Medication Data from Nationally Representative Provider- and Population-Based Surveys Lisa L. Dwyer, MPH Saeid Raofi, MS Pharmacy Karen A. Lees, MPH Ryne Paulose, PhD National Center for Health Statistics 2006 Data Users Conference (Session #50) Washington, D.C. July 12, 2006

2 Background  NCHS is the Nation’s principal health statistics agency compile statistical information to guide actions and policies to improve the health of our people compile statistical information to guide actions and policies to improve the health of our people provide public use files of survey data to the public provide public use files of survey data to the public  Congress  researchers  health planners

3 Background  Our health statistics allow us to: document the health status of the population document the health status of the population monitor trends in health status and health care delivery monitor trends in health status and health care delivery support biomedical and health services research support biomedical and health services research provide information to guide and evaluate health policy decisions and programs provide information to guide and evaluate health policy decisions and programs

4

5

6 Background  NCHS surveys that have collected medication data: National Health Care Survey (NHCS) National Health Care Survey (NHCS)  National Ambulatory Medical Care Survey (NAMCS)  National Hospital Ambulatory Medical Care Survey (NHAMCS)  National Nursing Home Survey (NNHS)  National Hospital Discharge Survey (NHDS) National Health and Nutrition Examination Survey (NHANES) National Health and Nutrition Examination Survey (NHANES)

7 Background  National Health Care Survey family of mostly provider-based surveys family of mostly provider-based surveys collects information about health care facilities, their services, and their patients collects information about health care facilities, their services, and their patients  National Health and Nutrition Examination Survey population-based survey population-based survey consists of a household interview, medical/dental examinations, and lab tests consists of a household interview, medical/dental examinations, and lab tests

8 Objectives  To describe how the National Center for Health Statistics (NCHS) collects medication data across its surveys  To describe how our data can be used to generate national estimates  To discuss the future direction of NCHS surveys

9 Prescription Medications  Drugs and their associated costs are at the forefront of national health care debates.  According to figures reported by CMS, prescription drug expenditures increased at a much faster rate than the total health care expenditure for most of  Access to and affordability of drugs for the elderly were major drivers behind the Medicare Part D Drug Benefit implementation.

10 Health Care Expenditures Source: Centers for Medicare & Medicaid Services;

11 Drug Utilization  This increase in cost is driven, in part, by an increase in utilization.  The national ambulatory health care surveys show that the number of drugs mentioned per visit increased between the 10-year period, 1993/1994 and 2003/2004.  Previous study reports that medication use is highest among the institutionalized elderly. This population continues to increase.

12 Increase in Drug Mention Rates Source: , NAMCS and NHAMCS

Collection and Processing of Drug Information in National Ambulatory Medical Care and National Hospital Ambulatory Medical Care Surveys

14 Drug Data Collection in National Health Care Surveys  I will focus on the National Ambulatory Health Care surveys, NAMCS and NHAMCS, which have collected drug data the longest.  The system developed for the processing and coding of the collected drug data for NAMCS and NHAMCS will be used for processing of the data in other surveys as well.  I will also give a detailed description of this processing and coding system.

15 NAMCS and NHAMCS Background  NAMCS Fielded , 1985, 1989-present Fielded , 1985, 1989-present Began collecting drug data in 1980 Began collecting drug data in 1980  NHAMCS Fielded annually since 1992 Fielded annually since 1992 Began collecting drug data in 1992 Began collecting drug data in 1992

16  Patient characteristics Age, sex, race, ethnicity Age, sex, race, ethnicity  Visit characteristics Source of payment, continuity of care, reason for visit, diagnosis, treatment, medications ordered or provided Source of payment, continuity of care, reason for visit, diagnosis, treatment, medications ordered or provided  Provider characteristics Physician specialty, hospital ownership Physician specialty, hospital ownership Items Collected

17  National probability sample surveys  Complex sample designs  Common definitions, data items, sampling frames  Medical diagnoses coded to ICD-9-CM  High response rates  Data processed by private contractor NCHS Common Methodology

