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Your Patient Journey Data Template

Oracle Health (Cerner)

Patient Journey Attributes (20) Patient Journey Activities (14) Extraction Guides (2)

Your Patient Journey Data Template

This comprehensive template outlines the essential data you need to effectively analyze and optimize patient journeys. It provides a structured overview of the critical attributes to collect, the key activities to track, and practical guidance on data extraction. Use this resource to prepare your event log for a seamless process mining experience.

Recommended attributes to collect
Key activities to track
Extraction guidance

New to event logs? Learn how to create a process mining event log.

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Patient Journey Attributes

These are the recommended data fields to include in your event log for a comprehensive analysis of the patient journey within your system.

5 Required 9 Recommended 6 Optional

	Name	Description
	Activity ClinicalEventTag	The name or description of the clinical or administrative event performed.
Description This attribute captures the specific action taken during the patient's care, such as 'Medication Administered', 'Vital Signs Taken', or 'Patient Discharged'. It provides the human-readable label for the process step. In Cerner, this is often derived from the `CLINICAL_EVENT` table, specifically mapping the `EVENT_CD` (Event Code) to its display value or using the `EVENT_TAG`. Consistent naming conventions here are crucial for readable process maps. Why it matters Defines the steps in the process map, enabling the visualization of the workflow. Where to get Table: CLINICAL_EVENT, Column: EVENT_TAG or linked CODE_VALUE for EVENT_CD Examples Triage AssessmentCBC with DifferentialDischarge OrderTransfer Patient
	Event Timestamp EventEndDateTime	The specific date and time when the activity occurred or was completed.
Description This attribute records the precise moment an event took place. It is used to order activities sequentially and calculate cycle times between process steps. In the `CLINICAL_EVENT` table, this usually corresponds to `EVENT_END_DT_TM`. Accuracy here is vital for calculating wait times, such as the duration between 'Patient Registered' and 'Triage Assessment'. Why it matters Essential for determining the sequence of events and calculating performance KPIs like lead times. Where to get Table: CLINICAL_EVENT, Column: EVENT_END_DT_TM Examples 2023-10-15T08:30:00Z2023-10-15T09:15:45Z2023-10-16T14:20:00Z
	Patient Episode EncounterId	Unique identifier for the specific patient visit or episode of care.
Description This attribute serves as the central case identifier for the patient journey. It groups all clinical events, orders, and administrative actions occurring within a single period of care (e.g., an inpatient stay or an emergency visit). In process mining, this ID is essential for correlating disjointed activities into a unified process view. Technically, this corresponds to the `ENCNTR_ID` in the `ENCOUNTER` table within the Cerner Millennium database. It is the primary key used to link patient demographics, orders, and clinical events. Why it matters It is the fundamental key required to reconstruct the end-to-end patient journey from admission to discharge. Where to get Table: ENCOUNTER, Column: ENCNTR_ID Examples 123456789876543211223344
	Last Data Update LastDataUpdate	The timestamp when the record was extracted or last modified in the warehouse.
Description Indicates the freshness of the data used in the analysis. This timestamp helps users understand if they are looking at real-time data or a snapshot from a previous load. It is typically generated during the ETL (Extract, Transform, Load) process rather than being a clinical attribute. Why it matters Critical for data governance and ensuring analysis is performed on up-to-date information. Where to get ETL System Timestamp Examples 2023-11-01T00:00:00Z2023-11-02T12:00:00Z
	Source System SourceSystem	The name of the system where the data originated.
Description Identifies the source application for the data record. In this context, it will predominantly be 'Oracle Health' or 'Cerner Millennium'. This is useful in multi-system environments where data might be blended with other EMRs or departmental systems. It allows analysts to filter or segment the process analysis based on data provenance if multiple sources are ingested. Why it matters Ensures data lineage and traceability, especially in multi-system process mining setups. Where to get Hardcoded string or System Metadata Examples Oracle HealthCerner Millennium
	Case Type EncounterType	Categorization of the patient visit, such as Inpatient, Outpatient, or Emergency.
Description Classifies the nature of the patient episode. This is a primary dimension for slicing the data, as the process flow for an 'Emergency' visit differs significantly from an 'Elective Inpatient' visit. This is derived from `ENCNTR_TYPE_CD` in the `ENCOUNTER` table, which references a code set value (e.g., 'Inpatient', 'Emergency'). Why it matters Allows for comparative analysis of pathways and throughput across different care settings. Where to get Table: ENCOUNTER, Column: ENCNTR_TYPE_CD (resolve via CODE_VALUE) Examples InpatientEmergencyOutpatientDay Surgery
	Department NurseUnit	The specific ward, unit, or department where the event occurred.
Description Identifies the physical location or organizational unit responsible for the patient at the time of the event (e.g., 'ICU', 'General Surgery', 'Emergency Dept'). This helps in the 'Inter-Ward Transfer Efficiency' dashboard by tracking movement between units. In Cerner, this is often `LOC_NURSE_UNIT_CD` on the encounter or tracking table. Why it matters Essential for analyzing bottlenecks in specific departments and visualizing patient flow geography. Where to get Table: ENCOUNTER or CLINICAL_EVENT, Column: LOC_NURSE_UNIT_CD Examples Emergency DeptCardiology WardICURadiology
	Discharge Status DischargeDisposition	The destination or status of the patient upon discharge.
Description Indicates where the patient went after the episode ended (e.g., 'Home', 'Skilled Nursing Facility', 'Expired'). This is critical for the 'Discharge Planning' analysis and identifying unsuccessful outcomes. Found in the `ENCOUNTER` table as `DISCH_DISPOSITION_CD`. Why it matters Key outcome metric; defines the 'end state' of the patient journey. Where to get Table: ENCOUNTER, Column: DISCH_DISPOSITION_CD (resolve via CODE_VALUE) Examples Discharged to HomeTransferred to RehabLeft Against Medical AdviceExpired
	Is Readmission IsReadmission	Flag indicating if this episode occurred within 30 days of a previous discharge.
