Special Article
Outcomes of Reference Pricing for Angiotensin-Converting–Enzyme Inhibitors
N Engl J Med 2002; 346:822-829March 14, 2002
- Abstract
Background
In January 1997, reference pricing for angiotensin-converting–enzyme (ACE) inhibitors for patients 65 years of age or older was introduced in British Columbia, Canada. For medications within a specific class, insurance covers the cost up to the reference price, and patients pay the extra cost of more expensive medications. Although reference pricing may reduce the costs of prescription drugs, there is concern that patients may switch to less effective medications or stop treatment.
Methods
We analyzed data from the Ministry of Health on all 37,362 residents of British Columbia who were 65 or older and were enrolled in the provincial health insurance program, received ACE inhibitors priced higher than the reference price of $27 a month in 1996, and were potentially affected by the new policy. We identified 5353 residents who switched to an ACE inhibitor not subject to cost sharing during the first six months and compared them with 27,938 residents who received only ACE inhibitors subject to cost sharing.
Results
Reference pricing for ACE inhibitors was not associated with changes in the rates of visits to physicians, hospitalizations, admissions to long-term care facilities, or mortality. The probability of stopping antihypertensive therapy decreased as compared with the probability before the change in policy (relative risk, 0.76; 95 percent confidence interval, 0.65 to 0.89). Eighteen percent of patients who had been prescribed ACE inhibitors subject to cost sharing switched to lower-priced alternatives. As compared with patients who did not switch, those who did had a moderate transitory increase in the rates of visits to physicians (rate ratio, 1.11; 95 percent confidence interval, 1.07 to 1.15) and hospital admissions through the emergency room (rate ratio, 1.19; 95 percent confidence interval, 0.99 to 1.42) during the two months after switching, but not subsequently.
Conclusions
We found little evidence that when reference pricing for ACE inhibitors was introduced in British Columbia, patients stopped treatment for hypertension or that health care utilization and costs increased.
Media in This Article
Figure 1
Average Monthly Number of Visits to a Physician per Patient for Cardiovascular Conditions and Acute Respiratory Infection in Patients Who Switched from ACE Inhibitors Subject to Cost Sharing to ACE Inhibitors Not Subject to Cost Sharing as Compared with Patients Who Did Not Switch.Figure 2
Standardized Mortality Ratios for the Study Cohort.Article Activity
- Article
In the United States, $117 billion — that is, 8.9 percent of overall health care expenditures — was spent for prescription drugs in 2000.1 Drug expenditures grew 2.5 to 3 times as fast as total health care expenditures between 1998 and 20001-3 and are about to exceed hospital expenditures for some health plans.4 Recently, reference pricing has been suggested as a cost-control mechanism for proposed Medicare drug benefits.5
Reference pricing is based on the assumption that medications within a specific class are interchangeable and a common level of reimbursement can be established. If a physician prescribes a medication priced higher than the reference price, the patient is required to pay the difference. Typically, the cost of drugs priced at or below the reference price is fully covered by insurance.
The main issues of concern about reference pricing are that patients may switch to less effective medications, become noncompliant, see their physician more frequently, or be hospitalized more frequently.6,7 For example, an uncontrolled study found an increase in thrombotic vascular complications when patients switched from simvastatin to fluvastatin under a system of reference pricing in New Zealand.8 Studies of fixed copayments for prescriptions have reported reductions in overall drug use (e.g., the number of prescriptions filled) of 5 to 10 percent.7,9-13 Nonetheless, there are almost no rigorous evaluations of the effect of reference pricing on health care utilization or costs.14,15 We studied the consequences of reference pricing for angiotensin-converting–enzyme (ACE) inhibitors, a class of antihypertensive medications that are particularly effective in patients with congestive heart failure,16 diabetes,17 or chronic renal disease.18
Methods
Patients
Beginning on January 1, 1997, residents of British Columbia, Canada, 65 years of age or older were fully covered for the least expensive ACE inhibitors — captopril (Capoten), quinapril (Accupril), and ramipril (Altace). Benazepril (Lotensin), cilazapril (Inhibace), enalapril (Vasotec), fosinopril (Monopril), and lisinopril (Prinivil, Zestril) were covered up to a maximum of $27 per month. For these medications subject to cost sharing, patients paid an extra $2 to $62 for a one-month supply. Previously, the costs of all these medications had been covered in full.19
In 1995, reference pricing for nitrates, histamine H2 blockers, and nonsteroidal antiinflammatory medications was instituted in British Columbia. In 1997, reference pricing for calcium-channel blockers was also introduced. We analyzed changes in expenditures and the rates of health care utilization, admissions to long-term care facilities, and mortality after the introduction of reference pricing for ACE inhibitors among elderly patients in British Columbia. The requirement for reference pricing had generous exemptions, including frailty or previous failure of treatment. Thirty-nine percent of those potentially affected obtained individual exemptions as “frail elderly patients.” No other major health policy interventions were initiated during the study period.
