Exploiting relationship directionality to enhance statistical modeling of peer-influence across social networks.

Risky-prescribing is the excessive or inappropriate prescription of drugs that singly or in combination pose significant risks of adverse health outcomes. In the United States, prescribing of opioids and other "risky" drugs is a national public health concern. We use a novel data framework-a directed network connecting physicians who encounter the same patients in a sequence of visits-to investigate if risky-prescribing diffuses across physicians through a process of peer-influence. Using a shared-patient network of 10 661 Ohio-based physicians constructed from Medicare claims data over 2014-2015, we extract information on the order in which patients encountered physicians to derive a directed patient-sharing network. This enables the novel decomposition of peer-effects of a medical practice such as risky-prescribing into directional (outbound and inbound) and bidirectional (mutual) relationship components. Using this framework, we develop models of peer-effects for contagion in risky-prescribing behavior as well as spillover effects. The latter is measured in terms of adverse health events suspected to be related to risky-prescribing in patients of peer-physicians. Estimated peer-effects were strongest when the patient-sharing relationship was mutual as opposed to directional. Using simulations we confirmed that our modeling and estimation strategies allows simultaneous estimation of each type of peer-effect (mutual and directional) with accuracy and precision. We also show that failing to account for these distinct mechanisms (a form of model mis-specification) produces misleading results, demonstrating the importance of retaining directional information in the construction of physician shared-patient networks. These findings suggest network-based interventions for reducing risky-prescribing.

Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force.

Importance: The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective: To estimate outcomes of various mammography screening strategies. Design, Setting, and Population: Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures: Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures: Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results: Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions: This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

Estimating the impact of physician risky-prescribing on the network structure underlying physician shared-patient relationships.

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 geographic 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 could inform interventions to reduce risky-prescribing (e.g., should interventions target groups of physicians or select physicians at random). 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 of select physicians 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 in both the state-wide and multiple HRR sub-networks, and that the level of homophily varied across HRRs. 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 could be applied to arbitrary shared-patient networks and even more generally to other kinds of network data that underlies other kinds of social phenomena.

Hospital Capabilities Associated With Behavioral Health Integration Within Emergency Departments.

OBJECTIVES: To identify hospital capabilities associated with behavioral health (BH) processes in emergency departments (EDs). RESEARCH DESIGN: Six hundred two hospital responses to the 2017/2018 National Survey of Healthcare Organizations and Systems were linked to 2017 American Hospital Association Annual Survey data. Separate multivariable regressions estimated how hospital capabilities (the use of quality improvement methods, approaches to disseminate best patient-care practices, barriers to using care delivery innovations, and inpatient beds for psychiatric or substance use) were associated with each of 4 ED-based BH processes: mental health and substance use disorder screening, team-based approaches to BH, telepsychiatry, and direct referrals to community-based BH clinicians. Models controlled for hospital structural characteristics and area-level socioeconomic factors. RESULTS: Most hospitals screened for BH conditions and provided direct referrals to community-based BH clinicians. Approximately half of the hospitals used a team approach to BH. A minority had implemented telepsychiatry. Each additional process used to disseminate best patient-care practices was associated with more screening for BH conditions (an increase of 4.07 points on the screening index, P <0.01) and greater likelihood of using a team approach to BH [4.41 percentage point ( P <0.01) increase]. Hospitals reporting more barriers to the use of care delivery innovations reported less screening and use of a team approach [a decrease of 0.15 points on the screening index ( P <0.01) and 0.28 percentage points reduction in likelihood of team approach use ( P <0.001) for 1-point increase in the barrier index]. CONCLUSIONS: Research and interventions focused on removing innovation barriers or adding processes to disseminate best practices offer a path to accelerate BH integration in hospital EDs.

Availability of Medication for Opioid Use Disorder Among Accountable Care Organizations: Evidence From a National Survey.