Description A boolean flag used to identify cases that represent a readmission. This is calculated by comparing the admission date of the current episode with the discharge date of the previous episode for the same `PersonId`. Essential for the 'Patient Readmission Trends' dashboard. Why it matters Directly supports the 'Patient Readmission Rate' KPI, a key quality of care metric. Where to get Derived via SQL Logic comparing ENCOUNTER records Examples truefalse
	Length of Stay LengthOfStay	Total duration of the patient episode in days or hours.
Description This is a calculated attribute representing the time difference between the admission timestamp and the discharge timestamp. It is the primary efficiency metric for the 'Overall Patient Length of Stay Analysis' dashboard. While this can be calculated within the process mining tool, importing it as a pre-calculated static attribute on the case level is often performance-efficient. Why it matters The single most important efficiency KPI for hospital management. Where to get Derived from ENCOUNTER.REG_DT_TM and DISCH_DT_TM Examples 4.5 days2 hours12 days
	Order Item OrderMnemonic	The name of the specific order placed, such as a lab test or medication.
Description Describes the content of an order event (e.g., 'Complete Blood Count', 'Aspirin 81mg'). This attribute provides necessary context for 'Diagnostic Order Placed' and 'Medication Administered' activities. It is typically found in the `ORDERS` table under `ORDER_MNEMONIC`. It acts as the 'Product' flowing through the process. Why it matters Necessary for granular analysis of diagnostic and treatment pathways. Where to get Table: ORDERS, Column: ORDER_MNEMONIC Examples Chest X-RayBasic Metabolic PanelAcetaminophenMRI Brain
	Patient ID PersonId	Unique identifier for the patient across multiple encounters.
Description Distinct from the Case ID, the Patient ID (or Person ID) remains constant for a patient across all their visits to the hospital. This attribute is crucial for analyzing readmission rates and understanding the patient's long-term history. In Cerner, this is the `PERSON_ID` from the `PERSON` table. It links multiple `ENCNTR_ID` records together. Why it matters Enables the 'Patient Readmission Rate' KPI by linking separate episodes to the same individual. Where to get Table: PERSON, Column: PERSON_ID Examples P10001P55992P99221
	Primary Diagnosis DiagnosisCode	The ICD-10 or SNOMED code representing the primary reason for care.
Description The standardized clinical code (e.g., 'J18.9' for Pneumonia) assigned to the episode. This allows for grouping patients by condition to analyze 'Treatment Protocol Deviation' for specific diseases. Found in the `DIAGNOSIS` table, linked to the encounter. Why it matters Enables apples-to-apples comparison of patient pathways for specific conditions. Where to get Table: DIAGNOSIS, Column: DIAGNOSIS_CODE (via nomenclature) Examples I10E11.9J18.9
	User PerformingPrsnlId	The identifier or name of the clinician who performed the activity.
Description Captures who executed the process step, such as the nurse administering medication or the doctor signing the discharge. This allows for resource utilization analysis. In Cerner, this is often `PERFORMED_PRSNL_ID` or `UPDT_ID` depending on the table (Orders vs Clinical Events). Mapping this to a generic 'User' attribute facilitates Segregation of Duties analysis. Why it matters Supports resource analysis and identifies potential training needs or workload imbalances. Where to get Table: CLINICAL_EVENT, Column: PERFORMED_PRSNL_ID Examples Dr. SmithRN JonesSysAdmin
	Admission Channel AdmissionSource	The origin of the patient admission.
Description Describes how the patient entered the hospital system, such as 'Physician Referral', 'Emergency Room', or 'Transfer from other Hospital'. This helps analyze the 'front door' of the hospital process. It maps to the `ADMIT_SRC_CD` in the `ENCOUNTER` table. Why it matters Contextualizes the 'Initial Assessment Wait Time' based on entry point. Where to get Table: ENCOUNTER, Column: ADMIT_SRC_CD Examples Emergency RoomPhysician ReferralTransfer from Hospital
	Medication Status MedAdminStatus	Status of the medication order (e.g., Given, Refused, Not Given).
Description Indicates the outcome of a medication administration task. For the 'Medication Admin Compliance' dashboard, it is vital to distinguish between medications actually administered versus those scheduled but missed or refused. Likely found in the `CLINICAL_EVENT` or specific Medication Administration Record (MAR) tables. Why it matters Identifies compliance gaps in treatment protocols. Where to get Consult Oracle Health (Cerner) documentation Examples AdministeredRefusedHeld
	Order Number OrderId	Unique identifier for a specific order (Lab, Med, Consult).
Description The system-generated ID for an order. While not the Case ID, this is a crucial secondary key. It links the 'Diagnostic Order Placed' event to the 'Diagnostic Result Verified' event. Without this, it is difficult to calculate the exact turnaround time for specific tests if a patient has multiple concurrent orders. Why it matters Essential for linking paired activities (Order -> Result) accurately. Where to get Table: ORDERS, Column: ORDER_ID Examples 88291028829103
	Payer Type FinancialClass	The primary insurance coverage or financial classification of the patient.
Description Categorizes the patient based on their payer source (e.g., Medicare, Private Insurance, Self-Pay). This attribute is used to analyze if process flows or lengths of stay vary based on insurance type. Derived from `FINANCIAL_CLASS_CD` in the `ENCOUNTER` table. Why it matters Helps identify disparities in care delivery or administrative processing based on payer type. Where to get Table: ENCOUNTER, Column: FINANCIAL_CLASS_CD (resolve via CODE_VALUE) Examples MedicareBlue CrossSelf-PayMedicaid
	Result Status ResultStatus	The status of a diagnostic result (e.g., Auth (Verified), Corrected, Preliminary).
Description Indicates the lifecycle stage of a diagnostic test result. This is used in the 'Diagnostic Result Delivery Time' analysis to determine when a result is officially available for clinical decision-making. Typically found in `CLINICAL_EVENT` with specific status codes. Why it matters Differentiates between preliminary and final results, which impacts when downstream activities can start. Where to get Table: CLINICAL_EVENT, Column: RESULT_STATUS_CD Examples Auth (Verified)In ErrorModified
	Triage Priority TriageAcuity	The urgency level assigned during triage assessment.
Description A numeric or categorical value indicating the severity of the patient's condition (e.g., 1-Immediate to 5-Non-urgent). This is a vital segmentation attribute for analyzing wait times, as higher priority patients should have shorter waits. Usually captured in clinical forms or specific observation codes during the Triage event. Why it matters Critical for validating if the process prioritizes patients correctly according to clinical urgency. Where to get Consult Oracle Health (Cerner) documentation Examples 12345

