Barriers to Esketamine Nasal Spray Treatment Among Adults With Treatment-Resistant Depression.

Background: Under a risk evaluation and mitigation strategy program, esketamine nasal spray CIII requires self administration at a certified treatment center. Our objective was to identify factors associated with esketamine initiation and continuation.Methods: A retrospective observational cohort study was conducted among US adults who met treatment-resistant depression (TRD) criteria. Cases (n = 966) initiated esketamine between October 11, 2019, and February 28, 2022, and were compared to controls (n = 39,219) with TRD but no esketamine use. Outcomes included initiation, induction (8 administrations within 45 days), and interruptions (30-day treatment gap). Comorbid psychiatric conditions were identified using International Classification of Diseases, Tenth Revision, Clinical Modification, codes.Results: Cases resided significantly closer to treatment centers (8.9 vs 20.3 miles). Compared to 0-9 miles, initiation rate decreased by 11.9%, 50.8%, 68.1%, 75.9%, and 92.8% for individuals residing 10-19, 20-29, 30-39, 40-49, and 50+ miles from a center. After adjustment, factors associated with increased likelihood of initiation were posttraumatic stress disorder, major depressive disorder with suicidal ideation, and male sex, while increasing distance, substance use disorder, Medicaid, Charlson Comorbidity Index (CCI), and older age were associated with lower likelihood. Factors associated with lower likelihood of completing induction were Medicaid, low socioeconomic status (SES), CCI, and Hispanic communities. Factors associated with increased likelihood of interruption were alcohol use disorder, distance, and minority communities, while generalized anxiety disorder and Medicaid were associated with lower likelihood.Conclusions: Travel distance, insurance, low SES, and minority communities are potential barriers to treatment. Alternative care models may be needed to ensure adequate access to care.J Clin Psychiatry 2024;85(2):23m15102.

Real-World Evidence of Aripiprazole Tablets with Sensor: Treatment Patterns and Impacts on Psychiatric Healthcare Resource Utilization.

Purpose: Maintaining adherence to antipsychotic (AP) medication is often challenging. Aripiprazole tablets with sensor (AS) contain an ingestible event marker and communicate with wearable patches and a smartphone app to provide objective medication ingestion data. This study evaluated real-world treatment patterns of AS usage and its impact on psychiatric healthcare resource utilization (HCRU). Patients and Methods: This retrospective, observational cohort study identified individuals who initiated AS between 1/1/2019 and 6/30/2020 with 3 months baseline and 6 months of follow-up data using a commercial medical and pharmacy claims database (Clarivate). Controls were propensity score-matched (4:1) to AS initiators based on age (±2 years), sex, diagnosis (major depressive disorder [MDD], schizophrenia, bipolar I disorder [BP-I], other), insurance, and baseline oral AP use (yes/no). Days of AP supply were evaluated using a general regression model. The frequency of psychiatric HCRU during follow-up was compared between groups using a zero-inflated regression model. Results: Most AS initiators were diagnosed with MDD (61.2%) and were women (61.2%); mean age was 37.7 years (standard deviation: 14.1). Most AS initiators (53.1%) continued treatment for >60 days (mean days of supply = 77). After adjusting for covariates, AS initiators had 41% more days of AP supply during follow-up compared with controls (P <0.0001) and significantly lower adjusted odds ratios (ORs) for psychiatric outpatient visits (adjusted OR = 0.80; P <0.05), emergency department visits (adjusted OR = 0.11; P <0.05), inpatient visits (adjusted OR = 0.42; P <0.05), and other medical services (adjusted OR = 0.25; P <0.05). Conclusion: Participants who implemented AS had significantly more days of AP supply and fewer psychiatric care visits. These preliminary results suggest AS usage can help build regular medication-taking habits and holds promise for reducing psychiatric HCRU. Additional studies with larger sample sizes are warranted to inform clinical practice and coverage decisions.

Association between Surgical Technical Skills and Clinical Outcomes: A Systematic Literature Review and Meta-Analysis.