OBJECTIVE: This report aimed to assess how accountable care organizations (ACOs) addressed ongoing opioid use disorder treatment needs over time. METHODS: Responses from the 2018 (N=308 organizations) and 2022 (N=276) National Survey of Accountable Care Organizations (response rate=55% in both years) were used to examine changes in availability of medication for opioid use disorder (MOUD) among ACOs with Medicare and Medicaid contracts. RESULTS: The percentage of respondents offering at least one MOUD grew from 39% in 2018 to 52% in 2022 (p<0.01). MOUDs were more likely to be available in 2022 among ACOs with (vs. without) in-network substance use treatment facilities (80% vs. 33%, p<0.001). The percentage of 2022 respondents who reported offering MOUD was similar in states with high versus low opioid overdose mortality rates. CONCLUSIONS: Despite growing availability of MOUD among ACOs, nearly half reported not offering any MOUD in 2022, and the availability of MOUD did not increase with treatment need.

Supplemental magnetic resonance imaging plus mammography compared with magnetic resonance imaging or mammography by extent of breast density.

BACKGROUND: Examining screening outcomes by breast density for breast magnetic resonance imaging (MRI) with or without mammography could inform discussions about supplemental MRI in women with dense breasts. METHODS: We evaluated 52 237 women aged 40-79 years who underwent 2611 screening MRIs alone and 6518 supplemental MRI plus mammography pairs propensity score-matched to 65 810 screening mammograms. Rates per 1000 examinations of interval, advanced, and screen-detected early stage invasive cancers and false-positive recall and biopsy recommendation were estimated by breast density (nondense = almost entirely fatty or scattered fibroglandular densities; dense = heterogeneously/extremely dense) adjusting for registry, examination year, age, race and ethnicity, family history of breast cancer, and prior breast biopsy. RESULTS: Screen-detected early stage cancer rates were statistically higher for MRI plus mammography vs mammography for nondense (9.3 vs 2.9; difference = 6.4, 95% confidence interval [CI] = 2.5 to 10.3) and dense (7.5 vs 3.5; difference = 4.0, 95% CI = 1.4 to 6.7) breasts and for MRI vs MRI plus mammography for dense breasts (19.2 vs 7.5; difference = 11.7, 95% CI = 4.6 to 18.8). Interval rates were not statistically different for MRI plus mammography vs mammography for nondense (0.8 vs 0.5; difference = 0.4, 95% CI = -0.8 to 1.6) or dense breasts (1.5 vs 1.4; difference = 0.0, 95% CI = -1.2 to 1.3), nor were advanced cancer rates. Interval rates were not statistically different for MRI vs MRI plus mammography for nondense (2.6 vs 0.8; difference = 1.8 (95% CI = -2.0 to 5.5) or dense breasts (0.6 vs 1.5; difference = -0.9, 95% CI = -2.5 to 0.7), nor were advanced cancer rates. False-positive recall and biopsy recommendation rates were statistically higher for MRI groups than mammography alone. CONCLUSION: MRI screening with or without mammography increased rates of screen-detected early stage cancer and false-positives for women with dense breasts without a concomitant decrease in advanced or interval cancers.

Benefits and Harms of Mammography Screening in 75 + Women to Inform Shared Decision-making: a Simulation Modeling Study.

BACKGROUND: Guidelines recommend shared decision-making (SDM) around mammography screening for women ≥ 75 years old. OBJECTIVE: To use microsimulation modeling to estimate the lifetime benefits and harms of screening women aged 75, 80, and 85 years based on their individual risk factors (family history, breast density, prior biopsy) and comorbidity level to support SDM in clinical practice. DESIGN, SETTING, AND PARTICIPANTS: We adapted two established Cancer Intervention and Surveillance Modeling Network (CISNET) models to evaluate the remaining lifetime benefits and harms of screening U.S. women born in 1940, at decision ages 75, 80, and 85 years considering their individual risk factors and comorbidity levels. Results were summarized for average- and higher-risk women (defined as having breast cancer family history, heterogeneously dense breasts, and no prior biopsy, 5% of the population). MAIN OUTCOMES AND MEASURES: Remaining lifetime breast cancers detected, deaths (breast cancer/other causes), false positives, and overdiagnoses for average- and higher-risk women by age and comorbidity level for screening (one or five screens) vs. no screening per 1000 women. RESULTS: Compared to stopping, one additional screen at 75 years old resulted in six and eight more breast cancers detected (10% overdiagnoses), one and two fewer breast cancer deaths, and 52 and 59 false positives per 1000 average- and higher-risk women without comorbidities, respectively. Five additional screens over 10 years led to 23 and 31 additional breast cancer cases (29-31% overdiagnoses), four and 15 breast cancer deaths avoided, and 238 and 268 false positives per 1000 average- and higher-risk screened women without comorbidities, respectively. Screening women at older ages (80 and 85 years old) and high comorbidity levels led to fewer breast cancer deaths and a higher percentage of overdiagnoses. CONCLUSIONS: Simulation models show that continuing screening in women ≥ 75 years old results in fewer breast cancer deaths but more false positive tests and overdiagnoses. Together, clinicians and 75 + women may use model output to weigh the benefits and harms of continued screening.