Required Recommended Optional

Patient Journey Activities

These are the key process steps and milestones to capture in your event log for accurate process discovery and bottleneck identification.

8 Recommended 6 Optional

	Activity	Description
	Department Transfer Occurred	Indicates the patient physically moved from one location (e.g., ER) to another (e.g., ICU). This is tracked via location history.
Why it matters Enables 'Inter-Ward Transfer Efficiency' analysis and helps visualize patient flow through the hospital. Where to get ENCNTR_LOC_HIST (Encounter Location History) table, capturing changes in LOC_NURSE_UNIT_CD. Capture Compare status field before/after Event type inferred
	Diagnosis Documented	Occurs when a formal diagnosis is added to the patient's encounter record. This is distinct from a test result and represents the clinician's confirmation of the condition.
Why it matters Essential for the 'Diagnosis Confirmed' milestone and analyzing the time to definitive diagnosis. Where to get DIAGNOSIS table, using the DIAGNOSIS_DT_TM linked to the ENCOUNTER_ID. Capture Logged when diagnosis is added/updated in PowerChart Event type explicit
	Diagnostic Order Placed	Occurs when a clinician enters an order for a lab test or imaging study. This timestamp initiates the diagnostic turnaround time calculation.
Why it matters The starting point for the 'Diagnostic Result Delivery Time' KPI; helps identify delays in ordering versus execution. Where to get ORDERS table, using ORIG_ORDER_DT_TM where the catalog type is Laboratory or Radiology. Capture Logged when order status is set to ORDERED Event type explicit
	Diagnostic Result Verified	The moment a lab or imaging result is finalized and made available to the clinician. This ends the diagnostic turnaround time interval.
Why it matters Completes the 'Diagnostic Result Delivery Time' cycle and triggers subsequent treatment decisions. Where to get CLINICAL_EVENT table (for labs) or ORDERS status change to COMPLETED. Capture Logged when result status changes to AUTH (Authenticated) Event type explicit
	Discharge Order Signed	The event where the physician places the order to discharge the patient. This starts the discharge planning clock.
Why it matters The start point for 'Discharge Planning Cycle Time'. A gap between this and actual discharge indicates operational delays. Where to get ORDERS table, where catalog type indicates Discharge. Capture Logged when discharge order status is ORDERED Event type explicit
	Patient Discharged	The final administrative event closing the patient's stay. This timestamp is used to calculate the total Length of Stay.
Why it matters The primary end event for the process. Essential for LOS and readmission calculations. Where to get ENCOUNTER table, specifically the DISCH_DT_TM (Discharge Date/Time). Capture Logged when encounter status changes to DISCHARGED Event type explicit
	Patient Registered	Marks the beginning of the patient episode when the patient arrives and is entered into the system. In Cerner Millennium, this is captured when the encounter record is created or the registration timestamp is set.
Why it matters Establishes the start time for Length of Stay (LOS) calculations and initial wait time analysis. Where to get ENCOUNTER table, specifically the REG_DT_TM (Registration Date/Time) column. Capture Logged when transaction creates new ENCOUNTER row Event type explicit
	Triage Assessment Completed	Represents the completion of the initial nursing assessment or triage form in the emergency or admission context. This is typically a specific form or clinical event documented within the system.
Why it matters Critical for calculating the 'Initial Assessment Wait Time' KPI and identifying bottlenecks at the front door. Where to get CLINICAL_EVENT table, filtered by event codes associated with Triage or Initial Assessment forms. Capture Logged when clinical document/form is signed/verified Event type explicit
	Care Plan Activated	Represents the initiation of a PowerPlan or care pathway in Cerner. This signals that a standardized treatment protocol has been selected.
Why it matters Crucial for 'Treatment Protocol Deviation Analysis' to compare actual care against the planned pathway. Where to get ACT_PW_CAT (Action Pathway Catalog) or DCP_FORMS_REF, linking the pathway to the encounter. Capture Logged when PowerPlan is initiated Event type explicit
	Consultation Completed	Marks the completion of a specialist consultation, usually evidenced by a signed consultation note or document.
Why it matters Identifies when specialist input was received, which can be a bottleneck in complex care pathways. Where to get CLINICAL_EVENT table, filtering for document types classified as Consultations. Capture Logged when consult note is signed Event type explicit
	Follow-up Appointment Scheduled	Occurs when a future appointment is booked for the patient linked to the same episode or care plan.
Why it matters Supports 'Follow-up Scheduling Timeliness' dashboard. Measures continuity of care efficiency. Where to get SCH_APPT (Schedule Appointment) table, linked to the PERSON_ID. Capture Logged when appointment is created in scheduling module Event type explicit
	Medication Administered	Records the actual administration of medication to the patient as documented in the Medication Administration Record (MAR).
Why it matters Supports the 'Medication Admin Compliance' dashboard by verifying if meds were given on time. Where to get CLINICAL_EVENT table, filtered for medication administration events (Task Status = Complete). Capture Logged upon barcode scan or manual MAR entry Event type explicit
	Procedure Performed	The timestamp indicating when a surgery or major procedure actually took place. This is often captured in the perioperative documentation.
Why it matters Key milestone for clinical pathways and resource utilization analysis. Where to get SURGICAL_CASE table (Case Start/Stop times) or CLINICAL_EVENT for bedside procedures. Capture Logged via SurgiNet or procedure documentation Event type explicit
	Procedure Scheduled	Indicates that a surgical case or major procedure has been booked for a specific time. This helps in understanding resource allocation and pre-procedure wait times.
Why it matters Highlights scheduling efficiency and potential bottlenecks in operating room or procedure room utilization. Where to get SURGICAL_CASE table or SCH_APPT table linked to the encounter. Capture Logged when scheduling transaction is committed Event type explicit

