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  • Sess_39_NAMCS&NHAMCS_hands-on_SCHAPPERT

    1. 1. Understanding and Using NAMCS and NHAMCS Data: A Hands-On Workshop Susan M. Schappert Donald K. Cherry
    2. 2. Overview <ul><li>I. Survey Background and Data Uses </li></ul><ul><li>II. Technical Considerations </li></ul><ul><li>III. Getting the Data – Navigate Our Website </li></ul><ul><li>IV. SETS Hands-On Training </li></ul><ul><li>* * Break * * </li></ul><ul><li>V. Using Raw Data Files </li></ul><ul><li>VI. Advanced Topics </li></ul><ul><li>VII. Summary </li></ul>
    3. 3. NAMCS and NHAMCS <ul><li>National Ambulatory Medical Care Survey (NAMCS) </li></ul><ul><ul><li>Visits to office-based physicians </li></ul></ul><ul><li>National Hospital Ambulatory Medical Care Survey (NHAMCS) </li></ul><ul><ul><li>Visits to hospital outpatient and emergency departments </li></ul></ul>
    4. 4. Original NAMCS survey goals <ul><li>National statistics </li></ul><ul><li>Professional education </li></ul><ul><li>Health policy formulation </li></ul><ul><li>Medical practice management </li></ul><ul><li>Quality assurance </li></ul>
    5. 6. Sample design - NAMCS <ul><li>112 PSUs (counties) </li></ul><ul><li>Nonfederally employed, office-based physicians stratified by specialty </li></ul><ul><li>About 30 visits per doctor over a randomly selected 1-week period </li></ul>
    6. 7. Sample design - NHAMCS <ul><li>112 PSUs (counties) </li></ul><ul><li>Panel of 600 non-Federal, general or short stay hospitals </li></ul><ul><li>Clinics (OPDs) and emergency service areas (EDs) </li></ul><ul><li>About 200 visits per OPD, </li></ul><ul><li>100 per ED over random 4-week period </li></ul>
    7. 8. Data Items <ul><li>Patient characteristics </li></ul><ul><ul><li>Age, sex, race, ethnicity </li></ul></ul><ul><li>Visit characteristics </li></ul><ul><ul><li>Source of payment, continuity of care, reason for visit, diagnosis, treatment </li></ul></ul><ul><li>Provider characteristics </li></ul><ul><ul><li>Physician specialty, hospital ownership… </li></ul></ul><ul><li>Drug characteristics added in 1980 </li></ul><ul><ul><li>Class, composition, control status, etc. </li></ul></ul>
    8. 9. Repeating fields (from text entries) <ul><li>Up to 3 fields each… </li></ul><ul><ul><li>Reason for visit </li></ul></ul><ul><ul><li>Physician’s diagnosis </li></ul></ul><ul><ul><li>Cause of injury </li></ul></ul><ul><li>Diagnostic services (6 fields) </li></ul><ul><li>Surgical procedures (2 fields) </li></ul><ul><li>Medications (6 fields) </li></ul><ul><ul><li>Drug ingredients (5 fields) </li></ul></ul><ul><ul><li>Therapeutic class (3 fields – 2002 on) </li></ul></ul>
    9. 10. Coding Systems Used <ul><li>Reason for Visit Classification (NCHS) </li></ul><ul><li>ICD-9-CM for diagnoses, causes of injury and procedures </li></ul><ul><li>Drug Classification System (NCHS) </li></ul><ul><li>National Drug Code Directory </li></ul>
    10. 11. Drug Data in NAMCS/ NHAMCS <ul><li>What is a “Drug Mention” ? </li></ul><ul><li>Any of up to 6 medications (including Rx and OTC medications, immunizations, allergy shots, anesthetics, and dietary supplements) that were ordered, supplied, administered, or continued during the visit. </li></ul><ul><li>Respondents are asked to report trade names or generic names only (not dosage, administration, or regimen). Can’t link drugs with diagnosis . </li></ul>
    11. 12. Drug Coding in NAMCS and NHAMCS <ul><li>Drug entries on the Patient Record form are coded twice, using two separate classifications, and yielding two separate types of information </li></ul><ul><li>All entries are coded “as written” using the Drug Entry Coding List </li></ul><ul><li>All entries are also coded according to their generic substance(s) using a separate classification of generic substance codes </li></ul>
    12. 13. Drug Coding in NAMCS and NHAMCS (cont.) <ul><li>Drug entry codes and generic substance codes are independent of each other </li></ul><ul><li>For example, there is a code for an entry of “acetaminophen” on the Patient Record form in the Drug Entry Classification and a separate code for acetaminophen in the Generic Classification. </li></ul>
    13. 14. Drug Characteristics <ul><li>Generic Name (for single ingredient drugs) </li></ul><ul><li>Prescription Status </li></ul><ul><li>Composition Status </li></ul><ul><li>Controlled Substance Status </li></ul><ul><li>Up to 3 NDC Therapeutic Classes (4-digit) </li></ul><ul><li>Up to 5 Ingredients (for multiple ingredient drugs) </li></ul>