All residents of British Columbia who are 65 or older are eligible for publicly funded health care, including pharmaceutical benefits, with prescriptions limited to a 100-day supply. For all prescriptions, the medications, dose, and dispensed quantity are entered into a single computer by retail pharmacists through a province-wide network. Underreporting and misclassification appear to be minimal.20 The Ministry of Health holds data on all drug claims, physicians' claims for services in offices and hospitals, hospitalizations, admissions for long-term care, and deaths for the study cohort. Up to 16 diagnoses for hospital discharges and 1 diagnosis for each medical service were coded in the data base. A previous report indicated high accuracy and completeness of data on health care utilization.21 The human-subjects review boards of Harvard Medical School, the Harvard School of Public Health, Brigham and Women's Hospital, and the University of British Columbia approved the protocol. The Ministry of Health supplied complete data bases linked by a unique, anonymous study number assigned to each patient.
We selected a cohort of all 59,074 patients who were 65 or older in December 1995, who received an ACE inhibitor between December 1995 and March 1996, and who were not in a long-term care institution at the time of their first use of an ACE inhibitor. The population was further restricted to 37,362 patients who were recipients of higher-priced drugs that required cost sharing after the change in policy and who were not using any medications to treat diabetes or asthma, since patients taking such drugs were exempt from the policy.
The subgroup of 5353 “switchers” who received an ACE inhibitor subject to cost sharing during the four months before the change in policy and started an ACE inhibitor not subject to cost sharing during the first six months after the implementation of reference pricing was compared with a subgroup of 27,938 patients who received only ACE inhibitors subject to cost sharing (“nonswitchers”) during both periods. Data collection stopped in June 1998. The remaining 4071 patients were the 1015 who stopped all drug therapy for hypertension and the 3056 who switched from ACE inhibitors to other antihypertensive medications.
Statistical Analysis
To compare trends in health care utilization in switchers and nonswitchers for the period from 10 months before to 10 months after the date of the switch, we used a longitudinal repeated-measures design. Each patient was assigned an index date; the index date for switchers was the day of switching from ACE inhibitors subject to cost sharing to those not subject to cost sharing between November 1, 1996 (the time the policy was announced), and June 30, 1997. The index date for nonswitchers was the first date that an ACE inhibitor subject to cost sharing was dispensed between January 1, 1997, and June 30, 1997.
For each of 10 30-day intervals before and after the index date, event rates were calculated for days on which patients visited a physician, hospital admissions through an emergency room, nonemergency hospital admissions, and admissions to long-term care facilities. We divided the sum of all events by the total number of eligible patients for each period. Admissions to long-term care facilities were treated as one-time events because patients almost never returned to the community. We compared event rates for switchers for each 30-day period with the corresponding rates for nonswitchers using Poisson regression models that included interactions between switching status (switching vs. nonswitching) and indicators for the 30-day initiation period before the index date, the early period (2 30-day periods after the index date), and the late period (3 to 10 30-day periods after the index date).11,22-24 Other covariates included in the models were age in years at the beginning of each 30-day interval, sex, household adjusted income (≤ $11,000 vs. > $11,000 per year), and chronic disease score25 computed from prescription medications used during a specified three-month period and the preceding three months. The chronic disease score ranges from 0 to 35, with an increase in score indicating a decrease in health status.26 Thus, a new chronic disease score was computed for every quarter and treated as a time-varying covariate. Additional covariates included the diagnoses of coronary heart disease, heart failure, or chronic renal failure (a primary diagnosis at hospital discharge or three claims for physician services with International Classification of Diseases 27 codes for the above diagnoses).