Background: A systematic literature review and meta-analysis was conducted to assess the association between intraoperative surgical skill and clinical outcomes. Methods: Peer-reviewed, original research articles published through August 31, 2021 were identified from PubMed and Embase. From the 1,513 potential articles, seven met eligibility requirements, reporting on 151 surgeons and 17,932 procedures. All included retrospective assessment of operative videos. Associations between surgical skill and outcomes were assessed by pooling odds ratios (OR) using random-effects models with the inverse variance method. Eligible studies included pancreaticoduodenectomy, gastric bypass, laparoscopic gastrectomy, prostatectomy, colorectal, and hemicolectomy procedures. Results: Meta-analytic pooling identified significant associations between the highest vs. lowest quartile of surgical skill and reoperation (OR: 0.44; 95% confidence interval [CI]: 0.23, 0.83), hemorrhage (OR: 0.66; 95% CI, 0.65, 0.68), obstruction (OR: 0.33; 95% CI, 0.30, 0.35), and any medical complication (OR: 0.23, 95% CI, 0.19, 0.27). Nonsignificant inverse associations were noted between skill and readmission, emergency department visit, mortality, leak, infection, venous thromboembolism, and cardiac and pulmonary complications. Conclusions: Overall, surgeon technical skill appears to predict clinical outcomes. However, there are surprisingly few articles that evaluate this association. The authors recommend a thoughtful approach for the development of a comprehensive surgical quality infrastructure that could significantly reduce the challenges identified by this study.

Adherence to augmentation therapy for the treatment of major depressive disorder.

BACKGROUND: Inadequate response to antidepressant medication is common. Often, adjunctive pharmacotherapy or psychotherapy is recommended. OBJECTIVE: To measure adherence to adjunctive pharmacotherapy and psychotherapy among individuals with major depressive disorder (MDD). METHODS: Retrospective cohort study of individuals with MDD on antidepressant monotherapy who added adjunctive pharmacotherapy and/or psychotherapy. Medication adherence was measured by proportion of days covered (PDC) with optimal adherence defined as PDC≥0.80 and psychotherapy adherence defined by count of visits (optimal 8+ visits). Factors associated with optimal adherence were assessed by logistic regression. RESULTS: Among 218,192 individuals with adjunctive therapy, 185,349 added pharmacotherapy and 32,843 added psychotherapy. In the subsequent 12 months, 36.2% and 54.9% achieved optimal adherence to adjunctive pharmacotherapy and psychotherapy, respectively. Adherence to adjunctive pharmacotherapy was associated with adding psychotherapy, index antidepressant adherence, medical comorbidities, and MDD severity codes. Adherence to adjunctive psychotherapy was associated with adding another medication, previous psychiatry visit and psychiatric comorbidities. CONCLUSION: Adjunctive psychotherapy appears under-utilized and adherence to adjunctive therapy was low. Low adherence to adjunctive therapy reinforces challenges in managing MDD. That a second adjunctive therapy enhanced adherence to the initial adjunctive therapy indicates an opportunity to explore alternative adjunctive therapies.

Predicting Poor Outcomes Among Individuals Seeking Care for Major Depressive Disorder.

Objective: To develop and validate algorithms to identify individuals with major depressive disorder (MDD) at elevated risk for suicidality or for an acute care event. Methods: We conducted a retrospective cohort analysis among adults with MDD diagnosed between January 1, 2018 and February 28, 2019. Generalized estimating equation models were developed to predict emergency department (ED) visit, inpatient hospitalization, acute care visit (ED or inpatient), partial-day hospitalization, and suicidality in the year following diagnosis. Outcomes (per 1000 patients per month, PkPPM) were categorized as all-cause, psychiatric, or MDD-specific and combined into composite measures. Predictors included demographics, medical and pharmacy utilization, social determinants of health, and comorbid diagnoses as well as features indicative of clinically relevant changes in psychiatric health. Models were trained on data from 1.7M individuals, with sensitivity, positive predictive value, and area-under-the-curve (AUC) derived from a validation dataset of 0.7M. Results: Event rates were 124.0 PkPPM (any outcome), 21.2 PkPPM (psychiatric utilization), and 7.6 PkPPM (suicidality). Among the composite models, the model predicting suicidality had the highest AUC (0.916) followed by any psychiatric acute care visit (0.891) and all-cause ED visit (0.790). Event-specific models all achieved an AUC >0.87, with the highest AUC noted for partial-day hospitalization (AUC = 0.938). Select predictors of all three outcomes included younger age, Medicaid insurance, past psychiatric ED visits, past suicidal ideation, and alcohol use disorder diagnoses, among others. Conclusions: Analytical models derived from clinically-relevant features identify individuals with MDD at risk for poor outcomes and can be a practical tool for health care organizations to divert high-risk populations into comprehensive care models.

