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Objective: As a result of the over-the-counter (OTC) introduction of loratadine, health plans have been strug- gling to determine the best policy to incorporate this change within their existing drug benefit structure for sec- ond-generation antihistamines (SGA). The objective of this study was to examine the economic impact of payer policies in response to the Rx-to-OTC switch of loratadine. Study Design: Decision analysis was used to model the budgetary impact and cost-effectiveness of four policies for SGA benefits for the managed care organization (MCO), employer, and Medicaid perspectives separately. Patients and Methods: Outcomes included direct medi- cal costs and lost productivity (employers only), dis- counted, quality-adjusted life-years (QALYs) saved because of amelioration of allergic rhinitis symptoms and avoidance of unintentional injuries associated with the use of first-generation antihistamines (FGA). Bayesian probabilistic sensitivity analysis was conducted using sec- ond-order Monte Carlo simulation. Results: Providing limited OTC and second-tier prescrip- tion benefits would cost approximately $0.13 and $0.30 compared to third-tier prescription benefits for employers and MCOs, respectively, and would save Medicaid $.02 per member per month (PMPM). Providing limited cov- erage for OTC loratadine while retaining second-tier pre- scription benefits for SGA was the optimal policy for a willingness to pay below $26,200 per QALY for all payers. Conclusions: Offering second-tier prescription and lim- ited OTC benefits provides greater effectiveness and is not significantly more expensive PMPM than discontinua- tion. Some of the drug savings from limiting coverage of prescription SGA may be attenuated by the cost of lost productivity and direct medical expenditures due to unin- tentional injuries associated with increased FGA use in addition to the increased cost of therapeutic substitutes.

ObjectivesTo determine adherence rates, transition probabilities, and factors associated with transition from higher to lower adherence in antihypertensive (AH) and lipid-lowering (LL) medications.MethodsCalifornia Medicaid data (1995–2003) were used to identify hypertensive patients with prescriptions for both AH and LL medications. Proportion of days covered (PDC) was used to define three adherence classifications: fully adherent (FA, PDC ≥ 0.8), partially adherent (PA, 0.2 ≤ PDC < 0.8), and nonadherent (NA, PDC < 0.2). Annual transition matrices documented the probability of adherence status changes.ResultsOnly 13% of the 5943 patients were FA to both drugs at baseline. Patients who were FA (60%) or NA (84%) to both drugs had high probability of maintaining status at year two (Y2). Significant variables associated with a transition from adherent to NA at Y2 included African American race (odds ratio [OR] 1.5), other race groups (OR 1.2), lack of Medicare eligibility (OR 1.3), and initiating LL therapy of fibric acid derivatives (OR 1.3) or niacin (OR 1.8).ConclusionsPatients FA or NA with both drugs at baseline were more likely to maintain their adherence status. Race, insurance coverage, and type of LL medication were significantly associated with transitioning from any adherence status to nonadherence. These findings may be useful in guiding cost-effectiveness analyses incorporating adherence estimates.

Objective To evaluate the impact of value-based benefit design (VBBD) on adherence to diabetes medications. Methods Health Alliance Medical Plans piloted VBBD for diabetes medications for a subgroup of 5400 enrollees in January 2007 while keeping drug benefits unchanged for the remaining plan enrollees. A difference in difference method (DID) was used to evaluate the effect of VBBD based on pharmacy claim data. Patients with unchanged benefits in the same plan were used as the control group. Adherence was measured by the proportion of days covered. Propensity score weighting was used to balance characteristics of the case group and the control group. Results There were 71 patients in the case group and 5037 patients in the control group. The patients in the two groups had comparable characteristics after propensity score weighting. After the implementation of VBBD, the average copayment per 30 days of supply for diabetes medications decreased from $15.3 to $10.1 for the case group and increased from $14.6 to $15.1 for the control group. The probability of being adherent increased from 75.3% to 82.6% for the case group and was roughly unchanged from 79.1% to 78.5% for the control group. Propensity score-weighted DID analysis showed that patients with copayment reduction had greater odds of being adherent: odds ratio=1.56, P = 0.03, 95% confidence interval 1.04–2.34. Conclusion A VBBD program that reduced the copayment for diabetes medications by 36.1% reduced the number of nonadherent patients by 30.0%.

