Residential greenspace and major depression among older adults living in urban and suburban areas with different climates across the United States.

BACKGROUND AND AIM: Residential greenspace could alleviate depression - a leading cause of disability. Fewer studies of depression and greenspace have considered major depression, and, to our knowledge, none have considered how climate, which determines vegetation abundance and type, may change the impacts of greenspace. Our aim was to investigate whether residential greenspace is associated with major depression among older adults and explore effect modification by climate. METHODS: We used biennial interviews between 2008 and 2016 from the Health and Retirement Study. We calculated greenness within walking distance of home addresses as the maximum NDVI for the year of each participant interview averaged within a 1 km buffer. Reflecting clinical criteria, a score of ≥5 on the CIDI-SF indicated major depression in the preceding 12-months. We characterized climate using Köppen-Geiger classifications. To estimate prevalence ratios, we used Poisson regression. Our models adjusted for sociodemographic characteristics, geography, annual sunshine, and bluespace. RESULTS: The 21,611 eligible participants were 65 ± 10 years old on average, 55% female, 81% White, 12% Black, 10% Hispanic/Latino, and 31% had at least a 4-year college degree. The 12-month prevalence of a major depression was 8%. In adjusted models, more residential greenspace was associated with a lower prevalence of major depression (prevalence ratio per IQR, 0.91; 95% CI, 0.84 to 0.98). There was evidence of effect modification by climate (P forinteraction, 0.062). We observed stronger associations in tropical (prevalence ratio per IQR 0.69; 95% CI, 0.47 to 1.01) and cold (prevalence ratio per IQR, 0.83; 95% CI, 0.74 to 0.93) climates compared to arid (prevalence ratio per IQR 0.99; 95% CI, 0.90 to 1.09) and temperate (prevalence ratio per IQR 0.98; 95% CI, 0.86 to 1.11) climates. CONCLUSIONS: Residential greenspace may help reduce major depression. However, climate may influence how people benefit from greenspace.

Societal costs of untreated perinatal mood and anxiety disorders in Vermont.

PURPOSE: To estimate the societal costs of untreated perinatal mood and anxiety disorders (PMADs) in Vermont for the 2018-2020 average annual birth cohort from conception through five years postpartum. METHODS: We developed a cost analysis model to calculate the excess cases of outcomes attributed to PMADs in the state of Vermont. Then, we modeled the associated costs of each outcome incurred by birthing parents and their children, projected five years for birthing parents who do not achieve remission by the end of the first year postpartum. RESULTS: We estimated that the total societal cost of untreated PMADs in Vermont could reach $48 million for an annual birth cohort from conception to five years postpartum, amounting to $35,910 in excess societal costs per birthing parent with an untreated PMAD and their child. CONCLUSION: Our model provides evidence of the high costs of untreated PMADs for birthing parents and their children in Vermont. Our estimates for Vermont are slightly higher but comparable to national estimates, which are $35,500 per birthing parent-child pair, adjusted to 2021 US dollars. Investing in perinatal mental health prevention and treatment could improve health outcomes and reduce economic burden of PMADs on individuals, families, employers, and the state.

Relationship between facility number of clinicians and prescribing intensity of psychotropic medications, opioids, and antibiotics in ambulatory practice.

BACKGROUND: Promoting appropriate pharmacotherapy requires understanding the factors that influence how clinicians prescribe medications. While prior work has focused on patient and clinician factors, features of the organizational setting have received less attention, though identifying sources of variation in prescribing may help identify opportunities to improve patient safety and outcomes. OBJECTIVE: To evaluate the relationship between the number of clinicians who prescribe medications in a facility and facility prescribing intensity of six individual medication classes by clinician specialty: benzodiazepines, antipsychotics, antiepileptics, and antidepressants by psychiatrists and antibiotics, opioids, antiepileptics, and antidepressants by primary care clinicians (PCPs). DESIGN: We used 2017 Veterans Health Administration (VHA) administrative data. SUBJECTS: We included patient-clinician dyads of older patients (> 55 years) with an outpatient encounter with a clinician in 2017. Patient-clinician data from 140 VHA facilities were included (n = 13,347,658). Analysis was repeated for years 2014 to 2016. MAIN MEASURES: For each medication, facility prescribing intensity measures were calculated as clinician prescribing intensity averaged over all clinicians at each facility. Clinician prescribing intensity measures included percentage of each clinician's patients prescribed the medication and mean number of days supply per patient among all patients of each clinician. KEY RESULTS: As the number of prescribing clinicians in a facility increased, the intensity of prescribing decreased. Every increase of 10 facility clinicians was associated with a significant decline in prescribing intensity for both specialties for different medication classes: for psychiatrists, declines ranged from 6 to 11%, and for PCPs, from 2 to 3%. The pattern of more clinicians less prescribing was significant across all years. CONCLUSION: Future work should explore the mechanisms that link the number of facility clinicians with prescribing intensity for benzodiazepines, antipsychotics, antiepileptics, antidepressants, antibiotics, and opioids. Facilities with fewer clinicians may need additional resources to avoid unwanted prescribing of potentially harmful or unnecessary medications.

