Your browser doesn't support JavaScript. Please upgrade to a modern browser or enable JavaScript in your existing browser.
Skip Navigation U.S. Department of Health and Human Services
Agency for Healthcare Research Quality
Archive print banner

This information is for reference purposes only. It was current when produced and may now be outdated. Archive material is no longer maintained, and some links may not work. Persons with disabilities having difficulty accessing this information should contact us at: Let us know the nature of the problem, the Web address of what you want, and your contact information.

Please go to for current information.

Appropriate Drug Use and Prescription Drug Programs

Tools for Appropriate Use


Thomas Fulda, Program Director, Drug Utilization Review, U.S. Pharmacopeia, Rockville, MD.

Edward Armstrong, Pharm.D., Associate Professor, Department of Pharmacy Practice and Science, University of Arizona, Tucson, AZ.

Sean Sullivan, Ph.D., Professor, Departments of Pharmacy and Health Services, Director, Pharmaceutical Outcomes Research and Policy Program, Department of Pharmacy, University of Washington, Seattle, WA.

David H. Kreling, Ph.D., School of Pharmacy, University of Wisconsin, Madison, WI.

Dr. Armstrong defined Drug Utilization Review (DUR) as a process used to assess the appropriateness of drug therapy against predefined criteria through the evaluation of drug therapy. Its role is primarily to help limit less-than-appropriate use of drugs, adverse consequences for patients, and potentially rising health care costs.

Two types of DUR are retrospective and prospective. Retrospective DUR is typically conducted after the medication is dispensed and should focus on population pattern analysis. Prospective DUR is typically conducted during or before dispensing and can detect drug-specific problems such as drug-drug interactions, dosage problems, or duration issues. The ultimate goal of DUR is to engage educational interventions with the physician and patient to improve prescribing and drug use.

While DUR has many benefits, it is not without some drawbacks. Armstrong pointed out that prospective DUR can incorporate too many alerts that can desensitize pharmacists to their significance. Armstrong highlighted that only the public sector (i.e., Medicaid programs), is still heavily engaged in retrospective DUR. While retrospective DUR can enable population-level pattern analysis and can inform disease management efforts, it has limited effects on outcomes. To improve on DUR programs, Armstrong suggested that States might consider partnerships with researchers to conduct more rigorous and effective evaluations than vendors typically conduct. Armstrong highlighted five studies to illustrate various points about the use of DUR programs.

  1. Pharmacists' Attitudes and Actions to On-Line DUR Messages, a survey of 1,500 community pharmacies using a 5-point Likert-type scale revealed that, of all DUR messages, drug-drug interaction messages received the highest rank of "very useful."
  2. How Pharmacists Respond to On-Line, Real-Time DUR Alerts, a study on claims data from Delaware Medicaid revealed that drug overutilization alerts resulted in the highest frequency of prescriptions not dispensed. This has implications for Medicaid due to a phenomenon that those who fear losing eligibility may work around the system to access more medications than they need or than they are due.
  3. Pharmacists' Assessment of Second Generation On-Line DUR, a Health Care Financing Administration demonstration project with the Iowa Medicaid program and survey of pharmacists for their opinions about online prospective DUR messages (OPDUR), revealed that:
    • 77 percent agree or strongly agree that OPDUR should be a part of the Medicaid system.
    • 81 percent agree or strongly agree that OPDUR is a valuable tool.
    • 65 percent believe that all prescriptions should be screened with a system like OPDUR.
  4. Performance of Drug Interaction Software, a study evaluating nine different software systems to detect well-established drug interactions, revealed that systems failed to detect clinically relevant interactions one-third of the time overall, and system performance was suboptimal.
  5. Hidden Cost to DUR Alerts revealed:
    • Every online prospective DUR alteration that required intervention cost a total of $3 in personnel time.
    • Overridden alerts cost $1.20 per alert and 88 percent of alerts were overridden.