18  NAMCS 3-stage sample 3-stage sample PSUs – physicians – physicians – visits during 1 week visits during 1 week  NHAMCS 4-stage sample 4-stage sample PSUs – hospitals – ED/OPD clinics – visits during 4 weeks visits during 4 weeks NAMCS and NHAMCS Sample Design

19 Generating National Estimates from Samples  Statistics from the NAMCS and NHAMCS are derived by a multistage estimation procedures that produce essentially unbiased national estimates.  The basic components of estimation are: Inflation by reciprocals of the sampling selection probabilities Inflation by reciprocals of the sampling selection probabilities Adjustment for nonresponse Adjustment for nonresponse Weight smoothing Weight smoothing A calibration ratio adjustment A calibration ratio adjustment

20 Sample Weight  The estimation procedure produces a single weight, called Patient Visit weight, for each NAMCS, OPD, and ED record.  This weight is used for both visits and drug mentions.  Weight must be applied or estimates of totals, percents and effects will be incorrect.

21 Definition of Drug Mentions A drug mention is the provider’s entry of drugs (prescription or over the counter), immunizations, allergy shots, anesthetics, chemotherapy, and dietary supplements that were ordered, supplied administered or continued during the visit.

22 Drug Data Processing  Since 2003, the provider can list up to eight drug mentions on the survey form. From 1995 to 2002 the provider could enter up to six drug mentions and before then up to five mentions.  Each drug mention will be associated with a drug code at data entry stage.  Drugs not in the database will be assigned a new unique code.

23 Adding Drug Characteristics  Upon completion of visit files, the following drug characteristics are added to visit files for each drug mention Generic name Generic name Therapeutic class Therapeutic class Ingredients Ingredients Composition Composition Control status Control status Rx or OTC Rx or OTC

24 Drug Coding and Characterization Example Drug name Generic name Therapeutic class ProzacMED#=25674FluoxetineGEN#=80006AntidepressantDRUGCL=0630 FluoxetineMED#=91079FluoxetineGen#=80006AntidepressantDRUGCL=0630 Fluoxetine HCL MED#=91079FluoxetineGEN#=80006AntidepressantDRUGCL=0630

25 Utility of Drug Characteristics  Drug characteristics can be used to create summary reports based on therapeutic class, active ingredients, etc.  They can be used in combination with patient and visit characteristics to study pharmacotherapy in specific disease areas.  They can be used in combination with physician characteristics in studies looking at prescribing behavior.

26 Example: Therapeutic classes with the highest mention rate in Therapeutic classification Number of mentions/100 visits Standard error of rate Drugs used for relief of pain Cardiovascular-renal drugs Respiratory tract drugs Central nervous system drugs Antimicrobial agents Metabolic/nutrient Hormones and agents affecting hormonal mechanisms Gastrointestinal agents Skin/mucous membrane drugs Immunologic agents

27 Example: Mentions of Antihypertensive Drugs for Ages from Probability of Hypertensive Visit having a Specific Drug Mention Predicted Probabilities Insurance Status VariableMeanInsuredUninsuredp-value ACE Inhibitors Beta Blockers Calcium Channel Blockers Diuretics Aspirin

28 Therapeutic Classification System Through 2004  Since 1985, the FDA’s NDC therapeutic classification has been used  Limitations of this system: Only has one level of sub-classification Only has one level of sub-classification FDA has discontinued this product FDA has discontinued this product

29 Adoption of Multum Lexicon as the Therapeutic Classification System  Starting with 2005 data, Multum therapeutic classification system will be used for classifying NAMCS and NHAMCS drug data.  This system has two level of sub-classification.  It is regularly updated.

