Relative Cost Differences of Initial Treatment Strategies for Newly Diagnosed Opioid Use Disorder: A Cohort Study.

BACKGROUND: Relative costs of care among treatment options for opioid use disorder (OUD) are unknown. METHODS: We identified a cohort of 40,885 individuals with a new diagnosis of OUD in a large national de-identified claims database covering commercially insured and Medicare Advantage enrollees. We assigned individuals to 1 of 6 mutually exclusive initial treatment pathways: (1) Inpatient Detox/Rehabilitation Treatment Center; (2) Behavioral Health Intensive, intensive outpatient or Partial Hospitalization Services; (3) Methadone or Buprenorphine; (4) Naltrexone; (5) Behavioral Health Outpatient Services, or; (6) No Treatment. We assessed total costs of care in the initial 90 day treatment period for each strategy using a differences in differences approach controlling for baseline costs. RESULTS: Within 90 days of diagnosis, 94.8% of individuals received treatment, with the initial treatments being: 15.8% for Inpatient Detox/Rehabilitation Treatment Center, 4.8% for Behavioral Health Intensive, Intensive Outpatient or Partial Hospitalization Services, 12.5% for buprenorphine/methadone, 2.4% for naltrexone, and 59.3% for Behavioral Health Outpatient Services. Average unadjusted costs increased from $3250 per member per month (SD $7846) at baseline to $5047 per member per month (SD $11,856) in the 90 day follow-up period. Compared with no treatment, initial 90 day costs were lower for buprenorphine/methadone [Adjusted Difference in Differences Cost Ratio (ADIDCR) 0.65; 95% confidence interval (CI), 0.52-0.80], naltrexone (ADIDCR 0.53; 95% CI, 0.42-0.67), and behavioral health outpatient (ADIDCR 0.54; 95% CI, 0.44-0.66). Costs were higher for inpatient detox (ADIDCR 2.30; 95% CI, 1.88-2.83). CONCLUSION: Improving health system capacity and insurance coverage and incentives for outpatient management of OUD may reduce health care costs.

Predicting Onset of Dementia Using Clinical Notes and Machine Learning: Case-Control Study.

BACKGROUND: Clinical trials need efficient tools to assist in recruiting patients at risk of Alzheimer disease and related dementias (ADRD). Early detection can also assist patients with financial planning for long-term care. Clinical notes are an important, underutilized source of information in machine learning models because of the cost of collection and complexity of analysis. OBJECTIVE: This study aimed to investigate the use of deidentified clinical notes from multiple hospital systems collected over 10 years to augment retrospective machine learning models of the risk of developing ADRD. METHODS: We used 2 years of data to predict the future outcome of ADRD onset. Clinical notes are provided in a deidentified format with specific terms and sentiments. Terms in clinical notes are embedded into a 100-dimensional vector space to identify clusters of related terms and abbreviations that differ across hospital systems and individual clinicians. RESULTS: When using clinical notes, the area under the curve (AUC) improved from 0.85 to 0.94, and positive predictive value (PPV) increased from 45.07% (25,245/56,018) to 68.32% (14,153/20,717) in the model at disease onset. Models with clinical notes improved in both AUC and PPV in years 3-6 when notes' volume was largest; results are mixed in years 7 and 8 with the smallest cohorts. CONCLUSIONS: Although clinical notes helped in the short term, the presence of ADRD symptomatic terms years earlier than onset adds evidence to other studies that clinicians undercode diagnoses of ADRD. De-identified clinical notes increase the accuracy of risk models. Clinical notes collected across multiple hospital systems via natural language processing can be merged using postprocessing techniques to aid model accuracy.

Assessment of Potentially Inappropriate Prescribing of Opioid Analgesics Requiring Prior Opioid Tolerance.

