Available Types of National Drug Use Data DSARM Advisory Committee Meeting Silver Spring, Maryland May 18, 2005 Judy Staffa, PhD, RPh, Epidemiology Team Leader Division of Surveillance, Research & Communication Support Office of Drug Safety Center for Drug Evaluation and Research

Overview Applications of drug use data Typical questions Challenges Available types of data by question and setting of care Summary Future challenges

Applications of drug use data in drug safety Denominators for putting AERS reports into context (e.g., reporting rates) Description of prescribing patterns physicians’ specialty patient demographics associated diagnoses/procedures Insight into duration of use and concomitant use of multiple drugs Surveillance of risk management practices to restrict drug use Impact of potential medication errors

How many patients in the U.S. take drug A? “$64,000 question” How many patients in the U.S. take drug A?

Other common questions What are the demographics of patients on drug A? How long do patients stay on drug A? How often do patients take drugs A and B together? For what indication is drug A prescribed? By which types of physicians? What drugs are being prescribed for condition X?

Challenges Fragmentation of U.S. health care system “Pockets” of use Settings of care/payers/buyers Projections to national estimates for “pocket” Sum across “pockets”

Settings Outpatient (Rx) Pharmacies/Mail order Physician Offices Clinics Inpatient Over-the-counter (OTC)

Additional challenges Secondary data sources Administrative/billing data Marketing data Newer data sources Linkage across “data streams”

How many patients take drug A How many patients take drug A? What are the demographics of these patients?

How many patients/demographics? Outpatient (Pharmacies) Traditional National estimates of dispensed prescriptions, projected from retail pharmacies mail order long-term care Patient age/gender- missing or incomplete More recent National estimate of dispensed prescriptions and patients, projected from multiple data streams (pharmacies, pharmacy benefit managers, insurers) Patient age & gender Limitations: -Doesn’t cover all outpatient settings -”Dispensed” is not “Taken”

How many patients/demographics? Outpatient (Other) Physician offices Convenience sample of office visits from 3-4000 physicians National Ambulatory Medical Care Survey (NAMCS) Clinics Little available Some J-codes in claims Rely on sales data into clinics Limitations: -Sample sizes are often small - unstable projections -Generalizability questionable -NAMCS data not timely enough Limitations: -Little patient-level information -Generalizability questionable

How many patients/demographics? Inpatient Traditional None More recent National estimates of discharges in which drug was billed Discharge-level age & gender, diagnosis and procedure data Limitations: -No link to drug indication -Double-counting of patients -“Billed” is not “Administered” -Some areas missing - surgery, radiology -Unclear universe - e.g., pediatrics

How many patients/demographics? Over-the-counter drugs Traditional Use sales data as proxy More recent Household survey data projected nationally Limitations: -Not patient-level Limitations: -Unknown

How long do patients stay on drug A How long do patients stay on drug A? How often do patients take drugs A and B together?

Duration/concomitancy? Outpatient Traditional Longitudinal patient-level insurance claims data More recent Longitudinal data linked across data streams, including pharmacy-based Includes cash payors Limitations: -National estimates not possible -Generalizability questionable -Not all drugs covered -”Dispensed” is not “taken” Limitations: -Unknown

Duration/concomitancy? Inpatient Traditional None More recent Day of stay billing detail for drugs and procedures Limitations: - National estimates not possible -Generalizability questionable -Indication unknown -”Billed” is not “administered”

For what indication is drug A prescribed. By which types of physicians For what indication is drug A prescribed? By which types of physicians? What drugs are being prescribed for condition X?

Indication/specialty? Outpatient Traditional National estimates of prescribing practices from marketing data NAMCS More recent Electronic medical records E-prescribing Limitations: - Sample size small -Generalizability questionable - NAMCS data not timely Limitations: -Generalizability questionable - Research-ready?

Indication/specialty? Inpatient Traditional None More recent Hospital billing data attending/consulting physician specialty all discharge diagnoses Limitations: -No linkages *prescriber drug *drug indication

Summary Our knowledge of drug use in the U.S. is largely setting-specific Drug use data varies in detail across settings Outpatient pharmacy - patient/Rx-level Most detail Outpatient physician office - visit-level Inpatient - discharge-level OTC - pilot work on patient-level data Outpatient clinics - sales only Least detail Intermediate detail

Future Challenges Increased coverage of other care settings Operating room/radiology Hospital outpatient clinics (e.g., chemotherapy) Staff model HMOs Home health care/long term care Over-the-counter drugs (patient-level) Increased coverage of special populations Elderly (Medicare Part D) Pediatrics Pregnant women HIV-infected (specialty pharmacies) Further linkage across care settings Outpatient - inpatient

Acknowledgements Drug Use Specialists Epidemiologists Laura Governale Michael Evans David Moeny Kendra Worthy Epidemiologists Aaron Mendelsohn Sigal Kaplan Andrea Feight Tarek Hammad Contracts Specialists Katrina Garry Martha O’Connor Kathy Rios