30 Example: Classification of Paroxetine by the two classification systems  NDC system 0600 central nervous system 0600 central nervous system  0630 antidepressants  Multum Lexicon system 242 psychotherapeutic agents 242 psychotherapeutic agents  249 antidepressants  208 SSRI antidepressants

Using NAMCS/NHAMCS public use files for analyzing drug data

32 Ambulatory Care Data Structure Provider provider info practice info geographic info Visit patient & visit info treatment & outcome info medications Medcode 1 Class 1 …Class 3 …Medcode 8 Ingredient 1..ingredient 5 Visit

33 File Structure  Flat ASCII files for each setting and year  Use file layout to read the data  Input and format code available for: SAS SAS STATA STATA SPSS SPSS  Can use SETS (but no sampling variance estimates)

34 Visit File Layout Setting & Year Patient Info: Age, Sex, Race, Ethnicity Visit Info: Date, Reason for Visit, Payment source, Diagnosis, Patient Weight Treatment Info: Diagnostic services, Counseling/ education, Therapeutic services Medication Info: Drug Name, Generic Name, Ingredients, Therapeutic class Outcome Measures: No follow up planned, Return, Refer, Admit to Hospital Provider Info: Specialty, Region, Urban, Solo Practice, Ownership

35 Ambulatory Health Care Data

36 Drug Database System

37 Example of Drug Lookup Function   By brand name PAXIL   BY GENERIC NAME PAROXETINE

38

39

40

41

42 For more information on the NAMCS and NHAMCS, please visit

Medication Data Collected in the 2004 National Nursing Home Survey

National Nursing Home Survey  Nationally representative sample survey of U.S. nursing homes  services/programs  staff  residents  Conducted periodically since  1977, 1985, 1995, 1997, 1999, 2004

National Nursing Home Survey  Taken out of the field after the 1999 survey for a major redesign.  Put back into the field in 2004 computerized data collection computerized data collection many new content items, including collection of medication data many new content items, including collection of medication data supplemental survey on nursing assistants, NNAS supplemental survey on nursing assistants, NNAS

National Nursing Home Survey  Two-stage probability survey design nursing home facility nursing home facility residents (up to 12 current residents) residents (up to 12 current residents)

National Nursing Home Survey  Sampling frame Centers for Medicare and Medicaid Services Provider of Services file of U.S. nursing homes Centers for Medicare and Medicaid Services Provider of Services file of U.S. nursing homes state licensing lists compiled by private organization state licensing lists compiled by private organization total of 16,628 nursing homes in frame total of 16,628 nursing homes in frame

National Nursing Home Survey  Eligibility criteria licensed by State as a nursing facility licensed by State as a nursing facility certified and non-certified facilities certified and non-certified facilities three or more beds three or more beds

National Nursing Home Survey  Survey items medications taken 24 hrs before facility interview medications taken 24 hrs before facility interview  standing or routine medications, or PRNs  up to 25 medications medications taken regularly but not 24 hrs before facility interview medications taken regularly but not 24 hrs before facility interview  up to 25 medications reason medications were prescribed reason medications were prescribed

National Nursing Home Survey  Medication data found in medication administration records found in medication administration records  did not collect dosage, frequency, route collected during in-person interview at facility collected during in-person interview at facility entered into CAPI system by interviewer entered into CAPI system by interviewer processed like NAMCS/NHAMCS data processed like NAMCS/NHAMCS data

National Nursing Home Survey  Medication data collected prescription and nonprescription medications prescription and nonprescription medications generics generics supplements supplements  vitamin/mineral, herbal, nutritional

National Nursing Home Survey  Drug characteristics appended generic name generic name ingredients ingredients therapeutic classes therapeutic classes composition status composition status prescription status prescription status DEA status DEA status

National Nursing Home Survey  Data collected in 2004 NNHS are organized into three independent files: Facility Facility Resident Resident Prescribed medication Prescribed medication

National Nursing Home Survey  Resident File age age sex sex race race marital status marital status admission diagnosis admission diagnosis current primary and secondary diagnoses current primary and secondary diagnoses services/treatments received services/treatments received activities of daily living (ADLs) activities of daily living (ADLs) vaccination status vaccination status expected source(s) of payment expected source(s) of payment  Facility File bed size bed size ownership ownership services services per diem rates per diem rates special programs special programs staffing staffing