To further control for differences between switchers and nonswitchers, we adjusted for quintiles of a score for the propensity to switch medications.28,29 The propensity to switch was calculated as the linear predictor of a logistic regression that modeled switching as a function of characteristics of patients and physicians, prior health care utilization, expenditures, chronic disease scores,25 and statistically significant interactions. The propensity score had slight predictive power (c=0.60; a c score of 0.5 indicates random prediction of future switching, and a c score of 1.0 indicates perfect predictive power30). We combined prognostic covariates and propensity scores in our multivariate models for increased robustness against selection bias.31 We estimated the relative rates of utilization as compared with base-line rates in switchers and nonswitchers with 95 percent confidence intervals.
We corrected for overdispersion by including a scale parameter.32 Within-patient correlation between the repeated events was corrected for with the use of the generalized estimating equations.33 Because of the delay between switching and events, an autoregressive covariance structure with lags of one month was adopted.34 We modeled payments for physicians' services in a linear regression assuming gamma-distributed errors for the right-skewed distribution of payments in Canadian dollars.35
The large number of study patients provided sufficient statistical power to detect a 3 percent change in the overall rate of visits to physicians.36 Any increase in health care utilization among people who switched ACE inhibitors would be diminished by the constant utilization among the majority of patients who did not switch and thus reduced the statistical power.37
We computed standardized mortality ratios to control for strong seasonal variation in mortality by dividing the monthly mortality rates for the study cohort by the monthly mortality rates for all other residents of British Columbia who were 65 years or older during the same time period. The standardized mortality ratios were further adjusted for age and sex and reported with their 95 percent confidence intervals.38
Results
The base-line characteristics of the switchers and nonswitchers are shown in Table 1Table 1
Base-Line Characteristics of the 33,291 Patients Who Received ACE Inhibitors before and after the Implementation of Reference Pricing.. Table 2Table 2
Changes in Health Care Utilization and Compliance after the Introduction of Reference Pricing among the 37,362 Recipients of High-Priced ACE Inhibitors That Required Cost Sharing. shows the overall effect of the policy on the 37,362 people in the cohort. After seasonal variation was accounted for, there were no significant changes in health care utilization. The probability of discontinuing antihypertensive therapy after the implementation of reference pricing was lower than the probability before the change in policy (relative risk, 0.76; 95 percent confidence interval, 0.65 to 0.89). Eighteen percent of patients receiving ACE inhibitors subject to cost sharing switched to lower-priced alternatives. Four percent of patients receiving ACE inhibitors not subject to cost sharing switched to higher-priced drugs during the first six months of the policy. There was no significant difference between switchers and nonswitchers in the proportion of patients who continued therapy with ACE inhibitors six months after the implementation of reference pricing (89.5 percent vs. 89.2 percent, P=0.50).Visits to Physicians
Switchers had an 11 percent increase in visits to physicians (95 percent confidence interval, 7 to 15 percent) as compared with nonswitchers during the two months after switching (Table 3Table 3
Differences in Health Care Utilization and Admission to Long-Term Care Facilities in 5353 Switchers as Compared with 27,938 Nonswitchers.). Both switchers and nonswitchers had additional visits to physicians just before the index date to receive or change prescriptions. There was a 39 percent decrease in the median time between two prescriptions for antihypertensive medications during the first three months after switching — from 82 days to 50 days. The increase in visits to physicians among switchers after the index date was specific to cardiovascular conditions. It was not found for acute respiratory infections, which are common during winter and spring (Figure 1Figure 1Average Monthly Number of Visits to a Physician per Patient for Cardiovascular Conditions and Acute Respiratory Infection in Patients Who Switched from ACE Inhibitors Subject to Cost Sharing to ACE Inhibitors Not Subject to Cost Sharing as Compared with Patients Who Did Not Switch.). Three months after switching, the rates of visits to physicians in switchers and nonswitchers were the same (Table 3).Hospitalizations
Although switchers appeared to have a higher rate of hospital admissions through emergency rooms for the first two months after the change in policy (rate ratio, 1.27; 95 percent confidence interval, 1.07 to 1.51), the association was no longer significant after adjustments were made for hospitalizations in the three months before switching (rate ratio, 1.19; 95 percent confidence interval, 0.99 to 1.42). The rate ratio for the entire period after the change in policy was 1.03 (95 percent confidence interval, 0.92 to 1.14) (Table 3). Analyses of patient subgroups defined by a low income, a high chronic disease score, or diagnoses of coronary heart disease, heart failure, or renal failure did not show any group-specific effects of the policy on any of the outcomes we studied (data not shown).
