Understanding and Using NAMCS and NHAMCS Data:

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Understanding and Using NAMCS and NHAMCS
Data A Hands-On Workshop Susan M.
Schappert Donald K. Cherry
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Overview

• I. Survey Background and Data Uses
• II. Technical Considerations
• III. Getting the Data Navigate Our Website
• IV. SETS Hands-On Training
• Break
• V. Using Raw Data Files
• VI. Advanced Topics
• VII. Summary

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NAMCS and NHAMCS

• National Ambulatory Medical Care Survey (NAMCS)
• Visits to office-based physicians
• National Hospital Ambulatory Medical Care Survey
  (NHAMCS)
• Visits to hospital outpatient and emergency
  departments

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Original NAMCS survey goals

• National statistics
• Professional education
• Health policy formulation
• Medical practice management
• Quality assurance

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Sample design - NAMCS

• 112 PSUs (counties)
• Nonfederally employed, office-based physicians
  stratified by specialty
• About 30 visits per doctor over a randomly
  selected 1-week period

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Sample design - NHAMCS

• 112 PSUs (counties)
• Panel of 600 non-Federal, general or short stay
  hospitals
• Clinics (OPDs) and emergency service areas (EDs)
• About 200 visits per OPD,
• 100 per ED over random 4-week period

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Data Items

• Patient characteristics
• Age, sex, race, ethnicity
• Visit characteristics
• Source of payment, continuity of care, reason for
  visit, diagnosis, treatment
• Provider characteristics
• Physician specialty, hospital ownership
• Drug characteristics added in 1980
• Class, composition, control status, etc.

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Repeating fields (from text entries)

• Up to 3 fields each
• Reason for visit
• Physicians diagnosis
• Cause of injury
• Diagnostic services (6 fields)
• Surgical procedures (2 fields)
• Medications (6 fields)
• Drug ingredients (5 fields)
• Therapeutic class (3 fields 2002 on)

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Coding Systems Used

• Reason for Visit Classification (NCHS)
• ICD-9-CM for diagnoses, causes of injury and
  procedures
• Drug Classification System (NCHS)
• National Drug Code Directory

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Drug Data in NAMCS/ NHAMCS

• What is a Drug Mention ?
• 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.
• Respondents are asked to report trade names or
  generic names only (not dosage, administration,
  or regimen). Cant link drugs with diagnosis.

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Drug Coding in NAMCS and NHAMCS

• Drug entries on the Patient Record form are coded
  twice, using two separate classifications, and
  yielding two separate types of information
• All entries are coded as written using the Drug
  Entry Coding List
• All entries are also coded according to their
  generic substance(s) using a separate
  classification of generic substance codes

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Drug Coding in NAMCS and NHAMCS (cont.)

• Drug entry codes and generic substance codes are
  independent of each other
• 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.

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Drug Characteristics

• Generic Name (for single ingredient drugs)
• Prescription Status
• Composition Status
• Controlled Substance Status
• Up to 3 NDC Therapeutic Classes (4-digit)
• Up to 5 Ingredients (for multiple ingredient
  drugs)

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• NAMCS or NHAMCS drug data can be analyzed
• at the visit level (for example, the number of
  visits at which a particular drug was prescribed)
• or at the medication level (for example, the
  number of mentions of a particular drug at
  ambulatory care visits

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Some User Considerations

• NAMCS/NHAMCS sample visits, not patients
• No estimates of incidence or prevalence
• No state-level estimates
• We do not sample by setting or by non-physician
  providers
• May capture different types of care for solo vs.
  group practice physicians

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A few words about item validity

• Counseling items from NAMCS and OPD are often
  used as analytic variables in research papers
• Medical records are accurate in reflecting
  diagnostic services, but not health habit
  counseling (Stange et al. 1998, Gilchrist et al.
  2004)
• Our surveys may be underestimating counseling
  services especially where data are abstracted

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Sample Weight

• Each NAMCS record contains a single weight, which
  we call Patient Visit Weight
• Same is true for OPD records and ED records
• This weight is used for both visits and drug
  mentions

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Reliability of Estimates

• Estimates should be based on at least 30 sample
  records AND
• Estimates with a relative standard error
  (standard error divided by the estimate) greater
  than 30 percent are considered unreliable by NCHS
  standards
• Both conditions should be met to obtain reliable
  estimates

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How Good are the Estimates?

• Depends on what you are looking at. In general,
  OPD estimates tend to be somewhat less reliable
  than NAMCS and ED.
• Since 1999, our Advance Data reports include
  standard errors in every table so it is easy to
  compute confidence intervals around the
  estimates.

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Reliability of Estimates in NAMCS

• Estimate of office visits by white persons was
  766.1 million in 2002, with a relative standard
  error of 3.5 percent
• range of 714.0-818.2 million visits
• Estimate of office visits by black persons was
  89.5 million in 2002 with a relative standard
  error of 9.1 percent
• range of 73.6-105.3 million visits

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Reliability of Estimates in NHAMCS

• OPD 9 and 12 RSE for visits by white persons
  vs. visits by black persons
• ED 4 and 7 RSE for visits by white persons
  vs. visits by black persons
• A higher RSE means that an estimate has a wider
  confidence interval and is less reliable.

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Sampling Error

• NAMCS and NHAMCS are not simple random samples
• Clustering effects of visits within the
  physicians practice, physician practices within
  PSUs, clinics within hospitals
• Must use some method to calculate standard errors
  for frequencies, percents, and rates

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Calculating Variance with NAMCS/NHAMCS Estimates

• Old way (least accurate) Generalized variance
  curves
• Better way (recommended) Masked design
  variables
• Multiple sampling stages
• Single stage of sampling or ultimate cluster
  design
• Most accurate way (expensive) Actual design
  variables

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Comparison of RSEs Produced Using GVC,
SUDAAN-True, and SUDAAN WR
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Comparisons of RSEs for Patient Race

• 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

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Ways to Improve Reliability of Estimates

• Combine NAMCS, ED and OPD data to produce
  ambulatory care visit estimates
• Combine multiple years of data
• Aggregate categories of interest into broader
  groups.

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NAMCS vs. NHAMCS

• Consider what types of settings are best for a
  particular analysis
• Persons of color are more likely to visit OPDs
  and EDs than physician offices
• Persons in some age groups make
  disproportionately larger shares of visits to
  EDs than offices and OPDs

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Additional Information

• Call us at [phone]
• Email me at SSchappert_at_cdc.gov
• Visit our website
• Join the ACLIST. Its a moderated newsgroup for
  persons interested in NAMCS/NHAMCS. It currently
  consists of more than 2,000 subscribers.