Importance: Opioid-tolerant only (OTO) medications, such as transmucosal immediate-release fentanyl products and certain extended-release opioid analgesics, require prior opioid tolerance for safe use, as patients without tolerance may be at increased risk of overdose. Studies using insurance claims have found that many patients initiating these medications do not appear to be opioid tolerant. Objectives: To measure prevalence of opioid tolerance in patients initiating OTO medications and to determine whether linked electronic health record (EHR) data contribute evidence of opioid tolerance not found in insurance claims data. Design, Setting, and Participants: This retrospective cohort study used a national database of deidentified longitudinal health information, including medical and pharmacy claims, insurance enrollment, and EHR data, from January 1, 2007, to December 31, 2016. Data included 131 756 US residents with at least 183 days of continuous enrollment in commercial or Medicare Advantage insurance (including medical and pharmacy benefits) who had received an OTO medication and who had no inpatient stays in the 30 days prior to starting an OTO medication; of these, 20 044 individuals had linked EHR data within the prior 183 days. Data were analyzed from July 1, 2017, to August 31, 2018. Exposures: Initiating an OTO medication. Main Outcomes and Measures: Prior opioid tolerance demonstrated through pharmacy fills or EHR data on prescriptions written. Results: Among 153 385 OTO use episodes identified, 89 029 (58.0%) occurred among women, 62 900 (41.0%) occurred among patients with Medicare Advantage insurance, 39 394 (25.7%) occurred in the Midwest, 17 366 (11.3%) occurred in the Northeast, 73 316 (47.8%) occurred in the South, and 23 309 (15.2%) occurred in the West. Less than half of use episodes (73 117 episodes [47.7%]) involved patients with evidence in claims data of opioid tolerance prior to initiating therapy with an OTO medication, including 31 392 of 101 676 episodes (30.9%) involving transdermal fentanyl, 1561 of 2440 episodes (64.0%) involving transmucosal fentanyl, 36 596 of 43 559 episodes (84.0%) involving extended-release oxycodone, and 3568 of 5710 episodes (62.5%) involving extended-release hydromorphone. Among 20 044 OTO use episodes with linked EHR and claims data, less than 1% of OTO episodes identified in claims had evidence of opioid tolerance in structured EHR data that was not present in claims data (108 episodes [0.5%]). After limiting the sample to OTO episodes identified in claims with a matching OTO prescription within 14 days in the structured EHR data, only 40 of 939 episodes (4.0%) occurred among patients with evidence of tolerance that was not present in claims data. Conclusions and Relevance: This cohort study found that most patients initiating OTO medications did not have evidence of prior opioid tolerance, suggesting they were at increased risk of opioid-related harms, including fatal overdose. Data from EHRs did not contribute substantial additional evidence of opioid tolerance beyond the data found in prescription claims. Future research is needed to understand the clinical rationale behind these observed prescribing patterns and to quantify the risk of harm to patients associated with potentially inappropriate prescribing.

Comparative Effectiveness of Different Treatment Pathways for Opioid Use Disorder.