National Nursing Home Survey  The Prescribed Medications (PM) file includes: medication codes medication codes ICD-9 codes ICD-9 codes drug characteristics drug characteristics

National Nursing Home Survey PM Data File + Resident = AnalyticFile Warning: Great analytic potential but very large file with over 13,000 records and over 1000 variables per record. (164,000 KB) (13,000 KB) Link data files using a randomly assigned ID #

National Nursing Home Survey  New data set provides information on: 1.5 million current residents (weighted estimate) 1.5 million current residents (weighted estimate)  71% female, 29% male  mean age = 81 (standard error = 0.24)  86% White, 12% Black, 2% Other Preliminary Results.

National Nursing Home Survey Resources available to data users:  Tab delimited ASCII file of PM data  Long-term Care Drug Database  Data dictionary document  User’s manual  SAS, SPSS, and STATA input statements

National Nursing Home Survey Things to consider when analyzing NNHS data: complex sample survey design complex sample survey design  multiple stages of selection sampling weights are required sampling weights are required  point estimate  standard error statistical software that takes the sample design into account statistical software that takes the sample design into account

National Nursing Home Survey Guidelines for Reporting Estimates  Check sample size and standard error.  Calculate the relative standard error (RSE). If sample size < 30, then the value of the estimate should not be reported. If sample size is 30  59, or greater than 59 and the RSE  30%, then the estimate can be reported but should not be considered reliable. If sample size  60 and the RSE < 30, then the estimate is considered reliable.

National Nursing Home Survey Example: Mean number of medications per resident Total population: Mean = 8.73, SE Mean = 0.07 Male population: Mean = 8.52, SE Mean = 0.11 Female population: Mean = 8.81, SE Mean = 0.07 Preliminary Results.

National Nursing Home Survey RSE = (S.E. of point estimate/point estimate) * 100 RSE for Total population = (0.07/8.73) * 100 = 0.80 RSE for Male population = (0.11/8.52) * 100 = 1.29 RSE for Female population = (0.07/8.81) * 100 = 0.79 Preliminary Results.

National Nursing Home Survey Other examples of how data can be used:  to analyze how medications are used and if used for off- label indications  to examine the differences in medication use among subpopulations  to explore which medications were taken by residents receiving hospice/palliative/end-of-life care  to determine the top therapeutic classes taken by nursing home residents

64 Therapeutic Class % of residents (n=1,492,207) % ther. classes (n=12,979,578) Vitamins or minerals Laxatives Antidepressants Non-narcotic analgesics Acid or peptic disorder drugs Antipyretics Diuretics Replenishers/regulators of electrolytes Antiarthritics Antipsychotics or antimanics Top Therapeutic Classes Taken by Residents Preliminary Results.

65 For more information on the NNHS, please visit

Collecting Medication Data in the National Hospital Discharge Survey: Results from a Pilot Study

67 National Hospital Discharge Survey  Conducted annually since 1965  Produces nationally representative data on characteristics of patients discharged from Non- Federal, short-stay hospitals

68 National Hospital Discharge Survey  National probability sample: Short-stay, non-Federal hospitals Short-stay, non-Federal hospitals  Three stage design: Geographic units (PSUs) Geographic units (PSUs) Hospitals Hospitals Discharges Discharges

69 National Hospital Discharge Survey  Hospitals included: General hospitals General hospitals Children’s general hospitals Children’s general hospitals Hospitals with an average length of stay of less than 30 days Hospitals with an average length of stay of less than 30 days  Hospitals excluded: Federal hospitals Federal hospitals Military and VA hospitals Military and VA hospitals Hospitals in institutions (such as prisons) Hospitals in institutions (such as prisons) Hospitals with fewer than 6 beds Hospitals with fewer than 6 beds

