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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.
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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
“$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?What are the demographics of these patients?
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 How many patients/demographics?Outpatient (Pharmacies) • Limitations: • -Doesn’t cover all outpatient settings • -”Dispensed” is not “Taken”
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 How many patients/demographics?Outpatient (Other) • Limitations: • -Sample sizes are often small - unstable projections • -Generalizability questionable • -NAMCS data not timely enough • Limitations: • -Little patient-level information • -Generalizability questionable
Traditional None More recent National estimates of discharges in which drug was billed Discharge-level age & gender, diagnosis and procedure data How many patients/demographics?Inpatient • Limitations: • -No link to drug indication • -Double-counting of patients • -“Billed” is not “Administered” • -Some areas missing - surgery, radiology • -Unclear universe - e.g., pediatrics
Traditional Use sales data as proxy More recent Household survey data projected nationally How many patients/demographics?Over-the-counter drugs • Limitations: • -Not patient-level • Limitations: • -Unknown
How long do patients stay on drug A?How often do patients take drugs A and B together?
Traditional Longitudinal patient-level insurance claims data More recent Longitudinal data linked across data streams, including pharmacy-based Includes cash payors Duration/concomitancy?Outpatient • Limitations: • -National estimates not possible • -Generalizability questionable • -Not all drugs covered • -”Dispensed” is not “taken” • Limitations: • -Unknown
Traditional None More recent Day of stay billing detail for drugs and procedures Duration/concomitancy?Inpatient • 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?What drugs are being prescribed for condition X?
Traditional National estimates of prescribing practices from marketing data NAMCS More recent Electronic medical records E-prescribing Indication/specialty?Outpatient • Limitations: • - Sample size small • -Generalizability questionable • - NAMCS data not timely • Limitations: • -Generalizability questionable • - Research-ready?
Traditional None More recent Hospital billing data attending/consulting physician specialty all discharge diagnoses Indication/specialty?Inpatient • 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
Drug Use Specialists 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 Acknowledgements