Recommended Optional

Extraction Guides

How to get your data from Oracle Health (Cerner)

Steps

Launch Discern Visual Developer: Open the Discern Visual Developer (DVDev) application within your Citrix or local Cerner domain access environment.
Create a New Script: Initialize a new Command Language (CCL) script file (e.g., extract_patient_journey.prg).
Define Prompts: At the top of the script, define user prompts for start_date and end_date to allow dynamic execution for specific time ranges.
Set Up Constants: Define constants for specific Code Sets (e.g., Encounter Types, Order Catalogs, Event Codes) to avoid hardcoding numeric code_value identifiers, which vary by domain. You may need to look up the specific code_value or display_key for your organization's Triage, Discharge, and Consult forms.
Construct the Query: Copy the SQL query provided below into the body of the script. This query uses UNION ALL to combine data from multiple tables (ENCOUNTER, CLINICAL_EVENT, ORDERS, SURG_CASE_TBL, etc.) into a single flat event log structure.
Compile the Script: Use the compile function (Ctrl+F7 or Build menu) to check for syntax errors. Ensure you have SELECT access to the referenced tables.
Execute and Export: Run the script (Go/F9). In the Output destination, select 'Spreadsheet' or 'Flat File'. Save the resulting output as a CSV file.
Data Transformation (Optional): If dates are returned in Cerner specific formats (e.g., Julian dates or non-ISO timestamps), use Excel or a script to convert them to YYYY-MM-DD HH:MM:SS format before upload.
Validation: Perform a spot check against a known patient Encounter ID (FIN) in PowerChart to verify the timestamps align with the extract.
Upload to ProcessMind: Import the CSV file into ProcessMind, mapping columns EncounterId to Case ID, ClinicalEventTag to Activity, and EventEndDateTime to Timestamp.

Configuration

Date Range: Recommended execution window is 3-6 months. Large date ranges may time out due to the size of the CLINICAL_EVENT table.
Code Sets (CDF): The query relies on code_value filters. You must replace placeholders like [REPLACE_WITH_TRIAGE_EVENT_CD] with the actual codes from your domain (found in CODE_VALUE table).
Permissions: The user executing the script requires d (Database) access rights to tables like ENCOUNTER, CLINICAL_EVENT, ORDERS, SURG_CASE_TBL, ENCNTR_LOC_HIST, and SCH_APPOINTMENT.
Performance: The CLINICAL_EVENT table is very large. Ensure the date filter on EVENT_END_DT_TM is indexed and applied strictly.
Readmission Logic: The IsReadmission attribute is included as a placeholder. Complex lookback logic is best handled within the ProcessMind application after loading, rather than in the extraction query.

a Sample Query sql

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Patient Registered'
    , EventEndDateTime = FORMAT(E.REG_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = P.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = 'N/A'
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1) /* Days */
    , IsReadmission = '0' /* Calculate in Tool */
    , DiagnosisCode = 'N/A'
FROM
    ENCOUNTER E
    , PERSON P
    , PRSNL PR
WHERE
    E.REG_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND E.PERSON_ID = P.PERSON_ID
    AND E.REG_PRSNL_ID = PR.PERSON_ID
    AND E.ACTIVE_IND = 1

