1 / 19

Understanding and Using NAMCS and NHAMCS Data: A Hands-On Workshop Part II-Using Raw Data Files

Understanding and Using NAMCS and NHAMCS Data: A Hands-On Workshop Part II-Using Raw Data Files Donald Cherry. Session Goals. A the end of this session I would like you to: Be able to successfully download data files and create a SAS dataset for analysis

raja
Download Presentation

Understanding and Using NAMCS and NHAMCS Data: A Hands-On Workshop Part II-Using Raw Data Files

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Understanding and Using NAMCS and NHAMCS Data: A Hands-On Workshop Part II-Using Raw Data Files Donald Cherry

  2. Session Goals • A the end of this session I would like you to: • Be able to successfully download data files and create a SAS dataset for analysis • Understand some of the limitations and advantages of using NAMCS/NHAMCS downloadable data • Perform simple analyses

  3. Using raw data files • File structure • Exercises using SUDAAN & SAS Proc Surveymeans • Downloading data & creating a SAS dataset • Simple frequencies with/without standard errors • Creating a new variable-Asthma • Visit rates-male/female • Total number of drug mentions • Antidepressant drug mentions • Time spent with physician • Trend considerations • Other issues--multiple years/settings • Summary

  4. File Structure • Download data and layout from website http://www.cdc.gov/nchs/about/major/ahcd/ahcd1.htm • Flat ASCII files for each setting and year NAMCS: 1973-2002 NHAMCS: 1992-2002

  5. Structure organization

  6. Hands-on Exercises • Double-click: My Computer\Local Disk C:\DUC_04 • Double-click: SAS file: Exercises

  7. SAS version 9.1 example procsurveyfreq data=namtest1; tables sex*ager; strata cstratm; cluster cpsum; weight patwt2; run;

  8. Visit estimates Female population=800 Calculation* New variable *Note: Rate=est/pop=Σ patwt/pop=1/pop*Σ patwt.

  9. Arrays Total drug mentions: 7 Note: 90000=No mention.

  10. Some considerations: SUDAAN vs. SAS Proc Surveymeans

  11. Trend considerations • Variables routinely rotate on and off survey • Be careful about trending diagnosis prior to 1979 because of ICDA (based on ICD-8) • Even after 1980- be careful about changes in ICD-9-CM • Number of medications varies over years 1980-81 – 8 medications 1985, 1989-94 – 5 medications 1995-2002 – 6 medications 2003+8 – medications • Diagnostic & therapeutic checkboxes vary • Use spreadsheet for significance of trends

  12. Combining multiple years • 2 year combinations are best for subpopulation analysis • 3-4 year combinations for disease specific analysis • Keep adding years until you have at least 30 raw cases in important cells • RSE improves incrementally with the number of years combined

  13. RSE improves incrementally with the number of years combined • RSE = SE/x • RSE for percent of visits by persons less than 21 years of age with diabetes • 1999 RSE = .08/.18 = .44 (44%) • 1998 & 1999 RSE = .06/.18 = .33 (33%) • 1998, 1999, & 2000 RSE = .05/.21 = .24 (24%)

  14. Combining multiple settings • NAMCS, ED, and OPD can be combined in one or multiple years • NAMCS & OPD variables virtually identical, many ED variables are same • OPD and NAMCS should be combined to get estimates of ambulatory physician care especially for African-American, Medicaid or adolescent subpopulations • Only NAMCS has physician specialty

  15. Design Variables—Survey Years 2002 2001* 1-Stage design variables 3- & 4-Stage design variables 3- & 4-Stage design variables 2003 1-Stage design variables only *Plan to re-release years with 1-stage design variables.

  16. Code to create design variables: survey years 2001 & earlier CPSUM=PSUM; CSTRATM = STRATM; IF CPSUM IN(1, 2, 3, 4) THEN DO; CPSUM = PROVIDER +100000; CSTRATM = (STRATM*100000) +(1000*(MOD(YEAR,100))) + (SUBFILE*100) + PROSTRAT; END; ELSE CSTRATM = (STRATM*100000);

  17. If nothing else, remember…The Public Use Data File Documentation is YOUR FRIEND! • Each booklet includes: • A description of the survey • Record format • Marginal data (summaries) • Various definitions • Reason for Visit classification codes • Medication & generic names • Therapeutic classes

  18. Where to get more information? • www.cdc.gov/nchs/about/major/ahcd1.htm • Call Ambulatory Care Statistics Branch at 301-458-4600

More Related