Objective: Despite evidence indicating therapeutic benefit for adhering to a prescribed regimen, many patients do not take their medications as prescribed. Non-adherence often leads to morbidity and to higher health care costs. The objective of the study was to assess patient characteristics associated with medication adherence across eight diseases. Design:Retrospective data from a repository within an integrated health system was used to identify patients ≥18 years of age with ICD-9-CM codes for primary or secondary diagnoses for any of eight conditions (depression, hypertension, hyperlipidemia, diabetes, asthma or chronic obstructive pulmonary disease, multiple sclerosis, cancer, or osteoporosis). Electronic pharmacy data was then obtained for 128 medications used for treatment.Methods: Medication possession ratios (MPR) were calculated for those with one condition and one drug (n=15,334) and then for the total population having any of the eight diseases (n=31,636). The proportion of patients adherent (MPR ≥80%) was summarized by patient and living-area (census) characteristics. Bivariate associations between drug adherence and patient characteristics (age, sex, race, education, and comorbidity) were tested using contingency tables and chi-square tests. Logistic regression analysis examined predictors of adherence from patient and living area characteristics. Results:Medication adherence for those with one condition was higher in males, Caucasians, older patients, and those living in areas with higher education rates and higher income. In the total population, adherence increased with lower comorbidity and increased number of medications. Substantial variation in adherence was found by condition with the lowest adherence for diabetes (51%) and asthma (33%). Conclusions:The expectation of high adherence due to a covered pharmacy benefit, and to enhanced medication access did not hold. Differences in medication adherence were found across condition and by patient characteristics. Great room for improvement remains, specifically for diabetes and asthma.

Context More than 1.5 million US adults use stimulants and other medications labeled for treatment of attention deficit hyperactivity disorder (ADHD). These agents can increase heart rate and blood pressure, raising concerns about their cardiovascular safety. Objective Examine whether current use of medications used primarily to treat ADHD is associated with increased risk of serious cardiovascular events in young and middle-aged adults. Design Retrospective, population-based cohort study Setting Computerized health records from 4 study sites (OptumInsight Epidemiology, Tennessee Medicaid, Kaiser Permanente California, and the HMO Research Network), starting in 1986 at one site and ending in 2005 at all sites, with additional covariate assessment using 2007 survey data. Participants Adults aged 25–64 years with dispensed prescriptions for methylphenidate, amphetamine, or atomoxetine at baseline. Each medication user (n=150,359) was matched to two non-users on study site, birth year, sex, and calendar year (total users and non-users=443,198). Main Outcome Serious cardiovascular events, including myocardial infarction (MI), sudden cardiac death (SCD), or stroke. Comparison between current or new users and remote users to account for potential healthy user bias. Results During 806,182 person-years of follow-up (median 1.3 years per person), 1357 cases of MI, 296 cases of SCD, and 575 cases of stroke occurred. There were 107,322 person-years of current use (median 0.33 years), with a crude incidence per 1000 person-years of 1.34 (95% CI, 1.14–1.57) for MI, 0.30 (95% CI, 0.20–0.42) for SCD, and 0.56 (95% CI, 0.43–0.72) for stroke. The multivariable adjusted rate ratio (RR) of serious cardiovascular events for current use vs non-use of ADHD medications was 0.83 (95% CI 0.72–0.96). Among new users of ADHD medications, the adjusted RR was 0.77 (95% CI 0.63–0.94). The adjusted RR was 1.03 (95% CI, 0.86–1.24) for current use vs remote use, and was 1.02 (95% CI, 0.82–1.28) for new use vs remote use. Conclusion Among young and middle-aged adults, current or new use of ADHD medications, compared with non-use or remote use, was not associated with an increased risk of serious cardiovascular events. Apparent protective associations likely represent healthy user bias.

