WHAT IS KNOWN AND OBJECTIVE: Pharmacy claims are commonly used to assess medication adherence. It is unclear how different approaches to handling hospitalizations compare to the gold standard of using outpatient and inpatient drug data. This study aimed to compare the impact of different approaches to handling hospitalizations on medication adherence estimation in administrative claims data. METHODS: We identified beta-blocker initiators after myocardial infarction (MI) and statin initiators regardless of hospitalization histories in the population-based, Taiwan database, which includes outpatient and inpatient drug claims data. Adherence to beta-blockers or to statins during a 365-day follow-up period was estimated in outpatient pharmacy claims using the proportion of days covered (PDC) in three ways: ignoring hospitalizations (PDC1); subtracting hospitalized days from the denominator (PDC2); and assuming drug use on all hospitalized days (PDC3). We compared these to an approach that incorporated inpatient drug use (PDC4). We also used a hypothetical example to examine variations across approaches in several scenarios, such as increasing hospitalized days. RESULTS AND DISCUSSION: Mean 365-day PDC was 74% among 1729 post-MI beta-blocker initiators (range: 73.1%-74.9%) and 44% among 69 435 statins initiators (range: 43.5%-44.0%), which varied little across approaches. Differences across approaches increased with increasing number of hospitalized days. For patients hospitalized for >28 days, mean difference across approaches was >15%. PDC3 consistently yielded the highest value and PDC1 the lowest. WHAT IS NEW AND CONCLUSIONS: On average, different approaches to handling hospitalizations lead to similar adherence estimates to the gold standard of incorporating inpatient drug use. When patients have many hospitalization days during follow-up, the choice of approach should be tailored to the specific setting.
BACKGROUND: Attempts to predict who is at risk of future nonadherence have largely focused on predictions at the time of therapy initiation; however, these users are only a small proportion of all patients on therapy at any point in time. Methods to predict nonadherence for established medication users, which have not been previously described in the literature, would be helpful to guide efforts to enhance the use of evidence-based therapies. OBJECTIVE: To test approaches for adherence prediction among prevalent statin users, namely the use of short-term filling behavior, investigator-specified predictors from medical and pharmacy administrative claims, and the empirical selection of potential predictors using the high-dimensional propensity score variable selection algorithm. METHODS: Medical and prescription claims data from a large national health insurer were used to create a cohort of patients who filled statin medication prescriptions in January 2012. We defined 6 groups of adherence predictors and estimated 10 main models to predict medication adherence in the full cohort. The same was done for the population stratified based on the days supply of the index statin prescription ( 30 days). RESULTS: The study cohort consisted of 93,777 individuals, 58.4% of which were adherent to statins during follow-up. The use of 3 pre-index adherence predictors alone achieved a c-statistic of 0.70. Investigator-specified and empirically selected pharmacy, medical, and demographic variables did substantially worse (0.57-0.60). The use of 3 indicators of post-index adherence achieved a higher c-statistic than the best-performing model using pre-index information (0.74 vs. 0.72). The addition of 3 pre-index adherence predictors further improved discrimination (0.78). CONCLUSIONS: This analysis demonstrated the ability to predict adherence among medication users using filling behavior before and immediately after an index prescription fill. DISCLOSURES: This work was supported by an unrestricted grant from CVS Health to Brigham and Women's Hospital. Shrank, Brennan, and Matlin were employees and shareholders at CVS Health at the time of this manuscript preparation; they report no financial interests in products or services that are related to the subject of the manuscript. Franklin has received consulting fees from Aetion. Chourdry has received grants from the National Heart, Lung, and Blood Institute, PhRMA Foundation, Merck, Sanofi, AstraZeneca, and MediSafe. Spettell is an employee of, and shareholder in, Aetna. The other authors have nothing to disclose. Krumme, Choudhry, Tong, and Franklin contributed to the study design, interpretation of results, and manuscript drafting. Tong prepared and analyzed the data. Isaman, Spettell, Shrank, Brennan, and Matlin provided interpretation of results and critical manuscript revisions.
