# Presentation: 139340

## Analyzing NCHS Drug Data  

**Amy B. Bernstein, Sc.D.**
**Presented at the NCHS Board of Scientific Counselors Meeting**
**January 28, 2005**

## Health, United States special feature on drugs—overview
Description of drug databases
Issues in drug analyses
Lessons learned
Future analyses using drug data

- Description of drug databases
- Issues in drug analyses
- Lessons learned
- Future analyses using drug data

**Topics**

## Slide 3

**Notes:**
You should have received a copy, if not, let me know...

## Slide 4

**Notes:**
  This appeared in early January.

## Health, United States, 2004 Special Feature

**Charts on:**
**Overall use**
**Asthma drugs**
**Antidepressants (and SSRIs in particular) prescribed for adults**
**Antianxiety and antidepressant drugs prescribed for children**
**Cholesterol-lowering drugs (and statins in particular)**
**Nonsteroidal anti-inflammatory drugs (and COX-2 selective inhibitors in particular)**

## Health, United States, 2004 Chartbook Special Feature on Drugs

**	****Collaboration with FDA’s Center for ****	****Drug Evaluation Research (CDER) **
**      ****Data Sources**
- NHANES (prescription drug use in past one month period)
-  N/HAMCS data on drugs prescribed, ordered, administered, provided or continued  during physician office and hospital outpatient department visits

**Notes:**
FDA helped us select drug classes to examine...as you can see from the previous slide, they picked ones they were thinking about (NSAIDS such as Celebrex, Bextra, VIoxx; antidepressants for children).  THey thought about including antiobesity drugs and accutaine, but thought they might be too controversial!

## Definition of “Drug”

- NHANES
- A drug is defined as a unique combination of generic ingredients.
- N/HAMCS
- Recorded on visit record and abstracted verbatim

**Notes:**
Our drug data come from two major data systems, although the NHIS does collect a little bit of information about whether children take asthma drugs, and we have drug-related poisoning for NHDS  and deaths from vital statistics.

## NHANES  Drug Data

- All drugs used in the past month at time of survey interview
- Only prescription drugs are included, with a few exceptions
- Example:
- --penicillin
- --penicillin, clavulanate potassium** **
** ****More closely approximates “prevalence” of use**

## N/HAMCS Drug Data

- Up to six drugs recorded (until 2003)—possible biases for drugs that are not salient to the physician or patient (e.g., PRN drugs)
- Both prescription and non-prescription drugs are included
- No information is available on compliance or use
**Approximates prescribing patterns of drugs associated with medical care visits**

## Issues in Drug Utilization AnalysesNHANES

- Strengths:
- Nationally representative and population-based
- Examination, laboratory and questionnaire data on conditions, biochemical markers, nutrition, health status, and other items
- Respondent-reported sociodemographic data (e.g., race and ethnicity are collected from respondent)

## Issues in Drug Utilization AnalysesNHANES

- Possible Limitations:
- Small sample size for less frequently prescribed drugs and small population subgroups
-  No trade names that help to determine therapeutic use on public use file
- Respondents may not report use of some drugs

**Notes:**
e.g., Viagra seems to be underreported relative to industry sales data.

## Issues in Drug Utilization AnalysesN/HAMCS

- Strengths:
- Nationally representative
- Physician/hospital characteristics
- Conditions (from medical record—but limited number)
- Selected procedures and tests
- Relatively large sample size of visits

## Issues in Drug Utilization AnalysesN/HAMCS

- Possible Limitations:
- Limited sociodemographic data
- Race/ethnicity data are reported by provider, not patient
- Limited information on episodes or continuity of care
- No data on compliance or actual utilization
- Censoring of both drugs and diagnoses
- Drugs are recorded verbatim from visit records, with  possible misspelling

## Issues in Drug Utilization AnalysesN/HAMCS

- Factors influencing N/HAMCS counts of drugs:
- Person must have visited a physician or OPD
- The more visits made for a specific condition requiring a specific drug, the greater the count of that drug on the N/HAMCS

**Notes:**
for example there is probably better reporting of hypertension and diabetes medication than of “as needed” medication such as asthma control drugs.

## Coding Issues

- Only generic ingredients provided on NHANES public use file, and some N/HAMCS drugs are reported as generic drugs (e.g., “aspirin”)
- “Main reason for use” is collected  and coded into ICD-9-CM classification
-  Some drugs have the same ingredients but different strengths, or different routes of administration that help determine therapeutic use
- Examples: Asthma drugs

**Notes:**
Dependent on NHANES codes—cannot recode  Beclomethasone is the major ingredient in Beconase@ and Beclovent@, but only Beclovent@ is indicated for asthma

Flunisolide is the ingredient in both Aerobid@ and 
   Nasalide@, but only Aerobid@ is indicated for asthma

## Coding IssuesChanges Over Time

- N/HAMCS 1980-2001:  one NCD therapeutic class for each drug recorded
- N/HAMCS 2002-2006: up to three NCD therapeutic classes for each drug recorded
- NHANES 1988-94:  three NDC therapeutic classes for each drug reported
- NHANES 1999-2000:  six NDC therapeutic classes for each drug reported

**Notes:**
When analyzing trends, other issues must be considered. N/NAMCS 1980-2001:  only “first-listed” NDC therapeutic class used. These slides pertain to the public use files only. 

