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# **SQL Scripts**

These SQL scripts have been developed by the community to facilitate the Extract, Transform, and Load (ETL) process from source data to the OMOP CDM. 

## **Vocabulary Mapping**

### Source to Standard

This script will create a large table containing all source codes and the Standard Concepts they map to. By creating this table ahead of time and referencing it during ETL, you can save processing time than if you were to map source codes on the fly. It is important to note that this script will show ALL mappings, not just those to Standard, Valid Concepts. Be sure to add a filter that will only grab the correct Standard, Valid codes. 

```{sql eval=FALSE, echo=TRUE}
SELECT c.concept_code AS SOURCE_CODE, c.concept_id AS SOURCE_CONCEPT_ID, c.concept_name AS SOURCE_CODE_DESCRIPTION, c.vocabulary_id AS SOURCE_VOCABULARY_ID, c.domain_id AS SOURCE_DOMAIN_ID, c.CONCEPT_CLASS_ID AS SOURCE_CONCEPT_CLASS_ID, c.VALID_START_DATE AS SOURCE_VALID_START_DATE, c.VALID_END_DATE AS SOURCE_VALID_END_DATE, c.INVALID_REASON AS SOURCE_INVALID_REASON, c1.concept_id AS TARGET_CONCEPT_ID, c1.concept_name AS TARGET_CONCEPT_NAME, c1.VOCABULARY_ID AS TARGET_VOCABUALRY_ID, c1.domain_id AS TARGET_DOMAIN_ID, c1.concept_class_id AS TARGET_CONCEPT_CLASS_ID, c1.INVALID_REASON AS TARGET_INVALID_REASON, c1.standard_concept AS TARGET_STANDARD_CONCEPT
       FROM CONCEPT C
             JOIN CONCEPT_RELATIONSHIP CR
                        ON C.CONCEPT_ID = CR.CONCEPT_ID_1
                        AND CR.invalid_reason IS NULL
                        AND lower(cr.relationship_id) = 'maps to'
              JOIN CONCEPT C1
                        ON CR.CONCEPT_ID_2 = C1.CONCEPT_ID
                        AND C1.INVALID_REASON IS NULL
       UNION
       SELECT source_code, SOURCE_CONCEPT_ID, SOURCE_CODE_DESCRIPTION, source_vocabulary_id, c1.domain_id AS SOURCE_DOMAIN_ID, c2.CONCEPT_CLASS_ID AS SOURCE_CONCEPT_CLASS_ID, c1.VALID_START_DATE AS SOURCE_VALID_START_DATE, c1.VALID_END_DATE AS SOURCE_VALID_END_DATE, stcm.INVALID_REASON AS SOURCE_INVALID_REASON,target_concept_id, c2.CONCEPT_NAME AS TARGET_CONCEPT_NAME, target_vocabulary_id, c2.domain_id AS TARGET_DOMAIN_ID, c2.concept_class_id AS TARGET_CONCEPT_CLASS_ID, c2.INVALID_REASON AS TARGET_INVALID_REASON, c2.standard_concept AS TARGET_STANDARD_CONCEPT
       FROM source_to_concept_map stcm
              LEFT OUTER JOIN CONCEPT c1
                     ON c1.concept_id = stcm.source_concept_id
              LEFT OUTER JOIN CONCEPT c2
                     ON c2.CONCEPT_ID = stcm.target_concept_id
       WHERE stcm.INVALID_REASON IS NULL