Admissions to Long-Term Care Facilities and Mortality
Rates of admission to long-term facilities decreased in switchers as compared with nonswitchers (Table 3). The monthly mortality rate, adjusted for seasonal variation, for the cohort of recipients of ACE inhibitors, which was 20 percent higher than that for all other residents in British Columbia who were 65 years or older (mortality ratio standardized for age and sex, 1.20; 95 percent confidence interval, 1.00 to 1.44), did not change after the implementation of reference pricing (P=0.58) (Figure 2Figure 2
Standardized Mortality Ratios for the Study Cohort.).Economic Effects
Switchers had a temporary increase in expenditures for medical services of approximately $11 per patient (95 percent confidence interval, $4 to $17) just before switching and of $13 (95 percent confidence interval, $7 to $20) afterward (Table 3); this reflected the increased number of visits to physicians. Under the conservative assumption that this difference in expenditures between switchers and nonswitchers was due entirely to the change in policy, the total cost of the policy in terms of payments to physicians from October 1996 to March 1998 would have been about $700,000 (95 percent confidence interval, $450,000 to $950,000). This cost was calculated by integrating payments to physicians that were temporarily above an average base-line difference of $10 per month between switchers and nonswitchers. This compares with savings in expenditures for antihypertensive drugs during the first year after the change in policy of about $6.7 million, resulting in a net savings of approximately $6 million (95 percent confidence interval, $5.75 million to $6.25 million).
Discussion
Our study was designed to address the concern that reference pricing of ACE inhibitors may cause discontinuations of antihypertensive therapy and unintended increases in health care utilization and health care costs because of inappropriate substitutions of medications.6,8,39,40 We found little evidence to support this concern. After reference pricing was implemented, there was no increase in the overall rate of visits to physicians, hospitalizations, or drug discontinuations. Despite the high statistical power of our overall analysis, we could have missed an effect on visits to physicians and hospitalizations among the 18 percent of patients who switched from higher-priced to lower-priced medications soon after the policy change.
When we examined the effects of switching ACE inhibitors as a consequence of the change in policy, as compared with expected outcomes if those patients had not switched, we found a transitory increase in visits to physicians and claims for physicians' services for the two months after the switch. This may be explained by the need to see a doctor for a new prescription and increased monitoring by physicians of the new medication.
Because hospitals excluded ACE inhibitors subject to cost sharing from their formularies after the implementation of reference pricing,41 patients admitted to hospitals were more likely to switch medications and because of their prior hospitalization were more likely to be readmitted. The temporary increase in hospitalizations after switching was largely explained by readmissions of patients who were hospitalized before switching and was based on only two months of data.
Determining the effects of switching drugs requires careful attention to the patients affected by the change in policy. Since patients who did not switch were presumed to be either sicker (the basis for an exemption) or to have higher incomes (i.e., to be able to pay the higher copayment for their drug of first choice), simultaneous adjustment was required for factors influencing the choice and outcomes of therapy.42 The data included in the propensity score, particularly before health care utilization, were not strong enough predictors of switching to discriminate between patients who switched and those who did not. Previous studies suggest that if switching is not related to prior health care utilization (a marker for health status), it is most likely related to the preferences of patients or physicians.43 We believe our control for selection bias was adequate because the best predictor of health care utilization is prior health care utilization, which we measured in many ways. The association between the preferences of patients or physicians and switching remains unclear. Preferences are unlikely to cause sudden changes in health care utilization as compared with base-line utilization. Our longitudinal design, comparing changes in trends between the two groups, controlled for unmeasured confounding, because it can be reasonably assumed that differences in outcomes caused by selection factors are the same before and after the index date.