The impact of the affordable care act on perinatal mood and anxiety disorder diagnosis and treatment rates among Michigan Medicaid enrollees 2012-2018.

BACKGROUND: Perinatal Mood and Anxiety Disorders (PMADs) affect one in five birthing individuals and represent a leading cause of maternal mortality. While these disorders are associated with a variety of poor outcomes and generate significant societal burden, underdiagnosis and undertreatment remain significant barriers to improved outcomes. We aimed to quantify whether the Patient Protection Affordable Care Act (ACA) improved PMAD diagnosis and treatment rates among Michigan Medicaid enrollees. METHODS: We applied an interrupted time series framework to administrative Michigan Medicaid claims data to determine if PMAD monthly diagnosis or treatment rates changed after ACA implementation for births 2012 through 2018. We evaluated three treatment types, including psychotherapy, prescription medication, and either psychotherapy or prescription medication. Participants included the 170,690 Medicaid enrollees who had at least one live birth between 2012 and 2018, with continuous enrollment from 9 months before birth through 3 months postpartum. RESULTS: ACA implementation was associated with a statistically significant 0.76% point increase in PMAD diagnosis rates (95% CI: 0.01 to 1.52). However, there were no statistically significant changes in treatment rates among enrollees with a PMAD diagnosis. CONCLUSION: The ACA may have improved PMAD detection and documentation in clinical settings. While a higher rate of PMAD cases were identified after ACA Implementation, Post-ACA cases were treated at similar rates as Pre-ACA cases.

PERSPECTIVE: Implications of Recent Health Policies for Women's Reproductive Mental Health.

BACKGROUND: The economic cost of perinatal mood and anxiety disorders (PMADs) is high and includes the cost of reduced maternal economic productivity, more preterm births, and increases in other maternal mental health expenditures. PMADs also substantially contribute the cost of maternal morbidity. This paper offers a discussion of the quality-of-care cascade model of PMADs, which outlines care pathways that people typically face as well as gaps and unmet needs that frequently happen along the way. The model uses the US health system as an example. A discussion of international implications follows. DISCUSSION: The quality-of-care cascade model outlines downward dips in quality of care along the perinatal mental health treatment continuum, including access (many Americans do not have access to affordable health insurance), enrollment (even when individuals are offered health insurance, some do not enroll), coverage (even if individuals have health insurance, some needed services or providers may not be covered), choice (even if services and providers are covered, patients may not be able to choose among plans, institutions, or clinicians), consistency (even if patients have a choice of plan or provider, a consistent source of care may not be accessible), referral (even if care is available and accessible, referral services may not be), quality (even if patients have access to both care and referral services, there may be gaps in the quality of care provided), adherence (even if patients receive high-quality care, they may not be adherent to treatment), barriers (societal forces that may influence people's choices and behaviors), and shocks (unanticipated events that could disrupt care pathways). In describing the quality-of-care cascade model, this paper uses the US healthcare system as the primary example. However, the model can extend to examine quality-of-care dips along the perinatal mental health treatment continuum within the international context. Although the US healthcare system may differ from other healthcare systems in many respects, shared commonalities lead to quality-of-care dips in countries with healthcare systems structured differently than in the US. IMPLICATIONS FOR HEALTH POLICIES: The global cost of PMADs remains substantial, and addressing the costs of these conditions could have a significant impact on overall cost and quality of care internationally. The quality-of-care cascade model presented in this paper could help identify, understand, and address the complex contributing factors that lead to dips in quality-of-care for perinatal mental health conditions across the world.