OBJECTIVES: Measurement errors in independent variables may lead to attenuated estimates of their effects and may contaminate estimates for other covariates in conventional linear regression models (LRM). However, the direction and magnitude of these biases are difficult to determine theoretically. Measurement error is a serious problem in health services research as health status is a latent variable that can only be measured with error using proxy variables. This study empirically evaluated the validity of LRM models in health outcomes research. METHODS: SEMs with a latent health construct are proposed and compared with LRM models to examine the bias of measurement errors in general health status using data from a study of the impact of pharmacist's consultation on both health outcomes and costs (KP/USC study). Perceived health status at a given time point was modeled as a latent variable measured by the multiple scales of the SF-36. RESULTS: The latent health construct with multiple scales of the SF-36 and its SEMs for health outcomes and costs are empirically supported by the KP/USC data. SEM estimations of the latent health construct in both the measurement model and the structural model were all statistically significant with expected signs. As predicted, LRM estimates for the SF-36 scales were attenuated. However, there is no strong evidence that LRM estimations of treatment effect were contaminated by the measurement errors in the SF-36 or that the simultaneity between health outcomes and costs. CONCLUSIONS: Measurement errors in health status variables may result in attenuated estimates of health status effects on patient outcomes. Fortunately, careful study design can eliminate the contamination of treatment effect estimates due to errors in measuring health status. Moreover, SEM methods can be used to control both attenuation and resonation biases.

Those concerned with the effects of occupational regulation have long argued the need for greater protection of consumer interests. One area of concern is the domination of occupational licensing boards by practitioners of the licensed profession. The professions were very successful in negotiating licensing statutes so that most, if not all, of the positions on licensing boards were allocated to members of the profession [10]. This practice could encourage capture of the regulatory process by the regulated profession. During the 1960s and '70s, various state legislatures responded to this concern by requiring consumer representation on occupational licensing boards.' Although this reform was widely adopted, its effects are largely unknown. Existing research assessing the effects of public board membership is sparse, limited to single states or professions. Schutz [36] identified no significant effects from increased public membership on California licensing boards on several board output measures. This study, however, only encompassed the two years before and the two years after the increase in public membership. Given the difficulty in finding, appointing, and then training and orienting new public members, it is not surprising that no effects were found. In fact, if past patterns regarding appointments prevailed, it is likely that many of the public member seats remained vacant during the entire study period [38]. Moreover, even if the public members were seated and oriented quickly, it is likely that they would take some time to become acquainted with board roles and responsibilities before seeking significant reforms in the licensing process. Schneider [35], however, found similar results in her study of the 1983 performance of Missouri licensing boards. She found no effects from public membership on four measures of board performance. Lammers [24] found that public members on boards regulating nursing home administrators affected only one regulatory policy: the extensiveness of the agency's continuing *We appreciate the cooperation and effort of many licensing board directors and staff members. We especially want to thank Ellen Hume of the National Clearinghouse on Licensure, Enforcement and Regulation for her assistance. Partial support for this research was provided by the University of Southern California Faculty Research and Innovation Fund. 1. The legislative empowerment act determines the composition of the boards. The governor of each state is usually responsible for appointing members of occupational licensing boards, although some states may require the governor

PURPOSE: The objective of this study was to assess utilization patterns of different antidepressants in patients served by a medical group using pharmacy claims data from two third-party insurers. METHODS: Patients must have been 18 to 65 years of age, receiving a new prescription of anti-depressant between the period of 1994–1996. Definition of adequate dose and duration of anti-depressant therapy were based on 1993 AHCPR guidelines. Switching of therapy was defined when the patient discontinued the original antidepressant after addition of a second antidepressant, whereas augmentation was defined when the patient continued to purchase the original antidepressant at least once after addition of the second antidepressant. A dosage was considered titrated if the average daily dose for any of the first three prescriptions was different from any of the other two. All the analyses were performed based on the initial therapy. RESULTS: The patient sample included 177 (18.8%) patients who received fluoxetine as initial therapy, 98 (10.4%) sertraline, 175 (18.6%) paroxetine, 373 (39.6%) tricyclic antidepressants (TCAs), and 119 (12.3%) other antidepressants. The treatment completion rate was: fluoxetine 18.6%, sertraline 14.3%, paroxetine 6.9%, TCAs 3%, and other antidepressants 7.6%. All of the pairwise comparisons vs. fluoxetine were statistically significant, except for the one with sertraline. The switch rate ranged from 5.6% for, TCAs to 13.7% for paroxetine. No difference in augmentation rate was found among SSRIs (fluoxetine, 6.8%; sertraline, 4.1%; paroxetine, 5.7%), while the augmentation rate for fluoxetine was statistically significantly higher than TCAs (6.8% vs. 1.9%). The titration rate was 20.3% for fluoxetine, 28.1% for sertraline, 21.9% for paroxetine, 40.2% for TCAs, and 33.3% for other antidepressants (significant difference between TCAs and fluoxetine). CONCLUSION: Our data have demonstrated that there were significant differences in utilization patterns among antidepressants. Much more attention must be paid to ensuring that newly treated patients achieve treatment completion.