Importance: Although clinical trials demonstrate the superior effectiveness of medication for opioid use disorder (MOUD) compared with nonpharmacologic treatment, national data on the comparative effectiveness of real-world treatment pathways are lacking. Objective: To examine associations between opioid use disorder (OUD) treatment pathways and overdose and opioid-related acute care use as proxies for OUD recurrence. Design, Setting, and Participants: This retrospective comparative effectiveness research study assessed deidentified claims from the OptumLabs Data Warehouse from individuals aged 16 years or older with OUD and commercial or Medicare Advantage coverage. Opioid use disorder was identified based on 1 or more inpatient or 2 or more outpatient claims for OUD diagnosis codes within 3 months of each other; 1 or more claims for OUD plus diagnosis codes for opioid-related overdose, injection-related infection, or inpatient detoxification or residential services; or MOUD claims between January 1, 2015, and September 30, 2017. Data analysis was performed from April 1, 2018, to June 30, 2019. Exposures: One of 6 mutually exclusive treatment pathways, including (1) no treatment, (2) inpatient detoxification or residential services, (3) intensive behavioral health, (4) buprenorphine or methadone, (5) naltrexone, and (6) nonintensive behavioral health. Main Outcomes and Measures: Opioid-related overdose or serious acute care use during 3 and 12 months after initial treatment. Results: A total of 40 885 individuals with OUD (mean [SD] age, 47.73 [17.25] years; 22 172 [54.2%] male; 30 332 [74.2%] white) were identified. For OUD treatment, 24 258 (59.3%) received nonintensive behavioral health, 6455 (15.8%) received inpatient detoxification or residential services, 5123 (12.5%) received MOUD treatment with buprenorphine or methadone, 1970 (4.8%) received intensive behavioral health, and 963 (2.4%) received MOUD treatment with naltrexone. During 3-month follow-up, 707 participants (1.7%) experienced an overdose, and 773 (1.9%) had serious opioid-related acute care use. Only treatment with buprenorphine or methadone was associated with a reduced risk of overdose during 3-month (adjusted hazard ratio [AHR], 0.24; 95% CI, 0.14-0.41) and 12-month (AHR, 0.41; 95% CI, 0.31-0.55) follow-up. Treatment with buprenorphine or methadone was also associated with reduction in serious opioid-related acute care use during 3-month (AHR, 0.68; 95% CI, 0.47-0.99) and 12-month (AHR, 0.74; 95% CI, 0.58-0.95) follow-up. Conclusions and Relevance: Treatment with buprenorphine or methadone was associated with reductions in overdose and serious opioid-related acute care use compared with other treatments. Strategies to address the underuse of MOUD are needed.

Machine learning models to predict onset of dementia: A label learning approach.

INTRODUCTION: The study objective was to build a machine learning model to predict incident mild cognitive impairment, Alzheimer's Disease, and related dementias from structured data using administrative and electronic health record sources. METHODS: A cohort of patients (n = 121,907) and controls (n = 5,307,045) was created for modeling using data within 2 years of patient's incident diagnosis date. Additional cohorts 3-8 years removed from index data are used for prediction. Training cohorts were matched on age, gender, index year, and utilization, and fit with a gradient boosting machine, lightGBM. RESULTS: Incident 2-year model quality on a held-out test set had a sensitivity of 47% and area-under-the-curve of 87%. In the 3-year model, the learned labels achieved 24% (71%), which dropped to 15% (72%) in year 8. DISCUSSION: The ability of the model to discriminate incident cases of dementia implies that it can be a worthwhile tool to screen patients for trial recruitment and patient management.

Observational retrospective study of the association of initial healthcare provider for new-onset low back pain with early and long-term opioid use.

OBJECTIVE: This study examined the association of initial provider treatment with early and long-term opioid use in a national sample of patients with new-onset low back pain (LBP). DESIGN: A retrospective cohort study of patients with new-onset LBP from 2008 to 2013. SETTING: The study evaluated outpatient and inpatient claims from patient visits, pharmacy claims and inpatient and outpatient procedures with initial providers seen for new-onset LBP. PARTICIPANTS: 216 504 individuals aged 18 years or older across the USA who were diagnosed with new-onset LBP and were opioid-naïve were included. Participants had commercial or Medicare Advantage insurance. EXPOSURES: The primary independent variable is type of initial healthcare provider including physicians and conservative therapists (physical therapists, chiropractors, acupuncturists). MAIN OUTCOME MEASURES: Short-term opioid use (within 30 days of the index visit) following new LBP visit and long-term opioid use (starting within 60 days of the index date and either 120 or more days' supply of opioids over 12 months, or 90 days or more supply of opioids and 10 or more opioid prescriptions over 12 months). RESULTS: Short-term use of opioids was 22%. Patients who received initial treatment from chiropractors or physical therapists had decreased odds of short-term and long-term opioid use compared with those who received initial treatment from primary care physicians (PCPs) (adjusted OR (AOR) (95% CI) 0.10 (0.09 to 0.10) and 0.15 (0.13 to 0.17), respectively). Compared with PCP visits, initial chiropractic and physical therapy also were associated with decreased odds of long-term opioid use in a propensity score matched sample (AOR (95% CI) 0.21 (0.16 to 0.27) and 0.29 (0.12 to 0.69), respectively). CONCLUSIONS: Initial visits to chiropractors or physical therapists is associated with substantially decreased early and long-term use of opioids. Incentivising use of conservative therapists may be a strategy to reduce risks of early and long-term opioid use.