Taking the savings in drug expenditures and the increase in physicians' services into account, we estimated the net savings from the policy to be $6 million Canadian during the first 12 months of reference pricing. This estimate is conservative, because it does not include the savings for patients who initiated ACE-inhibitor therapy after reference pricing began.
We found similar results in vulnerable groups of the elderly, including those patients with low income, chronic diseases, or diagnoses of myocardial infarction or heart failure at base line. However, the diagnostic information in the claims data might be too crude to identify these groups reliably. In general, misclassification of patients according to risk factors at base line attenuates the contrast between subgroups and decreases the power to detect adverse effects.
Our findings apply to the approach to reference pricing in British Columbia during a period of stability of health services in the province. That a relatively small proportion of patients switched ACE inhibitors is due mainly to the fact that the reference price was set at $27 per month and was independent of dose. Therefore, low doses of the drugs that were subject to cost sharing were fully covered, and the policy disproportionally affected patients needing higher doses. Another contribution to the low switching rate was the fact that about two fifths of patients who were potentially affected obtained individual exemptions as “frail elderly patients” through prior approval. Thus, our findings may not be generalizable to similar systems that lack such generous exemptions, such as three-tiered copayment systems in some health maintenance organizations in the United States.
The analysis is restricted to ACE inhibitors, a frequently prescribed and important class of medications for the treatment of hypertension and congestive heart failure. ACE inhibitors have a low within-class variability of effectiveness and thus represent particularly safe candidates for reference pricing. More caution may be necessary for other drug classes, such as calcium-channel blockers, in which there are more pharmacologic differences between the most common agents — verapamil, diltiazem, and the dihydropyridines. Our study focuses on the short-term outcomes of the change in policy. Longer-term data would be desirable but would also be difficult to attribute to one intervention, since many patient-level and system-level factors change over longer periods of observation. We could not directly measure all changes in the health status of patients but only changes that led to contact with health care professionals. Future research should include direct measures of health outcomes and randomized control groups to rule out potential selection biases.
Supported by grants from the U.S. Agency for Healthcare Research and Quality (RO3 HS09855 and RO1 HS10881), the Department of Health and Human Services; the Drug Information Association; Pharmacare, the British Columbia Ministry of Health; the Harvard Pilgrim Health Care Foundation; and the Deutsche Forschungsgemeinschaft (SCHN 527/3 and SCHN 527/4, to Dr. Schneeweiss); the Pharmacoepidemiology Teaching and Research Fund of the Harvard School of Public Health (to Dr. Schneeweiss); and the Takemi Associate Award of the Harvard School of Public Health (to Dr. Schneeweiss). Dr. Soumerai is an investigator in the Health Maintenance Organization Research Network Center for Education and Research in Therapeutics, supported by the Agency for Healthcare Research and Quality.
Dr. Schneeweiss receives funding from Pharmacia and Upjohn. Dr. Walker receives a salary from the United Health Group and funding for research and consultation from many large pharmaceutical firms. Dr. Glynn receives funding from Bristol-Myers Squibb and Pfizer.
Source Information
From the Divisions of Pharmacoepidemiology and Pharmacoeconomics (S.S., R.J.G.) and Preventive Medicine (R.J.G.), Brigham and Women's Hospital and Harvard Medical School, Boston; the Departments of Epidemiology (S.S., A.M.W., M.M.) and Biostatistics (R.J.G.), Harvard School of Public Health, Boston; the British Columbia Ministry of Health, Victoria, Canada (M.M., C.D.); and the Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, Boston (S.B.S.).
Address reprint requests to Dr. Schneeweiss at Brigham and Women's Hospital and Harvard Medical School, Division of Pharmacoepidemiology and Pharmacoeconomics, 221 Longwood Ave., Boston, MA 02115, or at schneeweiss@post.harvard.edu.