IMPORTANCE Obesity is associated with chronic noncancer pain. It is not known if opioid use for chronic pain in obese individuals undergoing bariatric surgery is reduced.OBJECTIVES To determine opioid use following bariatric surgery in patients using opioids chronically for pain control prior to their surgery and to determine the effect of preoperative depression, chronic pain, or postoperative changes in body mass index (BMI) on changes in postoperative chronic opioid use. DESIGN, SETTING, AND PARTICIPANTSRetrospective cohort study in a distributed health network (10 demographically and geographically varied US health care systems) of 11 719 individuals aged 21 years and older, who had undergone bariatric surgery between 2005 and 2009, and were assessed 1 year before and after surgery, with latest follow-up by December 31, 2010.MAIN OUTCOMES AND MEASURES Opioid use, measured as morphine equivalents 1 year before and 1 year after surgery, excluding the first 30 postoperative days. Chronic opioid use is defined as 10 or more opioid dispensings over 90 or more days or as dispensings of at least a 120-day supply of opioids during the year prior to surgery. RESULTS Before surgery, 8% (95% CI, 7%-8%; n = 933) of bariatric patients were chronic opioid users. Of these individuals, 77% (95% CI, 75%-80%; n = 723) continued chronic opioid use in the year following surgery. Mean daily morphine equivalents for the 933 bariatric patients who were chronic opioid users before surgery were 45.0 mg (95% CI, 40.0-50.1) preoperatively and 51.9 mg (95% CI, 46.0-57.8) postoperatively (P < .001). For this group with chronic opiate use prior to surgery, change in morphine equivalents before vs after surgery did not differ between individuals with loss of more than 50% excess BMI vs those with 50% or less (>50% BMI loss: adjusted incidence rate ratio [adjusted IRR, 1.17; 95% CI, 1.07-1.28] vs Յ50% BMI loss [adjusted IRR, 1.03; 95% CI, 0.93-1.14] model interaction, P = .06). In other subgroup analyses of preoperative chronic opioid users, changes in morphine equivalents before vs after surgery did not differ between those with or without preoperative diagnosis of depression or chronic pain (depression only [n = 75; IRR, 1.08; 95% CI, 0.90-1.30]; chronic pain only [n = 440; IRR, 1.17; 95% CI, 1.08-1.27]; both depression and chronic pain [n = 226; IRR, 1.11; 95% CI, 0.96-1.28]; neither depression nor chronic pain [n = 192; IRR, 1.22; 95% CI, 0.98-1.51); and P values for model interactions when compared with neither were P = .42 for depression, P = .76 for pain, and P = .48 for both. CONCLUSIONS AND RELEVANCEIn this cohort of patients who underwent bariatric surgery, 77% of patients who were chronic opioid users before surgery continued chronic opioid use in the year following surgery, and the amount of chronic opioid use was greater postoperatively than preoperatively. These findings suggest the need for better pain management in these patients following surgery.

Purpose To evaluate the validity of health plan and birth certificate data for pregnancy research. Methods A retrospective study was conducted using administrative and claims data from 11 U.S. health plans, and corresponding birth certificate data from state health departments. Diagnoses, drug dispensings, and procedure codes were used to identify infant outcomes (cardiac defects, anencephaly, preterm birth, and neonatal intensive care unit [NICU] admission) and maternal diagnoses (asthma and systemic lupus erythematosus [SLE]) recorded in the health plan data for live born deliveries between January 2001 and December 2007. A random sample of medical charts (n = 802) was abstracted for infants and mothers identified with the specified outcomes. Information on newborn, maternal, and paternal characteristics (gestational age at birth, birth weight, previous pregnancies and live births, race/ethnicity) was also abstracted and compared to birth certificate data. Positive predictive values (PPVs) were calculated with documentation in the medical chart serving as the gold standard. Results PPVs were 71% for cardiac defects, 37% for anencephaly, 87% for preterm birth, and 92% for NICU admission. PPVs for algorithms to identify maternal diagnoses of asthma and SLE were ≥ 93%. Our findings indicated considerable agreement (PPVs > 90%) between birth certificate and medical record data for measures related to birth weight, gestational age, prior obstetrical history, and race/ethnicity. Conclusions Health plan and birth certificate data can be useful to accurately identify some infant outcomes, maternal diagnoses, and newborn, maternal, and paternal characteristics. Other outcomes and variables may require medical record review for validation.