```

### Source to Source

This script will create a large table containing all source codes and their referent Concepts. While you may be tempted to use the Source to Standard query to find these, it is important to use this one instead to populate *_SOURCE_CONCEPT_ID fields. Some source codes map to multiple Standard Concepts though they have only one source Concept. By using the Source to Standard query you may inadvertently create duplicate records in your CDM instance.  

```{sql eval=FALSE, echo=TRUE}
SELECT c.concept_code AS SOURCE_CODE, c.concept_id AS SOURCE_CONCEPT_ID, c.CONCEPT_NAME AS SOURCE_CODE_DESCRIPTION, c.vocabulary_id AS SOURCE_VOCABULARY_ID, c.domain_id AS SOURCE_DOMAIN_ID, c.concept_class_id AS SOURCE_CONCEPT_CLASS_ID, c.VALID_START_DATE AS SOURCE_VALID_START_DATE, c.VALID_END_DATE AS SOURCE_VALID_END_DATE, c.invalid_reason AS SOURCE_INVALID_REASON, c.concept_ID as TARGET_CONCEPT_ID, c.concept_name AS TARGET_CONCEPT_NAME, c.vocabulary_id AS TARGET_VOCABULARY_ID, c.domain_id AS TARGET_DOMAIN_ID, c.concept_class_id AS TARGET_CONCEPT_CLASS_ID, c.INVALID_REASON AS TARGET_INVALID_REASON, c.STANDARD_CONCEPT AS TARGET_STANDARD_CONCEPT
       FROM CONCEPT c
       UNION
       SELECT source_code, SOURCE_CONCEPT_ID, SOURCE_CODE_DESCRIPTION, source_vocabulary_id, c1.domain_id AS SOURCE_DOMAIN_ID, c2.CONCEPT_CLASS_ID AS SOURCE_CONCEPT_CLASS_ID, c1.VALID_START_DATE AS SOURCE_VALID_START_DATE, c1.VALID_END_DATE AS SOURCE_VALID_END_DATE,stcm.INVALID_REASON AS SOURCE_INVALID_REASON, target_concept_id, c2.CONCEPT_NAME AS TARGET_CONCEPT_NAME, target_vocabulary_id, c2.domain_id AS TARGET_DOMAIN_ID, c2.concept_class_id AS TARGET_CONCEPT_CLASS_ID, c2.INVALID_REASON AS TARGET_INVALID_REASON, c2.standard_concept AS TARGET_STANDARD_CONCEPT
       FROM source_to_concept_map stcm
              LEFT OUTER JOIN CONCEPT c1
                     ON c1.concept_id = stcm.source_concept_id
              LEFT OUTER JOIN CONCEPT c2
                     ON c2.CONCEPT_ID = stcm.target_concept_id
       WHERE stcm.INVALID_REASON IS NULL
```