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Michael R. Law, Christine Y. Lu, Stephen B. Soumerai, Amy Johnson Graves, Robert F. LeCates, Fang Zhang, Dennis Ross-Degnan, Alyce S. Adams. (2010) Impact of two Medicaid prior-authorization policies on antihypertensive use and costs among Michigan and Indiana residents dually enrolled in Medicaid and Medicare: Results of a longitudinal, population-based study. Clinical Therapeutics 32:4, 729-741
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Atholl Johnston. (2010) Challenges of therapeutic substitution of drugs for economic reasons: focus on CVD prevention. Current Medical Research and Opinion 26:4, 871-878
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Adrianne C. Feldstein, Nancy Perrin, A. Gabriela Rosales, Jennifer Schneider, Mary M. Rix, Kara Keels, Stephanie Schoap, Russell E. Glasgow. (2009) Effect of a Multimodal Reminder Program on Repeat Mammogram Screening. American Journal of Preventive Medicine 37:2, 94-101
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Colin R. Dormuth, Peter Neumann, Malcolm Maclure, Robert J. Glynn, Sebastian Schneeweiss. (2009) Effects of Prescription Coinsurance and Income-Based Deductibles on Net Health Plan Spending for Older Users of Inhaled Medications. Medical Care 47:5, 508-516
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Boris Augurzky, Silja Göhlmann, Stefan Greß, Jürgen Wasem. (2009) Effects of the German reference drug program on ex-factory prices of prescription drugs: a panel data approach. Health Economics 18:4, 421-436
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William H. Shrank, Suzanne M. Cadarette, Emily Cox, Michael A. Fischer, Jyotsna Mehta, Alan M. Brookhart, Jerry Avorn, Niteesh K. Choudhry. (2009) Is There a Relationship Between Patient Beliefs or Communication About Generic Drugs and Medication Utilization?. Medical Care 47:3, 319-325
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Bach, Peter B., . (2009) Limits on Medicare's Ability to Control Rising Spending on Cancer Drugs. New England Journal of Medicine 360:6, 626-633
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Adrianne C. Feldstein, Derek Weycker, Gregory A. Nichols, Gerry Oster, Gabriela Rosales, David L. Boardman, Nancy Perrin. (2009) Effectiveness of bisphosphonate therapy in a community setting. Bone 44:1, 153-159
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Alena Morrison, Neil J. MacKinnon, Nicole R. Hartnell, Karen J. McCaffrey. (2008) Impact of drug plan management policies in Canada: A systematic review. Canadian Pharmacists Journal 141:6, 332-338.e2
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Jackevicius, Cynthia A., Tu, Jack V., Demers, Virginie, Melo, Magda, Cox, Jafna, Rinfret, Stephane, Kalavrouziotis, Dimitri, Johansen, Helen, Behlouli, Hassan, Newman, Alice, Pilote, Louise, . (2008) Cardiovascular Outcomes after a Change in Prescription Policy for Clopidogrel. New England Journal of Medicine 359:17, 1802-1810
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Julie M. Donohue, Michael A. Fischer, Haiden A. Huskamp, Joel S. Weissman. (2008) Potential Savings from an Evidence-Based Consumer-Oriented Public Education Campaign on Prescription Drugs. Health Services Research 43:5p1, 1557-1575
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Markus Müller. (2008) Generika in Österreich 2003–2008: ein Update. Wiener klinische Wochenschrift 120:3-4, 61-62
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Shadi S. Saleh, Steven Szebenyi, Judith A. Carter, Chris Zacher, Dan Belletti. (2008) Patterns and Associated Health Services Costs of Antihypertensive Drug Modifications. The Journal of Clinical Hypertension 10:1, 43-50
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R Padwal, A Kezouh, M Levine, M Etminan. (2007) Long-term persistence with orlistat and sibutramine in a population-based cohort. International Journal of Obesity 31:10, 1567-1570
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Adrianne C. Feldstein, William M. Vollmer, David H. Smith, Amanda Petrik, Jennifer Schneider, Harry Glauber, Michael Herson. (2007) An Outreach Program Improved Osteoporosis Management After a Fracture. Journal of the American Geriatrics Society 55:9, 1464-1469
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William H. Shrank, Margaret Stedman, Susan L. Ettner, Dee DeLapp, June Dirstine, M. Alan Brookhart, Michael A. Fischer, Jerry Avorn, Steven M. Asch. (2007) Patient, Physician, Pharmacy, and Pharmacy Benefit Design Factors Related to Generic Medication Use. Journal of General Internal Medicine 22:9, 1298-1304
