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Available Types of National Drug Use Data

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

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  1. 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

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

  3. 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

  4. “$64,000 question” • How many patients in the U.S. take drug A?

  5. 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?

  6. 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”

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

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

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

  10. 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”

  11. 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

  12. 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

  13. 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

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

  15. 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

  16. 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”

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

  18. 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?

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

  20. 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

  21. 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

  22. 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

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