Measuring Response to Adjunctive Therapy Among Individuals with Major Depressive Disorder.

Background: Incomplete or inadequate response to first-line antidepressant therapy (ADT) for major depressive disorder (MDD) is common. Response to adjunctive therapy is less understood. Objective: To estimate response to adjunctive pharmacotherapy or psychotherapy among individuals with MDD on an antidepressant using the PHQ-9 questionnaire. Methods: This was a retrospective cohort analysis using medical and pharmacy insurance claims among individuals with MDD or ADT who initiated adjunctive pharmacotherapy, psychotherapy, or both (dual). Eligible individuals initiated adjunctive therapy between 7/1/2014-12/31/2018. Symptom severity was measured by PHQ-9 score in the 6-month baseline and 12-month follow up. Multivariate logistic regression identified factors associated with improved symptom severity. Results: Most (81.8%) of the 2389 participants initiated adjunctive pharmacotherapy, followed by psychotherapy (12.7%) and dual adjunctive (5.5%). Only 30.2% had both a baseline and follow-up PHQ-9 score. Among those with mild or more severe PHQ-9 baseline scores, 36.7% had the same or worse MDD severity during follow-up. Among those with moderate or more severe baseline scores, 28.1% had the same or worse MDD severity during follow-up. Conclusion: Most individuals with moderate-to-severe MDD did not receive a follow-up questionnaire, suggesting incomplete monitoring of treatment response. Among those with a PHQ-9 following initiation of adjunctive therapy, many continued to report impactful symptoms. Future studies should explore alternate treatment approaches and methods to support the utilization of the PHQ-9 for monitoring treatment response.

Mental Health Care Provider's Perspectives Toward Adopting a Novel Technology to Improve Medication Adherence.

Objective: To understand perspectives of mental health care providers regarding barriers and drivers of adopting a medication ingestible event monitoring (IEM) system in clinical practice. Methods: Between April and October 2019, a cross-sectional, online survey was conducted among 131 prescribing clinicians and 119 non-prescribing clinicians providing care to patients with major depressive disorder, bipolar disorder, and schizophrenia. Results: Most prescribing clinicians were physicians (79.4%) while most non-prescribing clinicians (52.9%) were licensed clinical social workers, followed by counselors (30.8%), clinical psychologists (13.4%), and case managers (2.5%). Most respondents (93.2%) reported that clinicians can influence adherence, that the IEM technology was in their patients' best interest (63.6%), and a willingness to beta test the technology (54.8%). Support was positively associated with prescribing clinicians (OR: 2.2; 95% CI: 1.1, 4.5), belief that antipsychotics reduce the health, social, or financial consequences of the condition (OR: 3.8; 95% CI: 1.3, 11.0), concern for patients' well-being without monitoring (OR: 3.3; 95% CI: 1.2, 8.7), and belief the technology will enhance clinical alliance (OR: 3.1; 95% CI: 1.5, 6.3) or improve patient engagement (OR: 3.0; 95% CI: 1.5, 6.2). Support was inversely related to concerns about appropriate follow-up actions (OR: 0.4; 95% CI: 0.2, 0.9) and responsibilities (OR: 0.3; 95% CI: 0.1, 0.8) when using the technology. Conclusions: Our results suggest that IEM sensor technology adoption will depend upon additional evidence that patients will actively engage in the use of the technology, will benefit from the technology through improved outcomes, and that the additional burden placed upon providers is minimal compared to the potential benefit.

Impact of the COVID-19 Pandemic on Healthcare Resource Utilization in Individuals with Major Depressive Disorder.

Objective: To estimate the impact COVID-19 pandemic on healthcare resource utilization (HCRU) among individuals with major depressive disorder (MDD). Method: A retrospective cohort study was conducted to compare HCRU in the twelve months prior to and six months following pandemic onset among 1,318,709 individuals with MDD and propensity-score matched controls. Outcomes were monthly rates of all-cause and MDD-specific outpatient, inpatient, and prescription medication HCRU. Piecewise random effects models were used to adjust for patient-level clustering, trends over time, and pre-pandemic factors. Results: In the first month following onset, outpatient HCRU declined with primary care visits down 25.1%. Following this initial decline, outpatient HCRU increased, exceeding pre-pandemic rates within three months. By April 2020, three quarters of all psychotherapy sessions were delivered by telehealth, followed by psychiatry (62.3%), and primary care visits (30.1%). The use of telehealth remained highest for psychotherapy and psychiatry (representing 67.6% and 54.2% of visits, respectively, in September 2020). All-cause partial-day hospitalizations declined 50.5% and remained depressed through July 2020 (down 18.3%). Beginning in the first month post-onset, prescription medication HCRU increased for all antidepressant and antipsychotic medication classes: serotonin modulators ( + 11.8%), bupropion ( + 10.4%), SSRIs ( + 9.0%), SNRIs ( + 8.6%), and atypical antipsychotics ( + 7.5%). Conclusions: Following pandemic onset, individuals with MDD realized an immediate, but short-lived, reduction in primary care HCRU. Telehealth use remained elevated through the first six months. The most significant and sustained reduction in HCRU was noted for partial-day hospitalizations and all-cause ED visits.

