Explore the vast range of titles available.

An analysis of 2016–2019 Medicare claims data for patients with opioid use disorder showed that receipt of medications to treat OUD was more frequent among White patients than among Black and Hispanic patients.

More than 40 medical specialties have identified “Choosing Wisely” lists of five overused or low-value services. But these services vary widely in potential impact on care and spending, and specialty societies often name other specialties' services as low value. With its Choosing Wisely campaign, the American Board of Internal Medicine (ABIM) Foundation boldly invited professional societies to own their role as “stewards of finite health care resources.” 1 Beginning in 2009, the National Physicians Alliance, funded by the ABIM Foundation, guided volunteers from three primary care specialties through the development of “Top Five” lists — specialty-specific enumerations of five achievable practice changes to improve patient health through better treatment choices, reduced risks and, where possible, reduced costs. 2 In April 2012, the effort was expanded and launched as the Choosing Wisely campaign, with lists from nine specialty societies and a patient-education . . .

This analysis of 2016 and 2017 claims data for disabled Medicare beneficiaries compared filled opioid prescriptions between Black and White patients treated within the same health systems. The mean annual opioid dose was 36% lower among Black patients than White patients. In 75% of the 310 health systems studied, the mean annual dose was at least 15% higher among White patients than Black patients.

We are generally interested in the association between a prescribing physician’s position in a physician shared-patient network and their patients’ receipt of risky drug combinations. An informal physician network (not restricted to a hospital or a health system) of physicians based in Ohio was constructed based on overlapping care of patients between physicians reflected in face-to-face visits in Fee-for-service Medicare claims for Ohio-residing beneficiaries. Separately, Medicare prescription drug events for beneficiaries receiving opioids, benzodiazepines, or non-benzodiazepine sedative hypnotics (sedative hypnotics) prescribed by these physicians in 2014 were used to map patients’ drug status with respect to these three classes. We assigned patient prescription receipt to time-varying drug states and linked each drug state transition to a “responsible” prescribing physician. Outcomes of interest include transitions across drug states, particularly those resulting in combinations of increased risk (e.g., a benzodiazepine or sedative hypnotic with an opioid), and patients’ time to discontinuation of overlapping prescriptions of an opioid, benzodiazepine, and a sedative hypnotic while the key predictors of these transitions reflected characteristics of a prescriber’s physician network position and physician speciality. We found that among beneficiaries receiving none of the three risky drug groups, patients seeing physicians with higher closeness centrality (shorter average path lengths to other physicians through the network) were less likely to transition to two or three risky drugs; and they were more likely to discontinue overlapping prescriptions of an opioid, benzodiazepine, and sedative hypnotic. Compared to PCPs, psychiatrists appeared more likely to prescribe risky drug combinations, and their patients were less likely to discontinue overlapping three-drug prescriptions. This work demonstrates that characterizing physicians’ prescribing behavior in relation to their position in shared-patient networks may reveal strategies for optimizing network-based interventions to improve prescribing quality.

In this analysis of Medicare data and a data set of state laws, adoption of legislation to restrict the prescribing and dispensing of opioid medications was not associated with reductions in potentially hazardous use of opioids among disabled Medicare beneficiaries. States have responded to rising rates of prescription-opioid overdose by adopting laws that restrict the prescribing and dispensing of controlled substances. In 2010, after the adoption of many new controlled-substance restrictions, rates of prescription-opioid overdose dipped slightly before reaching a historic high in 2014. 1 – 3 The relationship between legal restrictions and prescription-opioid use remains unclear, because previous research evaluated one or two laws, short time periods, or few states. 4 – 6 Comprehensive national analyses of controlled-substance restrictions and prescription-opioid use do not yet exist. Successful regulation of prescription opioids involves a difficult balance. Well-designed laws may reduce misuse and overdose. However, . . .

Social network analysis and shared-patient physician networks have become effective ways of studying physician collaborations. Assortative mixing or “homophily” is the network phenomenon whereby the propensity for similar individuals to form ties is greater than for dissimilar individuals. Motivated by the public health concern of risky-prescribing among older patients in the United States, we develop network models and tests involving novel network measures to study whether there is evidence of homophily in prescribing and deprescribing in the specific shared-patient network of physicians linked to the US state of Ohio in 2014. Evidence of homophily in risky-prescribing would imply that prescribing behaviors help shape physician networks and would suggest strategies for interventions seeking to reduce risky-prescribing (e.g., strategies to directly reduce risky prescribing might be most effective if applied as group interventions to risky prescribing physicians connected through the network and the connections between these physicians could be targeted by tie dissolution interventions as an indirect way of reducing risky prescribing). Furthermore, if such effects varied depending on the structural features of a physician’s position in the network (e.g., by whether or not they are involved in cliques—groups of actors that are fully connected to each other—such as closed triangles in the case of three actors), this would further strengthen the case for targeting groups of physicians involved in risky prescribing and the network connections between them for interventions. Using accompanying Medicare Part D data, we converted patient longitudinal prescription receipts into novel measures of the intensity of each physician’s risky-prescribing. Exponential random graph models were used to simultaneously estimate the importance of homophily in prescribing and deprescribing in the network beyond the characteristics of physician specialty (or other metadata) and network-derived features. In addition, novel network measures were introduced to allow homophily to be characterized in relation to specific triadic (three-actor) structural configurations in the network with associated non-parametric randomization tests to evaluate their statistical significance in the network against the null hypothesis of no such phenomena. We found physician homophily in prescribing and deprescribing. We also found that physicians exhibited within-triad homophily in risky-prescribing, with the prevalence of homophilic triads significantly higher than expected by chance absent homophily. These results may explain why communities of prescribers emerge and evolve, helping to justify group-level prescriber interventions. The methodology may be applied, adapted or generalized to study homophily and its generalizations on other network and attribute combinations involving analogous shared-patient networks and more generally using other kinds of network data underlying other kinds of social phenomena.