70 National Hospital Discharge Survey  Sample Size Approximately 500 hospitals sampled per year Approximately 500 hospitals sampled per year Over 300,000 discharges sampled per year Over 300,000 discharges sampled per year  Data Collection 55% manual 55% manual 45% automated 45% automated  States, commercial firms, individual hospitals

71 National Hospital Discharge Survey  Data are abstracted from the patient’s medical record  Data are edited and weighted to produce national estimates

72 National Hospital Discharge Survey  Patient Data Age Age Sex Sex Race Race Expected source of payment Expected source of payment Admission source and type Admission source and type Discharge status Discharge status  Hospital Data Bed size Bed size Ownership Ownership Geographic region Geographic region

73 National Hospital Discharge Survey  Medical Data Diagnoses – principal and up to six secondary Diagnoses – principal and up to six secondary Surgical, diagnostic, or therapeutic procedures – up to four Surgical, diagnostic, or therapeutic procedures – up to four  Coded according to the International Classification of Diseases (ICD-9-CM)

74 National Hospital Discharge Survey  Weight: Inverse of the probability of selection Inverse of the probability of selection Adjustments for non-response Adjustments for non-response Population weighting ratio adjustment Population weighting ratio adjustment

75 National Hospital Discharge Survey and Uniform Bill-92 (UB-92)  Objective of UB-92 To standardize and increase the submission of electronic claims To standardize and increase the submission of electronic claims  UB-92 limits the information available for the NHDS to that which is necessary for billing  Unable to modify the variables collected in the NHDS

76 NHDS Pilot Study  To examine whether pharmaceutical data can be added to the manual or primary data collection part of NHDS  Two-phase study conducted in 34 hospitals in three areas of the country 791 discharges from discharges from 2003 Registered Health Information Technicians (RHIT) collected data Registered Health Information Technicians (RHIT) collected data Collected the names of all medications listed as administered in the medical record for that discharge Collected the names of all medications listed as administered in the medical record for that discharge

77 NHDS Pilot Study  Medications Total of 10,839 medications collected Total of 10,839 medications collected  74 were illegible or indeterminate (<1%) Range: 0 to 63 Range: 0 to 63 Mean: 13.61, Median: Mean: 13.61, Median: % had no medications listed 3% had no medications listed

78 Average number of medications overall and by gender

79 Average number of medications administered by age Overall: 13.6 medications

80 Average number of medications by length of stay Overall: 13.6 medications

81 Top Therapeutic Classes Therapeutic Class Medication Frequency (n=10,839) Patient Frequency (n=791) Narcotic analgesics 8.9%21.6% Laxatives4.9%12.4% Non-narcotic analgesics 4.8%16.2% Antipyretics4.6%10.1% Acid or peptic disorders 3.8%9.6% Antihistamines3.7%8.5% Replenishers or regulators of electrolytes 3.6%8.3% Vertigo or motion sickness or vomiting 3.5%9.0% Sedatives or hypnotics 2.9%10.1% NSAIDs2.8%11.1%

82 Top Generic Drugs Administered Therapeutic Class Medication Frequency (n=10,839) Patient Frequency (n=791) Acetaminophen7.2%66.2% Morphine2.2%25.7% Hydrocodone2.1%25.0% Docusate1.9%24.5% Magnesium antacids 1.8%24.9% Promethazine1.7%22.0% Potassium replacement solutions 1.6%18.6% Sodium chloride 1.5%16.6% Diphenhydramine1.4%18.6% Ondansetron hydrochloride 1.4%18.8%

83 For more information on the NHDS, please visit our webpage: For more information on the pilot study or the NHDS redesign, please contact me at: Karen Lees, MPH Phone: (301)

84 NHCS Future Steps  Adoption of Multum therapeutic classification system beginning with 2005 data  2007 National Home and Hospice Care Survey  2008 National Survey of Residential Care Facilities  2006 National Survey of Ambulatory Surgery  NHDS Redesign Contract currently let with RAND Contract currently let with RAND Options being evaluated currently Options being evaluated currently Anticipate new NHDS collecting data in 2010 Anticipate new NHDS collecting data in 2010