Factors associated with COVID-19 Infection among a national population of individuals with schizophrenia or schizoaffective disorder in the United States.

BACKGROUND: Individuals with schizophrenia are a vulnerable and under-served population who are also at risk for severe morbidity and mortality following COVID-19 infection. Our research was designed to identify factors that put individuals with schizophrenia at increased risk of COVID-19 infection. METHODS: This study was a retrospective cohort analysis of medical and pharmacy claims among 493,796 individuals residing in the United States with schizophrenia or schizoaffective disorder, between January 1, 2019 and June 30, 2020. A confirmed diagnosis of COVID-19 infection by September 30, 2020 was regressed on demographics, social determinants, comorbidity, and pre-pandemic (December 2019 - February 2020) healthcare utilization characteristics. RESULTS: A total of 35,249 (7.1%) individuals were diagnosed with COVID-19. Elevated odds of COVID-19 infection were associated with age, increasing consistently from 40-49 years (OR: 1.16) to 80+ years (OR:5.92), male sex (OR: 1.08), Medicaid (OR: 2.17) or Medicare (OR: 1.23) insurance, African American race (OR: 1.42), Hispanic ethnicity (OR: 1.23), and higher Charlson Comorbidity Index. Select psychiatric comorbidities (depressive disorder, adjustment disorder, bipolar disorder, anxiety, and sleep-wake disorder) were associated with elevated odds of infection, while alcohol use disorder and PTSD were associated with lower odds. A pre-pandemic psychiatry (OR:0.56) or community mental health center (OR:0.55) visit were associated with lower odds as was antipsychotic treatment with long-acting injectable antipsychotic (OR: 0.72) and oral antipsychotic (OR: 0.62). CONCLUSIONS: Among individuals with schizophrenia, risk of COVID-19 infection was substantially higher among those with fewer economic resources, with greater medical and psychiatric comorbidity burden, and those who resided in African American or Hispanic communities. In contrast, individuals actively engaged in psychiatric treatment had substantially lower likelihood of infection. These results provide insights for healthcare providers that can translate into improved identification of at-risk individuals and interventions to reduce the risk and consequences of COVID-19 infection.

Implications of Payment for Acute Myocardial Infarctions as a 90-Day Bundled Single Episode of Care: A Cost of Illness Analysis.

OBJECTIVES: Evaluate the cost of illness associated with the 90-day period following acute myocardial infarction (AMI) and the implication of care pathway (percutaneous coronary intervention [PCI] vs medical management [MM]), in order to assess the potential financial risk incurred by providers for AMI as an episode of care. PERSPECTIVE: Reimbursement payment systems for acute care episodes are shifting from 30-day to 90-day bundled payment models. Since follow-up care and readmissions beyond the early days/weeks post-AMI are common, financial risk may be transferred to providers. SETTING: AMI hospitalization Centers for Medicare & Medicaid Services (CMS) standard analytical files between 10/1/2015 and 9/30/2016 were reviewed. METHODS: Included patients were Medicare beneficiaries with a primary diagnosis of AMI subsequently treated with either PCI or MM. Payments were standardized to remove geographic variation and separated into reimbursements for services during the hospitalization and from discharge to 90 days post-discharge. Results were stratified by Medicare Severity Diagnosis Related Groups (MS-DRGs) individually and grouped between patients treated with MM and PCI. Risk-adjusted likelihood of utilization of post-acute nursing care and all-cause readmission was assessed by logistic regression. RESULTS: A total of 96,546 patients were included in the analysis. The highest total mean payment (US$32,714) was for MS-DRG 248 (PCI with non-drug-eluting stent with major complication or comorbidity). Total payments were similar between MM and PCI patients, but MM patients incurred the majority of costs in the post-acute period after discharge, with the converse true for PCI patients. MM without catheterization was associated with a twofold increase in risk of requiring post-acute nursing care and 90-day readmission versus PCI (odds ratio [95% confidence interval]: 2.01 [1.92-2.11] and 2.17 [2.08-2.27]). Smaller hospital size, diabetes, peripheral arterial disease, prior AMI, and multivessel disease were predictors of higher healthcare utilization. CONCLUSIONS: MS-DRGs associated with the lowest reimbursements (and presumably, lowest costs of inpatient care) incur the highest post-discharge expenditures. As the CMS Bundled Payment for Care Improvement and similar programs are implemented, there will be a need to account for heterogeneous post-discharge care costs. Video abstract (MP4 274659 KB).

