Definition
The Immunisation data model provides a comprehensive record of patient immunisation information derived from observation data. It captures coded immunisation entries recorded by clinicians, including the associated clinical code, vaccination details, date of administration, and contextual consultation information. This model is essential for understanding a patient’s vaccination history and supporting public health reporting across healthcare services.
Information
Section titled “Information”The Immunisation data model is a structured representation of immunisation observations recorded against patients in EMIS Web. Each immunisation record is derived from the broader observation data and filtered specifically to entries categorised as immunisations.
Each immunisation record is uniquely identified by a combination of
observation_id and organisation, ensuring a distinct entry for every
immunisation within a specific healthcare organisation.
This model includes some of the key identifiers:
- observation_id: The unique internal identifier for the observation record.
- observation_guid: GUID for the observation record
- observation_uuid: UUID for the observation record
The following datetime fields are important for tracking data lineage and freshness:
- is_deleted: Indicates whether the immunisation record has been soft-deleted in the source system.
- is_sensitive: Indicates whether the record is flagged as sensitive.
- is_confidential: Indicates whether the record is confidential.
- transform_datetime: The timestamp indicating when the record was last processed in the data warehouse.
Overview
Section titled “Overview”flowchart TB
subgraph container["Data Collection"]
n10["Vaccine Code"]
n11["Administration Dates"]
n12["Batch & Manufacturer Details"]
end
n17["Organisation 1"] --> n7
n17["Organisation 1"] --> n5
n18["Organisation 2"] --> n6
n18["Organisation 2"] --> n8
n18["Organisation 2"] --> n4
n7["Patient 123"] --> container
n5["Patient 98"] --> container
n6["Patient 456"] --> container
n4["Patient 20"] --> container
n8["Patient 47"] --> container
container --> n13["Gather Immunisation Data"]
n13 --> n14["ETL"]
n14 --> n15["Immunisation Data Model"]
n7["Patient 123"]:::rect
n5["Patient 98"]:::rect
n6["Patient 456"]:::rect
n4["Patient 20"]:::rect
Changes in iPCV v2
Section titled “Changes in iPCV v2”1. Removal of Columns
Section titled “1. Removal of Columns”Several columns previously available directly in the immunisation (v1) table have been removed from the immunisation_v2 (v2) table. These include:
Why?
These columns have been removed to streamline the data model and maintain a single source of truth for reference data:
- MKB reference columns: No longer included to reduce complexity and avoid duplication, as this data is now available through dedicated reference tables
- Patient opt flags columns: Removed as these flags are maintained in the patient scope dimension table, providing a single source of truth
| Decommissioned Column | Relevant ID / Column | Reason / Extended Data Model to be Referred |
|---|---|---|
other_code | code_id | codeable_concept_v2 |
other_code_system | code_id | codeable_concept_v2 |
other_display | code_id | codeable_concept_v2 |
readv2_code | code_id | codeable_concept_v2 |
snomed_concept_id | code_id | codeable_concept_v2 |
snomed_description_id | code_id | codeable_concept_v2 |
confidential_patient_flag | patient_id | patient_v2 |
dummy_patient_flag | patient_id | patient_v2 |
non_regular_and_current_active_flag | patient_id | patient_v2 |
opt_out_93c1_flag | patient_id | patient_v2 |
opt_out_9nd19nu09nu4_flag | patient_id | patient_v2 |
opt_out_9nd19nu0_flag | patient_id | patient_v2 |
opt_out_9nu0_flag | patient_id | patient_v2 |
regular_and_current_active_flag | patient_id | patient_v2 |
regular_current_active_and_inactive_flag | patient_id | patient_v2 |
regular_patient_flag | patient_id | patient_v2 |
sensitive_patient_flag | patient_id | patient_v2 |
data_filter | Removed as it is deprecated in v2 | |
_record_version | No longer available in v2 | |
_update_date | Changes tracked differently in v2 | |
_update_hour | Changes tracked differently in v2 |
Customer benefit
- Single source of truth for patient flags through the patient scope dimension table
- Reduced risk of data inconsistencies and synchronization issues
- Improved data lineage tracking with centralized reference tables
Customer action
- Review and update any processes or integrations that relied on the removed columns
- Use dedicated MKB reference tables for code mappings instead of inline columns
- Query the patient scope dimension table for patient opt flags and status information
- Ensure that any necessary mappings or transformations are adjusted accordingly
2. NULL value columns
Section titled “2. NULL value columns”Several columns in the immunisation_v2 table now consistently return NULL values and have been retained for backward compatibility. These include:
Why?
