Mastering SQL for Enhanced Data Management in Healthcare

1. Geoff Kimber SQL Reporting

2. With thanks to Shawn Toy

3. Objectives • Realize the importance of learning SQL • Recognize SQL platform differences • Identify relational database concepts • Apply SQL syntax to a real-life example • Review SQL references

4. Hierarchical Databases • Data organized in tree structure with parent and child segments • Parent to child is a one to many relationship • Implies repeating information, generally in child segments • Fileman • Prescription file with refill multiple field

5. Relational Databases • Data consists of records stored in tables • Each row is unique • Column values are of the same data type • Sequence of rows and columns is insignificant

6. What is SQL? • Structured Query Language [SQL] • Is an ANSI computer language that is used to interact with many relational databases • Oracle • MS-SQL Server • MySQL, PostgreSQL and others • SQL is a set-based language • SQL is structured like English • SEQUEL (Simple English QUEry Language)

7. Why Learn SQL? • VA is truly data rich • Each site has between 2-4 TB of data† • non-imaging data • VA FileManager [FileMan] • Only within VistA • Limited functionality for non-programmers • Runs in the production environment • Workflow and resource concerns † - Pham R. The VA Data Lifecycle (Internals, Data Flows, and Business Intelligence)

8. Why Learn SQL? • Data repositories (warehouses) • Moves the analysis off-line • Provides accessible, yet very secure, data • ODBC, ADO and LINQ • Greater functionality and access control • The “official” data is secured within VistA • Independent of VistA • Microsoft Active Directory based access • Maintain the front-line stance of CPRS/VistA

9. Why Learn SQL? • Various VA relational databases • Corporate Data Warehouse (CDW) • Regional Data Warehouse (RDW) • VISN Data Warehouse (VDW) • Potential for local data warehouses • Extract raw data from VistA off-hours • UPSERT the data into an SQL server automatically • Users run their own reports and access is secure

10. Why Learn SQL? • Data warehouses = relational databases • SQL = the language of relational databases • Relational databases are everywhere • Learn a portable skill • Take a systems approach to collaboration • Build reusable code • Work more efficiently

11. Why SQL Server? • VA has an enterprise license • Microsoft SQL Server is functionally superior to Microsoft Access • Secure • Backups • Procedural code • No database size limit (software) • Efficiency

12. Microsoft Access & SQL Server • Two of the different SQL flavors • Transact SQL (Microsoft SQL Server) • Manage databases/services, procedural code • Jet SQL (Microsoft Access) • Information retrieval, program component • Each program has its own SQL flavor • Core keywords and functions follow standards • ANSI guidelines are “considered”

13. A Set-Based Language • In SQL: • Something is either part of a set or it is not • Order is meaningless • SQL Server supports procedural code • VBA can be used in MS Access for procedures

14. Corporate data warehouse structure • Dimension tables • Fact tables

15. Dimension tables • Contain attributes that describe records in fact tables • Each record contains unique identifier • Generally more stable • Drug name, provider name, patient name and address • Similar to Drug file (#50), New Person file (#200), Patient file (#2)

16. Fact tables • Capture operational data • Contain multiple unique identifiers • One identifier for each record • One identifier for each data element in dimension tables • Similar to Fileman IEN

17. Fact tables • Usually contain numerical and date fields • Prescription fills, Outpatient visits, lab test results • Similar to prescription file (#52), V POV (#9000010.07)

18. Dimension table examples • Dim.LocalDrug • LocalDrugSID • Sta3n (3 digit station number) • LocalDrugNameWithDose • VaClassification • PricePerDispenseUnit • NationalDrugSID

19. Dimension table examples

20. Dimension table examples • Dim.NationalDrug • NationalDrugSID • DrugNameWithoutDose • DosageForm • Strength

21. Dimension table examples

22. Dimension table examples • sPatient.sPatient • PatientSID • PatientName • PatientSSN • AddressLine1 • City • State • ZipCode

23. Fact table examples • RxOut.RxOutpat • RxOutpatSID • PatientSID • ProviderSID • LocalDrugSID • IssueDate • RxNumber

24. Fact table examples • Rxout.RxoutpatFill • RxoutpatFillSID • RxOutpatSID • FillType • ReleaseDateTime • Qty • DaysSupply • UnitPrice