Around 805,000 heart attacks occur annually in the US. With an average age over 65 years, many heart attack patients qualify for Medicare health insurance. Under Medicare, hospitals (or 'providers') receive reimbursements for the cost of care associated with 'acute care episodes' (e.g., heart attacks) as a 'bundled' payment. The bundled reimbursements are typically based on pre-defined prices, with hospitals paying the difference if actual costs exceed these. Reimbursements are typically given for care costs from the initial heart attack through to hospital discharge and care in the 30-day post-discharge period. However, recently introduced reimbursement models such as BPCI Advanced have moved to expand this to 90 days. Since follow-up care and additional cardiovascular readmissions are common beyond 30 days, extension of the reimbursement period to 90 days could increase financial risk to hospitals/providers if these additional costs are not included in reimbursements. To assess the potential impact of this, we investigated the cost of illness for heart attack and the implication of type of care: medical management (standard medication given after heart attack) vs. percutaneous coronary intervention (PCI; standard medication plus a non-surgical procedure to widen heart blood vessels). We found that 90-day costs after heart attack are substantial regardless of type of care. We found that post-discharge costs were generally high, but higher for medically managed patients than those receiving PCI. Our analysis also suggests Medicare disease classifications associated with lowest payments for heart attack (and presumably, lowest hospitalization costs) are associated with the highest post-discharge expenditures. Overall, our study suggests that new payment models should account for variable post-discharge care costs, and new therapies are needed to reduce additional events, readmissions, and associated costs in heart attack patients.

Prescriber Attitudes, Experiences, and Proclivities Toward Digital Medicine and How They Influence Adoption of Digital Medicine Platforms.

BACKGROUND: Psychiatric prescribers (prescribers) typically assess medication adherence by patient or caregiver self-report. Despite likely clinical benefit of a new digital medicine technology, the role of specific prescriber attitudes, behaviors, and experiences in the likelihood of adoption is unclear. OBJECTIVE: To identify prescriber characteristics that may affect adoption of the ingestible event marker (IEM) platform. DESIGN: A survey of prescribers treating seriously mentally ill patients was conducted. Factor analysis was performed on 11 items representing prescriber characteristics believed to be related to endorsement of the IEM platform. Four factors were extracted. Regression analysis was used to test the strength of the relationships between the factors and likelihood of adoption of the IEM platform. RESULTS: A total of 131 prescribers completed the survey. Most (84%) agreed that visits allow enough time to monitor adherence. Factor analysis revealed four underlying dimensions: 1) perspectives on the value of adherence; 2) concerns about measuring adherence; 3) views toward digital health technologies; and 4) views on payer role/reimbursement. Factors 1 and 3 were related to gender, the belief that computerization benefits prescribers, the presence of office support staff, and the belief that new digital medicine (DM) technology will be cost prohibitive. Willingness to adopt the IEM platform was related to gender (p < 0.05) and perspectives on the value of adherence (p < 0.05), with those scoring higher on that measure also being more likely to adopt. CONCLUSION: Psychiatric prescribers are concerned about medication adherence, perceive current monitoring tools to be problematic, and are open to using digital technologies to improve accuracy of adherence assessment. Relationships among prescriber characteristics, beliefs, and experiences should be considered when developing educational materials, particularly when the goal is to encourage adoption and use of the IEM platform.

Predicting Incident Treatment-Resistant Depression: A Model Designed for Health Systems of Care.