Population simulation modeling of disparities in US breast cancer mortality.

BACKGROUND: Populations of African American or Black women have persistently higher breast cancer mortality than the overall US population, despite having slightly lower age-adjusted incidence. METHODS: Three Cancer Intervention and Surveillance Modeling Network simulation teams modeled cancer mortality disparities between Black female populations and the overall US population. Model inputs used racial group-specific data from clinical trials, national registries, nationally representative surveys, and observational studies. Analyses began with cancer mortality in the overall population and sequentially replaced parameters for Black populations to quantify the percentage of modeled breast cancer morality disparities attributable to differences in demographics, incidence, access to screening and treatment, and variation in tumor biology and response to therapy. RESULTS: Results were similar across the 3 models. In 2019, racial differences in incidence and competing mortality accounted for a net ‒1% of mortality disparities, while tumor subtype and stage distributions accounted for a mean of 20% (range across models = 13%-24%), and screening accounted for a mean of 3% (range = 3%-4%) of the modeled mortality disparities. Treatment parameters accounted for the majority of modeled mortality disparities: mean = 17% (range = 16%-19%) for treatment initiation and mean = 61% (range = 57%-63%) for real-world effectiveness. CONCLUSION: Our model results suggest that changes in policies that target improvements in treatment access could increase breast cancer equity. The findings also highlight that efforts must extend beyond policies targeting equity in treatment initiation to include high-quality treatment completion. This research will facilitate future modeling to test the effects of different specific policy changes on mortality disparities.

Challenges and Opportunities of Epidemiological Studies to Reduce the Burden of Cancers in Young Adults.

There are >1.9 million survivors of adolescent and young adult cancers (AYA, diagnosed at ages 15-39) living in the U.S. today. Epidemiologic studies to address the cancer burden in this group have been a relatively recent focus of the research community. In this article, we discuss approaches and data resources for cancer epidemiology and health services research in the AYA population. We consider research that uses data from cancer registries, vital records, healthcare utilization, and surveys, and the accompanying challenges and opportunities of each. To illustrate the strengths of each data source, we present example research questions or areas that are aligned with these data sources and salient to AYAs. Integrating the respective strengths of cancer registry, vital records, healthcare data, and survey-based studies sets the foundation for innovative and impactful research on AYA cancer treatment and survivorship to inform a comprehensive understanding of diverse AYA needs and experiences.

Provision of Digital Health Technologies for Opioid Use Disorder Treatment by US Health Care Organizations.