BACKGROUND:The October 1, 2015 US health care diagnosis and procedure codes update, from the 9th to 10th version of the International Classification of Diseases (ICD), abruptly changed the structure, number, and diversity of codes in health care administrative data. Translation from ICD-9 to ICD-10 risks introducing artificial changes in claims-based measures of health and health services. OBJECTIVE:Using published ICD-9 and ICD-10 definitions and translation software, we explored discontinuity in common diagnoses to quantify measurement changes introduced by the upgrade. DESIGN:Using 100% Medicare inpatient data, 2012–2015, we calculated the quarterly frequency of condition-specific diagnoses on hospital discharge records. Years 2012–2014 provided baseline frequencies and historic, annual fourth-quarter changes. We compared these to fourth quarter of 2015, the first months after ICD-10 adoption, using Centers for Medicare and Medicaid Services Chronic Conditions Data Warehouse (CCW) ICD-9 and ICD-10 definitions and other commonly used definitions sets. RESULTS:Discontinuities of recorded CCW-defined conditions in fourth quarter of 2015 varied widely. For example, compared with diagnosis appearance in 2014 fourth quarter, in 2015 we saw a sudden 3.2% increase in chronic lung disease and a 1.8% decrease in depression; frequency of acute myocardial infarction was stable. Using published software to translate Charlson-Deyo and Elixhauser conditions yielded discontinuities ranging from −8.9% to +10.9%. CONCLUSIONS:ICD-9 to ICD-10 translations do not always align, producing discontinuity over time. This may compromise ICD-based measurements and risk-adjustment. To address the challenge, we propose a public resource for researchers to share discovered discontinuities introduced by ICD-10 adoption and the solutions they develop.

Background Specialty societies in the United States identified low-value tests and procedures that contribute to waste and poor health care quality via implementation of the American Board of Internal Medicine Foundation’s Choosing Wisely initiative. Objective To develop claims-based algorithms, to use them to estimate the prevalence of select Choosing Wisely services and to examine the demographic, health and health care system correlates of low-value care at a regional level. Design Using Medicare data from 2006 to 2011, we created claims-based algorithms to measure the prevalence of 11 Choosing Wisely-identified low-value services and examined geographic variation across hospital referral regions (HRRs). We created a composite low-value care score for each HRR and used linear regression to identify regional characteristics associated with more intense use of low-value services. Patients Fee-for-service Medicare beneficiaries over age 65. Main Measures Prevalence of selected Choosing Wisely low-value services. Key Results The national average annual prevalence of the selected Choosing Wisely low-value services ranged from 1.2% (upper urinary tract imaging in men with benign prostatic hyperplasia) to 46.5% (preoperative cardiac testing for low-risk, non-cardiac procedures). Prevalence across HRRs varied significantly. Regional characteristics associated with higher use of low-value services included greater overall per capita spending, a higher specialist to primary care ratio and higher proportion of minority beneficiaries. Conclusions Identifying and measuring low-value health services is a prerequisite for improving quality and eliminating waste. Our findings suggest that the delivery of wasteful and potentially harmful services may be a fruitful area for further research and policy intervention for HRRs with higher per-capita spending. These findings should inform action by physicians, health systems, policymakers, payers and consumer educators to improve the value of health care by targeting services and areas with greater use of potentially inappropriate care.

BACKGROUND:Opioid overdose deaths in the United States have climbed since 1999. In 2014, the Affordable Care Act prompted some states to expand Medicaid programs, providing low-cost prescription access to millions of Americans. Some have questioned whether Medicaid expansion might worsen the opioid crisis. OBJECTIVE:To test the association between the expansion of state Medicaid programs and Medicaid-paid prescriptions of opioid pain relievers and opioid addiction therapies. RESEARCH DESIGN:We analyzed the 2010–2016 Medicaid State Drug Utilization Data using a difference-in-differences regression approach, comparing prescriptions per enrollee between states that expanded Medicaid in 2014 and states that did not. We compared opioid pain relievers and opioid addiction therapies to 5 other commonly prescribed drug types important to the Medicaid expansion population (antidepressants, antihypertensives, diabetes medications, cholesterol treatments, and contraceptives) and to overall prescription volume. A secondary analysis compared opioid pain relievers and opioid addiction therapies, between states with high and low overdose death rates. RESULTS:We found overall prescription use per enrollee was higher after 2014. Relative growth in opioid pain reliever prescriptions was modest compared with growth in medications for depression, hypertension, diabetes, and high cholesterol. Growth in prescriptions used to treat opioid use disorder greatly outpaced other drugs, suggesting important gains in access to addiction treatments; growth was higher in states with higher pre-2014 overdose death rates. CONCLUSIONS:Our results suggest Medicaid expansion benefited a population with unique needs, and that Medicaid expansion could be a valuable tool in addressing the opioid overdose epidemic.