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Triage Assessment Completed'
    , EventEndDateTime = FORMAT(CE.EVENT_END_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = CE.EVENT_TAG
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    CLINICAL_EVENT CE
    , ENCOUNTER E
    , PRSNL PR
WHERE
    CE.EVENT_END_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND CE.EVENT_CD IN ([REPLACE_WITH_TRIAGE_EVENT_CD]) /* e.g., Triage Acuity */
    AND CE.VALID_UNTIL_DT_TM > CNVTDATETIME(CURDATE, CURTIME3)
    AND CE.ENCNTR_ID = E.ENCNTR_ID
    AND CE.PERFORMED_PRSNL_ID = PR.PERSON_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Diagnostic Order Placed'
    , EventEndDateTime = FORMAT(O.ORIG_ORDER_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = O.ORDER_MNEMONIC
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    ORDERS O
    , ENCOUNTER E
    , PRSNL PR
WHERE
    O.ORIG_ORDER_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND O.CATALOG_TYPE_CD IN ([REPLACE_WITH_LAB_RAD_CODES]) /* General Lab, Radiology */
    AND O.ENCNTR_ID = E.ENCNTR_ID
    AND O.ORDER_STATUS_CD != [REPLACE_WITH_CANCELED_CODE]
    AND O.STATUS_PRSNL_ID = PR.PERSON_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Procedure Scheduled'
    , EventEndDateTime = FORMAT(SCT.UPDT_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = 'Surgical Case'
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    SURG_CASE_TBL SCT
    , ENCOUNTER E
    , PRSNL PR
WHERE
    SCT.UPDT_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND SCT.ENCNTR_ID = E.ENCNTR_ID
    AND SCT.UPDT_ID = PR.PERSON_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Diagnosis Documented'
    , EventEndDateTime = FORMAT(D.DIAG_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = D.DIAGNOSIS_DISPLAY
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = D.DIAGNOSIS_DISPLAY
FROM
    DIAGNOSIS D
    , ENCOUNTER E
    , PRSNL PR
WHERE
    D.DIAG_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND D.ENCNTR_ID = E.ENCNTR_ID
    AND D.ACTIVE_IND = 1
    AND D.DIAG_PRSNL_ID = PR.PERSON_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Care Plan Activated'
    , EventEndDateTime = FORMAT(PWC.START_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = PWC.DESCRIPTION
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    ACT_PW_COMP PWC
    , ENCOUNTER E
    , PRSNL PR
WHERE
    PWC.START_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND PWC.ENCNTR_ID = E.ENCNTR_ID
    AND PWC.ACTIVE_IND = 1
    AND PWC.START_PRSNL_ID = PR.PERSON_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Medication Administered'
    , EventEndDateTime = FORMAT(CE.EVENT_END_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = CE.EVENT_TAG
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    CLINICAL_EVENT CE
    , ENCOUNTER E
    , PRSNL PR
WHERE
    CE.EVENT_END_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND CE.EVENT_CLASS_CD = [REPLACE_WITH_MED_ADMIN_CLASS] /* e.g., 232 (MED) */
    AND CE.ENCNTR_ID = E.ENCNTR_ID
    AND CE.VALID_UNTIL_DT_TM > CNVTDATETIME(CURDATE, CURTIME3)
    AND CE.PERFORMED_PRSNL_ID = PR.PERSON_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Diagnostic Result Verified'
    , EventEndDateTime = FORMAT(CE.VERIFIED_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = CE.EVENT_TAG
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    CLINICAL_EVENT CE
    , ENCOUNTER E
    , PRSNL PR
WHERE
    CE.VERIFIED_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND CE.EVENT_CLASS_CD IN ([REPLACE_WITH_LAB_RAD_CLASS_CODES])
    AND CE.RESULT_STATUS_CD = [REPLACE_WITH_AUTH_STATUS_CD]
    AND CE.ENCNTR_ID = E.ENCNTR_ID
    AND CE.VERIFIED_PRSNL_ID = PR.PERSON_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Procedure Performed'
    , EventEndDateTime = FORMAT(SCT.SURG_START_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = 'N/A'
    , OrderMnemonic = 'Surgical Case'
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    SURG_CASE_TBL SCT
    , ENCOUNTER E
WHERE
    SCT.SURG_START_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND SCT.ENCNTR_ID = E.ENCNTR_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Department Transfer Occurred'
    , EventEndDateTime = FORMAT(ELH.BEG_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(ELH.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = 'Transfer'
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    ENCNTR_LOC_HIST ELH
    , ENCOUNTER E
    , PRSNL PR
WHERE
    ELH.BEG_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND ELH.ENCNTR_ID = E.ENCNTR_ID
    AND ELH.UPDT_ID = PR.PERSON_ID
    AND ELH.ACTIVE_IND = 1

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Consultation Completed'
    , EventEndDateTime = FORMAT(CE.EVENT_END_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = CE.EVENT_TAG
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    CLINICAL_EVENT CE
    , ENCOUNTER E
    , PRSNL PR
WHERE
    CE.EVENT_END_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND CE.EVENT_CD IN ([REPLACE_WITH_CONSULT_NOTE_CODES])
    AND CE.ENCNTR_ID = E.ENCNTR_ID
    AND CE.PERFORMED_PRSNL_ID = PR.PERSON_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Discharge Order Signed'
    , EventEndDateTime = FORMAT(O.ORIG_ORDER_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = O.ORDER_MNEMONIC
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    ORDERS O
    , ENCOUNTER E
    , PRSNL PR
WHERE
    O.ORIG_ORDER_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND O.ORDER_MNEMONIC = '*Discharge*'
    AND O.ENCNTR_ID = E.ENCNTR_ID
    AND O.STATUS_PRSNL_ID = PR.PERSON_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Patient Discharged'
    , EventEndDateTime = FORMAT(E.DISCH_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = E.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = 'N/A'
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    ENCOUNTER E
    , PERSON P
    , PRSNL PR
WHERE
    E.DISCH_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND E.PERSON_ID = P.PERSON_ID
    AND E.ACTIVE_IND = 1
    AND E.UPDT_ID = PR.PERSON_ID

UNION ALL

SELECT
    EncounterId = E.ENCNTR_ID
    , ClinicalEventTag = 'Follow-up Appointment Scheduled'
    , EventEndDateTime = FORMAT(SA.UPDT_DT_TM, 'YYYY-MM-DD HH:MM:SS')
    , SourceSystem = 'Cerner'
    , LastDataUpdate = FORMAT(CNVTDATETIME(CURDATE, CURTIME3), 'YYYY-MM-DD HH:MM:SS')
    , PersonId = SA.PERSON_ID
    , EncounterType = UAR_GET_CODE_DISPLAY(E.ENCNTR_TYPE_CD)
    , NurseUnit = UAR_GET_CODE_DISPLAY(E.LOC_NURSE_UNIT_CD)
    , PerformingPrsnlId = PR.NAME_FULL_FORMATTED
    , OrderMnemonic = 'Follow-up'
    , DischargeDisposition = UAR_GET_CODE_DISPLAY(E.DISCH_DISPOSITION_CD)
    , LengthOfStay = DATETIFF(E.DISCH_DT_TM, E.REG_DT_TM, 1)
    , IsReadmission = '0'
    , DiagnosisCode = 'N/A'
FROM
    SCH_APPOINTMENT SA
    , ENCOUNTER E
    , PRSNL PR
WHERE
    SA.UPDT_DT_TM BETWEEN CNVTDATETIME($start_date) AND CNVTDATETIME($end_date)
    AND SA.ENCNTR_ID = E.ENCNTR_ID
    AND SA.BEG_DT_TM > E.DISCH_DT_TM
    AND SA.SCH_STATE_CD != [REPLACE_WITH_CANCELED_STATE_CD]
    AND SA.UPDT_ID = PR.PERSON_ID