## Coding IssuesChanges Over Time

- Approved indications for drugs change over time (added or subtracted)
- “Major” uses for drugs with multiple therapeutic uses change over time
- Drugs may be replaced by other similar drugs
- Codes and categories are periodically revised
- Codes do not reflect “off-label” use

## Coding IssuesChanges Over Time

- Because therapeutic indications change over time
- Analysts can merge the most current classifications to drug data from previous years
- Otherwise drugs may be classified differently in different data years
- This is less of an issue when analyzing specific drugs

**Notes:**
This helps with the problem of changing indications over time, as well as the issue that only one therapeutic classification was coded for N/HAMCS drugs in older datasets and now three are coded (as Cathy discussed).

## Drugs Prescribed, Administered or Provided During Physician Office or OPD Visits, by Therapeutic Drug Class, 1995-96 and 2001-02

- SOURCE: Centers for Disease Control and Prevention, National Center for Health Statistics.
- Health, United States, 2004, table 87

**Notes:**
Example of therapeutic category analysis.  Because there are many different antidepressants it is useful to combine them into their therapeutic category. This does not imply that all antidepressants are prescribed for depression, however. 

## Antidepressant Use by Adults in N/HAMCS and NHANES

- Sources:  National Health and Nutrition Examination Surveys, National Ambulatory Medical Care Surveys and National Hospital Ambulatory Medical Care Surveys

**Notes:**
Different data; same trends.

## Use of Drugs in Past Month by Race/Ethnicity:  United States, 1988-94 and 1999-2000

| Persons age 18 and over with a prescription drug in the past month, by race and Hispanic origin, United States, 1988-94 and 1999-2000 |  |  |  |  |
| --- | --- | --- | --- | --- |
|  | Crude Percent |  | Age-adjusted Percent |  |
|  | 1988-94 | 1999-2000 | 1988-94 | 1999-2000 |
| White, not Hispanic or Latino | 41.4 | 48.2 | 41.1 | 47.4 |
| Black, not Hispanic or Latino | 31.2 | 34.6 | 36.9 | 40.1 |
| Mexican | 24.0 | 24.1 | 31.7 | 32.0 |

- Source: Centers for Disease Control and Prevention, National Center for Health Statistics. Health, United States, 2004, table 86

**Notes:**
Just a slide to show the effect of age adjustment...Mexican Americans are on average younger than other groups so when comparing age-adjustment makes a large difference (24 versus 32 percent)...

## Figure 33. Stimulant drug visits among children 5-17 years of age by sex: United States, 1994-2002

**Figure 33. Stimulant drug visits among children 5-17 years of age by sex: United States, 1994-2002**

- Boys

- 

- 

*Centers for Disease Control and Prevention, National Center for Health Statistics. Health, United States, 2004*

*Centers for Disease Control and Prevention, National Center for Health Statistics. Health, United States, 2004*

- Source: Centers for Disease Control and Prevention, National Center for Health Statistics. Health, United States, 2004

- Girls

**Notes:**
This is from HUS 2005

## Figure 36. Percent of nonsteroidal anti-inflammatory drug (NSAID) visits with COX-2 NSAIDs prescribed, ordered or provided among adults 18 years of age and over by sex: United States, 1999-2002

- 18-44 years

- 45-64 years

- 65-74 years

- 75 years and over

**Figure 36. Percent of nonsteroidal anti-inflammatory drug (NSAID) visits with COX-2 NSAIDs prescribed, ordered or provided among adults 18 years of age and over by sex: United States, 1999-2002**

- Percent of NSAID visits

- Centers for Disease Control and Prevention, National Center for Health Statistics. Health, United States, 2004

- 1999-2000

- 2001-2002

**Notes:**
This is not in HUS, but I thought you might be interested given the huge controversy over the COX-2’s.  The denominator is any NSAID, including ibuprofin (motrin) and naproxen (Aleve), so this shows the rapid switch in prescribing from the “older” NSAIDS to the ones that have now been pulled off the market..

## Lessons Learned From Health, United States, 2004 Drug Analyses

- Drug data are extremely complicated to analyze
- Each drug analysis is an entire study in and of itself, with different audiences, constituents, and language
- Simple statistics are the best received in the press (e.g., 44 percent of Americans taking at least one drug in the past month)
- Rates per population can be difficult to present effectively or to explain to reporters

**Notes:**
There should be a handout showing how popular our drug data are—it contains only a sample of articles using N/HAMCS data, and there are other studies using NHANES.  We did have some issues with explaining visit rates/population to some press people, though.

## Future Drug Analyses

- Trend tables showing percent of population with prescription drug use in past month (NHANES) and common therapeutic classes mentioned during ambulatory care visits (N/HAMCS) will be updated in HUS every year
- Several papers underway using both NHANES and N/HAMCS drug data (statins; antihypertensive drugs; antidepressants)
- New therapeutic coding systems are being investigated