BACKGROUND: Major depressive disorder (MDD) is a prevalent and debilitating condition. While numerous treatment options are available, low treatment response and high remission rates remain common, leading to the concept of treatment-resistant depression (TRD): a classification applied to patients who fail multiple courses of therapy. A patient with TRD can only be identified after repeated, and often prolonged, therapeutic efforts. OBJECTIVE: To use data readily available to integrated delivery networks to identify characteristics predictive of TRD among patients initiating pharmacotherapy for MDD. METHODS: Decision Resources Group Real-World Data, an integrated medical/pharmacy claims and electronic health record dataset, was used to conduct a retrospective, longitudinal cohort study of patients with MDD who initiated antidepressant treatment between July 1, 2014, and December 31, 2015. Individuals were followed for 24 months to determine treatment resistance. Eligible individuals had integrated claims and electronic health record data available, completed at least 1 course of therapy of adequate dose and duration to achieve response, and had 30 months of continuous benefits eligibility (6 months before and 24 months after treatment initiation). Stepwise logistic regression and demographic, health history, health care utilization, medication, provider, and related characteristics were used to predict onset of TRD. RESULTS: 35,246 people met eligibility and 7,098 (20.1%) met TRD criteria after an average of 402 days. Significant predictors of TRD included patient age, diagnosis of insomnia and hypertension, psychiatric office visits, nurse telephonic encounters, anticonvulsant medication use, suicidality, physician specialty associated with index prescription, total prescription drug claims, unique antidepressants attempted, and duration of untreated illness (the lag between diagnosis and index prescription). The final model achieved an area under the curve (AUC) = 0.83. Structured patient-generated health data, specifically, the Patient Health Questionnaire-2 and the Patient Health Questionnaire-9 were only reported for 542 patients (1.5%). CONCLUSIONS: TRD transition occurs after a prolonged treatment period, suggesting clinical inertia. Using data routinely available to integrated delivery networks and accountable care organizations, it is feasible to identify patients likely to qualify as treatment resistant. Monitoring risk factors may allow health systems to identify patients at risk for TRD earlier, potentially improving outcomes. Early identification of this at-risk population can allow for targeted resources for earlier intervention, more aggressive follow-up, and alternative treatment options. Furthermore, this model can be used to estimate future demand for specialized care resources, such as those delivered by mood disorder clinics. DISCLOSURES: This project was sponsored by Janssen Scientific Affairs. Pesa, Chow, and Verbanac are employed by Janssen Scientific Affairs and report stock ownership in Johnson & Johnson. Liberman, Davis, Heverly-Fitt, and Ruetsch are employed by Health Analytics, which received funding from Janssen Scientific Affairs for work on this project. This study was presented as a poster at the U.S. Psych Congress; October 3-6, 2019; San Diego, CA.

Assessing the burden of illness of chronic hepatitis C and impact of direct-acting antiviral use on healthcare costs in Medicaid.

OBJECTIVES: To quantify the burden of illness of chronic hepatitis C virus (HCV) infection and estimate the impact of interferon-free direct-acting antiviral treatment on healthcare costs in Medicaid. STUDY DESIGN: Observational, retrospective analysis. METHODS: Medicaid claims data from 2012 for nonelderly adult enrollees with chronic HCV in 16 states were used to estimate the burden of HCV in Medicaid. Annual measures of health services utilization and cost for patients with HCV were compared with a control group of patients without HCV exactly matched on a robust set of individual characteristics and stratified according to liver disease severity, Medicaid eligibility group, and plan type. Subsequently, HCV burden-of-illness estimates were used in a separate analysis of Medicaid State Drug Utilization Data on interferon-free drug utilization and expenditures to estimate the annual and cumulative impact of these curative medications on national Medicaid costs from 2013 through 2022. RESULTS: Annual per-person Medicaid healthcare costs attributed to HCV infection were estimated to range from $10,561 for noncirrhotic disabled adults to $46,263 for nondisabled adults with end-stage liver disease. The costs were due mainly to inpatient hospitalizations and outpatient hospital visits, prescription drug utilization, outpatient physician's office/clinic visits, and laboratory tests. By 2014, the first full year following the approval of interferon-free treatment, an estimated 12,175 adults with HCV were cured in Medicaid nationwide, each avoiding an estimated $15,907 per year in healthcare costs associated with the disease. As more patients in Medicaid are treated and net savings continue to grow year after year-due to recurring avoidance of health services use and declining drug prices-total cumulative treatment costs since 2013 are expected to be fully offset by total cumulative healthcare expenditure reductions by the end of 2019. By 2022, the recurrent annual avoidance of healthcare costs will have delivered an estimated $12 billion in total cumulative savings to Medicaid, net of DAA drug expenditures. CONCLUSIONS: The introduction of interferon-free HCV treatments enables the avoidance of significant healthcare costs previously associated with treating the disease year after year, producing annual cumulative Medicaid savings beginning in 2019. A main finding from this study is that the cost of a complete DAA treatment course, at 2018 estimated net prices, can be expected to be fully offset by healthcare cost savings after only 16 months, on average, on a per-person basis. Given the tremendous value provided by these curative drugs, Medicaid policies aimed toward restricting access to these treatments based on disease severity or other requirements would be shortsighted.

