router worker” based on the sending facility so that messages from a given facility are processed in chronological order. The number of router workers is elastic and can be ramped up or down depending on incoming message volume. Once a message is assigned to a router worker, it is decrypted and sent to a second database, Health Central.

When a message arrives in the Health Central database its data is extracted and transformed into various relational tables which makes querying the data more efficient. The Health Central database is the basis for the EpiCenter application, its surveillance tasks, and all other analyses.

The Vault

While most data collected for use in EpiCenter is considered a limited dataset by HIPAA, there are some components such as clinician notes that may contain more sensitive information. These fields are encrypted and stored in the “Vault”, a separate component from Health Central. For more details on the Vault, please see the “Reviewing Vault Access by Users” bulletin.