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10 Steps to Easier SAS Code Maintenance

Jessica Hampton, CIGNA

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IntroductionUSE:• Simple organization techniques• Macro variables• Parameterized macros • Appropriate documentation

TO:• Reduce hard coding• Reduce code volume• Make regularly updated values easy to find

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Steps 1-2: Chunking & Numbering

• Break up large processes into individual programs

• Number programs in order of process flow

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Steps 1-2: example

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Step 3: Initial Setup• Create an initial setup program

for:– Libnames– Remote sessions– Macro variables– System options

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Step 3: Initial Setup example

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Step 4: Final Cleanup• Create a final cleanup program to:

– Download files on remote server– Delete interim files no longer needed– Create final table listing and export

“data dictionary” to Excel– Use data dictionary to identify problems

•Unexpected row counts•Unnecessarily long fields

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Step 4: Final Cleanup

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Step 5: Macro Variables• Use macro variables for date selection

criteria:

…where ben_feat_eff_dt <=”&startdate”d and ben_feat_can_dt>”&startdate”d;

…Case when HRA_Month_Start = 1 Then &yearmonth + HRA_Month_Start Else &yearlastmonth +

HRA_Month_Start End as HRA_Prog_Yr_Start,…

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Step 6: Macro Variables• Use macro variables for file

names:

Create Table qry_Ben_Feat_&year as…

Proc Download Data = WHP.Internal_EPop_&year OUT=HRA.Internal_EPop_&year;

Libname PPO “/projects/hedis/ppo&year”;

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Step 7: Macro Variables• Use macro variables for frequently updated/referenced lists:

%let markets = %str('WA','OR','CA','CO','TN','FL','SC','MD','DC','OH','NJ','NY','CT'); /*eValu8 markets*/

%let diabetes = %str('25000','25001','25002','25003','25010','25011','25012','25013','25020','25021','25022','25023','25030','25050','25051','25052','25053','25060','25061','25062','25063','25070','25071','25072','25073','25080','25031','25032','25033','25040','25041','25042','25043','25081','25082','25083','25090','25091','25092','25093');/*diabetes diagnosis codes, used in measures 1,3,14,16*/

SELECT code INTO: opnaiprev separated by '","' /*outpatient, non-acute inpatient revenue proc codes*/

FROM ref.ectWHERE description in('outpatient','nonacute_inpatient')AND typeofcode='RevCode'AND tablename='CDC_C';

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Step 7: (continued)• Code is shorter • Easier to understand• Can update all in one place

WHERE svc_dt BETWEEN "01jan&yearp"d AND "31dec&year"d /*current year or year prior*/

AND (diag_cd1 IN (&diagcd) OR diag_cd2 IN (&diagcd) OR diag_cd3 IN (&diagcd))/*primary or secondary diagnosis code*/

AND (proc_cd IN("&aipedcpt")/*acute inpatient or ED cpt codes*/

OR (proc_cd IN("&aipedrev")

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Step 8: Parameterized Macros

• Analyze processes for similarities• Identify re-usable pieces of code• Convert to parameterized

macros• Reduce code volume

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Step 8: Analysis

Measure Numerator Exclusions

1,3,10,14

include discharges with principal diagnosis code specified:diabetes short term complicationsdiabetes long term complicationshypovolemiauncontrolled diabetes transfers

7*,8,13

include discharges with principal diagnosis code specified: hypertensionCHFangina

transferscardiac procedure codes in any field*For 7 only, also exclude kidney disease diagnoses if accompanied by hemodialysis procs

11,12

include discharges with principal diagnosis code specified: bacterial pneumoniaUTI

transfersimmunocompromised state proc codesimmunocompromised state diagnoses*For 11, also exclude anemia principal or secondary diagnoses*For 12, also exclude principal or secondary kidney disorder diagnoses

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Step 8: Parameterized Macro%macro transfer(filename=)/STORE SOURCE; /*identify and delete transfers from

numerator*/

CREATE TABLE &filename._TRANS AS

SELECT B.conf_id, B.admit_dt, A.disch_dt

FROM PQI.&filename A

JOIN PQI.&filename B ON A.rhmo=B.rhmo AND A.bkey=B.bkey

AND A.disch_dt BETWEEN B.admit_dt AND intnx('DAY',B.admit_dt,-1)/*re-admitted within 24 hours of discharge date*/

WHERE A.conf_id <> B.conf_id

AND A.src_sys_prov_id <> B.src_sys_prov_id /*transferred from different facility*/

;

DELETE

FROM PQI.&filename

WHERE conf_ID IN

(SELECT conf_id FROM &filename._TRANS)

;

%mend transfer;

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Step 8: Putting it Together

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Steps 9-10: Documentation

• Comment code• Use program headers

– Program name– Developer name– Date created– Purpose– Update information

• Programmer name• Date modified• Reason for modification

– Input/output tables

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Conclusion1. Break up large processes into smaller steps2. Number programs in order of process flow3. Create initial setup program4. Create final cleanup program5. Use macro variables for date selection criteria6. Use macro variables for file names7. Use macro variables for long lists that need

frequent updating and/or are referenced frequently

8. Use parameterized macros for similar processes9. Document using comments10.Document using program headers

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References• SAS Institute Inc. 2009. SAS 9.2 Macro

Language Reference. Cary, NC: SAS Institute, Inc.

• Patridge, C. Best Practices: Using SAS Effectively/Efficiently. HASUG presentation 2/24/2011.

• Rhodes, D. If You Have Programming Standards, Please Raise Your Hand: An Everyman’s Guide. http://www.nesug.org/Proceedings/nesug10/ma/ma10.pdf (5/31/2011).

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AcknowledgementSAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration.

Other brand and product names are registered trademarks or trademarks of their respective companies.