Michael A. Fischer

Primary Medication Non-Adherence: Analysis of 195,930 Electronic Prescriptions

ABSTRACTBACKGROUNDNon-adherence to essential medications represents an important public health problem. Little is known about the frequency with which patients fail to fill prescriptions when new medications are started (“primary non-adherence”) or predictors of failure to fill.OBJECTIVEEvaluate primary non-adherence in community-based practices and identify predictors of non-adherence.PARTICIPANTS75,589 patients treated by 1,217 prescribers in the first year of a community-based e-prescribing initiative.DESIGNWe compiled all e-prescriptions written over a 12-month period and used filled claims to identify filled prescriptions. We calculated primary adherence and non-adherence rates for all e-prescriptions and for new medication starts and compared the rates across patient and medication characteristics. Using multivariable regressions analyses, we examined which characteristics were associated with non-adherence.MAIN MEASURESPrimary medication non-adherence.KEY RESULTSOf 195,930 e-prescriptions, 151,837 (78%) were filled. Of 82,245 e-prescriptions for new medications, 58,984 (72%) were filled. Primary adherence rates were higher for prescriptions written by primary care specialists, especially pediatricians (84%). Patients aged 18 and younger filled prescriptions at the highest rate (87%). In multivariate analyses, medication class was the strongest predictor of adherence, and non-adherence was common for newly prescribed medications treating chronic conditions such as hypertension (28.4%), hyperlipidemia (28.2%), and diabetes (31.4%).CONCLUSIONSMany e-prescriptions were not filled. Previous studies of medication non-adherence failed to capture these prescriptions. Efforts to increase primary adherence could dramatically improve the effectiveness of medication therapy. Interventions that target specific medication classes may be most effective.

Epidemiology and sociodemographics of systemic lupus erythematosus and lupus nephritis among US adults with Medicaid coverage, 2000–2004

OBJECTIVE Systemic lupus erythematosus (SLE) and lupus nephritis (LN) disproportionately affect individuals who are members of racial/ethnic minority groups and individuals of lower socioeconomic status (SES). This study was undertaken to investigate the epidemiology and sociodemographics of SLE and LN in the low-income US Medicaid population. METHODS We utilized Medicaid Analytic eXtract data, with billing claims from 47 states and Washington, DC, for 23.9 million individuals ages 18-65 years who were enrolled in Medicaid for >3 months in 2000-2004. Individuals with SLE (≥3 visits >30 days apart with an International Classification of Diseases, Ninth Revision [ICD-9] code of 710.0) and with LN (≥2 visits with an ICD-9 code for glomerulonephritis, proteinuria, or renal failure) were identified. We calculated SLE and LN prevalence and incidence, stratified by sociodemographic category, and adjusted for number of American College of Rheumatology (ACR) member rheumatologists in the state and SES using a validated composite of US Census variables. RESULTS We identified 34,339 individuals with SLE (prevalence 143.7 per 100,000) and 7,388 (21.5%) with LN (prevalence 30.9 per 100,000). SLE prevalence was 6 times higher among women, nearly double in African American compared to white women, and highest in the US South. LN prevalence was higher among all racial/ethnic minority groups compared to whites. The areas with lowest SES had the highest prevalence; areas with the fewest ACR rheumatologists had the lowest prevalence. SLE incidence was 23.2 per 100,000 person-years and LN incidence was 6.9 per 100,000 person-years, with similar sociodemographic trends. CONCLUSION In this nationwide Medicaid population, there was sociodemographic variation in SLE and LN prevalence and incidence. Understanding the increased burden of SLE and its complications in this low-income population has implications for resource allocation and access to subspecialty care.

Patient, Physician, and Payment Predictors of Statin Adherence

Background:Although many patient, physician, and payment predictors of adherence have been described, knowledge of their relative strength and overall ability to explain adherence is limited. Objectives:To measure the contributions of patient, physician, and payment predictors in explaining adherence to statins. Research Design:Retrospective cohort study using administrative data. Subjects:A total of 14,257 patients insured by Horizon Blue Cross Blue Shield of New Jersey who were newly prescribed a statin cholesterol-lowering medication. Measures:Adherence to statin medication was measured during the year after the initial prescription, based on proportion of days covered. The impact of patient, physician, and payment predictors of adherence were evaluated using multivariate logistic regression. The explanatory power of these models was evaluated with C statistics, a measure of the goodness of fit. Results:Overall, 36.4% of patients were fully adherent. Older patient age, male gender, lower neighborhood percent black composition, higher median income, and fewer number of emergency department visits were significant patient predictors of adherence. Having a statin prescribed by a cardiologist, a patients primary care physician, or a US medical graduate were significant physician predictors of adherence. Lower copayments also predicted adherence. All of our models had low explanatory power. Multivariate models including patient covariates only had greater explanatory power (C = 0.613) than models with physician variables only (C = 0.566) or copayments only (C = 0.543). A fully specified model had only slightly more explanatory power (C = 0.633) than the model with patient characteristics alone. Conclusions:Despite relatively comprehensive claims data on patients, physicians, and out-of-pocket costs, our overall ability to explain adherence remains poor. Administrative data likely do not capture many complex mechanisms underlying adherence.