Identifying incident dementia by applying machine learning to a very large administrative claims dataset.

Alzheimer's disease and related dementias (ADRD) are highly prevalent conditions, and prior efforts to develop predictive models have relied on demographic and clinical risk factors using traditional logistical regression methods. We hypothesized that machine-learning algorithms using administrative claims data may represent a novel approach to predicting ADRD. Using a national de-identified dataset of more than 125 million patients including over 10,000 clinical, pharmaceutical, and demographic variables, we developed a cohort to train a machine learning model to predict ADRD 4-5 years in advance. The Lasso algorithm selected a 50-variable model with an area under the curve (AUC) of 0.693. Top diagnosis codes in the model were memory loss (780.93), Parkinson's disease (332.0), mild cognitive impairment (331.83) and bipolar disorder (296.80), and top pharmacy codes were psychoactive drugs. Machine learning algorithms can rapidly develop predictive models for ADRD with massive datasets, without requiring hypothesis-driven feature engineering.

Clinical Effectiveness of Antifibrotic Medications for Idiopathic Pulmonary Fibrosis.

Rationale: Since their approval, there has been no real-world or randomized trial evidence evaluating the effect of the antifibrotic medications pirfenidone and nintedanib on clinically important outcomes such as mortality and hospitalizations. Objectives: To evaluate the clinical effectiveness of the antifibrotic medications pirfenidone and nintedanib in patients with idiopathic pulmonary fibrosis. Methods: Using a large U.S. insurance database, we identified 8,098 patients with idiopathic pulmonary fibrosis between October 1, 2014 and March 1, 2018. A one-to-one propensity score-matched cohort was created to compare patients treated with antifibrotic medications (n = 1,255) with those not on treatment (n = 1,255). The primary outcome was all-cause mortality. The secondary outcome was acute hospitalizations. Subgroup analyses were performed to evaluate mortality differences by drug. Measurements and Main Results: The use of antifibrotic medications was associated with a decreased risk of all-cause mortality (hazard ratio [HR], 0.77; 95% confidence interval [CI], 0.62-0.98; P value = 0.034). However, this association was present only through the first 2 years of treatment. There was also a decrease in acute hospitalizations in the treated cohort (HR, 0.70; 95% CI, 0.61-0.80; P value <0.001). There was no significant difference in all-cause mortality between patients receiving pirfenidone and those on nintedanib (HR, 1.14; 95% CI, 0.79-1.65; P = 0.471). Conclusions: Among patients with idiopathic pulmonary fibrosis, antifibrotic agents may be associated with a lower risk of all-cause mortality and hospitalization compared with no treatment. Future research should test the hypothesis that these treatments reduce early, but not long-term, mortality as demonstrated in our study.

Implementation Research to Address the United States Health Disadvantage: Report of a National Heart, Lung, and Blood Institute Workshop.

Four decades ago, U.S. life expectancy was within the same range as other high-income peer countries. However, during the past decades, the United States has fared worse in many key health domains resulting in shorter life expectancy and poorer health-a health disadvantage. The National Heart, Lung, and Blood Institute convened a panel of national and international health experts and stakeholders for a Think Tank meeting to explore the U.S. health disadvantage and to seek specific recommendations for implementation research opportunities for heart, lung, blood, and sleep disorders. Recommendations for National Heart, Lung, and Blood Institute consideration were made in several areas including understanding the drivers of the disadvantage, identifying potential solutions, creating strategic partnerships with common goals, and finally enhancing and fostering a research workforce for implementation research. Key recommendations included exploring why the United States is doing better for health indicators in a few areas compared with peer countries; targeting populations across the entire socioeconomic spectrum with interventions at all levels in order to prevent missing a substantial proportion of the disadvantage; assuring partnership have high-level goals that can create systemic change through collective impact; and finally, increasing opportunities for implementation research training to meet the current needs. Connecting with the research community at large and building on ongoing research efforts will be an important strategy. Broad partnerships and collaboration across the social, political, economic, and private sectors and all civil society will be critical-not only for implementation research but also for implementing the findings to have the desired population impact. Developing the relevant knowledge to tackle the U.S. health disadvantage is the necessary first step to improve U.S. health outcomes.