Prevalence of Testing for Human Immunodeficiency Virus, Hepatitis B Virus, and Hepatitis C Virus Among Medicaid Enrollees Treated With Medications for Opioid Use Disorder in 11 States, 2016-2019.

BACKGROUND: Limited information exists about testing for human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV) among Medicaid enrollees after starting medication for opioid use disorder (MOUD), despite guidelines recommending such testing. Our objectives were to estimate testing prevalence and trends for HIV, HBV, and HCV among Medicaid enrollees initiating MOUD and examine enrollee characteristics associated with testing. METHODS: We conducted a serial cross-sectional study of 505 440 initiations of MOUD from 2016 to 2019 among 361 537 Medicaid enrollees in 11 states. Measures of MOUD initiation; HIV, HBV, and HCV testing; comorbidities; and demographics were based on enrollment and claims data. Each state used Poisson regression to estimate associations between enrollee characteristics and testing prevalence within 90 days of MOUD initiation. We pooled state-level estimates to generate global estimates using random effects meta-analyses. RESULTS: From 2016 to 2019, testing increased from 20% to 25% for HIV, from 22% to 25% for HBV, from 24% to 27% for HCV, and from 15% to 19% for all 3 conditions. Adjusted rates of testing for all 3 conditions were lower among enrollees who were male (vs nonpregnant females), living in a rural area (vs urban area), and initiating methadone or naltrexone (vs buprenorphine). Associations between enrollee characteristics and testing varied across states. CONCLUSIONS: Among Medicaid enrollees in 11 US states who initiated medications for opioid use disorder, testing for human immunodeficiency virus, hepatitis B virus, hepatitis C virus, and all 3 conditions increased between 2016 and 2019 but the majority were not tested.

Behavioral Health Provider Burnout and Mental Health Care in the Veterans Health Administration.

BACKGROUND: Although many studies assess predictors of provider burnout, few analyses provide high-quality, consistent evidence on the impact of provider burnout on patient outcomes exist, particularly among behavioral health providers (BHPs). OBJECTIVE: To assess the impact of burnout among psychiatrists, psychologists, and social workers on access-related quality measures in the Veterans Health Administration (VHA). DESIGN: This study used burnout in VA All Employee Survey (AES) and Mental Health Provider Survey (MHPS) data to predict metrics assessed by the Strategic Analytics for Improvement and Learning Value, Mental Health Domain (MH-SAIL), VHA's quality monitoring system. The study used prior year (2014-2018) facility-level burnout proportion among BHPs to predict subsequent year (2015-2019) facility-level MH-SAIL domain scores. Analyses used multiple regression models, adjusting for facility characteristics, including BHP staffing and productivity. PARTICIPANTS: Psychologists, psychiatrists, and social workers who responded to the AES and MHPS at 127 VHA facilities. MAIN MEASURES: Four compositive outcomes included two objective measures (population coverage, continuity of care), one subjective measure (experience of care), and one composite measure of the former three measures (mental health domain quality). KEY RESULTS: Adjusted analyses showed prior year burnout generally had no impact on population coverage, continuity of care, and patient experiences of care but had a negative impact on provider experiences of care consistently across 5 years (p < 0.001). Pooled across years, a 5% higher facility-level burnout in AES and MHPS had a 0.05 and 0.09 standard deviation worse facility experiences of care from the prior year, respectively. CONCLUSIONS: Burnout had a significant negative impact on provider-reported experiential outcome measures. This analysis showed that burnout had a negative effect on subjective but not on objective quality measures of Veteran access to care, which could inform future policies and interventions regarding provider burnout.

Identifying Quality Indicators for Nursing Home Residents with Dementia: A Modified Delphi Method.

BACKGROUND: We convened a two-round, modified Delphi panel to identify and reach consensus on additional potential quality indicators (QIs) for nursing home residents with dementia. METHODS: The study team identified 12 potential QIs for nursing home dementia care and treatment of behavioral disturbances based on review of the literature. All proposed QIs were readily available in administrative claims data. Panelists rated each QI on importance, usefulness, and feasibility (a total of 36 items) using a 9-point Likert scale. Data were collected using an online survey platform and virtual group discussion. We defined consensus as ≥70% of the panelists responding within a three-point range surrounding the median. A QI achieved relevance on a domain (importance, usefulness, feasibility) when the panel reached consensus and a median rating of 7-9. RESULTS: The study had a 100% response rate for both survey rounds. Twenty-four items achieved consensus, with 15 reaching relevance with a median >7. Three QIs (percent of long-stay residents with dementia prescribed APs, percent with physical restraint use, and percent with a positive behavioral symptom score) reached consensus at the highest median score (9) for importance. Only 2 of the 12 proposed QIs reached relevance on all three domains: percent of long-stay residents with dementia prescribed antipsychotics (APs) and percent prescribed benzodiazepines. CONCLUSIONS: Of the proposed QIs, our panel of dementia care experts only reached consensus on two QIs: measuring long-stay resident prescriptions of APs and benzodiazepines. Challenges remain in identifying QIs that meet threshold of all three areas and accurately reflect quality nursing home dementia care.