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Jack V. Tu. (2007) Would a national pharmaceuticals strategy be bad for the cardiovascular health of Canadians?. Canadian Journal of Cardiology 23:9, 719-720
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Stefan Gre, Dea Niebuhr, Uwe May, J??rgen Wasem. (2007) Reform of Prescription Drug Reimbursement and Pricing in??the??German Social Health Insurance Market. PharmacoEconomics 25:6, 443-454
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Rubin Minhas. (2007) Statin utilisation - recognising the role of the invisible hand. International Journal of Clinical Practice 61:1, 3-6
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William H. Shrank, Steven M. Asch, John Adams, Claude Setodji, Eve A. Kerr, Joan Keesey, Shaista Malik, Elizabeth A. McGlynn. (2006) The Quality of Pharmacologic Care for Adults in the United States. Medical Care 44:10, 936-945
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Paul Grootendorst, David Stewart. (2006) A re-examination of the impact of reference pricing on anti-hypertensive drug plan expenditures in British Columbia. Health Economics 15:7, 735-742
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Colin R. Dormuth, Robert J. Glynn, Peter Neumann, Malcolm Maclure, Alan M. Brookhart, Sebastian Schneeweiss. (2006) Impact of two sequential drug cost-sharing policies on the use of inhaled medications in older patients with chronic obstructive pulmonary disease or asthma. Clinical Therapeutics 28:6, 964-978
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Til Stürmer, Manisha Joshi, Robert J. Glynn, Jerry Avorn, Kenneth J. Rothman, Sebastian Schneeweiss. (2006) A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. Journal of Clinical Epidemiology 59:5, 437.e1-437.e24
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Morten Aaserud, Astrid Austvoll-Dahlgren, Jan Peter Kösters, Andrew D Oxman, Craig Ramsay, Heidrun Sturm, Andrew D Oxman. 2006. Pharmaceutical policies: effects of reference pricing, other pricing, and purchasing policies. .
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Lucie Blais, Catherine Lemière, Dick Menzies, Djamal Berbiche. (2006) Validity of asthma diagnoses recorded in the Medical Services database of Quebec. Pharmacoepidemiology and Drug Safety 15:4, 245-252
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Malcolm Maclure, Anne Nguyen, Greg Carney, Colin Dormuth, Hendrik Roelants, Kendall Ho, Sebastian Schneeweiss. (2006) Measuring Prescribing Improvements in Pragmatic Trials of Educational Tools for General Practitioners. Basic <html_ent glyph="@amp;" ascii="&"/> Clinical Pharmacology <html_ent glyph="@amp;" ascii="&"/> Toxicology 98:3, 243-252
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Douglas W. Roblin, Richard Platt, Michael J. Goodman, John Hsu, Winnie W. Nelson, David H. Smith, Susan E. Andrade, Stephen B. Soumerai. (2005) Effect of Increased Cost-Sharing on Oral Hypoglycemic Use in Five Managed Care Organizations. Medical Care 43:10, 951-959
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Haiden A. Huskamp, Nancy L. Keating. (2005) The new medicare drug benefit: Formularies and their potential effects on access to medications. Journal of General Internal Medicine 20:7, 662-665
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Sebastian Schneeweiss, Jerry Avorn. (2005) A review of uses of health care utilization databases for epidemiologic research on therapeutics. Journal of Clinical Epidemiology 58:4, 323-337
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MALCOLM MACLURE. (2005) Drug Insurance Utilization Management Policies and "Reference Pricing": An Illustrated Commentary on the Article by Vittorio Maio and Colleagues. The Milbank Quarterly 83:1, 131-147
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Steven R. Simon, K. Arnold Chan, Stephen B. Soumerai, Anita K. Wagner, Susan E. Andrade, Adrianne C. Feldstein, Jennifer Elston Lafata, Robert L. Davis, Jerry H. Gurwitz. (2005) Potentially Inappropriate Medication Use by Elderly Persons in U.S. Health Maintenance Organizations, 2000â2001. Journal of the American Geriatrics Society 53:2, 227-232
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Jaume Puig-Junoy. (2005) What is Required to Evaluate the Impact of Pharmaceutical Reference Pricing?. Applied Health Economics and Health Policy 4:2, 87-98