## **Era Tables**

### Condition Eras

This script will insert values into the CONDITION_ERA table given that the CONDITION_OCCURRENCE table is populated. It will string together condition records that have <= 30 days between them into eras during which the Person is assumed to have the given condition. **NOTE** This query only works with 5.3 and below.

```{sql eval= FALSE, echo=TRUE}
/****************************************************
OHDSI-SQL File Instructions
-----------------------------
 1. Set parameter name of schema that contains CDMv4 instance
    (@SOURCE_CDMV4, @SOURCE_CDMV4_SCHEMA)
 2. Set parameter name of schema that contains CDMv5 instance
    (@TARGET_CDMV5, @TARGET_CDMV5_SCHEMA)
 3. Run this script through SqlRender to produce a script that will work in your
    source dialect. SqlRender can be found here: https://github.com/OHDSI/SqlRender
 4. Run the script produced by SQL Render on your target RDBDMS.
<RDBMS> File Instructions
-------------------------
 1. This script will hold a number of placeholders for your CDM V4 and CDMV5
    database/schema. In order to make this file work in your environment, you
	should plan to do a global "FIND AND REPLACE" on this file to fill in the
	file with values that pertain to your environment. The following are the
	tokens you should use when doing your "FIND AND REPLACE" operation:
	
     [CDM]
	 [CDM].[CDMSCHEMA]
	
*********************************************************************************/
/* SCRIPT PARAMETERS */

	
	{DEFAULT @TARGET_CDMV5 = '[CDM]' } -- The target CDMv5 database name
	{DEFAULT @TARGET_CDMV5_SCHEMA = '[CDM].[CDMSCHEMA]' } -- the target CDMv5 database plus schema

USE @TARGET_CDMV5;



/****
CONDITION ERA
Note: Eras derived from CONDITION_OCCURRENCE table, using 30d gap
 ****/
IF OBJECT_ID('tempdb..#condition_era_phase_1', 'U') IS NOT NULL
	DROP TABLE #condition_era_phase_1;

/* / */

IF OBJECT_ID('tempdb..#cteConditionTarget', 'U') IS NOT NULL
	DROP TABLE #cteConditionTarget;

/* / */

-- create base eras from the concepts found in condition_occurrence
SELECT co.PERSON_ID
	,co.condition_concept_id
	,co.CONDITION_START_DATE
	,COALESCE(co.CONDITION_END_DATE, DATEADD(day, 1, CONDITION_START_DATE)) AS CONDITION_END_DATE
INTO #cteConditionTarget
FROM @TARGET_CDMV5_SCHEMA.CONDITION_OCCURRENCE co;

/* / */

IF OBJECT_ID('tempdb..#cteCondEndDates', 'U') IS NOT NULL
	DROP TABLE #cteCondEndDates;

/* / */

SELECT PERSON_ID
	,CONDITION_CONCEPT_ID
	,DATEADD(day, - 30, EVENT_DATE) AS END_DATE -- unpad the end date
INTO #cteCondEndDates
FROM (
	SELECT E1.PERSON_ID
		,E1.CONDITION_CONCEPT_ID
		,E1.EVENT_DATE
		,COALESCE(E1.START_ORDINAL, MAX(E2.START_ORDINAL)) START_ORDINAL
		,E1.OVERALL_ORD
	FROM (
		SELECT PERSON_ID
			,CONDITION_CONCEPT_ID
			,EVENT_DATE
			,EVENT_TYPE
			,START_ORDINAL
			,ROW_NUMBER() OVER (
				PARTITION BY PERSON_ID
				,CONDITION_CONCEPT_ID ORDER BY EVENT_DATE
					,EVENT_TYPE
				) AS OVERALL_ORD -- this re-numbers the inner UNION so all rows are numbered ordered by the event date
		FROM (
			-- select the start dates, assigning a row number to each
			SELECT PERSON_ID
				,CONDITION_CONCEPT_ID
				,CONDITION_START_DATE AS EVENT_DATE
				,- 1 AS EVENT_TYPE
				,ROW_NUMBER() OVER (
					PARTITION BY PERSON_ID
					,CONDITION_CONCEPT_ID ORDER BY CONDITION_START_DATE
					) AS START_ORDINAL
			FROM #cteConditionTarget

			UNION ALL

			-- pad the end dates by 30 to allow a grace period for overlapping ranges.
			SELECT PERSON_ID
				,CONDITION_CONCEPT_ID
				,DATEADD(day, 30, CONDITION_END_DATE)
				,1 AS EVENT_TYPE
				,NULL
			FROM #cteConditionTarget
			) RAWDATA
		) E1
	INNER JOIN (
		SELECT PERSON_ID
			,CONDITION_CONCEPT_ID
			,CONDITION_START_DATE AS EVENT_DATE
			,ROW_NUMBER() OVER (
				PARTITION BY PERSON_ID
				,CONDITION_CONCEPT_ID ORDER BY CONDITION_START_DATE
				) AS START_ORDINAL
		FROM #cteConditionTarget
		) E2 ON E1.PERSON_ID = E2.PERSON_ID
		AND E1.CONDITION_CONCEPT_ID = E2.CONDITION_CONCEPT_ID
		AND E2.EVENT_DATE <= E1.EVENT_DATE
	GROUP BY E1.PERSON_ID
		,E1.CONDITION_CONCEPT_ID
		,E1.EVENT_DATE
		,E1.START_ORDINAL
		,E1.OVERALL_ORD
	) E
WHERE (2 * E.START_ORDINAL) - E.OVERALL_ORD = 0;

/* / */

IF OBJECT_ID('tempdb..#cteConditionEnds', 'U') IS NOT NULL
	DROP TABLE #cteConditionEnds;

/* / */

SELECT c.PERSON_ID
	,c.CONDITION_CONCEPT_ID
	,c.CONDITION_START_DATE
	,MIN(e.END_DATE) AS ERA_END_DATE
INTO #cteConditionEnds
FROM #cteConditionTarget c
INNER JOIN #cteCondEndDates e ON c.PERSON_ID = e.PERSON_ID
	AND c.CONDITION_CONCEPT_ID = e.CONDITION_CONCEPT_ID
	AND e.END_DATE >= c.CONDITION_START_DATE
GROUP BY c.PERSON_ID
	,c.CONDITION_CONCEPT_ID
	,c.CONDITION_START_DATE;

/* / */

INSERT INTO @TARGET_CDMV5_SCHEMA.condition_era (
	condition_era_id
	,person_id
	,condition_concept_id
	,condition_era_start_date
	,condition_era_end_date
	,condition_occurrence_count
	)
SELECT row_number() OVER (
		ORDER BY person_id
		) AS condition_era_id
	,person_id
	,CONDITION_CONCEPT_ID
	,min(CONDITION_START_DATE) AS CONDITION_ERA_START_DATE
	,ERA_END_DATE AS CONDITION_ERA_END_DATE
	,COUNT(*) AS CONDITION_OCCURRENCE_COUNT
FROM #cteConditionEnds
GROUP BY person_id
	,CONDITION_CONCEPT_ID
	,ERA_END_DATE;
```