Physician Perceptions About Generic Drugs

Background With constrained health-care resources, there is a need to understand barriers to cost-effective medication use. Objective To study physician perceptions about generic medications. Methods Physicians used 5-point Likert scales to report perceptions about cost-related medication nonadherence, the efficacy and quality of generic medications, preferences for generic use, and the implications of dispensing medication samples. Descriptive statistics were used to assess physician perceptions and logistic regression models were used to evaluate predictors of physician perceptions. Results: Among the invited sample. 839 (30.4%) responded and 506 (18.3%) were eligible and included in the final study population. Over 23% of physicians surveyed expressed negative perceptions about efficacy of generic drugs, almost 50% reported negative perceptions about quality of generic medications, and more than one quarter do not prefer to use generics as first-line medications for themselves or for their family. Physicians over the age of 55 years were 3.3 times more likely to report negative perceptions about generic quality, 5.8 times more likely to report that they would not use generics themselves, and 7.5 times more likely to state that they would not recommend generics for family members (p < 0.05 for all). Physicians reported that pharmaceutical company representatives are the most common (75%) source of information about market entry of a generic medication. Almost half of the respondents expressed concern that free samples may adversely affect subsequent affordability, yet two thirds of respondents provide free samples. Conclusions: A meaningful proportion of physicians expressed negative perceptions about generic medications, representing a potential barrier to generic use. Payors and policymakers trying to encourage generic use may consider educational campaigns targeting older physicians.

Patterns of Medication Initiation in Newly Diagnosed Diabetes Mellitus: Quality and Cost Implications

OBJECTIVE Six oral medication classes have been approved by the Food and Drug Administration for the treatment of type 2 diabetes. Although all of these agents effectively lower blood glucose, the evidence supporting their impact on other clinical events is variable. There also are substantial cost differences between agents. We aimed to evaluate temporal trends in the use of specific drugs for the initial management of type 2 diabetes and to estimate the economic consequences of non-recommended care. METHODS We studied a cohort of 254,973 patients, aged 18 to 100 years, who were newly initiated on oral hypoglycemic monotherapy between January 1, 2006, and December 31, 2008, by using prescription claims data from a large pharmacy benefit manager. Linear regression models were used to assess whether medication initiation patterns changed over time. Multivariate logistic regression models were constructed to identify independent predictors of receiving initial therapy with metformin. We then measured the economic consequences of prescribing patterns by drug class for both patients and the insurer. RESULTS Over the course of the study period, the proportion of patients initially treated with metformin increased from 51% to 65%, whereas those receiving sulfonylureas decreased from 26% to 18% (P<.001 for both). There was a significant decline in the use of thiazolidinediones (20.1%-8.3%, P<.001) and an increase in prescriptions for dipeptidyl peptidase-4 inhibitors (0.4%-7.3%, P<.001). Younger patients, women, and patients receiving drug benefits through Medicare were least likely to initiate treatment with metformin. Combined patient and insurer spending for patients who were initiated on alpha-glucosidase inhibitors, thiazolidinediones, meglitinides, or dipeptidyl peptidase-4 inhibitors was

Trouble Getting Started: Predictors of Primary Medication Nonadherence

677 over a 6-month period compared with

Effect of Electronic Prescribing With Formulary Decision Support on Medication Use and Cost

116 and

Risk of fractures in older adults using antihypertensive medications

118 for patients initiated on metformin or a sulfonylurea, respectively, a cost difference of approximately

Isoflurane Minimum Alveolar Concentration Decreases during Anesthesia and Surgery

1120 annually per patient. CONCLUSION Approximately 35% of patients initiating an oral hypoglycemic drug did not receive recommended initial therapy with metformin. These practice patterns also have substantial implications for health care spending.

Economic Consequences of Underuse of Generic Drugs: Evidence from Medicaid and Implications for Prescription Drug Benefit Plans

BACKGROUND Patient nonadherence to prescribed medication is common and limits the effectiveness of treatment for many conditions. Most adherence studies evaluate behavior only among patients who have filled a first prescription. The advent of electronic prescribing (e-prescribing) systems provides the opportunity to track initial prescriptions and identify nonadherence that may have previously been undetected. METHODS We analyzed e-prescribing data and filled claims for all patients with CVS Caremark (Woonsocket, RI) drug coverage who received e-prescriptions from the iScribe e-prescribing system in calendar 2008. We matched e-prescriptions with filled claims by using data on the drug name, date of e-prescription, and date of filled claims, allowing up to 180 days for patients to fill e-prescriptions. We evaluated the rate of primary nonadherence to newly prescribed medications across multiple characteristics of patients, prescribers, and prescriptions and developed multivariable models to identify predictors of nonadherence. RESULTS We identified 423,616 e-prescriptions for new medications, with 3634 prescribers and 280,081 patients. The primary nonadherence rate was 24.0%. Several factors were associated with nonadherence to e-prescriptions, including nonformulary status of medications (odds ratio [OR] 1.31 compared with preferred medications; 95% confidence interval [CI], 1.26-1.36; P<.001) and residence in a low-income ZIP code (OR 1.23 compared with high-income ZIP code; 95% CI, 1.17-1.30; P<.001) Nonadherence occurred less often when e-prescriptions were transmitted directly to the pharmacy rather than printed to give to patients (OR 0.54; 95% CI, 0.52-0.57; P<.001). CONCLUSION 24% of e-prescriptions for new medications were not filled. Our results suggest that interventions to address economic barriers and increase electronic integration in the healthcare system may be promising approaches to improve medication adherence.