Design, Implementation, and Evolution of the Medicaid Outcomes Distributed Research Network (MODRN).

BACKGROUND: In the US, Medicaid covers over 80 million Americans. Comparing access, quality, and costs across Medicaid programs can provide policymakers with much-needed information. As each Medicaid agency collects its member data, multiple barriers prevent sharing Medicaid data between states. To address this gap, the Medicaid Outcomes Distributed Research Network (MODRN) developed a research network of states to conduct rapid multi-state analyses without sharing individual-level data across states. OBJECTIVE: To describe goals, design, implementation, and evolution of MODRN to inform other research networks. METHODS: MODRN implemented a distributed research network using a common data model, with each state analyzing its own data; developed standardized measure specifications and statistical software code to conduct analyses; and disseminated findings to state and federal Medicaid policymakers. Based on feedback on Medicaid agency priorities, MODRN first sought to inform Medicaid policy to improve opioid use disorder treatment, particularly medication treatment. RESULTS: Since its 2017 inception, MODRN created 21 opioid use disorder quality measures in 13 states. MODRN modified its common data model over time to include additional elements. Initial barriers included harmonizing utilization data from Medicaid billing codes across states and adapting statistical methods to combine state-level results. The network demonstrated its utility and addressed barriers to conducting multi-state analyses of Medicaid administrative data. CONCLUSIONS: MODRN created a new, scalable, successful model for conducting policy research while complying with federal and state regulations to protect beneficiary health information. Platforms like MODRN may prove useful for emerging health challenges to facilitate evidence-based policymaking in Medicaid programs.

The economic impact of untreated maternal mental health conditions in Texas.

BACKGROUND: Maternal mental health conditions (MMHCs), which include depression and anxiety disorders during pregnancy and through five years postpartum, are among the most common obstetric complications in the United States overall and in Texas in particular. In the context of potential expansion of postpartum Medicaid coverage from 60 days to one year, we sought to capture the societal, financial burden of untreated MMHCs. METHODS: We estimated the economic impact of untreated maternal mental health conditions (MMHCs) among births in Texas in 2019 using a cost-of-illness model. RESULTS: We found that MMHCs affected 13.2% of mothers and, when left untreated, cost $2.2 billion among mothers and children born in Texas in 2019 when following the birth cohort from conception through five years postpartum. We found that MMHCs affected 17.2% of mothers enrolled in Texas' Medicaid for Pregnant Women and cost $962 million. In addition, the prevalence of MMHCs and resulting costs varied considerably among women of different races and ethnicities. Employers and health care payers, including Medicaid, bore most of these costs. CONCLUSIONS: The Texas Health and Human Services Commission's (HHSC) efforts to increase awareness about MMHCs and increase access to care represent an important step toward improving maternal and child health and maximizing benefits to Texas HHSC, employers, and insurers.

From zero to thrive: A model of cross-system and cross-sector relational health to promote early childhood development across the child-serving ecosystem.

Early relational health between caregivers and children is foundational for child health and well-being. Children and caregivers are also embedded within multiple systems and sectors, or a "child-serving ecosystem", that shapes child development. Although the COVID-19 pandemic has made this embeddedness abundantly clear, systems remain siloed and lack coordination. Fostering relational health amongst layers of this ecosystem may be a way to systematically support young children and families who are facing adversity. We integrate theory, examples, and empirical findings to develop a conceptual model informed by infant mental health and public health frameworks that illustrates how relational health across the child-serving ecosystem may promote child health and well-being at a population level. Our model articulates what relational health looks like across levels of this ecosystem from primary caregiver-child relationships, to secondary relationships between caregivers and child-serving systems, to tertiary relationships among systems that shape child outcomes directly and indirectly. We posit that positive relational health across levels is critical for promoting child health and well-being broadly. We provide examples of evidence-based approaches that address primary, secondary, and tertiary relational health, and suggest ways to promote relational health through cross-sector training and psychoeducation in the science of early development. This model conceptualizes relational health across the child-serving ecosystem and can serve as a template for promoting child health and well-being in the context of adversity.