Effect of an educational outreach program on prescribing potential drug-drug interactions.

BACKGROUND: The topic of improving prescribing practices is a major focus of many national initiatives, not only to enhance the quality of health care but also to reduce medical care costs. Educational outreach (also known as academic detailing) is a type of postgraduate education where trained clinical consultants meet face-to-face with prescribers to provide one-on-one information. Ideally, such visits promote evidence-based knowledge, create trusting relationships, and induce practice change, particularly with regard to prescribing potentially interacting medications. OBJECTIVE: To evaluate the effect of an educational outreach program delivered by clinical pharmacists on reducing the rate of prescribing potential drug-drug interactions (DDIs). METHODS: The intervention was a prescriber-directed educational outreach program focused on 25 clinically important DDIs. The effect of the educational outreach was evaluated using a retrospective pre-post study design with a control group was conducted. A total of 19,606 prescribers were educated on the DDIs of interest. A control group of 19,606 prescribers, matched on prescribing volume and who did not receive the educational session were selected. Multivariate regression models were used to assess the impact of the educational program on the rate of prescribing potential DDIs. RESULTS: The 2 groups were significantly different with respect to age, profession, specialty, and geographic region. At baseline, mean DDI rates per 100 drug prescriptions were 0.8 and 0.7 for prescribers who received the educational session and those who did not, respectively. Following delivery of the educational outreach program, mean potential DDI rates increased to 1.46 and 1.53 per 100 precipitant drug prescriptions, an increase of 13.9% and 9.15% for the intervention and control groups, respectively. CONCLUSION: The current study was not able to demonstrate a significant beneficial effect of the educational outreach program on reducing the rate of prescribing potential DDIs.

Adherence to varenicline and associated smoking cessation in a community-based patient setting.

BACKGROUND: Varenicline, a selective α4ß2 nicotinic acetylcholine receptor partial agonist, is a pharmacotherapy indicated for smoking cessation treatment. To our knowledge, no studies have described varenicline treatment adherence and efficacy from real-world treatment patterns in a U.S. primary care setting. OBJECTIVE: To estimate adherence to varenicline prescription orders and subsequent quit rates among smokers in a primary care setting. METHODS: In this retrospective cohort study, eligible patients were enrolled with Geisinger Health Plan, had an initial varenicline prescription written by a Geisinger provider between January 1, 2006, and December 31, 2009, and had a follow-up clinic visit within the subsequent 12 months. Adherence was derived from linking electronic prescriptions with adjudicated pharmacy claims. Smoking status was collected at each health care encounter. RESULTS: Of the 1,477 eligible patients, 823 (55.7%) were primary nonadherent, having failed to initiate on the prescribed varenicline therapy. Of the remaining 654 patients, 359 (54.9%) were adherent, having completed a full 12-week course of therapy, and 295 (45.1%) were partially adherent, having initiated but not completed the full course of therapy. A total of 521 patients (35.3%) ceased smoking during the 12-month follow-up period: 182 (50.7%) of the adherent cohort, 82 (27.8%) of the partially adherent population, and 257 (31.2%) of the nonadherent cohort. No significant difference was found in quit rates between the partially adherent and nonadherent patient cohorts (adjusted HR 0.88 [95% CI=0.69-1.13]). However, patients adherent to the varenicline regimen were almost twice as likely to succeed in quitting smoking compared with completely nonadherent patients (HR 1.93 [95% CI=1.59-2.33]). CONCLUSION: Smoking cessation occurred more often among individuals adherent to varenicline therapy; however, medication nonadherence was common. After prescribing varenicline, clinicians and payers could consider active patient follow-up to maximize adherence and optimize treatment outcomes.

Warnings without guidance: patient responses to an FDA warning about ezetimibe.