Importance Forgetfulness is a major contributor to nonadherence to chronic disease medications and could be addressed with medication reminder devices.Objective To compare the effect of 3 low-cost reminder devices on medication adherence.Design, Setting, and Participants This 4-arm, block-randomized clinical trial involved 53 480 enrollees of CVS Caremark, a pharmacy benefit manager, across the United States. Eligible participants were aged 18 to 64 years and taking 1 to 3 oral medications for long-term use. Participants had to be suboptimally adherent to all of their prescribed therapies (with a medication possession ratio of 30% to 80%) in the 12 months before randomization. Participants were stratified on the basis of the medications they were using at randomization: medications for cardiovascular or other nondepression chronic conditions (the chronic disease stratum) and antidepressants (the antidepressant stratum). In each stratum, randomization occurred within blocks defined by whether all of the patient’s targeted medications were dosed once daily. Patients were randomized to receive in the mail a pill bottle strip with toggles, digital timer cap, or standard pillbox. The control group received neither notification nor a device. Data were collected from February 12, 2013, through March 21, 2015, and data analyses were on the intention-to-treat population. Main Outcomes and Measures The primary outcome was optimal adherence (medication possession ratio ≥80%) to all eligible medications among patients in the chronic disease stratum during 12 months of follow-up, ascertained using pharmacy claims data. Secondary outcomes included optimal adherence to cardiovascular medications among patients in the chronic disease stratum as well as optimal adherence to antidepressants.Results Of the 53 480 participants, mean (SD) age was 45 (12) years and 56% were female. In the primary analysis, 15.5% of patients in the chronic disease stratum assigned to the standard pillbox, 15.1% assigned to the digital timer cap, 16.3% assigned to the pill bottle strip with toggles, and 15.1% assigned to the control arm were optimally adherent to their prescribed treatments during follow-up. There was no statistically significant difference in the odds of optimal adherence between the control and any of the devices (standard pillbox: odds ratio [OR], 1.03 [95% CI, 0.95-1.13]; digital timer cap: OR, 1.00 [95% CI, 0.92-1.09]; and pill bottle strip with toggles: OR, 0.94 [95% CI, 0.85-1.04]). In direct comparisons, the odds of optimal adherence were higher with a standard pillbox than with the pill bottle strip (OR, 1.10 [95% CI, 1.00-1.21]). Secondary analyses yielded similar results.Conclusions and Relevance Low-cost reminder devices did not improve adherence among nonadherent patients who were taking up to 3 medications to treat common chronic conditions. The devices may have been more effective if coupled with interventions to ensure consistent use or if targeted to individuals with an even higher risk of nonadherence.Trial Registration clinicaltrials.gov Identifier: NCT02015806
Background: Despite the widespread adoption of patient-centered medical homes into primary care practice, the evidence supporting their effect on health care outcomes has come primarily from geographically localized and well-integrated health systems. Objective: To assess the association between medication adherence and medical homes in a national patient and provider population, given the strong ties between adherence to chronic disease medications and health care quality and spending. Design: Retrospective cohort study. Setting: Claims from a large national health insurer. Patients: Patients initiating therapy with common medications for chronic diseases (diabetes, hypertension, and hyperlipidemia) between 2011 and 2013. Measurements: Medication adherence in the 12 months after treatment initiation was compared among patients cared for by providers practicing in National Committee for Quality Assurance-recognized patient-centered medical homes and propensity score-matched control practices in the same Primary Care Service Areas. Linear mixed models were used to examine the association between medical homes and adherence. Results: Of 313 765 patients meeting study criteria, 18 611 (5.9%) received care in patient-centered medical homes. Mean rates of adherence were 64% among medical home patients and 59% among control patients. Among 4660 matched control and medical home practices, medication adherence was significantly higher in medical homes (2.2% [95% CI, 1.5% to 2.9%]). The association between medical homes and better adherence did not differ significantly by disease state (diabetes, 3.0% [CI, 1.5% to 4.6%]; hypertension, 3.2% [CI, 2.2% to 4.2%]; hyperlipidemia, 1.5% [CI, 0.6% to 2.5%]). Limitation: Clinical outcomes related to medication adherence were not assessed. Conclusion: Receipt of care in a patient-centered medical home is associated with better adherence, a vital measure of health care quality, among patients initiating treatment with medications for common high-cost chronic diseases. Primary Funding Source: CVS Health.