Finally, Armstrong discussed disease management approaches as a form of "expanded DUR." Key components to disease management efforts include treatment guidelines, formulary guidelines, educational interventions (related to how physicians or patients can improve or manage disease states), and modeling therapy interventions.

Disease management programs can:

  • Identify patients with the same disease processes.
  • Use multidisciplinary processes to coordinate care.
  • Develop treatment guidelines.
  • Disseminate information to improve patient care.
  • Improve efficiency of care delivery.
  • Measure appropriate outcomes to assess results of an intervention.

Armstrong noted that it is important for States to think about treatment guidelines and learn from the Pharmaceutical Researchers and Manufacturers Association's (PhRMA) marketing success in altering doctors' prescribing behaviors through guidelines.

Dr. Sullivan gave an overview of the definition and function of both formularies and prior authorization and discussed their respective effects on drug costs. He defined a drug formularies as: "A continually revised compilation of covered pharmaceuticals and ancillary prescribing information (algorithms, guidance, prior authorization, population restrictions) that reflects evidence-based decisions and good clinical judgment about the safe, effective, and cost-effective use of pharmaceuticals."

Some formularies are open (no restrictions on prescribing), and others are closed (including a limited list of covered drugs selected by a pharmacy and therapeutics committee). Prior authorization is a process by which administrators of prescription drug programs can limit the number and prescription size and duration of drugs covered within explicit formulary guidelines by requiring approval for certain drugs. Typically these drugs tend to be costly and subject to inappropriate use.

Sullivan explained that to date there have been relatively few studies revealing that formularies have a direct impact on costs but highlighted certain studies that shed some light on the issue of formulary impact. Some conclusions of these studies are:

  • A well-controlled hospital formulary is associated with lower pharmaceutical spending (Hazlet, 1992).
  • Hospital bed days declined most rapidly for those diagnoses with the greatest increase in the number of drugs prescribed. (PhRMA funding) (Lichtenberg, 1996).
  • Presence of a formulary system lowered drug expenditures but had little impact on overall institutional costs. (National Pharmaceutical Council [NPC] funding) (Moore, 1993).
  • Liberalization of antibiotics in Illinois Medicaid formulary resulted in increased drug costs but lower number of physician visits. (PhRMA funding) (Dranove, 1989).
  • Use of restrictive formularies was associated with increases in visits, hospital stays, and costs of care (NPC funding) (Horn, 1996).

Sullivan emphasized caution when interpreting the results of studies. For example, the Horn study raised many questions among researchers because its findings were counter-intuitive and not documented or supported by any other similar research.

Sullivan highlighted two prior authorization studies and explained that research design is very important in evaluating the costs and benefits of implementing formularies and prior authorization programs. With respect to formulary and prior authorization studies, Sullivan noted that all of the observational studies had little or no control group and that it is difficult to evaluate the "true" impact of a formulary. Also, he noted that there have been no long-term impact studies on how formularies affect outcomes of care and few evaluations of the administrative cost of managing a formulary system.

Sullivan summarized by saying that drug formularies vary in terms of application, co-existing policies, and restrictiveness, and that there is currently little evidence regarding whether they have a positive or negative impact on outcomes or costs. Prior authorization (PA) policies are really exception policies for non-listed drugs, except within Medicaid, where PA is the only legal formulary tool. Some evidence exists that PA benefits outweigh the costs of implementation.

Dr. Kreling based his talk on tools that pharmacy benefit managers (PBMs) employ to affect appropriateness of drug use. PBMs use both qualitative appropriateness tools and quantitative tools. Qualitative tools include:

  • Retrospective DUR.
  • Concurrent or prospective DUR.
  • Formularies.
  • Prior authorization.
  • Disease management.
  • E-prescribing.

Kreling explained that the research on qualitative tools is challenging because:

  • The tools and strategies overlap.
  • The literature is incomplete and inconclusive.
  • All the tools and strategies have their shortcomings.

