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Onur Baser

Publications and source records attributed to Onur Baser.

6 recordsLinked to original sources

Guidelines for selecting among different types of bootstraps.

BACKGROUND: The bootstrap has become very popular in health economics. Its success lies in the ease of estimating sampling distribution, standard error and confidence intervals with few or no assumptions about the distribution of the underlying population. OBJECTIVE: The purpose of this paper is three-fold: (1) to provide an overview of four common bootstrap techniques for readers who have little or no statistical background; (2) to suggest a guideline for selecting the most applicable bootstrap technique for your data; and (3) to connect guidelines with a real world example, to illustrate how different bootstraps behave in one model, or in different models. RESULTS: The assumptions of homoscedasticity and normality are key to selecting the best bootstrapping technique. These assumptions should be tested before applying any bootstrapping technique. If homoscedasticity and normality hold, then parametric bootstrapping is consistent and efficient. Paired and wild bootstrapping are consistent under heteroscedasticity and non-normality assumptions. CONCLUSION: Selecting the correct type of bootstrapping is crucial for arriving at efficient estimators. Our example illustrates that if we selected an inconsistent bootstrapping technique, results could be misleading. An insignificant effect of controller treatment on total health expenditures among asthma patients would have been found significant and negative by an improperly chosen bootstrapping technique, regardless of the type of model chosen.

Confidence Intervals↗

Impact of statin copayments on adherence and medical care utilization and expenditures.

OBJECTIVE: To examine the effects of statin cost-sharing (ie, copayments, coinsurance) on adherence to statin medications and the impact of adherence on healthcare utilization and spending. STUDY DESIGN: Retrospective, observational study of statin users receiving health benefits or supplemental coverage from employer-sponsored health plans. METHODS: Medical and pharmacy claims were selected from the Medstat MarketScan database for patients who were continuously enrolled from 2000 through 2003. Two-stage residual inclusion models were estimated. The first stage modeled adherence to statins, which was derived from the medication possession ratio, and represented the percentage of days on therapy in an 18-month time frame, July 2001 through December 2002. In the second stage, generalized linear models were used to estimate 2003 utilization and expenditures. Separate estimates were produced for new statin users (n = 24 113) and continuing statin users (n = 93 253). RESULTS: Lower statin copayments were associated with higher levels of statin adherence. In percentage terms, when holding all other variables at their mean value, a $10 increase in copayment resulted in a 1.8 percentage point reduction in the probability of adherence for new users and a 3 percentage point reduction in the probability of adherence for continuing users. For continuing users adherent to statins, total costs did not change, but fewer negative events (emergency department visits, hospitalizations, and coronary heart disease-related hospitalizations) occurred. CONCLUSIONS: Policy makers and plan managers should consider interventions that improve adherence to statins, such as lower copayments.

Aged↗

Risperidone treatment in elderly patients with dementia: relative risk of cerebrovascular events versus other antipsychotics.

BACKGROUND: The possibility that low-dose antipsychotic treatment is associated with increased risk of cerebrovascular events (CVEs) in elderly patients with dementia has been raised. The objective was to determine whether risperidone is associated with an increased risk of CVEs relative to other commonly considered alternative treatments. METHODS: An analysis of Medicaid data from 1999 to 2002, representing approximately 8 million enrollees from multiple states, was conducted. The primary outcome was the incidence of acute inpatient admission for a CVE within 3 months following initiation of treatment with atypical antipsychotics (risperidone, olanzapine, quetiapine, or ziprasidone), haloperidol, or benzo-diazepines. RESULTS: Descriptive analyses found similar rates of incident CVEs across evaluated agents. Multivariate analyses found no differences in comparisons of risperidone with olanzapine or quetiapine. Risperidone and other antipsychotics as a group were also not associated with a higher odds ratio (OR) of incident CVE than either haloperidol or benzodiazepines. With risperidone as the reference group: olanzapine, OR = 1.05, 95% CI 0.63-1.73; quetiapine, OR = 0.66, 95% CI 0.23-1.87; haloperidol, OR = 1.91, 95% CI 1.02-3.60; benzodiazepines, OR = 1.97, 95% CI 1.30-2.98. With benzodiazepines as the reference group, the OR of incident CVE for all antipsychotics as a class was 0.49, 95%CI 0.35-0.69. CONCLUSIONS: This study found no significant difference in the incidence of CVEs between patients taking risperidone and those taking other atypical antipsychotics. Risperidone and all atypical antipsychotics were not associated with higher risk than two common treatment alternatives (haloperidol and benzodiazepines). These findings do not support the conclusion that risperidone is associated with a higher risk of CVE than other available treatment alternatives. The data also suggest that patient characteristics other than antipsychotic use are more significant predictors of CVEs. Given the relatively low rates of incident CVEs, a larger sample of patients with groups closely balanced on a wide spectrum of potential risk factors could provide a more precise assessment of risk.