BackgroundHypertension is a major contributor to the health and economic burden imposed by stroke, heart disease, and renal insufficiency. Antihypertensives can prevent many of the harmful effects of elevated blood pressure, but medication nonadherence is a known barrier to the effectiveness of these treatments. Smartphone-based applications that remind patients to take their medications, provide education, and allow for social interactions between individuals with similar health concerns have been widely advocated as a strategy to improve adherence but have not been subject to rigorous testing.
BACKGROUND: Patients treated with warfarin are often coprescribed selective serotonin reuptake inhibitors (SSRIs) for coexisting depression. Some SSRIs are potent CYP2C9 inhibitors that may increase warfarin plasma concentrations and the risk of bleeding. We aimed to examine the effect of the putative CYP2C9-mediated warfarin-SSRI interaction on clinical outcomes. METHODS: We conducted an observational cohort study among warfarin initiators who had a subsequent SSRI prescription in 5 US claims databases. Patients were followed for up to 180 days as long as they were exposed to both warfarin and their index SSRI groups. Cox regression models were used to estimate hazard ratios and 95% confidence intervals for bleeding events, ischemic or thromboembolic events, and mortality comparing patients treated with SSRIs that are potent CYP2C9 inhibitors (fluoxetine, fluvoxamine) with those treated with other SSRIs after propensity score matching. FINDINGS: The eligible cohort comprised 52,129 patients. Hazard ratios were 1.14 (95% confidence interval [CI], 0.94-1.38) for bleeding events, 1.03 (95% CI, 0.87-1.21) for ischemic or thromboembolic events, and 0.90 (95% CI, 0.72-1.14) for mortality. Results were consistent across individual component outcomes, different warfarin stabilization periods, and subgroup analyses. CONCLUSIONS: Patients concomitantly treated with warfarin and SSRIs that are potent CYP2C9 inhibitors had comparable rates of bleeding events, ischemic or thromboembolic events, and mortality as did patients cotreated with warfarin and other SSRIs, although small but potentially meaningful effects on bleeding cannot be completely excluded. SSRI inhibition of CYP2C9 does not appear to affect major safety or effectiveness outcomes of warfarin treatment in clinical practice, where patients may be closely monitored.
BACKGROUND: With rising health spending, predicting costs is essential to identify patients for interventions. Many of the existing approaches have moderate predictive ability, which may result, in part, from not considering potentially meaningful changes in spending over time. Group-based trajectory modeling could be used to classify patients into dynamic long-term spending patterns. OBJECTIVES: To classify patients by their spending patterns over a 1-year period and to assess the ability of models to predict patients in the highest spending trajectory and the top 5% of annual spending using prior-year predictors. SUBJECTS: We identified all fully insured adult members enrolled in a large US nationwide insurer and used medical and prescription data from 2009 to 2011. RESEARCH DESIGN: Group-based trajectory modeling was used to classify patients by their spending patterns over a 1-year period. We assessed the predictive ability of models that categorized patients in the top fifth percentile of annual spending and in the highest spending trajectory, using logistic regression and split-sample validation. Models were estimated using investigator-specified variables and a proprietary risk-adjustment method. RESULTS: Among 998,651 patients, in the best-performing model, prediction was strong for patients in the highest trajectory group (C-statistic: 0.86; R: 0.47). The C-statistic of being in the top fifth percentile of spending in the best-performing model was 0.82 (R: 0.26). Approaches using nonproprietary investigator-specified methods performed almost as well as other risk-adjustment methods (C-statistic: 0.81 vs. 0.82). CONCLUSIONS: Trajectory modeling may be a useful way to predict costly patients that could be implementable by payers to improve cost-containment efforts.