costs. In this model, prescription non-procurement was more likely to be reported in the Medicare-only population (OR: 1.47; 95% CI 1.46–1.48) and in the Medicare plus Medicaid population (OR: 1.11; 95% CI 1.10–1.12) as compared to respondents with Medicare plus private insurance coverage. CONCLUSIONS: Significantly different rates of persons who forego filling a prescription for cost reasons were observed among Medicare beneficiaries. More vulnerable groups of seniors were identified. Dual eligible Medicare/Medicaid enrollees and those with Medicare alone are more likely to restrict medication procurement due to cost.

OBJECTIVES: The purpose of this study is to adapt a previously validated questionnaire to a pharmacy claims database and examine its construct validity in measuring severity of illness in chronic respiratory disease (CRD). METHODS: The authors modified an asthma severity of illness questionnaire (13 items, total score range 0–28) based upon symptoms, medication use, hospitalization information and intubation history to a scale that is more conducive to retrospective data analysis. The adapted CRD scale (CRDS) was based on pharmacy claims data and hospitalization history (11 items, total score range 0–18). The CRDS was compared to utility as measured by a general health visual analogue scale and quality of life (QoL) as measured by the Physical Component Scale (PCS), Physical Function (PF) and General Health (GH) domains of the SF-36. Panel data analysis was performed on pharmacy claims and survey data from the Kaiser Permanente/USC Consultation Study. QoL and utility were regressed on the CRDS, along with covariates. A non-respiratory chronic disease score was used to control for chronic disease while avoiding significant multicollinearity. The analysis was limited to 126 patients with CRD followed over 3 years. The Hausman specification test was used to determine the appropriateness of the random-effects model formulation. RESULTS: The Hausman specification test suggested the use of the fixed-effects formulation for utility (m = 8.2, p> m = 0.0420). The CRDS was negative and significant (−1.79, p m = 0.0333) and random-effects for GH (p> m = 0.0628) and PF (p> m = 0.1495). The CRDS was significant and negative for all three QoL domains: (PCS: −0.68, p < 0.0085; PF: −0.97, p

Quality adjusted life years (QALYs) are well recognized as a valid measure for outcomes in cost-effectiveness analyses. However, it is difficult to obtain a summary utility score from health status measure such as the SF-36. OBJECTIVE: To predict a summary utility score (represented by HUI) from the scores on the SF-36. METHODS: A structural equation framework was applied to data collected from 1992 to 1995 on the Southern California Kaiser Permanente population (n = 5,794). An instrumental variable (IV) method mitigated the endogeneity in estimating the HUI(MarkII). Socioeconomic and disease variables were used as covariates. A split-sample analysis provided cross-validation. RESULT: This model predicted 33.68% of the observed variance in HUI index scores with an adjusted R2of 0.3335. Observed HUI index scores were distributed with a mean of 0.7963 and std. deviation of 0.1796. Parameter estimates of most of the SF-36 components (except General Health & Social Functioning) showed statistical significance at α= 0.05 level. People with high chronic disease scores were found to have low SF-36 scores, and parameter estimates of this covariate were also found statistically significant at α= 0.05 level in all structural equations. However, all the socioeconomic variables showed statistical insignificance. Comparison of “Forecasting” and “Estimation” sub-samples showed satisfactory results during cross-validation. CONCLUSION: Result of this study provides a quantitative link between two important measures of health status. The present model can be used to estimate overall health utility summary scores from previous studies using the SF-36.