### Drug Eras

If the DRUG_EXPOSURE table is populated this script will string together periods of time that a person is exposed to an active drug ingredient, allowing for 30 gaps in between. It will then insert the resulting era records into the DRUG_ERA table. **NOTE** This query only works with 5.3 and below.

```{sql eval = FALSE, echo = TRUE}

/****************************************************
OHDSI-SQL File Instructions
-----------------------------
 1. Set parameter name of schema that contains CDMv4 instance
    (@SOURCE_CDMV4, @SOURCE_CDMV4_SCHEMA)
 2. Set parameter name of schema that contains CDMv5 instance
    (@TARGET_CDMV5, @TARGET_CDMV5_SCHEMA)
 3. Run this script through SqlRender to produce a script that will work in your
    source dialect. SqlRender can be found here: https://github.com/OHDSI/SqlRender
 4. Run the script produced by SQL Render on your target RDBDMS.
<RDBMS> File Instructions
-------------------------
 1. This script will hold a number of placeholders for your CDM V4 and CDMV5
    database/schema. In order to make this file work in your environment, you
	should plan to do a global "FIND AND REPLACE" on this file to fill in the
	file with values that pertain to your environment. The following are the
	tokens you should use when doing your "FIND AND REPLACE" operation:
	
     [CDM]
	 [CDM].[CDMSCHEMA]
	
*********************************************************************************/
/* SCRIPT PARAMETERS */

	
	{DEFAULT @TARGET_CDMV5 = '[CDM]' } -- The target CDMv5 database name
	{DEFAULT @TARGET_CDMV5_SCHEMA = '[CDM].[CDMSCHEMA]' } -- the target CDMv5 database plus schema

USE @TARGET_CDMV5;



/****
DRUG ERA
Note: Eras derived from DRUG_EXPOSURE table, using 30d gap
 ****/
IF OBJECT_ID('tempdb..#cteDrugTarget', 'U') IS NOT NULL
	DROP TABLE #cteDrugTarget;

/* / */

-- Normalize DRUG_EXPOSURE_END_DATE to either the existing drug exposure end date, or add days supply, or add 1 day to the start date
SELECT d.DRUG_EXPOSURE_ID
	,d.PERSON_ID
	,c.CONCEPT_ID
	,d.DRUG_TYPE_CONCEPT_ID
	,DRUG_EXPOSURE_START_DATE
	,COALESCE(DRUG_EXPOSURE_END_DATE, DATEADD(day, DAYS_SUPPLY, DRUG_EXPOSURE_START_DATE), DATEADD(day, 1, DRUG_EXPOSURE_START_DATE)) AS DRUG_EXPOSURE_END_DATE
	,c.CONCEPT_ID AS INGREDIENT_CONCEPT_ID
INTO #cteDrugTarget
FROM @TARGET_CDMV5_SCHEMA.DRUG_EXPOSURE d
INNER JOIN @TARGET_CDMV5_SCHEMA.CONCEPT_ANCESTOR ca ON ca.DESCENDANT_CONCEPT_ID = d.DRUG_CONCEPT_ID
INNER JOIN @TARGET_CDMV5_SCHEMA.CONCEPT c ON ca.ANCESTOR_CONCEPT_ID = c.CONCEPT_ID
WHERE c.DOMAIN_ID = 'Drug'
	AND c.CONCEPT_CLASS_ID = 'Ingredient'
	AND c.STANDARD_CONCEPT = 'S';

/* / */

IF OBJECT_ID('tempdb..#cteEndDates', 'U') IS NOT NULL
	DROP TABLE #cteEndDates;

/* / */