Clopidogrel is a pro-drug that requires activation by the cytochrome P450 (CYP) enzyme system. Patients receiving clopidogrel are often treated with selective serotonin reuptake inhibitors (SSRIs) for co-existing depression. SSRIs that inhibit the CYP2C19 enzyme have the potential to reduce the effectiveness of clopidogrel. Using 5 US databases (1998 to 2013), we conducted a cohort study of adults who initiated clopidogrel while being treated with either an SSRI that inhibits CYP2C19 (fluoxetine and fluvoxamine) or a noninhibiting SSRI. Patients were matched by propensity score and followed for as long as they were exposed to both clopidogrel and the index SSRI group (primary analysis) or for 180 days after clopidogrel initiation (sensitivity analysis). Outcomes included a composite ischemic event (myocardial infarction, ischemic stroke, or a revascularization procedure) and a composite major bleeding event (gastrointestinal bleed or hemorrhagic stroke). The final propensity score-matched cohort comprised 9,281 clopidogrel initiators on CYP2C19-inhibiting SSRIs and 44,278 clopidogrel initiators on a noninhibiting SSRIs. Compared with those treated with a noninhibiting SSRI, patients on a CYP2C19-inhibiting SSRI had an increased risk of ischemic events (hazard ratio [HR] 1.12; 95% confidence interval [CI] 1.01 to 1.24), which was more pronounced in patients >/=65 years (HR 1.22; 95% CI 1.00 to 1.48). The HR for major bleeding was 0.76 (95% CI 0.50 to 1.17). In conclusion, the findings from this large, population-based study suggest that being treated with a CYP2C19-inhibiting SSRI when initiating clopidogrel may be associated with slight decrease in effectiveness of clopidogrel.
BACKGROUND/AIMS: Renally excreted medications often require dose adjustment in patients with kidney impairment. While drug development and approval in the United States are typically based on several Phase I and II studies and one or more larger Phase III randomized trials, the basis for labeled dosing recommendations for patients with renal impairment is less well known. In response, we aimed to quantify the level of evidence used to recommend labeled dosing adjustments for newly approved drugs in patients with renal impairment. METHODS: We reviewed publicly available drug labels and approval packages for new molecular entities approved in the United States between 2012 and 2014. The sample was restricted to 29 renally excreted new molecular entities that were not granted orphan drug status. We extracted data regarding approved indications, normal dosing, dosing adjustments for patients with mild (estimated glomerular filtration rate >60 mL/min/1.73 m2), moderate (estimated glomerular filtration rate 30-<60 mL/min/1.73 m2), and severe (estimated glomerular filtration rate <30 mL/min/1.73 m2) renal impairment, characteristics of studies used to justify dosing adjustments, and numbers of subjects in each study. RESULTS: In all, 14 of 29 (48%) new molecular entities had labels that recommended dosing adjustments for patients with mild, moderate, and/or severe renal impairment. Among these 14 new molecular entities, 4 (29%) used only pharmacokinetic studies to justify the recommendations, with no examination of clinical outcomes for patients with renal impairment. Where data were available, the median number of patients with renal impairment evaluated in studies used for dosing adjustment was 34 (range, 4-5976). Of the 15 new molecular entities with no recommended dosing adjustments for this population, 2 (13%) did not report assessing the effects of renal impairment. CONCLUSION: Nearly half of newly approved renally excreted drugs include dosing adjustments for kidney impairment on the label, but the recommendations are usually based on very small numbers of patients and often utilize pharmacokinetic studies alone. More research is needed to understand the benefits and risks of new drugs in patients with renal impairment.
