Search Criteria

A SearchCriteria object defines the filtering logic for API search operations. It determines which records to include or exclude from your result set, functioning similarly to a WHERE clause in SQL.

Overview

Search criteria allow you to filter data based on specific conditions. Each criteria definition consists of one or more filter conditions that can be combined using logical operators (AND/OR) and parenthetical grouping to create precise data queries.

Structure of a SearchCriteria Object

Property Type Description
searchConfigId string Identifies which search configuration to use (e.g., "CLAIMBATCH", "CLAIM")
criteria_Key number Unique identifier for saved criteria (system-generated for persistent criteria)
description string Human-readable description of the criteria's purpose
temporary boolean When true, criteria is stored temporarily; when false, it's persisted
criteriaDetails array Collection of individual filter condition objects

Filter Condition Properties

Each object in the criteriaDetails array defines a single filter condition:

Property Type Description
criteria_Table string Database table containing the field to filter
criteria_Column string Column/field name to apply the filter to
criteria_Data_Type string Data type ("string", "number", "date", etc.)
criteria_Operator string Comparison operator ("=", ">", "<", "LIKE", "BETWEEN", etc.)
criteria_From_Value string Primary comparison value (all values are sent as strings)
criteria_To_Value string Optional upper bound for range operations like "BETWEEN"
criteria_Join string Logical operator ("AND", "OR") connecting to the next condition
criteria_Group number Groups conditions with parentheses (same number = same group)

Visual Representation

Basic Single Condition

A simple filter using one condition:

Search Criteria Example

Advanced Multiple Conditions

Complex filtering with logical grouping:

Grouped Search Criteria Example

JSON Examples

Single Condition Example

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{
  "searchConfigId": "CLAIMBATCH",
  "criteria_Key": 84,
  "description": "Claim Batches with Proc Code 99212",
  "temporary": false,
  "criteriaDetails": [
    {
      "criteria_Table": "CLAIMBATCHDETAIL",
      "criteria_Column": "Procedure_Code",
      "criteria_Data_Type": "string",
      "criteria_Operator": "=",
      "criteria_From_Value": "99212"
    }
  ]
}

Multiple Conditions Example

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{
  "searchConfigId": "CLAIM",
  "criteria_Key": 92,
  "description": "High Value Claims from Last Month",
  "temporary": true,
  "criteriaDetails": [
    {
      "criteria_Table": "CLAIM",
      "criteria_Column": "Claim_Amount",
      "criteria_Data_Type": "number",
      "criteria_Operator": ">",
      "criteria_From_Value": "5000",
      "criteria_Join": "AND"
    },
    {
      "criteria_Table": "CLAIM",
      "criteria_Column": "Claim_Date",
      "criteria_Data_Type": "date",
      "criteria_Operator": "BETWEEN",
      "criteria_From_Value": "2023-01-01",
      "criteria_To_Value": "2023-01-31"
    }
  ]
}

Implementation Best Practices

Transient vs. Persistent Criteria

For One-Time Searches

Use "In Memory" criteria when executing one-time or ad-hoc searches. This approach prevents unnecessary storage in the CriteriaTable, reducing database overhead.

For Temporary Use (temporary: true)

  • Criteria are stored transiently in the system
  • Each SearchConfig maintains the five most recent temporary criteria for quick reuse
  • Ideal for criteria you may need again in the short term but don't need permanently

For Long-Term Use (temporary: false)

  • Criteria are persisted indefinitely in the database
  • Recommended for:
    • Frequently used search patterns
    • User-defined filters
    • Report templates
    • Common query definitions

Performance Optimization

  • Minimize conditions : Include only necessary filter conditions
  • Leverage indexed columns : Prioritize filtering on indexed fields when possible
  • Break down complex queries : For intricate search needs, consider multiple smaller, targeted criteria
  • Order conditions efficiently : Place the most restrictive conditions first when filtering large datasets