    14. 15. <ul><li>NAMCS or NHAMCS drug data can be analyzed </li></ul><ul><ul><li>at the visit level (for example, the number of visits at which a particular drug was prescribed) </li></ul></ul><ul><ul><li>or at the medication level (for example, the number of “mentions” of a particular drug at ambulatory care visits </li></ul></ul>
    15. 16. Some User Considerations <ul><li>NAMCS/NHAMCS sample visits, not patients </li></ul><ul><li>No estimates of incidence or prevalence </li></ul><ul><li>No state-level estimates </li></ul><ul><li>We do not sample by setting or by non-physician providers </li></ul><ul><li>May capture different types of care for solo vs. group practice physicians </li></ul>
    16. 17. A few words about item validity <ul><li>Counseling items from NAMCS and OPD are often used as analytic variables in research papers </li></ul><ul><li>Medical records are accurate in reflecting diagnostic services, but not health habit counseling (Stange et al. 1998, Gilchrist et al. 2004) </li></ul><ul><li>Our surveys may be underestimating counseling services especially where data are abstracted </li></ul>
    17. 18. Sample Weight <ul><li>Each NAMCS record contains a single weight, which we call Patient Visit Weight </li></ul><ul><li>Same is true for OPD records and ED records </li></ul><ul><li>This weight is used for both visits and drug mentions </li></ul>
    18. 19. Reliability of Estimates <ul><li>Estimates should be based on at least 30 sample records AND </li></ul><ul><li>Estimates with a relative standard error (standard error divided by the estimate) greater than 30 percent are considered unreliable by NCHS standards </li></ul><ul><li>Both conditions should be met to obtain reliable estimates </li></ul>
    19. 20. How Good are the Estimates? <ul><li>Depends on what you are looking at. In general, OPD estimates tend to be somewhat less reliable than NAMCS and ED. </li></ul><ul><li>Since 1999, our Advance Data reports include standard errors in every table so it is easy to compute confidence intervals around the estimates. </li></ul>
    20. 21. Reliability of Estimates in NAMCS <ul><li>Estimate of office visits by white persons was 766.1 million in 2002, with a relative standard error of 3.5 percent – </li></ul><ul><ul><li>range of 714.0-818.2 million visits </li></ul></ul><ul><li>Estimate of office visits by black persons was 89.5 million in 2002 with a relative standard error of 9.1 percent – </li></ul><ul><ul><li>range of 73.6-105.3 million visits </li></ul></ul>
    21. 22. Reliability of Estimates in NHAMCS <ul><li>OPD = 9% and 12% RSE for visits by white persons vs. visits by black persons </li></ul><ul><li>ED = 4% and 7% RSE for visits by white persons vs. visits by black persons </li></ul><ul><li>A higher RSE means that an estimate has a wider confidence interval and is less reliable. </li></ul>
    22. 23. Sampling Error <ul><li>NAMCS and NHAMCS are not simple random samples </li></ul><ul><li>Clustering effects of visits within the physician’s practice, physician practices within PSUs, clinics within hospitals </li></ul><ul><li>Must use some method to calculate standard errors for frequencies, percents, and rates </li></ul>
    23. 24. Calculating Variance with NAMCS/NHAMCS Estimates <ul><li>Old way (least accurate) = Generalized variance curves </li></ul><ul><li>Better way (recommended) = Masked design variables </li></ul><ul><ul><li>Multiple sampling stages </li></ul></ul><ul><ul><li>Single stage of sampling or ultimate cluster design </li></ul></ul><ul><li>Most accurate way (expensive) = Actual design variables </li></ul>
    24. 25. Comparison of RSEs Produced Using GVC, SUDAAN-True, and SUDAAN WR
    25. 26. Comparisons of RSEs for Patient Race <ul><li>Variances for clustered items (like race, diagnosis, type of provider) are predicted less accurately using the GVC. If you use the GVC, use p = .01, not .05 </li></ul>
    26. 27. Ways to Improve Reliability of Estimates <ul><li>Combine NAMCS, ED and OPD data to produce ambulatory care visit estimates </li></ul><ul><li>Combine multiple years of data </li></ul><ul><li>Aggregate categories of interest into broader groups. </li></ul>
    27. 28. NAMCS vs. NHAMCS <ul><li>Consider what types of settings are best for a particular analysis </li></ul><ul><ul><li>Persons of color are more likely to visit OPD’s and ED’s than physician offices </li></ul></ul><ul><ul><li>Persons in some age groups make disproportionately larger shares of visits to ED’s than offices and OPD’s </li></ul></ul>
    28. 30. Additional Information <ul><li>Call us at (301) 458-4600 </li></ul><ul><li>Email me at </li></ul><ul><li>Visit our website </li></ul><ul><li>Join the ACLIST. It’s a moderated newsgroup for persons interested in NAMCS/NHAMCS. It currently consists of more than 2,000 subscribers. </li></ul>