Rethinking Medicaid Coverage and Payment Policy to Promote High Value Care: The Case of Long-Acting Reversible Contraception.

CONTEXT: Long-acting reversible contraception (LARC) is the most effective reversible method to prevent unplanned pregnancies. Variability in state-level policies and the high cost of LARC could create substantial inconsistencies in Medicaid coverage, despite federal guidance aimed at enhancing broad access. This study surveyed state Medicaid payment policies and outreach activities related to LARC to explore the scope of services covered. METHODS: Using publicly available information, we performed a content analysis of state Medicaid family planning and LARC payment policies. Purposeful sampling led to a selection of nine states with diverse geographic locations, political climates, Medicaid expansion status, and the number of women covered by Medicaid. RESULTS: All nine states' Medicaid programs covered some aspects of LARC. However, only a single state's payment structure incorporated all core aspects of high-quality LARC service delivery, including counseling, device, insertion, removal, and follow-up care. Most states did not explicitly address counseling, device removal, or follow-up care. Some states had strategies to enhance access, including policies to increase device reimbursement, stocking and delivery programs to remove cost barriers, and covering devices and insertion after an abortion. CONCLUSIONS: Although Medicaid policy encourages LARC methods, state payment policies frequently fail to address key aspects of care, including counseling, follow-up care, and removal, resulting in highly variable state-level practices. Although some states include payment policy innovations to support LARC access, significant opportunities remain.

Weight management and physical activity throughout the cancer care continuum.

Mounting evidence suggests that weight management and physical activity (PA) improve overall health and well being, and reduce the risk of morbidity and mortality among cancer survivors. Although many opportunities exist to include weight management and PA in routine cancer care, several barriers remain. This review summarizes key topics addressed in a recent National Academies of Science, Engineering, and Medicine workshop entitled, "Incorporating Weight Management and Physical Activity Throughout the Cancer Care Continuum." Discussions related to body weight and PA among cancer survivors included: 1) current knowledge and gaps related to health outcomes; 2) effective intervention approaches; 3) addressing the needs of diverse populations of cancer survivors; 4) opportunities and challenges of workforce, care coordination, and technologies for program implementation; 5) models of care; and 6) program coverage. While more discoveries are still needed for the provision of optimal weight-management and PA programs for cancer survivors, obesity and inactivity currently jeopardize their overall health and quality of life. Actionable future directions are presented for research; practice and policy changes required to assure the availability of effective, affordable, and feasible weight management; and PA services for all cancer survivors as a part of their routine cancer care. CA Cancer J Clin 2018;68:64-89. © 2017 American Cancer Society.

Population Health Measurement at Centers for Medicare & Medicaid Services: Bridging the Gap Between Public Health and Clinical Quality.

As Medicare and Medicaid increasingly shift to alternative payment models focused on population-based payments, there is an urgent need to develop measures of population health that can drive health improvement. In response, an assessment and design project established a framework for developing population health measures from a payer perspective, conducted environmental scans of existing measures and available data infrastructure, and conducted a gap analysis informing measure development and infrastructure needs. The work, summarized here, makes recommendations for creating a set of core measures, demonstrates some of the key challenges in applying a traditional quality measure development framework to population health, and complements recent efforts by the National Academy of Medicine and others with a focus on a payer perspective.