OBJECTIVE: To evaluate the impact of the 2006 Massachusetts health reform, the model for the Affordable Care Act, on short-term enrollment and utilization in the unsubsidized individual health insurance market. DATA SOURCE: Seven years of administrative and claims data from Harvard Pilgrim Health Care. RESEARCH DESIGN: We employed pre-post survival analysis and an interrupted time series design to examine changes in enrollment length, utilization patterns, and use of elective procedures (discretionary inpatient surgeries and infertility treatment) among nonelderly adult enrollees before (n = 6,912) and after (n = 29,207) the MA reform. PRINCIPAL FINDINGS: The probability of short-term enrollment dropped immediately after the reform. Rates of inpatient encounters (HR = 0.83, 95 percent CI: 0.74, 0.93), emergency department encounters (HR = 0.85, 95 percent CI: 0.80, 0.91), and discretionary inpatient surgeries (HR = 0.66 95 percent CI: 0.45, 0.97) were lower in the postreform period, whereas the rate of ambulatory visits was somewhat higher (HR = 1.04, 95 percent CI: 1.00, 1.07). The rate of infertility treatment was higher after the reform (HR = 1.61, 95 percent CI: 1.33, 1.97), driven by women in individual (vs. family) plans. The reform was not associated with increased utilization among short-term enrollees. CONCLUSIONS: MA health reform was associated with a decrease in short-term enrollment and changes in utilization patterns indicative of reduced adverse selection in the unsubsidized individual market. Adverse selection may be a problem for specific, high-cost treatments.
OBJECTIVE: With more antiepileptic drugs (AED) becoming available in generic form, we estimated the risk of seizure-related events associated with refilling generic AEDs and the effect of switching between different manufacturers of the same generic drug. METHODS: We designed a population-based case-crossover study using the Medicaid Analytic eXtract and a US commercial health insurance database. We identified 83,001 generic AED users who experienced a seizure-related hospital admission or emergency room visit between 2000 and 2013 and assessed whether they received a refill of the same AED from the same manufacturer or a different manufacturer. Patients served as their own controls and conditional logistic regression was used to compare exposure to a refill during the hazard period, defined as days 2-36 preceding the seizure-related event, to exposure during the control period, defined as days 51-85 preceding the seizure-related event. RESULTS: Generic AED refilling was associated with an 8% increase in the odds of seizure-related events (odds ratio [OR] 1.08; 95% confidence interval [CI] 1.06-1.11). The OR following a switch to a different manufacturer of the same AED was 1.09 (95% CI 1.03-1.15); however, after adjusting for the process of refilling, there was no association between switching and seizure-related hospital visits (OR 1.00; 95% CI 0.94-1.07). CONCLUSIONS: Among patients on a generic AED, refilling the same AED was associated with an elevated risk of seizure-related event; however, there was no additional risk from switching during that refill to a different manufacturer. Generic AEDs available to US patients, with Food and Drug Administration-validated bioequivalence, appear to be safe clinical choices.
OBJECTIVE: The use of retail purchasing data may improve adherence prediction over approaches using healthcare insurance claims alone.
DESIGN: Retrospective. Setting and participants: A cohort of patients who received prescription medication benefits through CVS Caremark, used a CVS Pharmacy ExtraCare Health Care (ECHC) loyalty card, and initiated a statin medication in 2011.
OUTCOME: We evaluated associations between retail purchasing patterns and optimal adherence to statins in the 12 subsequent months.
RESULTS: Among 11 010 statin initiators, 43% were optimally adherent at 12 months of follow-up. Greater numbers of store visits per month and dollar amount per visit were positively associated with optimal adherence, as was making a purchase on the same day as filling a prescription ( p<0.0001 for all). Models to predict adherence using retail purchase variables had low discriminative ability (C-statistic: 0.563), while models with both clinical and retail purchase variables achieved a C-statistic of 0.617.
CONCLUSIONS: While the use of retail purchases may improve the discriminative ability of claims-based approaches, these data alone appear inadequate for adherence prediction, even with the addition of more complex analytical approaches. Nevertheless, associations between retail purchasing behaviours and adherence could inform the development of quality improvement interventions.