Importance: Digital health technologies may expand organizational capacity to treat opioid use disorder (OUD). However, it remains unclear whether these technologies serve as substitutes for or complements to traditional substance use disorder (SUD) treatment resources in health care organizations. Objective: To characterize the use of patient-facing digital health technologies for OUD by US organizations with accountable care organization (ACO) contracts. Design, Setting, and Participants: This cross-sectional study analyzed responses to the 2022 National Survey of Accountable Care Organizations (NSACO), collected between October 1, 2021, and June 30, 2022, from US organizations with Medicare and Medicaid ACO contracts. Data analysis was performed between December 15, 2022, and January 6, 2023. Exposures: Treatment resources for SUD (eg, an addiction medicine specialist, sufficient staff to treat SUD, medications for OUD, a specialty SUD treatment facility, a registry to identify patients with OUD, or a registry to track mental health for patients with OUD) and organizational characteristics (eg, organization type, Medicaid ACO contract). Main Outcomes and Measures: The main outcomes included survey-reported use of 3 categories of digital health technologies for OUD: remote mental health therapy and tracking, virtual peer recovery support programs, and digital recovery support for adjuvant cognitive behavior therapy (CBT). Statistical analysis was conducted using descriptive statistics and multivariable logistic regression models. Results: Overall, 276 of 505 organizations responded to the NSACO (54.7% response rate), with a total of 304 respondents. Of these, 161 (53.1%) were from a hospital or health system, 74 (24.2%) were from a physician- or medical group-led organization, and 23 (7.8%) were from a safety-net organization. One-third of respondents (101 [33.5%]) reported that their organization used at least 1 of the 3 digital health technology categories, including remote mental health therapy and tracking (80 [26.5%]), virtual peer recovery support programs (46 [15.1%]), and digital recovery support for adjuvant CBT (27 [9.0%]). In an adjusted analysis, organizations with an addiction medicine specialist (average marginal effect [SE], 32.3 [4.7] percentage points; P < .001) or a registry to track mental health (average marginal effect [SE], 27.2 [3.8] percentage points; P < .001) were more likely to use at least 1 category of technology compared with otherwise similar organizations lacking these capabilities. Conclusions and Relevance: In this cross-sectional study of 276 organizations with ACO contracts, organizations used patient-facing digital health technologies for OUD as complements to available SUD treatment capabilities rather than as substitutes for unavailable resources. Future studies should examine implementation facilitators to realize the potential of emerging technologies to support organizations facing health care practitioner shortages and other barriers to OUD treatment delivery.

Health-related quality of life in high-cost, high-need populations.

OBJECTIVES: To characterize patient-reported health and assess the psychometric performance of health-related quality of life (HRQOL) in high-cost, high-need (HCHN) populations. STUDY DESIGN: Retrospective longitudinal study examining health care utilization, expenditures, and patient-reported health comparing a baseline (year 1) and follow-up year (year 2). METHODS: The sample includes adults (n = 46,934) participating in the Medical Expenditure Panel Survey between 2011 and 2016. We estimated HRQOL for each sample member using the physical and mental health scales from the Medical Outcomes Study Short Form 12. We compared HRQOL stratified by HCHN, defined as patients whose baseline (year 1) demographics, utilization, and clinical characteristics predicted top decile health spending in year 2. Analyses assessed the validity, reliability, and responsiveness of physical and, separately, mental health scales. RESULTS: Among HCHN adults, the physical health scale exhibited robust measure validity, reliability, and responsiveness across all age groups; the mental health scale did not. Mean physical health was 1.25 SDs lower in HCHN vs other patients (37.9 vs 51.0 on a 0-100 scale increasing in self-perceived health; pooled SD, 10.5). Regressions indicated that a 0.5-SD increase in year 1 physical health among HCHN adults predicted a 5-percentage-point (10%) decrease in the probability of top decile health spending in year 2. In contrast to health care spending, HRQOL did not exhibit reversion to the mean in HCHN patients. CONCLUSIONS: Patient-reported health outcomes remain poor in HCHN populations, even after health care utilization recedes. HRQOL is a promising outcome measure for HCHN-focused payment and delivery interventions.

Risk of cancer versus risk of cancer diagnosis? Accounting for diagnostic bias in predictions of breast cancer risk by race and ethnicity.