Aged↗

Benefit plan design and prescription drug utilization among asthmatics: do patient copayments matter?

The ratio of controller-to-reliever medication use has been proposed as a measure of treatment quality for asthma patients. In this study we examine the effects of plan-level mean out-of-pocket asthma medication patient copayments and other features of benefit plan design on the use of controller medications alone, controller and reliever medications (combination therapy), and reliever medications alone. The 1995--2000 MarketScan claims data were used to construct plan-level out-of-pocket copayment and physician/practice prescriber preference variables for asthma medications. Separate multinomial logit models were estimated for patients in fee-for-service (FFS) and non-FFS plans relating benefit plan design features, physician/practice prescribing preferences, patient demographics, patient comorbidities, and county-level income variables to patient-level asthma treatment patterns. We find that the controller-to-reliever ratio rose steadily over 1995--2000, along with out-of-pocket payments for asthma medications, which rose more for controllers than for relievers. After controlling for other variables, however, plan-level mean out-of-pocket copayments were not found to have a statistically significant influence on patient-level asthma treatment patterns. On the other hand, physician/practice prescribing patterns strongly influenced patient-level treatment patterns. There is no strong statistical evidence that higher levels of out-of-pocket copayments for prescription drugs influence asthma treatment patterns. However, physician/practice prescribing preferences influence patient treatment.

Adult↗

Too much ado about propensity score models? Comparing methods of propensity score matching.

OBJECTIVE: A large number of possible techniques are available when conducting matching procedures, yet coherent guidelines for selecting the most appropriate application do not yet exist. In this article we evaluate several matching techniques and provide a suggested guideline for selecting the best technique. METHODS: The main purpose of a matching procedure is to reduce selection bias by increasing the balance between the treatment and control groups. The following approach, consisting of five quantifiable steps, is proposed to check for balance: 1) Using two sample t-statistics to compare the means of the treatment and control groups for each explanatory variable; 2) Comparing the mean difference as a percentage of the average standard deviations; 3) Comparing percent reduction of bias in the means of the explanatory variables before and after matching; 4) Comparing treatment and control density estimates for the explanatory variables; and 5) Comparing the density estimates of the propensity scores of the control units with those of the treated units. We investigated seven different matching techniques and how they performed with regard to proposed five steps. Moreover, we estimate the average treatment effect with multivariate analysis and compared the results with the estimates of propensity score matching techniques. The Medstat MarketScan Data Base provided data for use in empirical examples of the utility of several matching methods. We conducted nearest neighborhood matching (NNM) analyses in seven ways: replacement, 2 to 1 matching, Mahalanobis matching (MM), MM with caliper, kernel matching, radius matching, and the stratification method. RESULTS: Comparing techniques according to the above criteria revealed that the choice of matching has significant effects on outcomes. Patients with asthma are compared with patients without asthma and cost of illness ranged from 2040 dollars to 4463 dollars depending on the type of matching. After matching, we looked at the insignificant differences or larger P-values in the mean values (criterion 1); low mean differences as a percentage of the average standard deviation (criterion 2); 100% reduction bias in the means of explanatory variables (criterion 3); and insignificant differences when comparing the density estimates of the treatment and control groups (criterion 4 and criterion 5). Mahalanobis matching with caliber yielded the better results according all five criteria (Mean = 4463 dollars, SD = 3252 dollars). We also applied multivariate analysis over the matched sample. This decreased the deviation in cost of illness estimates more than threefold (Mean = 4456 dollars, SD = 996 dollars). CONCLUSION: Sensitivity analysis of the matching techniques is especially important because none of the proposed methods in the literature is a priori superior to the others. The suggested joint consideration of propensity score matching and multivariate analysis offers an approach to assessing the robustness of the estimates.

Confounding Factors, Epidemiologic↗

Higher costs and therapeutic factors associated with adherence to NCQA HEDIS antidepressant medication management measures: analysis of administrative claims.