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Gerald W. Smetana, Roger B. Davis, Russell S. Phillips. (2004) Factors That Influence Patient Response to Requests to Change to a Unified Restrictive Formulary. A Prospective Study. Journal of General Internal Medicine 19:12, 1212-1219
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Fischer, Michael A., Schneeweiss, Sebastian, Avorn, Jerry, Solomon, Daniel H., . (2004) Medicaid Prior-Authorization Programs and the Use of Cyclooxygenase-2 Inhibitors. New England Journal of Medicine 351:21, 2187-2194
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Arlene S. Bierman, Chaim M. Bell. (2004) Penny-Wise, Pound-Foolish. Medical Care 42:7, 623-625
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Sebastian Schneeweiss, Colin Dormuth, Paul Grootendorst, Stephen B. Soumerai, Malcolm Maclure. (2004) Net Health Plan Savings From Reference Pricing for Angiotensin-Converting Enzyme Inhibitors in Elderly British Columbia Residents. Medical Care 42:7, 653-660
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Sebastian Schneeweiss, Philip S. Wang, Jerry Avorn, Malcolm Maclure, Raia Levin, Robert J. Glynn. (2004) Consistency of Performance Ranking of Comorbidity Adjustment Scores in Canadian and U.S. Utilization Data. Journal of General Internal Medicine 19:5p1, 444-450
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Shuen-Zen Liu, James C. Romeis. (2003) Assessing the Effect of Taiwan???s Outpatient Prescription Drug Copayment Policy in the Elderly. Medical Care 41:12, 1331-1342
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Michael A. Fischer, Jerry Avorn. (2003) Economic Consequences of Underuse of Generic Drugs: Evidence from Medicaid and Implications for Prescription Drug Benefit Plans. Health Services Research 38:4, 1051-1064
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Carolyn S Dewa, Jeffrey S Hoch. (2003) Fixed and flexible formularies as cost-control mechanisms. Expert Review of Pharmacoeconomics & Outcomes Research 3:3, 303-315
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Thomas S. Rector, Michael D. Finch, Patricia M. Danzon, Mark V. Pauly, Bharati S. Manda. (2003) Effect of Tiered Prescription Copayments on the Use of Preferred Brand Medications. Medical Care 41:3, 398-406
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Suzanne Hill, Nick Freemantle. (2003) A Role for Two-Stage Pharmacoeconomic Appraisal?. PharmacoEconomics 21:11, 761-767
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Margreet S Duetz, Sebastian Schneeweiss, Malcolm Maclure, Thomas Abel, Robert J Glynn, Stephen B Soumerai. (2003) Physician gender and changes in drug prescribing after the implementation of reference pricing in British Columbia. Clinical Therapeutics 25:1, 273-284
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Markus Müller. (2003) Generika — medizinischer Fortschritt zum günstigen Preis. Wiener Klinische Wochenschrift 115:1-2, 1-2
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Silvia M. Ess, Sebastian Schneeweiss, Thomas D. Szucs. (2003) European Healthcare Policies for Controlling Drug Expenditure. PharmacoEconomics 21:2, 89-103
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William E Encinosa. (2002) Pharmacy benefit design options available to employers. Expert Review of Pharmacoeconomics & Outcomes Research 2:4, 389-396
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Sebastian Schneeweiss, Malcolm Maclure, Stephen B Soumerai, Alexander M Walker, Robert J Glynn. (2002) Quasi-experimental longitudinal designs to evaluate drug benefit policy changes with low policy compliance. Journal of Clinical Epidemiology 55:8, 833-841
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Altman, Stuart H., Parks-Thomas, Cindy, . (2002) Controlling Spending for Prescription Drugs. New England Journal of Medicine 346:11, 855-856
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Steinbrook, Robert, . (2002) The Prescription-Drug Problem. New England Journal of Medicine 346:11, 790-790
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Lisa L. Ioannides-Demos, Joseph E. Ibrahim, John J. McNeil. (2002) Reference-Based Pricing Schemes. PharmacoEconomics 20:9, 577-591
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Sebastian Schneeweiss, Malcolm Maclure, Colin Dormuth. (2002) On the Evaluation of Drug Benefits Policy Changes with Longitudinal Claims Data. Disease Management & Health Outcomes 10:12, 763-769
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Jerry Avorn. (2002) Balancing the Cost and Value of Medications. PharmacoEconomics 20:Supplement 3, 67-72
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