OBJECTIVES: Cancer risk prediction may be subject to detection bias if utilization of screening is related to cancer risk factors. We examine detection bias when predicting breast cancer risk by race/ethnicity. METHODS: We used screening and diagnosis histories from the Breast Cancer Surveillance Consortium to estimate risk of breast cancer onset and calculated relative risk of onset and diagnosis for each racial/ethnic group compared with non-Hispanic White women. RESULTS: Of 104,073 women aged 40-54 receiving their first screening mammogram at a Breast Cancer Surveillance Consortium facility between 2000 and 2018, 10.2% (n = 10,634) identified as Asian, 10.9% (n = 11,292) as Hispanic, and 8.4% (n = 8719) as non-Hispanic Black. Hispanic and non-Hispanic Black women had slightly lower screening frequencies but biopsy rates following a positive mammogram were similar across groups. Risk of cancer diagnosis was similar for non-Hispanic Black and White women (relative risk vs non-Hispanic White = 0.90, 95% CI 0.65 to 1.14) but was lower for Asian (relative risk = 0.70, 95% CI 0.56 to 0.97) and Hispanic women (relative risk = 0.82, 95% CI 0.62 to 1.08). Relative risks of disease onset were 0.78 (95% CI 0.68 to 0.88), 0.70 (95% CI 0.59 to 0.83), and 0.95 (95% CI 0.84 to 1.09) for Asian, Hispanic, and non-Hispanic Black women, respectively. CONCLUSIONS: Racial/ethnic differences in mammography and biopsy utilization did not induce substantial detection bias; relative risks of disease onset were similar to or modestly different than relative risks of diagnosis. Asian and Hispanic women have lower risks of developing breast cancer than non-Hispanic Black and White women, who have similar risks.

Breast cancer risk characteristics of women undergoing whole-breast ultrasound screening versus mammography alone.

BACKGROUND: There are no consensus guidelines for supplemental breast cancer screening with whole-breast ultrasound. However, criteria for women at high risk of mammography screening failures (interval invasive cancer or advanced cancer) have been identified. Mammography screening failure risk was evaluated among women undergoing supplemental ultrasound screening in clinical practice compared with women undergoing mammography alone. METHODS: A total of 38,166 screening ultrasounds and 825,360 screening mammograms without supplemental screening were identified during 2014-2020 within three Breast Cancer Surveillance Consortium (BCSC) registries. Risk of interval invasive cancer and advanced cancer were determined using BCSC prediction models. High interval invasive breast cancer risk was defined as heterogeneously dense breasts and BCSC 5-year breast cancer risk ≥2.5% or extremely dense breasts and BCSC 5-year breast cancer risk ≥1.67%. Intermediate/high advanced cancer risk was defined as BCSC 6-year advanced breast cancer risk ≥0.38%. RESULTS: A total of 95.3% of 38,166 ultrasounds were among women with heterogeneously or extremely dense breasts, compared with 41.8% of 825,360 screening mammograms without supplemental screening (p < .0001). Among women with dense breasts, high interval invasive breast cancer risk was prevalent in 23.7% of screening ultrasounds compared with 18.5% of screening mammograms without supplemental imaging (adjusted odds ratio, 1.35; 95% CI, 1.30-1.39); intermediate/high advanced cancer risk was prevalent in 32.0% of screening ultrasounds versus 30.5% of screening mammograms without supplemental screening (adjusted odds ratio, 0.91; 95% CI, 0.89-0.94). CONCLUSIONS: Ultrasound screening was highly targeted to women with dense breasts, but only a modest proportion were at high mammography screening failure risk. A clinically significant proportion of women undergoing mammography screening alone were at high mammography screening failure risk.

Racial Inequality in Receipt of Medications for Opioid Use Disorder.