OBJECTIVES: Medication discrepancies at the time of hospital discharge are common and can harm patients. Medication reconciliation by pharmacists has been shown to prevent such discrepancies and the adverse drug events (ADEs) that can result from them. Our objective was to estimate the economic value of nontargeted and targeted medication reconciliation conducted by pharmacists and pharmacy technicians at hospital discharge versus usual care. STUDY DESIGN: Discrete-event simulation model. METHODS: We developed a discrete-event simulation model to prospectively model the incidence of drug-related events from a hospital payer’s perspective. The model assumptions were based on data published in the peerreviewed literature. Incidences of medication discrepancies, preventable ADEs, emergency department visits, rehospitalizations, costs, and net benefit were estimated. RESULTS: The expected total cost of preventable ADEs was estimated to be $472 (95% credible interval [CI], $247-$778) per patient with usual care. Under the base-case assumption that medication reconciliation could reduce medication discrepancies by 52%, the cost of preventable ADEs could be reduced to $266 (95% CI, $150-$423), resulting in a net benefit of $206 (95% CI, $73-$373) per patient, after accounting for intervention costs. A medication reconciliation intervention that reduces medication discrepancies by at least 10% could cover the initial cost of intervention. Targeting medication reconciliation to high-risk individuals would achieve a higher net benefit than a nontargeted intervention only if the sensitivity and specificity of a screening tool were at least 90% and 70%, respectively. CONCLUSIONS: Our study suggests that implementing a pharmacist-led medication reconciliation intervention at hospital discharge could be cost saving compared with usual care.
BACKGROUND: The incidence of opioid-related death in women has increased 5-fold over the past decade. For many women, their initial opioid exposure will occur in the setting of routine medical care. Approximately 1 in 3 deliveries in the United States is by cesarean, and opioids are commonly prescribed for postsurgical pain management. OBJECTIVE: The objective of this study was to determine the risk that opioid-naive women prescribed opioids after cesarean delivery will subsequently become consistent prescription opioid users in the year following delivery and to identify predictors for this behavior. STUDY DESIGN: We identified women in a database of commercial insurance beneficiaries who underwent cesarean delivery and who were opioid naive in the year prior to delivery. To identify persistent users of opioids, we used trajectory models, which group together patients with similar patterns of medication filling during follow-up, based on patterns of opioid dispensing in the year following cesarean delivery. We then constructed a multivariable logistic regression model to identify independent risk factors for membership in the persistent user group. RESULTS: A total of 285 of 80,127 (0.36%, 95% confidence interval, 0.32-0.40), opioid-naive women became persistent opioid users (identified using trajectory models based on monthly patterns of opioid dispensing) following cesarean delivery. Demographics and baseline comorbidity predicted such use with moderate discrimination (c statistic = 0.73). Significant predictors included a history of cocaine abuse (risk, 7.41%; adjusted odds ratio, 6.11, 95% confidence interval, 1.03-36.31) and other illicit substance abuse (2.36%; adjusted odds ratio, 2.78, 95% confidence interval, 1.12-6.91), tobacco use (1.45%; adjusted odds ratio, 3.04, 95% confidence interval, 2.03-4.55), back pain (0.69%; adjusted odds ratio, 1.74, 95% confidence interval, 1.33-2.29), migraines (0.91%; adjusted odds ratio, 2.14, 95% confidence interval, 1.58-2.90), antidepressant use (1.34%; adjusted odds ratio, 3.19, 95% confidence interval, 2.41-4.23), and benzodiazepine use (1.99%; adjusted odds ratio, 3.72, 95% confidence interval, 2.64-5.26) in the year prior to the cesarean delivery. CONCLUSION: A very small proportion of opioid-naive women (approximately 1 in 300) become persistent prescription opioid users following cesarean delivery. Preexisting psychiatric comorbidity, certain pain conditions, and substance use/abuse conditions identifiable at the time of initial opioid prescribing were predictors of persistent use.