Estimating Longitudinal Risks and Benefits From Cardiovascular Preventive Therapies Among Medicare Patients: The Million Hearts Longitudinal ASCVD Risk Assessment Tool: A Special Report From the American Heart Association and American College of Cardiology.

The Million Hearts Initiative has a goal of preventing 1 million heart attacks and strokes-the leading causes of mortality-through several public health and healthcare strategies by 2017. The American Heart Association and American College of Cardiology support the program. The Cardiovascular Risk Reduction Model was developed by Million Hearts and the Center for Medicare & Medicaid Services as a strategy to assess a value-based payment approach toward reduction in 10-year predicted risk of atherosclerotic cardiovascular disease (ASCVD) by implementing cardiovascular preventive strategies to manage the "ABCS" (aspirin therapy in appropriate patients, blood pressure control, cholesterol management, and smoking cessation). The purpose of this special report is to describe the development and intended use of the Million Hearts Longitudinal ASCVD Risk Assessment Tool. The Million Hearts Tool reinforces and builds on the "2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk" by allowing clinicians to estimate baseline and updated 10-year ASCVD risk estimates for primary prevention patients adhering to the appropriate ABCS over time, alone or in combination. The tool provides updated risk estimates based on evidence from high-quality systematic reviews and meta-analyses of the ABCS therapies. This novel approach to personalized estimation of benefits from risk-reducing therapies in primary prevention may help target therapies to those in whom they will provide the greatest benefit, and serves as the basis for a Center for Medicare & Medicaid Services program designed to evaluate the Million Hearts Cardiovascular Risk Reduction Model.

Estimating Longitudinal Risks and Benefits From Cardiovascular Preventive Therapies Among Medicare Patients: The Million Hearts Longitudinal ASCVD Risk Assessment Tool: A Special Report From the American Heart Association and American College of Cardiology.

The Million Hearts Initiative has a goal of preventing 1 million heart attacks and strokes-the leading causes of mortality-through several public health and healthcare strategies by 2017. The American Heart Association and American College of Cardiology support the program. The Cardiovascular Risk Reduction Model was developed by Million Hearts and the Center for Medicare & Medicaid Services as a strategy to assess a value-based payment approach toward reduction in 10-year predicted risk of atherosclerotic cardiovascular disease (ASCVD) by implementing cardiovascular preventive strategies to manage the "ABCS" (aspirin therapy in appropriate patients, blood pressure control, cholesterol management, and smoking cessation). The purpose of this special report is to describe the development and intended use of the Million Hearts Longitudinal ASCVD Risk Assessment Tool. The Million Hearts Tool reinforces and builds on the "2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk" by allowing clinicians to estimate baseline and updated 10-year ASCVD risk estimates for primary prevention patients adhering to the appropriate ABCS over time, alone or in combination. The tool provides updated risk estimates based on evidence from high-quality systematic reviews and meta-analyses of the ABCS therapies. This novel approach to personalized estimation of benefits from risk-reducing therapies in primary prevention may help target therapies to those in whom they will provide the greatest benefit, and serves as the basis for a Center for Medicare & Medicaid Services program designed to evaluate the Million Hearts Cardiovascular Risk Reduction Model.

Patterns of care for clinically distinct segments of high cost Medicare beneficiaries.

