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Causes of and Potential Solutions to the High Cost of Health Care

Designing Pharmacy Benefits to Improve Quality and Contain Costs


On October 10, 2003, Stephen Soumerai, Sc.D., made a presentation in a Web-Assisted Audioconference at Session 3, which was entitled Designing Pharmacy Benefits to Improve Quality and Contain Costs.

This is the text version of Dr. Soumerai's slide presentation. Select to access the PowerPoint® Slides (2.3 MB).


Designing Pharmacy Benefits to Improve Quality and Contain Costs

Stephen Soumerai, Sc.D.
Professor
Department of Ambulatory Care and Prevention
Harvard Medical School and Harvard Pilgrim Health Care
Evolution of Prescription Drug Benefits Designs

Slide 1

Evolution of Prescription Drug Benefits Designs

  • Non-selective "blunt" tools can have unintended consequences, reduce clinical effectiveness, and increase total costs.
    • Caps on number of prescriptions.
    • Non-selective cost sharing.
    • Triplicate prescriptions.

Slide 2

Evolution of Prescription Drug Benefits Designs (cont'd)

  • Initial studies suggest that selective "sharp" tools that recognize relative effectiveness of drugs within a class can reduce inappropriate use and promote least-costly alternatives.
    • Reference pricing.
    • Tiered copayments.
    • Evidence-based preferred drug lists and formularies.

Slide 3

Unintended effects of non-selective cost-sharing policies

  • Reduces use of clinically important medicines (e.g., insulin, cardiac meds).
  • Increases use of institutional services.
    • Nursing homes and hospitals (elderly).
    • Day hospital and acute care (patients with schizophrenia.).
  • May increase total health care costs.
    • Mental health cost offsets 17 x drug savings.

Slide 4

Time Series of Constant-Size Rxs per Continuously Eligible Patient per Month among Multiple Drug Recipients (N=860) and Other Outpatients (N=8002)

Line graph showing a precipitous drop in mean number of prescriptions per patient at the onset of a three drug cap, and a steady rise in the mean number of prescriptions filled when the cap was replaced by a one-dollar copay. All other patients remain steady at about 0.80 mean prescriptions. The information is from 1980 to 1984.

Source: Soumerai, et al. New England Journal of Medicine 1987;317:550-6.

Slide 5

Cap-induced Changes in Essential Drugs: "Droppers" vs. "Maintainers"

Line graph plotting standard doses per eligible person from July 1980 to the end of 1982. Those whose does were reduced maintained a relatively steady number of doses as a 3 drug cap, and later a 1 dollar copay were implemented. Those whose does were maintained had a large drop upon implementation of a 3 drug cap, and a steady rise following the 1 dollar copay.

Source: Soumerai, et al. New England Journal of Medicine 1994;331:650-5.

Slide 6

Effects of Prescription Cap on Nursing Home Admissions

A line graph depicting the steady decline of percent of patients outside of nursing homes with the implementation of a prescription drug cap. Graph flows from 100 percent to roughly 87 percent, and shows information from the states of New Jersey and New Hampshire.

Source: Soumerai, et al. New England Journal of Medicine 1991;325:1072-7.

Slide 7

Effect of Cap on Emergency Mental Health Services

Line graph showing two groups labeled CMHC 1 and CMHC 2. The graph shows the effects on number of services per patient over a 42 month period as caps are introduced and then removed. CMHC 1 shows a slight increase to 0.15 at the beginning of caps, and a decrease back to 0 when caps were removed. CMHC 2 shows a relatively large increase in services per patient to 0.4, followed by a gradual reduction in the use of those services at the removal of caps, but not returning to 0.

Source: Soumerai, et al. New England Journal of Medicine 1994;331:650-5.

Slide 8

Changes in Use of Essential Drugs With Change in Cost Sharing

Two line graphs, one of an elderly population, one of an adult welfare populations, showing a predicted and an actual line of number of drugs per day from November 1993- November 1997. The number steadily increases in both populations, though the baseline value is lower for the adult welfare population. Upon the implementation of the cost sharing policy, the number of drugs drops away from the predicted values in both populations, showing a slight widening of that gap over time.

Source: Tamblyn R, et al. JAMA 2001;285:421-9.

Slide 9

Effect of a $0.50 per Rx Copayment on Medication Use by Medicaid Recipients in South Carolina

Graph showing mean prescriptions per patient in Tennessee and South Carolina from January 1976 until mid-1979. While Tennessee's mean number of prescriptions steadily increases from about 2.5 to about 3.1, South Carolina's remains steady with periodic decreases from a baseline of about 2 upon the implementation of a 50 cent per drug copay.

Source: Nelson, Reeder, Dickson. Medical Care 1984 Aug;724.

Slide 10

Impact of Triplicate Prescription Program (TPP) on Benzodiazepine (BZ) Prescribing

Line graph comparing New Jersey to New York's rates of BZ recipients per 100 continuous enrollees from January 1988 to Mid-1990. Populations are steady at around 7 to 8 until a Triplicate Policy is implemented in New York where BZ recipients drop 54.8 percent to about 3.5 per 100 in a period of about a month.

Source: Ross-Degnan, et al. (submitted).

Slide 11

Impact of TPP on Use of BZ Indicated for Seizure and Panic Disorder

Graph comparing percent of enrollees using Clonazepam in New York and New Jersey from January, 1988 until January, 1991. With the Triplicate policy in New York, New Jersey rises steadily from a little less than 0.2 percent to a little more than 0.4 percent while New York remains fairly steady below 0.2 percent.

Source: Ross-Degnan, et al. (submitted).

Slide 12

Reduction in BZ Use Among Patients with Seizure Disorder

Graph showing the percent of patients with Benzodiazopene use in the New Jersey control cohort, and the New York study cohort from 1988 to 1991. With the Triplicate Prescription Policy, the percentage in New York drops from about 12 percent to about 4 percent in just 2 months, while the New Jersey control group remains steady at about 12 percent.

Source: Simoni-Wastila, et al. (submitted).

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Current as of July 2003


Internet Citation:

Designing Pharmacy Benefits to Improve Quality and Contain Costs. Slide Presentation by Stephen Soumerai, at Web-Assisted Audioconference, "Causes of and Potential Solutions to the High Cost of Health Care." Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/news/ulp/hicosttele/sess3/soumeraitxt.htm


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