Effects of a prior-authorization policy for celecoxib on medical service and prescription drug use in a managed care Medicaid population.
ABSTRACT Prior authorization (PA) is a poorly studied but commonly employed policy used by health care payers to manage the rising costs of pharmacy benefits.
The aim of this study was to evaluate the intended and unintended effects of a PA policy for celecoxib on pharmacy and medical-service utilization in a Medicaid managed-care organization.
This was a retrospective, interrupted time-series analysis of 22 monthly health-related utilization rates from January 1, 1999, to October 31, 2000. All Medicaid claims for CareOregon (a managed-care organization) and a fee-for-service program were reviewed. A model was constructed to evaluate changes in utilization of therapeutically related drug classes (eg, conventional nonsteroidal anti-inflammatory drugs [NSAIDs], gastrointestinal agents), office and emergency-department encounters, and hospitalizations before and after the PA policy was implemented on November 16, 1999. A secondary analysis evaluated these changes among a sample of prior NSAID users.
After the PA policy was implemented, use of celecoxib was immediately reduced from 1.07 to 0.53 days' supply per person-year (58.9%; 95% CI, 50.0%-67.9%). The monthly rate of increase was also reduced (P < 0.001). Utilization changes were not observed in other drug classes. Similar changes were observed in the secondary analysis. An 18% (95% CI, 2.2%-33.9%) nonsignificant increase in emergency-department visits was observed in the entire sample after the PA policy was implemented. However, a similar change was not observed in the secondary analysis of prior NSAID users. No other changes in medical service encounters were noted after the PA policy was activated.
This observational study found that celecoxib use was substantially reduced after the implementation of a PA policy. No important changes in use of other drug classes were detected. The overall increase in emergency-department visits--although not observed among previous NSAID users--should be explored on the individual level.
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ABSTRACT: This study examines the evolutionary impact of valsartan initiation on medical costs. A retrospective time series study design was used with a large, US national commercial claims database for the period of 2004-2008. Hypertensive patients who initiated valsartan between the ages of 18 and 63, and had continuous enrollment for 24-month pre-initiation period and 24-month post-initiation period were selected. Patients' monthly medical costs were calculated based on individual claims. A novel time series model was devised with monthly medical costs as its dependent variables, autoregressive integrated moving average (ARIMA) as its stochastic components, and four indicative variables as its decomposed interventional components. The number of post-initiation months before a cost-offset point was also assessed. Patients (n = 18,269) had mean age of 53 at the initiation date, and 53% of them were female. The most common co-morbid conditions were dyslipidemia (52%), diabetes (24%), and hypertensive complications (17%). The time series model suggests that medical costs were increasing by approximately $10 per month (p < 0.01) before the initiation, and decreasing by approximately $6 per month (p < 0.01) after the initiation. After the 4th post-initiation month, medical costs for patients with the initiation were statistically significantly lower (p < 0.01) than forecasted medical costs for the same patients without the initiation. The study has its limitations in data representativeness, ability to collect unrecorded clinical conditions, treatments, and costs, as well as its generalizability to patients with different characteristics. Commercially insured hypertensive patients experienced monthly medical cost increase before valsartan initiation. Based on our model, the evolutionary impact of the initiation on medical costs included a temporary cost surge, a gradual, consistent, and statistically significant cost decrease, and a cost-offset point around the 4th post-initiation month.Journal of Medical Economics 01/2012; 15(1):8-18.
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ABSTRACT: Objective: To evaluate the effectiveness of an automated prior authorization (PA) system (SmartPA) in reducing use of and expen- ditures for cyclooxygenase-2 (COX-2) inhibitors. Study Design: Before and after with control group. Methods: After implementation of SmartPA in Missouri, changes in use of and expenditures for COX-2 inhibitors, COX-2 substitutes (traditional nonsteroidal anti-inflammatory drugs (NSAIDs) and other products for pain), and gastrointestinal (GI) protective agents were compared between the Medicaid program of Missouri and that of a state with no PA program for COX-2 inhibitors. Subjects were continuously enrolled for the 24-month study period and had a claim for a COX-2 inhibitor in the 12- month baseline period. Analyses included comparison of means and linear regression. Regressions controlled for age, sex, risk for GI complications, severity of illness, and the interaction between state and risk. Results: Changes in expenditures for COX-2 inhibitors, NSAIDs, other pain drugs, and GI-protective drugs were $256 higher, $56 lower, $21 higher, and $198 higher, respectively, in the control state among low-risk patients. Changes in expenditures were $102 higher, $12 lower, $21 lower, and $185 higher, respectively, in the control state among high-risk patients. Results were similar for drug utilization. Conclusion: Implementation of SmartPA resulted in reduced use of and expenditures for COX-2 inhibitors and reduced net expen- ditures for all pain and GI-protective medications. These effects were greatest for patients at low risk for GI complications. (Am J Manag Care. 2006;12:501-508)Value in Health 01/2005; 8(3):405-405. · 2.19 Impact Factor
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ABSTRACT: Taiwan's National Health Insurance's (NHI) generous coverage and patients' freedom to access different tiers of medical facilities have resulted in accelerating outpatient care utilization and costs. To deter nonessential visits and encourage initial contact in primary care (physician clinics), a differential co-payment was introduced on 15th July 2005. Under this, patients pay more for outpatient consultations at "higher tiers" of medical facilities (local community hospitals, regional hospitals, medical centers), particularly if accessed without referral. This study explored the impact of this policy on outpatient medical activities and expenditures, different co-payment groups, and tiers of medical facilities. A segmented time-series analysis on regional weekly outpatient medical claims (January 2004 to July 2006) was conducted. Outcome variables (number of visits, number of outpatients, total cost of outpatient care) and variables for cost structure were stratified by tiers of medical facilities and co-payment groups. Analysis used the auto-regressive integrated moving-average model in STATA 9.0. The overall number of outpatient visits significantly decreased after policy implementation due to a reduction in the number of patients using outpatient facilities, but total costs of care remained unchanged. The policy had its greatest impact on the number of visits to regional and local community hospitals but had no influence on those to the medical centers. Medical utilization in physician clinics decreased due to an audit of reimbursement declarations. Overall, the policy failed to encourage referrals from primary care to higher tiers because there was no obvious shifting of medical utilization and costs reversely. Differential co-payment policy decreased total medication utilization but not costs to NHI. The results suggest that the increased level of co-payment charge and the strategy of a single cost-sharing policy are not sufficient to promote referrals within the system. To achieve an effective co-payment policy, further research is needed to explore how patients' out-of-pocket payment affects medical utilization and which forces (not susceptible to co-payment) act in tertiary facilities.Research in Social and Administrative Pharmacy 10/2009; 5(3):211-24. · 2.35 Impact Factor