Steps

Prerequisite Configuration: Ensure you have Python installed with necessary libraries (pandas, requests) and valid OAuth2 credentials (client_id, client_secret) for the Oracle Health (Cerner) FHIR R4 endpoint. You must have scopes enabled for Patient, Encounter, Observation, Condition, Procedure, MedicationAdministration, ServiceRequest, and DiagnosticReport.
Authentication Handling: Implement an authentication handler to retrieve a Bearer token from the authorization server. Cerner implementations typically use SMART on FHIR or standard OAuth2 client credentials flows. The script provided handles token retrieval.
Define Scope and Timeframe: Determine the extraction window (e.g., last_updated_gt or date parameters). It is best practice to iterate by a date range on the Encounter resource to define the scope of Patient Episodes.
Fetch Encounters (Patient Episodes): Query the Encounter resource. This object serves as the central hub (Case Identifier). From the Encounter resource itself, extract period.start for Patient Registered, period.end for Patient Discharged, and iterate through location history for Department Transfer Occurred.
Extract Clinical Orders: Query ServiceRequest resources filtered by the Encounter ID. Filter by intent=order to capture Diagnostic Order Placed and Procedure Scheduled (if categorized as surgical orders). Map authoredOn to the event timestamp.
Extract Diagnoses and Problems: Query Condition resources linked to the Encounter. Use recordedDate or onsetDateTime to create Diagnosis Documented events. Filter for category encounter-diagnosis where possible.
Extract Procedures: Query Procedure resources. Use performedDateTime to generate Procedure Performed events. This distinguishes completed surgeries from scheduled ones.
Extract Medications: Query MedicationAdministration resources. This is distinct from MedicationRequest as it logs the actual intake. Use effectiveDateTime for the Medication Administered event.
Extract Labs and Results: Query Observation or DiagnosticReport resources. Use issued or effectiveDateTime for Diagnostic Result Verified events. Look for status=final. Also, use specific Observation codes (e.g., LOINC for triage acuity) to identify Triage Assessment Completed.
Extract Documentation and Care Plans: Query DocumentReference for Consultation Completed (using document type codes) and CarePlan for Care Plan Activated events.
Identify Discharge Activities: Deriving Discharge Order Signed often requires checking ServiceRequest for specific discharge order codes or parsing Encounter.statusHistory for a status preceding the final discharge.
Data Transformation and Export: Flatten the JSON responses into a tabular format. Create the required columns (EncounterId, ClinicalEventTag, EventEndDateTime, etc.). Convert timestamps to ISO 8601 format and export the final dataset to a CSV file ready for ProcessMind upload.

Configuration

FHIR Base URL: The specific endpoint for your Oracle Health/Cerner instance (e.g., https://fhir-myrecord.cerner.com/r4/...).
Authentication Scopes: Ensure the application has system/Encounter.read, system/Observation.read, system/Patient.read, system/Procedure.read, system/Condition.read, etc.
Date Filtering: Use date=ge[YYYY-MM-DD] on the Encounter resource to pull episodes starting from a specific date. Avoid querying the entire history.
Pagination: The API returns data in Bundles. The script must handle pagination links (relation: next) to retrieve full datasets.
Concurrency: For high-volume extraction, consider parallelizing requests by Encounter ID ranges, but respect API rate limits (Throttling).
Code Filtering: Configure specific LOINC or SNOMED codes in the script mapping section to accurately identify Triage vs. General Observations.

a Sample Query python

import requests
import pandas as pd
import time
from datetime import datetime, timedelta

class=class="hl-string">"hl-comment"># === CONFIGURATION ===
FHIR_BASE_URL = class="hl-string">"https://fhir-ehr.cerner.com/r4/ec2458f2-1e24-41c8-b71b-0e701af7583d"  class=class="hl-string">"hl-comment"># Placeholder
CLIENT_ID = class="hl-string">"[YOUR_CLIENT_ID]"
CLIENT_SECRET = class="hl-string">"[YOUR_CLIENT_SECRET]"
TOKEN_URL = class="hl-string">"https://authorization.cerner.com/tenants/ec2458f2-1e24-41c8-b71b-0e701af7583d/protocols/oauth2/profiles/smart-v1/token"

class=class="hl-string">"hl-comment"># Standard headers
HEADERS = {
    class="hl-string">"Accept": class="hl-string">"application/fhir+json",
    class="hl-string">"Content-Type": class="hl-string">"application/json"
}

class=class="hl-string">"hl-comment"># === AUTHENTICATION ===
def get_access_token():
    class=class="hl-string">"hl-comment"># Basic OAuth2 Client Credentials implementation
    class=class="hl-string">"hl-comment"># Adjust for specific SMART on FHIR flows if needed
    payload = {
        class="hl-string">"grant_type": class="hl-string">"client_credentials",
        class="hl-string">"client_id": CLIENT_ID,
        class="hl-string">"client_secret": CLIENT_SECRET,
        class="hl-string">"scope": class="hl-string">"system/Encounter.read system/Patient.read system/Observation.read system/Procedure.read system/Condition.read system/MedicationAdministration.read system/ServiceRequest.read"
    }
    try:
        response = requests.post(TOKEN_URL, data=payload, auth=(CLIENT_ID, CLIENT_SECRET))
        response.raise_for_status()
        return response.json()[class="hl-string">"access_token"]
    except Exception as e:
        print(fclass="hl-string">"Auth failed: {e}")
        return None

class=class="hl-string">"hl-comment"># === API HELPER ===
def fetch_resource(url, token):
    resources = []
    headers = HEADERS.copy()
    headers[class="hl-string">"Authorization"] = fclass="hl-string">"Bearer {token}"
    