Key Points Question How long does blood pressure remain lower compared with usual care after a 12-month intensive intervention (home telemonitoring and pharmacist management)? Findings In this follow-up of a cluster randomized trial of 326 patients with uncontrolled hypertension, research clinic measurements showed that home blood pressure telemonitoring with pharmacist management lowered blood pressure more than usual care in the first 18 months, but this was not sustained through 54 months. The results from routine clinical measurements suggested significantly lower blood pressure in the intervention group for up to 24 months. Meaning Long-term maintenance strategies may be needed to sustain blood pressure intervention effects over several years.

The tree-based scan statistic can be successfully applied as a data mining tool in drug safety surveillance using observational data. The total number of statistical signals was modest and does not imply a causal relationship. Rather, data mining results should be used to generate candidate drug-event pairs for rigorous epidemiological studies to evaluate the individual and comparative safety profiles of drugs.

Purpose To validate an algorithm that uses delivery date and diagnosis codes to define gestational age at birth in electronic health plan databases. Methods Using data from 225,384 live born deliveries among women aged 15–45 years in 2001–2007 within 8 of the 11 health plans participating in the Medication Exposure in Pregnancy Risk Evaluation Program, we compared 1) the algorithm-derived gestational age versus the “gold-standard” gestational age obtained from the infant birth certificate files; and 2) the prenatal exposure status of two antidepressants (fluoxetine and sertraline) and two antibiotics (amoxicillin and azithromycin) as determined by the algorithm-derived versus the gold-standard gestational age. Results The mean algorithm-derived gestational age at birth was lower than the mean obtained from the birth certificate files among singleton deliveries (267.9 versus 273.5 days) but not among multiple-gestation deliveries (253.9 versus 252.6 days). The algorithm-derived prenatal exposure to the antidepressants had a sensitivity and a positive predictive value (PPV) of ≥95%, and a specificity and a negative predictive value (NPV) of almost 100%. Sensitivity and PPV were both ≥90%, and specificity and NPV were both >99% for the antibiotics. Conclusions A gestational age algorithm based upon electronic health plan data correctly classified medication exposure status in most live born deliveries, but misclassification may be higher for drugs typically used for short durations.

Purpose To estimate the prevalence of and temporal trends in prenatal antipsychotic medication use within a cohort of pregnant women in the U.S. Methods We identified live born deliveries to women aged 15–45 years in 2001–2007 from 11 U.S. health plans participating in the Medication Exposure in Pregnancy Risk Evaluation Program (MEPREP). We ascertained prenatal exposure to antipsychotics from health plan pharmacy dispensing files, gestational age from linked infant birth certificate files, and ICD-9-CM diagnosis codes from health plan claims files. We calculated the prevalence of prenatal use of atypical and typical antipsychotics according to year of delivery, trimester of pregnancy, and mental health diagnosis. Results Among 585,615 qualifying deliveries, 4,223 (0.72%) were to women who received an atypical antipsychotic and 548 (0.09%) were to women receiving a typical antipsychotic any time from 60 days before pregnancy through delivery. There was a 2.5-fold increase in atypical antipsychotic use during the study period, from 0.33% (95% confidence interval: 0.29%, 0.37%) in 2001 to 0.82% (0.76%, 0.88%) in 2007, while the use of typical antipsychotics remained stable. Depression was the most common mental health diagnosis among deliveries to women with atypical antipsychotic use (63%), followed by bipolar disorder (43%) and schizophrenia (13%). Conclusions The number and proportion of pregnancies exposed to atypical antipsychotics has increased dramatically in recent years. Studies are needed to examine the comparative safety and effectiveness of these medications relative to other therapeutic options in pregnancy.