BACKGROUND: Since 2010, Black persons in the United States have had a greater increase in opioid overdose-related mortality than other groups, but national-level evidence characterizing racial and ethnic disparities in the use of medications for opioid use disorder (OUD) is limited. METHODS: We used Medicare claims data from the 2016-2019 period for a random 40% sample of fee-for-service beneficiaries who were Black, Hispanic, or White; were eligible for Medicare owing to disability; and had an index event related to OUD (nonfatal overdose treated in an emergency department or inpatient setting, hospitalization with injection drug use-related infection, or inpatient or residential rehabilitation or detoxification care). We measured the receipt of medications to treat OUD (buprenorphine, naltrexone, and naloxone), the receipt of high-risk medications (opioid analgesics and benzodiazepines), and health care utilization, all in the 180 days after the index event. We estimated differences in outcomes according to race and ethnic group with adjustment for beneficiary age, sex, index event, count of chronic coexisting conditions, and state of residence. RESULTS: We identified 25,904 OUD-related index events among 23,370 beneficiaries, with 3937 events (15.2%) occurring among Black patients, 2105 (8.1%) among Hispanic patients, and 19,862 (76.7%) among White patients. In the 180 days after the index event, patients received buprenorphine after 12.7% of events among Black patients, after 18.7% of those among Hispanic patients, and after 23.3% of those among White patients; patients received naloxone after 14.4%, 20.7%, and 22.9%, respectively; and patients received benzodiazepines after 23.4%, 29.6%, and 37.1%, respectively. Racial differences in the receipt of medications to treat OUD did not change appreciably from 2016 to 2019 (buprenorphine receipt: after 9.1% of index events among Black patients vs. 21.6% of those among White patients in 2016, and after 14.1% vs. 25.5% in 2019). In all study groups, patients had multiple ambulatory visits in the 180 days after the index event (mean number of visits, 6.6 after events among Black patients, 6.7 after events among Hispanic patients, and 7.6 after events among White patients). CONCLUSIONS: Racial and ethnic differences in the receipt of medications to treat OUD after an index event related to this disorder among patients with disability were substantial and did not change over time. The high incidence of ambulatory visits in all groups showed that disparities persisted despite frequent health care contact. (Funded by the National Institute on Drug Abuse and the National Institute on Aging.).

Internal and Environmental Predictors of Physician Practice Use of Screening and Medications for Opioid Use Disorders.

Medications for opioid use disorder (MOUD) remain highly inaccessible despite demonstrated effectiveness. We examine the extent of screening for opioid use and availability of MOUD in a national cross-section of multi-physician primary care and multispecialty practices. Drawing on an existing framework to characterize the internal and environmental context, we assess socio-technical, organizational-managerial, market-based, and state-regulation factors associated with the use of opioid screening and offering of MOUD in a practice. A total of 26.2% of practices offered MOUD, while 69.4% of practices screened for opioid use. Having advanced health information technology functionality was positively associated with both screening for opioid use and offering MOUD in a practice, while access to on-site behavioral clinicians was positively associated with offering MOUD in adjusted models. These results suggest that improving access to information and expertise may enable physician practices to respond more effectively to the nation's ongoing opioid epidemic.

Changes in spending and quality after ACO contract participation for dually eligible beneficiaries with mental illness.

BACKGROUND: Fragmented care and misaligned payment across Medicare and Medicaid lower care quality for dually eligible beneficiaries with mental illness. Accountable care organizations aim to improve the quality and value of care. METHODS: Using Medicare fee-for-service Part A and B claims data from 2009 to 2017 and a difference-in-differences design, we compared the spending and utilization of dually eligible beneficiaries with mental illness that were and were not attributed to Medicare ACO providers before and after ACO contract entry. RESULTS: Dually eligible beneficiaries with mental illness (N = 5,157,533, 70% depression, 22% bipolar, 27% schizophrenia and other psychotic disorders) had average annual Medicare spending of $17,899. ACO contract participation was generally not associated with spending or utilization changes. However, ACO contract participation was associated with higher rates of follow-up visits after mental health hospitalization: 1.17 and 1.30 percentage points within 7 and 30 days of discharge, respectively (p < 0.001). ACO-attributed beneficiaries with schizophrenia, bipolar, or other psychotic disorders received more ambulatory visits (393.9 per 1000 person-years, p = 0.002), while ACO-attributed beneficiaries with depression experienced fewer emergency department visits (-29.5 per 1000 person-years, p = 0.003) after ACO participation. CONCLUSIONS: Dually eligible beneficiaries served by Medicare ACOs did not have lower spending, hospitalizations, or readmissions compared with other beneficiaries. However, ACO participation was associated with timely follow-up after mental health hospitalization, as well as more ambulatory care and fewer ED visits for certain diagnostic groups. IMPLICATIONS: ACOs that include dually eligible beneficiaries with mental illness should tailor their designs to address the distinct needs of this population.

Excess Deaths In A Time Of Dual Public Health Crises: Parsing The Effects Of The Pandemic, Drug Overdoses, And Recession.