BACKGROUND: The use of oral P2Y12 receptor inhibitors after acute myocardial infarction (MI) can reduce risks of subsequent major adverse cardiovascular events (composite of all-cause death, recurrent MI, and stroke), yet medication persistence is suboptimal. Although copayment cost has been implicated as a factor influencing medication persistence, it remains unclear whether reducing or eliminating these costs can improve medication persistence and/or downstream clinical outcomes. DESIGN: ARTEMIS is a multicenter, cluster-randomized clinical trial designed to examine whether eliminating patient copayment for P2Y12 receptor inhibitor therapy affects medication persistence and clinical outcomes. We will enroll approximately 11,000 patients hospitalized for acute ST-elevation and non-ST-elevation MI at 300 hospitals. Choice and duration of treatment with a P2Y12 receptor inhibitor will be determined by the treating physician. Hospitals randomized to the copayment intervention will provide vouchers to cover patients' copayments for their P2Y12 receptor inhibitor for up to 1 year after discharge. The coprimary end points are 1-year P2Y12 receptor inhibitor persistence and major adverse cardiovascular events. Secondary end points include choice of P2Y12 receptor inhibitor, patient-reported outcomes, and postdischarge cost of care. CONCLUSION: ARTEMIS will be the largest randomized assessment of a medication copayment reduction intervention on medication persistence, clinical outcomes, treatment selection, and cost of care after acute MI.
BACKGROUND: Variation in physician adoption of new medications is poorly understood. Traditional approaches (eg, measuring time to first prescription) may mask substantial heterogeneity in technology adoption. OBJECTIVE: Apply group-based trajectory models to examine the physician adoption of dabigratran, a novel anticoagulant. METHODS: A retrospective cohort study using prescribing data from IMS Xponent on all Pennsylvania physicians regularly prescribing anticoagulants (n=3911) and data on their characteristics from the American Medical Association Masterfile. We examined time to first dabigatran prescription and group-based trajectory models to identify adoption trajectories in the first 15 months. Factors associated with rapid adoption were examined using multivariate logistic regressions. OUTCOMES: Trajectories of monthly share of oral anticoagulant prescriptions for dabigatran. RESULTS: We identified 5 distinct adoption trajectories: 3.7% rapidly and extensively adopted dabigatran (adopting in 55 y). CONCLUSIONS: Trajectories of physician adoption of dabigatran were highly variable with significant differences across specialties. Heterogeneity in physician adoption has potential implications for the cost and effectiveness of treatment.
OBJECTIVE: Several trials suggest that triple therapy (methotrexate, sulfasalazine, and hydroxychloroquine) and biologic disease-modifying antirheumatic drugs (bDMARD) have similar efficacy in rheumatoid arthritis (RA). We investigated intensification to triple therapy after initial non-biologic (nbDMARD) prescription among patients with RA. METHODS: We used US insurance claims data to evaluate triple therapy use from 2009-2014. Patients with a visit for RA and initial nbDMARD prescription were included. Frequencies and rates to intensification to triple therapy or bDMARD were calculated. We evaluated whether sociodemographic, temporal, geographic, clinical, and healthcare utilization factors were associated with triple therapy intensification using Cox regression. Among those who intensified therapy, we investigated factors associated with triple therapy use by logistic regression. RESULTS: There were 24,576 patients initially with mean age of 50.3 (SD 12.3) years, and 78% were female. During the study period, 2,739 (11.1%) intensified treatment to bDMARD compared to 181 (0.7%) who intensified to triple therapy. There was no significant change in triple therapy use across calendar years. Patients who intensified to triple therapy were more likely to use glucocorticoids (HR 1.91, 95%CI 1.41-2.60) compared to no glucocorticoids and more likely to use nonsteroidal anti-inflammatory drugs (NSAID, HR 1.48, 95%CI 1.10-1.99) compared to no NSAID use within 180 days of initial nbDMARD prescription. Among those who intensified treatment to triple therapy or bDMARD, significant associations for triple therapy use included older age, US region (highest odds for triple therapy use in the West, lowest odds for triple therapy use in the Northeast), glucocorticoid use, and lower number of outpatient visits within 180 days of initial nbDMARD prescription. CONCLUSION: Despite reports published during the study period suggesting equivalent efficacy of triple therapy and bDMARDs for RA, the use of triple therapy was infrequent and did not increase over time in this large nationwide study. This article is protected by copyright. All rights reserved.