    while url:
        try:
            resp = requests.get(url, headers=headers)
            if resp.status_code == 429:
                time.sleep(2)
                continue
            resp.raise_for_status()
            data = resp.json()
            
            if class="hl-string">'entry' in data:
                resources.extend([item[class="hl-string">'resource'] for item in data[class="hl-string">'entry']])
            
            class=class="hl-string">"hl-comment"># Handle Pagination
            url = None
            for link in data.get(class="hl-string">'link', []):
                if link[class="hl-string">'relation'] == class="hl-string">'next':
                    url = link[class="hl-string">'url']
                    break
        except Exception as e:
            print(fclass="hl-string">"Error fetching {url}: {e}")
            break
    return resources

class=class="hl-string">"hl-comment"># === MAIN EXTRACTION ===
def extract_patient_journey(start_date, end_date):
    token = get_access_token()
    if not token:
        return

    class=class="hl-string">"hl-comment"># 1. Fetch Encounters (Episodes)
    print(class="hl-string">"Fetching Encounters...")
    enc_url = fclass="hl-string">"{FHIR_BASE_URL}/Encounter?date=ge{start_date}&date=le{end_date}"
    encounters = fetch_resource(enc_url, token)
    
    event_log = []

    print(fclass="hl-string">"Processing {len(encounters)} encounters...")
    
    for enc in encounters:
        enc_id = enc.get(class="hl-string">'id')
        patient_id = enc.get(class="hl-string">'subject', {}).get(class="hl-string">'reference', class="hl-string">'').replace(class="hl-string">'Patient/', class="hl-string">'')
        enc_type = enc.get(class="hl-string">'class', {}).get(class="hl-string">'code', class="hl-string">'Unknown')
        
        class=class="hl-string">"hl-comment"># Helper to append event
        def add_event(tag, timestamp, order_item=None, location=None):
            if timestamp:
                event_log.append({
                    class="hl-string">"EncounterId": enc_id,
                    class="hl-string">"PersonId": patient_id,
                    class="hl-string">"ClinicalEventTag": tag,
                    class="hl-string">"EventEndDateTime": timestamp,
                    class="hl-string">"SourceSystem": class="hl-string">"OracleHealth_Cerner",
                    class="hl-string">"EncounterType": enc_type,
                    class="hl-string">"NurseUnit": location,
                    class="hl-string">"OrderMnemonic": order_item,
                    class="hl-string">"LastDataUpdate": datetime.now().isoformat()
                })

        class=class="hl-string">"hl-comment"># --- Activity 1: Patient Registered ---
        start_time = enc.get(class="hl-string">'period', {}).get(class="hl-string">'start')
        add_event(class="hl-string">"Patient Registered", start_time)

        class=class="hl-string">"hl-comment"># --- Activity 13: Patient Discharged ---
        end_time = enc.get(class="hl-string">'period', {}).get(class="hl-string">'end')
        class=class="hl-string">"hl-comment"># Activity 12: Discharge Order Signed (Inferred from status or specific request)
        class=class="hl-string">"hl-comment"># For simplicity, if end_time exists, we assume discharge order preceded it slightly or check ServiceRequest
        add_event(class="hl-string">"Patient Discharged", end_time)

        class=class="hl-string">"hl-comment"># --- Activity 10: Department Transfer Occurred ---
        locations = enc.get(class="hl-string">'location', [])
        for i, loc in enumerate(locations):
            loc_name = loc.get(class="hl-string">'location', {}).get(class="hl-string">'display', class="hl-string">'Unknown Unit')
            loc_start = loc.get(class="hl-string">'period', {}).get(class="hl-string">'start')
            class=class="hl-string">"hl-comment"># Skip the first location as it's usually registration
            if i > 0 and loc_start:
                add_event(class="hl-string">"Department Transfer Occurred", loc_start, location=loc_name)

        class=class="hl-string">"hl-comment"># === FETCH SUB-RESOURCES ===
        class=class="hl-string">"hl-comment"># Note: In production, consider batch requests or bulk export if available to avoid N+1 queries
        
        class=class="hl-string">"hl-comment"># --- Activity 5: Diagnosis Documented ---
        cond_url = fclass="hl-string">"{FHIR_BASE_URL}/Condition?patient={patient_id}&encounter={enc_id}"
        conditions = fetch_resource(cond_url, token)
        for cond in conditions:
            dx_name = cond.get(class="hl-string">'code', {}).get(class="hl-string">'text', class="hl-string">'Unknown Diagnosis')
            dx_time = cond.get(class="hl-string">'recordedDate') or cond.get(class="hl-string">'onsetDateTime')
            add_event(class="hl-string">"Diagnosis Documented", dx_time, order_item=dx_name)

        class=class="hl-string">"hl-comment"># --- Activity 9: Procedure Performed ---
        proc_url = fclass="hl-string">"{FHIR_BASE_URL}/Procedure?patient={patient_id}&encounter={enc_id}"
        procedures = fetch_resource(proc_url, token)
        for proc in procedures:
            if proc.get(class="hl-string">'status') == class="hl-string">'completed':
                proc_name = proc.get(class="hl-string">'code', {}).get(class="hl-string">'text', class="hl-string">'Unknown Procedure')
                proc_time = proc.get(class="hl-string">'performedDateTime')
                add_event(class="hl-string">"Procedure Performed", proc_time, order_item=proc_name)

        class=class="hl-string">"hl-comment"># --- Activity 7: Medication Administered ---
        med_url = fclass="hl-string">"{FHIR_BASE_URL}/MedicationAdministration?patient={patient_id}&encounter={enc_id}"
        meds = fetch_resource(med_url, token)
        for med in meds:
            if med.get(class="hl-string">'status') == class="hl-string">'completed':
                med_name = med.get(class="hl-string">'medicationCodeableConcept', {}).get(class="hl-string">'text', class="hl-string">'Unknown Med')
                med_time = med.get(class="hl-string">'effectiveDateTime')
                add_event(class="hl-string">"Medication Administered", med_time, order_item=med_name)