A detailed examination of deaths in the US by cause and age suggests that the 2020 recession did not contribute to excess deaths overall. However, high excess mortality occurred because of drug overdoses both from recession effects and from COVID-19 pandemic effects. Understanding the risk for heightened substance use mortality can help mitigate this risk in the next pandemic.

ACO Participation Associated With Decreased Spending For Medicare Beneficiaries With Serious Mental Illness.

Serious mental illness (SMI) is a major source of suffering among Medicare beneficiaries. To date, limited evidence exists evaluating whether Medicare accountable care organizations (ACOs) are associated with decreased spending among people with SMI. Using national Medicare data from the period 2009-17, we performed difference-in-differences analyses evaluating changes in spending and use associated with enrollment in the Medicare Shared Savings Program (MSSP) among beneficiaries with SMI. After five years, participation in MSSP ACOs was associated with small savings for beneficiaries with SMI (-$233 per person per year) in total health care spending, primarily related to savings from chronic medical conditions (excluding mental health; -$227 per person per year) and not from savings related to mental health services (-$6 per person per year). Savings were driven by reductions in acute and postacute care for medical conditions. Further work is needed to ensure that Medicare ACOs invest in strategies to reduce potentially unnecessary care related to mental health disorders and to improve health outcomes.

Association of Screening With Digital Breast Tomosynthesis vs Digital Mammography With Risk of Interval Invasive and Advanced Breast Cancer.

Importance: Digital breast tomosynthesis (DBT) was developed with the expectation of improving cancer detection in women with dense breasts. Studies are needed to evaluate interval invasive and advanced breast cancer rates, intermediary outcomes related to breast cancer mortality, by breast density and breast cancer risk. Objective: To evaluate whether DBT screening is associated with a lower likelihood of interval invasive cancer and advanced breast cancer compared with digital mammography by extent of breast density and breast cancer risk. Design, Setting, and Participants: Cohort study of 504 427 women aged 40 to 79 years who underwent 1 003 900 screening digital mammography and 375 189 screening DBT examinations from 2011 through 2018 at 44 US Breast Cancer Surveillance Consortium (BCSC) facilities with follow-up for cancer diagnoses through 2019 by linkage to state or regional cancer registries. Exposures: Breast Imaging Reporting and Data System (BI-RADS) breast density; BCSC 5-year breast cancer risk. Main Outcomes and Measures: Rates per 1000 examinations of interval invasive cancer within 12 months of screening mammography and advanced breast cancer (prognostic pathologic stage II or higher) within 12 months of screening mammography, both estimated with inverse probability weighting. Results: Among 504 427 women in the study population, the median age at time of mammography was 58 years (IQR, 50-65 years). Interval invasive cancer rates per 1000 examinations were not significantly different for DBT vs digital mammography (overall, 0.57 vs 0.61, respectively; difference, -0.04; 95% CI, -0.14 to 0.06; P = .43) or among all the 836 250 examinations with BCSC 5-year risk less than 1.67% (low to average-risk) or all the 413 061 examinations with BCSC 5-year risk of 1.67% or higher (high risk) across breast density categories. Advanced cancer rates were not significantly different for DBT vs digital mammography among women at low to average risk or at high risk with almost entirely fatty, scattered fibroglandular densities, or heterogeneously dense breasts. Advanced cancer rates per 1000 examinations were significantly lower for DBT vs digital mammography for the 3.6% of women with extremely dense breasts and at high risk of breast cancer (13 291 examinations in the DBT group and 31 300 in the digital mammography group; 0.27 vs 0.80 per 1000 examinations; difference, -0.53; 95% CI, -0.97 to -0.10) but not for women at low to average risk (10 611 examinations in the DBT group and 37 796 in the digital mammography group; 0.54 vs 0.42 per 1000 examinations; difference, 0.12; 95% CI, -0.09 to 0.32). Conclusions and Relevance: Screening with DBT vs digital mammography was not associated with a significant difference in risk of interval invasive cancer and was associated with a significantly lower risk of advanced breast cancer among the 3.6% of women with extremely dense breasts and at high risk of breast cancer. No significant difference was observed in the 96.4% of women with nondense breasts, heterogeneously dense breasts, or with extremely dense breasts not at high risk.