OBJECTIVE: To explore the association between unexpected potentially disruptive life events in a patient or family member that may challenge an individual's ability to take medications as prescribed and the discontinuation of evidence-based medications for common, chronic conditions. Understanding the relationship between medication adherence and life stressors, especially those that can be identified using administrative data, may help identify patients at risk of non-adherence. DESIGN: Observational self-controlled case-crossover design. SETTING: Individuals in a nationally representative US commercial health insurance database. PARTICIPANTS: Adult individuals who initiated an oral hypoglycaemic, antihypertensive and/or statin and subsequently stopped the medication for >/=90 days. MAIN OUTCOME MEASURE: Potentially disruptive life events among patients and their family members measured in the 30 days just before the medication was discontinued ('hazard period') compared with the 30 days before this period ('control period'). These events included personal injury, hospitalisation, emergency room visits, changes in insurance coverage, acute stress or acute anxiety. RESULTS: Among the 326 519 patients meeting study criteria who discontinued their chronic disease medications, 88 896 (27.2%) experienced at least one potentially disruptive life event. Newly experiencing an injury (OR: 1.26, 95% CI 1.12 to 1.42), an emergency room visit (OR: 1.19, 95% CI 1.13 to 1.26) and acute stress (OR: 1.19, 95% CI 1.08 to 1.31) were associated with discontinuation. Life events among patients' family members did not appear to be associated with medication discontinuation or occurred less frequently just prior to discontinuation. CONCLUSIONS: Potentially disruptive life events among individuals identified using routinely collected claims data are associated with discontinuation of chronic disease medications. Awareness of these events may help providers or payers identify patients at risk of non-adherence to maximise patient outcomes.
Background Approximately half of patients with chronic cardiometabolic conditions are nonadherent with their prescribed medications. Interventions to improve adherence have been only modestly effective because they often address single barriers to adherence, intervene at single points in time, or are imprecisely targeted to patients who may not need adherence assistance. Objective To evaluate the effect of a multicomponent, behaviorally tailored pharmacist-based intervention to improve adherence to medications for diabetes, hypertension, and hyperlipidemia. Trial design The STIC2IT trial is a cluster-randomized pragmatic trial testing the impact of a pharmacist-led multicomponent intervention that uses behavioral interviewing, text messaging, mailed progress reports, and video visits. Targeted patients are those who are nonadherent to glucose-lowering, antihypertensive, or statin medications and who also have evidence of poor disease control. The intervention is tailored to patients' individual health barriers and their level of health activation.We cluster-randomized 14 practice sites of a large multispecialty group practice to receive either the pharmacist-based intervention or usual care. STIC2IT has enrolled 4,076 patients who will be followed up for 12 months after randomization. The trial's primary outcome is medication adherence, assessed using pharmacy claims data. Secondary outcomes are disease control and health care resource utilization. Conclusion This trial will determine whether a technologically enabled, behaviorally targeted pharmacist-based intervention results in improved adherence and disease control. If effective, this strategy could be a scalable method of offering tailored adherence support to those with the greatest clinical need.
Prescription opioid misuse is a major public health issue in the United States. Since the late 1990s, sales of prescription opioids have risen 4-fold, and the rates of admissions for substance use treatment and of death from opioid overdose have grown proportionately.1 In response, training programs about the appropriate prescribing of opioid therapy have been developed, prescription monitoring programs implemented, and access to naloxone facilitated to reduce deaths among people who overdose. In general, these strategies focus on detecting and preventing harm in those who are already dependent on or misusing opioids. Although the impact of many of these programs is uncertain, the opioid epidemic continues to grow.