OBJECTIVE: To determine if the type of antidepressant drug is related to adherence to National Committee for Quality Assurance (NCQA) Antidepressant Medication Management (AMM) quality measures and to assess the 6-month health care costs among newly diagnosed depressed patients. METHODS: The MarketScan Commercial Claims and Encounter database for medical and pharmacy claims from January 2001 to September 2004 was used to assess adherence to the 3 AMM quality-of-care measures. AMM measures include (a) acute phase, the percentage of eligible members who remained on antidepressant medication continuously for 3 months after the initial diagnosis as determined by at least 84 days supply of antidepressant drugs during the first 114 days following receipt of the index antidepressant; (b) continuation phase, the percentage of eligible members who remained on antidepressant medication continuously for the 6 months after the initial diagnosis as determined by at least 180 days supply of antidepressants during the first 214 days following receipt of the index antidepressant; and (c) practitioner contacts, the percentage of members who received at least 3 follow-up office visits or telephone contacts with health care providers, including at least 1 contact with a practitioner licensed to prescribe (may not necessarily be the prescriber of the antidepressant). A fourth measure, overall adherence, was added, if all 3 AMM measures were met. Multivariate regression models determined demographic, clinical (such as receipt of mental health specialty care, the Charlson Comorbidity Index score, and co-occurring bipolar or schizophrenia), and therapy-related factors associated with outcomes of adherence and costs (paid amounts for insurance-reimbursable health care services for inpatient admissions, emergency department services, outpatient services, and outpatient prescription drugs). Health care expenditures (both total and mental-health-specific costs) were measured for each patient for 6 months following the date of service for the index antidepressant. RESULTS: A total of 60,386 adult patients (10.7%) of 562,898 patients with a depression diagnosis met NCQA inclusion criteria in the AMM Technical Specifications (e.g., aged 18 years or older, newly diagnosed with depression and initiating antidepressant therapy, 365 days of continuous enrollment; patients were excluded if there were missing data on dose or quantity of index drug in pharmacy claims or initiated therapy on 2 or more antidepressants as the index medication, exclusion criteria not in the AMM Technical Specifications). Only 19% of patients achieved overall adherence. Rates for the 3 AMM measures were 39% for practitioner contacts, 65% for acute phase, and 44% for continuation phase. Receipt of mental health specialty care was the only factor that was positively associated with greater adherence on all 4 measures (overall measure: odds ratio [OR]=3.895, 95% confidence interval [CI], 3.72-4.07; acute OR=1.38, 95% CI, 1.33-1.43; continuation OR=1.46, 95% CI, 1.41-1.51; contacts OR=5.83, 95% CI, 5.62-6.06). Most patients were initiated on selective serotonin reuptake inhibitors (SSRIs, 69.5%), followed by venlafaxine (21.4%), tricyclic antidepressants (TCAs, 21.4%), bupropion (11.0%), and other antidepressants (e.g., mirtazapine, nefazadone, trazadone; 7.2%). Before adjustment for confounding factors, patients initiated on venlafaxine, TCAs, or other antidepressants had higher rates of adherence on the overall performance measure versus initiators on SSRIs, but the absolute differences were relatively small: 21.4% for venlafaxine and TCAs and 23.1% for other antidepressants versus 18.5% for SSRIs (P <0.001). Patients initiated on venlafaxine, TCAs, or other antidepressants were also more likely to receive care from a mental health specialist, 16.8%, 15.0%, and 54.8%, respectively, compared with SSRIs (13.0%, all P <0.001). Regression analysis showed that only venlafaxine had a higher OR (1.13; 95% CI, 1.05-1.22) compared with SSRIs for adherence on the overall measure. Initiating dose level was in the target range for 70.0% of all patients (24.9% were below target dose and 5.2% above target dose), and adherent patients on all 3 AMM measures were less likely than nonadherent patients (70.4% vs. 68.4%, P <0.001) to be initiated in the target dose range. After multivariate adjustment, the initiating dose (target vs. high) was a significant factor in explaining adherence to the overall measure (OR=1.26; 95% CI, 1.16- 1.37). Adherent patients had 6-month median unadjusted total health care expenses that were nearly 2 times higher compared with nonadherent patients ($5,169 vs. $2,734) and mental health expenditures that were nearly 3 times higher ($1,922 vs. $677). After adjustment, adherent patients compared with nonadherent patients incurred an additional $644 in mental health expenditures and $806 in overall health care expenditures in the 6 months following initiation of antidepressant therapy. CONCLUSIONS: Only 19% of depressed patients initiated on antidepressants met all 3 criteria set forth in the NCQA Health Plan Employer Data and Information Set (HEDIS) AMM quality-of-care performance measures. Receipt of mental health specialty care was the single factor most strongly associated with quality treatment by these measures. Type and dosage level of initial antidepressant was associated with adherence to the NCQA HEDIS AMM measures, but the absolute difference in rates of adherence were relatively small among types of antidepressants. Costs were higher for guideline-adherent individuals in the 6 months following treatment initiation. These analyses were limited to administrative claims that lack indicators of depression disease severity.

Adult↗