BACKGROUND: In January 2008, the Food and Drug Administration (FDA) communicated concerns about the efficacy of ezetimibe, but did not provide clear clinical guidance, and substantial media attention ensued. We investigated the proportion of patients who discontinued therapy and switched to a clinically appropriate alternative after the FDA communication. METHODS: Using claims data from a national pharmacy benefits manager, we created a rolling cohort of new users of ezetimibe between January 2006 and August 2008 and created a supply diary for each patient in the year after cohort entry. A patient was identified as nonpersistent if a gap of 90 days was seen in the diary. Using segmented linear regression, we compared rates of nonpersistence before and after the FDA communication and assessed patient-level characteristics associated with discontinuation. Among nonpersistent patients, we determined whether a patient made a clinically appropriate switch in the subsequent 90 days by adding a new cholesterol-lowering medication or by increasing the dose of an existing one. We used a weighted t test to compare the rates of appropriate switching before and after the communication. RESULTS: Among 867,027 new ezetimibe users, 407,006 (46.9%) were nonpersistent in the first year. After the FDA communication, the monthly level of ezetimibe nonpersistence increased by 5.7 percentage points (P<0.0001). Younger patients, those who lived in low-income zip codes, and female patients were less likely to discontinue therapy (P<0.0001 for all). Among nonpersistent patients, rates of clinically appropriate switching increased from 10.8% before to 16.5% after the FDA warning (P = 0.004). CONCLUSIONS: A substantial increase in ezetimibe nonpersistence rates was seen after an FDA communication regarding its efficacy and following associated media attention, and a small proportion of patients made a clinically appropriate switch after discontinuation. Further consideration is needed to deliver messages that promote appropriate use of chronic therapy rather than simply reduce use.

Targeting cardiovascular medication adherence interventions.

OBJECTIVES: To determine whether adherence interventions should be administered to all medication takers or targeted to nonadherers. DATA SOURCES AND STUDY SELECTION: Systematic search (Medline and Embase, 1966-2009) of randomized controlled trials of interventions to improve adherence to medications for preventing or treating cardiovascular disease or diabetes. DATA EXTRACTION: Articles were classified as (1) broad interventions (targeted all medication takers), (2) focused interventions (targeted nonadherers), or (3) dynamic interventions (administered to all medication takers; real-time adherence information targets nonadherers as intervention proceeds). Cohen's d effect sizes were calculated. DATA SYNTHESIS: We identified 7,190 articles; 59 met inclusion criteria. Broad interventions were less likely (18%) to show medium or large effects compared with focused (25%) or dynamic (32%) interventions. Of the 33 dynamic interventions, 6 used externally generated adherence data to target nonadherers. Those with externally generated data were less likely to have a medium or large effect (20% vs. 34.8% self-generated data). CONCLUSION: Adherence interventions targeting nonadherers are heterogeneous but may have advantages over broad interventions. Dynamic interventions show promise and require further study.

Reducing long-term cost by transforming primary care: evidence from Geisinger's medical home model.

OBJECTIVES: To estimate cost savings associated with ProvenHealth Navigator (PHN), which is an advanced model of patient-centered medical homes (PCMHs) developed by Geisinger Health System, and determine whether those savings increase over time. STUDY DESIGN: A retrospective claims data analysis of 43 primary care clinics that were converted into PHN sites between 2006 and 2010. The study population included Geisinger Health Plan's Medicare Advantage plan enrollees who were 65 years or older treated in these clinics (26,303 unique members). METHODS: Two patient-level multivariate regression models (with and without interaction effects between prescription drug coverage and PHN exposure) with member fixed effects were used to estimate the effect of members' exposure to PHN on per-member per-month total cost, controlling for member risk, seasonality, yearly trend, and a set of baseline clinic characteristics. RESULTS: In both models, a longer period of PHN exposure was significantly associated with a lower total cost. The total cumulative cost savings over the study period was 7.1% (95% confi dence interval [CI] 2.6-11.6) using the model with the prescription drug coverage interaction effects and 4.3% (95% CI 0.4-8.3) using the model without the interaction effects. Corresponding return on investment was 1.7 (95% CI 0.3-3.0) and 1.0 (95% Cl -0.1 to 2.0), respectively. CONCLUSIONS: Our finding suggests that PCMHs can lead to significant and sustainable cost savings over time.

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 $677 over a 6-month period compared with $116 and $118 for patients initiated on metformin or a sulfonylurea, respectively, a cost difference of approximately $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.