25. CDW Tables • Metadata • Information about data • Includes CDW to VistA field crosswalk • http://vaww.dwh.cdw.portal.va.gov/metadata/default.aspx

26. CDW diagram

27. Drug file to national drug file

28. Prescription to prescription fill

29. Common SQL Clauses • Clauses perform set-based calculations

30. Common SQL Functions Microsoft Access supports the aggregate functions FIRST and LASTSQL Server has a COUNT(DISTINCT...) aggregate function

31. Common SQL Operators Access uses “*” as a wildcard and double quotes; SQL Server uses “%” and single quotesAccess uses the ampersand to concatenate “&”, SQL Server the plus sign “+”

32. Code example SelectLocalDrugSID ,NationalDrugSID ,LocalDrugNameWithDose fromvdw.dim.localdrug WhereLocalDrugNameWithDose like '%atenolol%'

33. Code example • Case is not normally important, but helps with readability • Spaces, tabs, and hard returns have limited importance • Important in text fields • Not important between commands • Help improve readability • Microsoft query analyzer color codes key words for readability

34. Code example • SQL databases have many different data types • Varchar • Int • Bigint • Smallint • Decimal • Float • Datetime • Money

35. Code example • Select • Main command used to retrieve data from SQL tables • Followed by list of fields to return • ‘*’ (without quotes) returns all fields in table • Normally, avoid using ‘*’ unless you need all the fields in a table

36. Code example • From vdw.dim.localdrug • Indicates source of data from which you are selecting • Vdw.dim.localdrug • VDW is database name • VDW => VISN Data Warehouse • RDW => Regional Data Warehouse • CDW => Corporate Data Warehouse • Dim is schema • Localdrug is table name

37. Code example • Where • Allows you to restrict or filter the table contents to just the results you want • Extremely versatile • Like • ‘%’ is a multicharacter wildcard • ‘%atenolol%’ - contains ‘atenolol’ • ‘atenolol%’ – begins with ‘atenolol’ • ‘%atenolol’ – ends with ‘atenolol’

38. Code example • Case is not normally important, but helps with readability • Spaces, tabs, and hard returns have limited importance • Important in text fields • Not important between commands • Help improve readability • Microsoft query analyzer color codes key words for readability

39. Code example SelectLocalDrugSID ,NationalDrugSID ,LocalDrugNameWithDose fromvdw.dim.localdrug Wherelocaldrugnamewithdose like '%atenolol%'

40. Code examples - Results

41. Fileman equivalent Select VA FileMan Option: PRINT File Entries OUTPUT FROM WHAT FILE: DRUG// SORT BY: GENERIC NAME// 'GENERIC NAME["ATENOLOL" WITHIN GENERIC NAME["ATENOLOL", SORT BY: FIRST PRINT FIELD: NUMBER THEN PRINT FIELD: PSNDF:NUMBER THEN PRINT FIELD: GENERIC NAME THEN PRINT FIELD:

42. Fileman equivalent

43. Joins • Used to connect two or more tables together using data elements that are shared by individual tables • Similar to fileman jumps, with more power • Inner joins, outer joins and full joins

44. Inner Joins • Produces a result that includes only the records that are the same in both tables

45. Inner Joins

46. Inner joins – Example Selecta.localdrugnamewithdose , b.strength fromvdw.dim.localdrug as a inner join vdw.dim.nationaldrug b ona.NationalDrugSID = b.NationalDrugSID whereLocalDrugNameWithDose like ‘%atenolol%’

47. Inner joins - Results

48. Outer joins • Results contain all records in one table and only matching records in another table • Left joins – return all results in table specified in ‘from’ statement and all matching tables from ‘joined’ table • Right joins – return all results in table specified in ‘joined’ table ‘from’ statement and all matching tables from ‘from’ statement

49. Outer joins

50. Outer joins – example Selecta.localdrugnamewithdose , b.strength fromvdw.dim.localdrug as a left outer join vdw.dim.nationaldrug b ona.NationalDrugSID = b.NationalDrugSID whereLocalDrugNameWithDose like ‘%atenolol%’