SELECT PERSON_ID
	,INGREDIENT_CONCEPT_ID
	,DATEADD(day, - 30, EVENT_DATE) AS END_DATE -- unpad the end date
INTO #cteEndDates
FROM (
	SELECT E1.PERSON_ID
		,E1.INGREDIENT_CONCEPT_ID
		,E1.EVENT_DATE
		,COALESCE(E1.START_ORDINAL, MAX(E2.START_ORDINAL)) START_ORDINAL
		,E1.OVERALL_ORD
	FROM (
		SELECT PERSON_ID
			,INGREDIENT_CONCEPT_ID
			,EVENT_DATE
			,EVENT_TYPE
			,START_ORDINAL
			,ROW_NUMBER() OVER (
				PARTITION BY PERSON_ID
				,INGREDIENT_CONCEPT_ID ORDER BY EVENT_DATE
					,EVENT_TYPE
				) AS OVERALL_ORD -- this re-numbers the inner UNION so all rows are numbered ordered by the event date
		FROM (
			-- select the start dates, assigning a row number to each
			SELECT PERSON_ID
				,INGREDIENT_CONCEPT_ID
				,DRUG_EXPOSURE_START_DATE AS EVENT_DATE
				,0 AS EVENT_TYPE
				,ROW_NUMBER() OVER (
					PARTITION BY PERSON_ID
					,INGREDIENT_CONCEPT_ID ORDER BY DRUG_EXPOSURE_START_DATE
					) AS START_ORDINAL
			FROM #cteDrugTarget

			UNION ALL

			-- add the end dates with NULL as the row number, padding the end dates by 30 to allow a grace period for overlapping ranges.
			SELECT PERSON_ID
				,INGREDIENT_CONCEPT_ID
				,DATEADD(day, 30, DRUG_EXPOSURE_END_DATE)
				,1 AS EVENT_TYPE
				,NULL
			FROM #cteDrugTarget
			) RAWDATA
		) E1
	INNER JOIN (
		SELECT PERSON_ID
			,INGREDIENT_CONCEPT_ID
			,DRUG_EXPOSURE_START_DATE AS EVENT_DATE
			,ROW_NUMBER() OVER (
				PARTITION BY PERSON_ID
				,INGREDIENT_CONCEPT_ID ORDER BY DRUG_EXPOSURE_START_DATE
				) AS START_ORDINAL
		FROM #cteDrugTarget
		) E2 ON E1.PERSON_ID = E2.PERSON_ID
		AND E1.INGREDIENT_CONCEPT_ID = E2.INGREDIENT_CONCEPT_ID
		AND E2.EVENT_DATE <= E1.EVENT_DATE
	GROUP BY E1.PERSON_ID
		,E1.INGREDIENT_CONCEPT_ID
		,E1.EVENT_DATE
		,E1.START_ORDINAL
		,E1.OVERALL_ORD
	) E
WHERE 2 * E.START_ORDINAL - E.OVERALL_ORD = 0;

/* / */

IF OBJECT_ID('tempdb..#cteDrugExpEnds', 'U') IS NOT NULL
	DROP TABLE #cteDrugExpEnds;

/* / */

SELECT d.PERSON_ID
	,d.INGREDIENT_CONCEPT_ID
	,d.DRUG_TYPE_CONCEPT_ID
	,d.DRUG_EXPOSURE_START_DATE
	,MIN(e.END_DATE) AS ERA_END_DATE
INTO #cteDrugExpEnds
FROM #cteDrugTarget d
INNER JOIN #cteEndDates e ON d.PERSON_ID = e.PERSON_ID
	AND d.INGREDIENT_CONCEPT_ID = e.INGREDIENT_CONCEPT_ID
	AND e.END_DATE >= d.DRUG_EXPOSURE_START_DATE
GROUP BY d.PERSON_ID
	,d.INGREDIENT_CONCEPT_ID
	,d.DRUG_TYPE_CONCEPT_ID
	,d.DRUG_EXPOSURE_START_DATE;

/* / */

INSERT INTO @TARGET_CDMV5_SCHEMA.drug_era
SELECT row_number() OVER (
		ORDER BY person_id
		) AS drug_era_id
	,person_id
	,INGREDIENT_CONCEPT_ID
	,min(DRUG_EXPOSURE_START_DATE) AS drug_era_start_date
	,ERA_END_DATE
	,COUNT(*) AS DRUG_EXPOSURE_COUNT
	,30 AS gap_days
FROM #cteDrugExpEnds
GROUP BY person_id
	,INGREDIENT_CONCEPT_ID
	,drug_type_concept_id
	,ERA_END_DATE;