        class=class="hl-string">"hl-comment"># --- Activity 2, 8: Observations (Triage & Labs) ---
        obs_url = fclass="hl-string">"{FHIR_BASE_URL}/Observation?patient={patient_id}&encounter={enc_id}"
        observations = fetch_resource(obs_url, token)
        for obs in observations:
            obs_code = obs.get(class="hl-string">'code', {}).get(class="hl-string">'text', class="hl-string">'')
            obs_time = obs.get(class="hl-string">'effectiveDateTime') or obs.get(class="hl-string">'issued')
            categories = [c.get(class="hl-string">'code') for cat in obs.get(class="hl-string">'category', []) for c in cat.get(class="hl-string">'coding', [])]
            
            if class="hl-string">'triage' in str(categories).lower() or class="hl-string">'acuity' in obs_code.lower():
                add_event(class="hl-string">"Triage Assessment Completed", obs_time, order_item=obs_code)
            elif class="hl-string">'laboratory' in str(categories).lower() and obs.get(class="hl-string">'status') == class="hl-string">'final':
                add_event(class="hl-string">"Diagnostic Result Verified", obs_time, order_item=obs_code)

        class=class="hl-string">"hl-comment"># --- Activity 3, 4, 12: Service Requests (Orders) ---
        req_url = fclass="hl-string">"{FHIR_BASE_URL}/ServiceRequest?patient={patient_id}&encounter={enc_id}"
        requests_list = fetch_resource(req_url, token)
        for req in requests_list:
            req_name = req.get(class="hl-string">'code', {}).get(class="hl-string">'text', class="hl-string">'Unknown Order')
            req_time = req.get(class="hl-string">'authoredOn')
            intent = req.get(class="hl-string">'intent')
            
            if intent == class="hl-string">'order':
                class=class="hl-string">"hl-comment"># Simple logic to distinguish Labs vs other orders based on code or category
                add_event(class="hl-string">"Diagnostic Order Placed", req_time, order_item=req_name)
            elif intent == class="hl-string">'plan':
                 add_event(class="hl-string">"Procedure Scheduled", req_time, order_item=req_name)
            
            class=class="hl-string">"hl-comment"># Discharge Order Logic (Placeholder: Check for specific discharge code)
            if class="hl-string">"discharge" in req_name.lower():
                add_event(class="hl-string">"Discharge Order Signed", req_time)

        class=class="hl-string">"hl-comment"># --- Activity 6: Care Plan Activated ---
        cp_url = fclass="hl-string">"{FHIR_BASE_URL}/CarePlan?patient={patient_id}&encounter={enc_id}"
        careplans = fetch_resource(cp_url, token)
        for cp in careplans:
            cp_start = cp.get(class="hl-string">'period', {}).get(class="hl-string">'start')
            add_event(class="hl-string">"Care Plan Activated", cp_start)

        class=class="hl-string">"hl-comment"># --- Activity 11: Consultation Completed ---
        class=class="hl-string">"hl-comment"># Often DocumentReference
        doc_url = fclass="hl-string">"{FHIR_BASE_URL}/DocumentReference?patient={patient_id}&encounter={enc_id}"
        docs = fetch_resource(doc_url, token)
        for doc in docs:
            type_text = doc.get(class="hl-string">'type', {}).get(class="hl-string">'text', class="hl-string">'').lower()
            if class="hl-string">'consult' in type_text or class="hl-string">'note' in type_text:
                doc_date = doc.get(class="hl-string">'date') class=class="hl-string">"hl-comment"># When document was created/signed
                add_event(class="hl-string">"Consultation Completed", doc_date, order_item=type_text)
        
        class=class="hl-string">"hl-comment"># --- Activity 14: Follow-up Appointment Scheduled ---
        class=class="hl-string">"hl-comment"># Check for appointments created strictly after encounter start, linked to patient
        apt_url = fclass="hl-string">"{FHIR_BASE_URL}/Appointment?patient={patient_id}&date=ge{start_time}"
        appointments = fetch_resource(apt_url, token)
        for apt in appointments:
            created_date = apt.get(class="hl-string">'created') class=class="hl-string">"hl-comment"># When the booking happened
            if created_date and start_time and created_date >= start_time:
                 add_event(class="hl-string">"Follow-up Appointment Scheduled", created_date)

    class=class="hl-string">"hl-comment"># === EXPORT ===
    df = pd.DataFrame(event_log)
    class=class="hl-string">"hl-comment"># Basic cleaning
    df.drop_duplicates(inplace=True)
    df.fillna(class="hl-string">'', inplace=True)
    
    output_file = class="hl-string">"cerner_extraction.csv"
    df.to_csv(output_file, index=False)
    print(fclass="hl-string">"Extraction complete. Saved to {output_file}")

class=class="hl-string">"hl-comment"># Run extraction for a specific window
extract_patient_journey(class="hl-string">"2023-01-01", class="hl-string">"2023-01-07")

Your Patient Journey Data Template

Your Patient Journey Data Template

Patient Journey Attributes

Patient Journey Activities

Extraction Guides

Cerner Command Language Extraction via Discern

Steps

Configuration

a Sample Query sql

Python Extraction via Oracle Health FHIR R4 API

Steps

Configuration

a Sample Query python

Ready to Get Started?

Optimize Patient Journeys Now, Improve Outcomes Fast

Your Patient Journey Data Template

Your Patient Journey Data Template

Patient Journey Attributes

Patient Journey Activities

Extraction Guides

Cerner Command Language Extraction via Discern

Steps

Configuration

a Sample Query sql

Python Extraction via Oracle Health FHIR R4 API

Steps

Configuration

a Sample Query python

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Ready to Get Started?

Optimize Patient Journeys Now, Improve Outcomes Fast