He further explained that quantitative tools generally focus on potential overutilization issues, and underutilization issues are largely ignored. These tools include strategies such as:

  • Cost-sharing (co-pays and co-insurance).
  • Size limits.
  • Caps on the number of prescriptions.

The research on quantitative tools is also limited due to dated literature, overlap in using them, and a prevalence of unintended effects related to using them.

Kreling highlighted several studies related to quantitative tools, specifically those evaluating co-pays and prescription limits. With regard to co-pays in general, Kreling pointed out that increased co-pay levels sensitize consumers to utilization, generally reducing utilization, and shift costs from the sponsor to the consumer. Differential co-pays for brand and generic drugs increase the acceptance and use of generic drugs and shift costs to consumers. However, a lower difference in co-pay amounts reduced consumers' awareness of real cost differences between brand and generic drugs. Furthermore, three-tired co-pay structures lead to the increased use of formulary or preferred drugs by shifting costs to consumers for "non-preferred drugs." This also can also drive use away from high-cost drugs when they may be the most appropriate. Kreling explained that since setting prescription limits reduces the number of prescriptions paid by the sponsor, it may result in the "spillover effect" of increasing other health care costs.

To conclude, Kreling explained that, in spite of PBM efforts to improve quantitative and qualitative appropriateness in prescribing, drug expenditures are still one of the fastest growing components in health care and that covered individuals use more costly prescriptions and more brand name drugs than do the uninsured. Covered populations have markedly different utilization levels, which may signal moral hazard or adverse selection.

Finally, Kreling explained that all PBM tools have limitations and that the reasons for drug use and increasing drug expenditures are complex. He suggested that PBM approaches or other strategies can be used to empower better informed decision making by patients and providers about need, appropriateness, and cost.


Dranove D. Medicaid drug formulary restrictions. Journal of Law and Economics 1989 Apr;32(1):143-62.

Hazlet TK, Hu TW. Association between formulary strategies and hospital drug expenditures. Am J Hosp Pharm 1992 Sep;49(9):2207-10.

Horn SD, Sharkey PD, Phillips-Harris C. Formulary limitations and the elderly: results from the Managed Care Outcomes Project. Am J Manag Care 1998 Aug;4(8):1105-13.

Kreling DH. Cost Control for Prescription Drug Programs: Pharmacy Benefit Manager (PBM) Efforts, Effects, and Implications. Background report prepared for the U.S. Department of Health and Human Services' Conference on Pharamceutical Pricing Practices, Ulitization, and Cost. August 8-9, 2000. Washington, DC.

Lichtenberg Frank R. Do (more and better) drugs keep people out of hospitals? American Economic Review 1996 May;86(2):384-8.

Moore WJ, Newman RJ. Drug formulary restrictions as a cost-containment policy in Medicaid programs. Journal of Law and Economics 1993 Apr;36(1):71-97.

Strongin RJ. The ABCs of PBMs. National Health Policy Forum. Issue Brief No. 749. October 1999.

Sullivan SD, Lyles A, Luce B, Grigar J. AMCP Guidance for Submission of Clinical and Economic Evaluation Data to Support Formulary Listing in U.S. Health Plans and Pharmacy Benefits Management Organizations. Journal of Managed Care Pharmacy July/Aug 2001;7(4):20-30.

The U.S. Pharmacopeia Drug Utilization Review Advisory Panel. Drug utilization review: mechanisms to improve its effectiveness and broaden its scope. J Am Pharm Assoc 2000;40(4):538-45.

U.S. Pharmacopeia. Guiding Principles Supporting Appropriate Drug Use at the Patient and Population Level. March 12, 2001.

U.S. Pharmacopeia. Principles of a Sound Drug Formulary System. Coalition Working Group. August 2000.

Previous Section Previous Section         Contents         Next Section Next Section


The information on this page is archived and provided for reference purposes only.

AHRQ Advancing Excellence in Health Care