BACKGROUND: Efforts to improve the efficiency of care for the Medicare population commonly target high cost beneficiaries. We describe and evaluate a novel management approach, population segmentation, for identifying and managing high cost beneficiaries. METHODS: A retrospective cross-sectional analysis of 6,919,439 Medicare fee-for-service beneficiaries in 2012. We defined and characterized eight distinct clinical population segments, and assessed heterogeneity in managing practitioners. RESULTS: The eight segments comprised 9.8% of the population and 47.6% of annual Medicare payments. The eight segments included 61% and 69% of the population in the top decile and top 5% of annual Medicare payments. The positive-predictive values within each segment for meeting thresholds of Medicare payments ranged from 72% to 100%, 30% to 83%, and 14% to 56% for the upper quartile, upper decile, and upper 5% of Medicare payments respectively. Sensitivity and positive-predictive values were substantially improved over predictive algorithms based on historical utilization patterns and comorbidities. The mean [95% confidence interval] number of unique practitioners and practices delivering E&M services ranged from 1.82 [1.79-1.84] to 6.94 [6.91-6.98] and 1.48 [1.46-1.50] to 4.98 [4.95-5.00] respectively. The percentage of cognitive services delivered by primary care practitioners ranged from 23.8% to 67.9% across segments, with significant variability among specialty types. CONCLUSIONS: Most high cost Medicare beneficiaries can be identified based on a single clinical reason and are managed by different practitioners. IMPLICATIONS: Population segmentation holds potential to improve efficiency in the Medicare population by identifying opportunities to improve care for specific populations and managing clinicians, and forecasting and evaluating the impact of specific interventions.

Drugs for Primary Prevention of Atherosclerotic Cardiovascular Disease: An Overview of Systematic Reviews.

IMPORTANCE: The Million Hearts initiative emphasizes ABCS (aspirin for high-risk patients, blood pressure [BP] control, cholesterol level management, and smoking cessation). Evidence of the effects of drugs used to achieve ABCS has not been synthesized comprehensively in the prevention of primary atherosclerotic cardiovascular disease (ASCVD). OBJECTIVE: To compare the efficacy and safety of aspirin, BP-lowering therapy, statins, and tobacco cessation drugs for fatal and nonfatal ASCVD outcomes in primary ASCVD prevention. EVIDENCE REVIEW: Structured search of the Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects (DARE), Health Technology Assessment Database (HTA), MEDLINE, EMBASE, and PROSPERO International Prospective Systematic Review Trial Register to identify systematic reviews published from January 1, 2005, to June 17, 2015, that reported the effect of aspirin, BP-lowering therapy, statin, or tobacco cessation drugs on ASCVD events in individuals without prevalent ASCVD. Additional studies were identified by searching the reference lists of included systematic reviews, meta-analyses, and health technology assessment reports. Reviews were selected according to predefined criteria and appraised for methodologic quality using the Assessment of Multiple Systematic Reviews (AMSTAR) tool (range, 0-11). Studies were independently reviewed for key participant and intervention characteristics. Outcomes that were meta-analyzed in each included review were extracted. Qualitative synthesis was performed, and data were analyzed from July 2 to August 13, 2015. FINDINGS: From a total of 1967 reports, 35 systematic reviews of randomized clinical trials were identified, including 15 reviews of aspirin, 4 reviews of BP-lowering therapy, 12 reviews of statins, and 4 reviews of tobacco cessation drugs. Methodologic quality varied, but 30 reviews had AMSTAR ratings of 5 or higher. Compared with placebo, aspirin (relative risk [RR], 0.90; 95% CI, 0.85-0.96) and statins (RR, 0.75; 95% CI, 0.70-0.81) reduced the risk for ASCVD. Compared with placebo, BP-lowering therapy reduced the risk for coronary heart disease (RR, 0.84; 95% CI, 0.79-0.90) and stroke (RR, 0.64; 95% CI, 0.56-0.73). Tobacco cessation drugs increased the odds of continued abstinence at 6 months (odds ratio range, 1.82 [95% CI, 1.60-2.06] to 2.88 [95% CI, 2.40-3.47]), but the direct effects on ASCVD were poorly reported. Aspirin increased the risk for major bleeding (RR, 1.54; 95% CI, 1.30-1.82), and statins did not increase overall risk for adverse effects (RR, 1.00; 95% CI, 0.97-1.03). Adverse effects of BP-lowering therapy and tobacco cessation drugs were poorly reported. CONCLUSIONS AND RELEVANCE: This overview demonstrates high-quality evidence to support aspirin, BP-lowering therapy, and statins for primary ASCVD prevention and tobacco cessation drugs for smoking cessation. Treatment effects of each drug can be used to enrich discussions between health care professionals and patients in primary ASCVD prevention.