These columns are retained to maintain backward compatibility while returning NULL values to ensure consistent behavior in downstream processes.
| Deprecated Column | Replacement ID / Column | Reason / Extended Data Model to be Referred |
|---|---|---|
emis_enteredby_userinrole_guid | entered_by_user_in_role_id | user_in_role_v2 |
emis_authorising_userinrole_guid | authorising_user_in_role_id | user_in_role_v2 |
practitioner_id | authorising_user_in_role_id | user_in_role_v2 |
registration_ods_code | Always NULL as it is deprecated in v2. | |
processing_id | Always NULL as it is deprecated in v2 |
Customer benefit
- User in role information is now standardized through
entered_by_user_in_role_idandauthorising_user_in_role_idforeign keys joined withuser_in_role_v2 - Reduced risk of unexpected behavior in downstream processes
- Clear distinction between deprecated columns and new standardized relationships
Customer action
- Identify any queries or reports that use the deprecated columns
- Update processes to use
entered_by_user_in_role_idandauthorising_user_in_role_id, joining withuser_in_role_v2to retrieve user in role details
3. Addition of new columns
Section titled “3. Addition of new columns”The v2 immunisation model introduces additional columns to enhance auditability, relationships, and vaccine administration details. These include:
User tracking columns:
entered_by_user_in_role_idauthorising_user_in_role_id
Relationship and context columns:
observation_idparent_observation_idparent_observation_guidparent_observation_uuidconsultation_idproblem_observation_idproblem_observation_guidproblem_observation_uuidproblem_end_datetimeepisodicityepisodicity_descriptionobservation_organisation_idis_parentis_abnormalassociated_text
Numeric and range columns:
numeric_operatornumeric_valueunit_of_measureuom_dmducum_coderange_minimum_operatorrange_minimumrange_minimum_textrange_maximum_operatorrange_maximumrange_maximum_textrange_unitsrange_qualifier_descriptionqualifier_mapping
Why?
These columns have been added to enhance the data model:
- User tracking columns: Enable auditing and lineage tracking by providing
standardized foreign keys to the
user_in_role_v2table, replacing the previously nullable GUID columns - Relationship and context columns: Support hierarchical immunisation structures, link immunisations to consultations and problems, and provide clear organisational context
- Numeric and range columns: Standardize how vaccine doses and measurements are represented with operators, units of measure, and reference ranges for dosing schedules and administration guidelines
Customer benefit
- Improved data consistency through standardized foreign key relationships
- Enhanced ability to track immunisation hierarchies and linked clinical context
- Accurate vaccine dose interpretation with standardized operators and units
- Comprehensive reference range information for vaccination schedules
- Better temporal and encounter-based analysis capabilities
Customer action
- Join user tracking columns with
user_in_role_v2for audit trails - Use relationship columns to build hierarchical immunisation structures and link to consultations and observations.
- Incorporate vaccine administration columns when analysing doses to ensure correct interpretation
- Utilize range columns for dosing schedules and administration guidelines
Examples
Section titled “Examples”Get all immunisations for a patient
SELECT *FROM hive.explorer_ipcv_vanilla.immunisation_v2WHERE patient_id = 123456789LIMIT 100Find sensitive or confidential immunisations
SELECT *FROM hive.explorer_ipcv_vanilla.immunisation_v2WHERE is_sensitive = TRUE OR is_confidential = TRUELIMIT 100Get immunisations with SNOMED mapping for interoperability
SELECT i.observation_id, i.code_id, i.original_term, i.batch_number, i.manufacturer, m.snomed_concept_id, m.snomed_description_idFROM hive.explorer_ipcv_vanilla.immunisation_v2 iLEFT JOIN hive.explorer_ipcv_vanilla.mkb_mapping_dmdpreparation_v2 m ON i.code_id = m.emis_code_id AND i.organisation = m.organisationWHERE m.snomed_concept_id IS NOT NULLLIMIT 100