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Automation Filters

Filters allow you to refine when automations run by specifying conditions that must be met. This creates more targeted, efficient automations that only execute when truly relevant.

Understanding Filters​

Filters act as conditional gates that determine whether an automation should proceed to its actions. When a trigger event occurs, all configured filters are evaluated:

  • If all filters pass (return true), the automation actions will execute
  • If any filter fails (returns false), the automation stops and no actions are performed

Filter types

Available Filter Types​

Patient Filters​

The "Patient" filter can be used to specify the patient(s) to which the trigger should be applied. This filter ensures that the trigger is only applied to patients meeting specific criteria, allowing you to customize the automation to operate with precision.

Patient filters can include conditions based on:

  • Demographics (age, gender)
  • Geographic information (zip code, address)
  • Instance assignment
  • Tags and categories
  • Creation or update dates

Observation Filters​

The "Observation" filter type includes two key components:

Observation Code Filter​

The "Observation Code" filter specifies which clinical observations should trigger the automation. This allows you to target automations based on specific types of clinical data, such as:

  • Vital signs (blood pressure, weight, temperature)
  • Lab results
  • Assessment scores
  • Custom observations

Observation Value Filter​

The "Observation Value" filter allows you to set conditions based on the actual measurement values. This creates powerful clinical decision support capabilities by triggering automations only when values meet specific thresholds, such as:

  • Blood pressure exceeding a certain value
  • Lab results in abnormal ranges
  • Assessment scores indicating intervention need
  • Custom thresholds for any measurable value

Task Filters​

Task filters allow automations to execute based on task-related conditions, including:

  • Task status changes
  • Due date proximity
  • Assignment changes
  • Task type specifics
  • Completion status

Filter Operators​

Depending on the field type, different operators are available:

String Operators​

  • equals: Exact match (case-sensitive)
  • not equals: Not an exact match
  • contains: String contains the value
  • does not contain: String does not contain the value

Numeric Operators​

  • equals: Value is exactly equal
  • not equals: Value is not equal
  • greater than: Value exceeds threshold
  • less than: Value is below threshold

Date Operators​

  • equals: Exact date match
  • not equals: Not the specified date
  • before: Date is earlier than specified
  • after: Date is later than specified

Best Practices for Filtering​

  1. Start Specific: Begin with precise filters and broaden if needed
  2. Test Thoroughly: Verify filters work as expected with various test cases
  3. Use Multiple Filters: Combine filters for more precise targeting
  4. Consider Edge Cases: Account for null values, unusual data, and exceptions
  5. Document Purpose: Add comments or descriptions to explain filter logic

Advanced Filter Use Cases​

Clinical Alert Automation​

Combine observation code and value filters to trigger alerts when patients have concerning clinical measurements, such as:

  • High blood pressure readings
  • Abnormal lab results
  • Elevated pain scores

Patient Segmentation​

Use patient demographic filters with clinical data to automatically segment patients into appropriate care pathways:

  • High-risk chronic disease management
  • Preventive care reminders
  • Age and gender-appropriate screenings

Workflow Optimization​

Combine task filters with temporal conditions to improve operational efficiency:

  • Follow-up for tasks not completed within SLA timeframes
  • Reassignment of tasks for absent staff members
  • Escalation of urgent tasks that remain unclaimed