```

## **Example ETL Script**

### CDM_SOURCE Table

The script below is an example for how to fill in the CDM_SOURCE table. This table is required for the [Data Quality Dashboard](https://github.com/OHDSI/DataQualityDashboard) package to run. This was taken from the [ETL-Synthea](https://github.com/OHDSI/ETL-Synthea) package, a good example on how to write a complete extract-transform-load script from start to finish, including vocabulary import. 

```{sql eval = FALSE, echo = TRUE}
insert into @cdm_schema.cdm_source (
cdm_source_name,
cdm_source_abbreviation,
cdm_holder,
source_description,
source_documentation_reference,
cdm_etl_reference,
source_release_date,
cdm_release_date,
cdm_version,
vocabulary_version
) 
select
'Synthea synthetic health database',
'Synthea',
'OHDSI Community',
'SyntheaTM is a Synthetic Patient Population Simulator. The goal is to output synthetic, realistic (but not real), patient data and associated health records in a variety of formats.',
'https://synthetichealth.github.io/synthea/',
'https://github.com/OHDSI/ETL-Synthea',
getdate(), -- NB: Set this value to the day the source data was pulled
getdate(), 
'v5.3',
vocabulary_version
from @cdm_schema.vocabulary 
where vocabulary_id = 'None';
```

## **Bonus Queries**

### Visit Concept Roll-up

The query below will utilize the Visit Concept hierarcy to find the highest-level ancestors. In the case that both the VISIT_OCCURRENCE and VISIT_DETAIL tables are populated, it is good practice (though not required) to use the highest-level ancestors as the VISIT_CONCEPT_IDs in the VISIT_OCCURRENCE table and their children as the VISIT_DETAIL_CONCEPT_IDs in the VISIT_DETAIL table. This relationship between the VISIT_OCCURRENCE and VISIT_DETAIL tables allow for standardized Visit logic to be written, building Visits from Visit Details. For more information on how this can be done, please see the [Optum Extended ETL documentation](https://ohdsi.github.io/ETL-LambdaBuilder/Optum%20Clinformatics/Optum_visit_occurrence.html).

```{sql eval=FALSE, echo=TRUE}
SELECT concept_id, concept_name
  FROM concept 
  LEFT JOIN concept_ancestor 
 	ON concept_id=descendant_concept_id 
    AND ancestor_concept_id!=descendant_concept_id
  WHERE domain_id='Visit' 
 	AND standard_concept='S'
    AND ancestor_concept_id IS NULL
```