La salud de la temprana relación entre quienes prestan cuidado y los niños es fundamental para la salud y el bienestar del niño. Los niños y quienes les cuidan forman parte de múltiples sistemas y sectores, o un "ecosistema de servicio al niño," que moldea el desarrollo del niño. Aunque la pandemia del COVID-19 ha demostrado abundante y claramente esta pertenencia, los sistemas permanecen aislados y les hace falta coordinación. Fomentar la salud de la relación entre las capas del ecosistema pudiera ser una manera de apoyar sistemáticamente a los niños pequeños y familias que se enfrentan con situaciones adversas. Presentamos un modelo conceptual con base en marcos de trabajo de la salud mental infantil y la salud pública que ilustra cómo la salud de la relación a lo largo del ecosistema de servicio al niño pudiera promover el desarrollo del niño al nivel de grupo de población. Nuestro modelo articula cómo aparece la salud de la relación a lo largo de los niveles del ecosistema desde las relaciones entre quien presta el cuidado primario y el niño, hasta las relaciones secundarias entre quienes prestan el cuidado y loa sistemas de servicio al niño, y las relaciones terciarias entre sistemas que amoldan directa e indirectamente los resultados en el niño. Una positiva salud de la relación a través de todos los niveles es esencial para promover la salud y el bienestar del niño de manera amplia. Describimos ejemplos específicos de salud de la relación primaria, secundaria y terciaria, y sugerimos maneras de promover la salud de la relación a través del entrenamiento intersectorial y la educación sicológica dentro de la ciencia del desarrollo temprano. Este modelo conceptualiza la salud de la relación a lo largo del ecosistema de servicio al niño y puede ser un esquema patrón para promover el desarrollo del niño dentro del contexto de situaciones adversas.

La Santé Relationnelle Précoce entre les personnes prenant soin des enfants et les enfants est fondamentale pour la santé de l'enfant et son bien-être. Les enfants et les personnes prenant soin d'eux sont encastrés dans de multiples systèmes et des secteurs, ou un « écosystème ¼ servant l'enfant qui forme le développement de l'enfant. Bien que la pandémie du Covid19 ait rendu cet encastrement très clair, les systèmes demeurent compartimentés et manquent de coordination. Cultiver la santé relationnelle au sein des couches de l'écosystème pourrait s'avérer être une manière de soutenir des jeunes enfants et les familles faisant face aux obstacles. Nous présentons un modèle conceptuel informé par les structures de la santé mentale du nourrisson et de la santé publique qui illustre la manière dont la santé relationnelle au travers de l'écosystème servant les enfants peut promouvoir le développement de l'enfant au niveau de la population. Notre modèle articule ce à quoi la santé relationnelle ressemble au travers des niveaux de l'écosystème, des relations entre la personne principale qui s'occupe de l'enfant et l'enfant aux relations secondaires entre les personnes prenant soin de l'enfant et les systèmes servant l'enfant, jusqu'aux relations tertiaires entres les systèmes qui donnent forme aux résultats directement et indirectement. Une santé relationnelle positive au travers de tous les niveaux est critique pour la promotion de la santé de l'enfant et de son bien-être en général. Nous décrivons des exemples spécifiques de santé relationnelle primaire, secondaire et tertiaire, et suggérons des manières de promouvoir la santé relationnelle au travers de la formation entre secteurs et de la psychoéducation dans la science du développement précoce. Ce modèle conceptualise la santé relationnelle au travers de l'écosystème servant l'enfant et peut servir de modèle pour la promotion du développement de l'enfant dans le contexte de l'adversité.

Perinatal insurance coverage and behavioural health-related maternal mortality.

Increases in postpartum maternal deaths, including a substantial number associated with behavioural health conditions, are a public health crisis and have contributed to overall increases in maternal mortality. A leading hypothesis to explain this pattern suggests lack of availability or continuity of resources for behavioural health treatment after delivery, often secondary to lapses in insurance coverage. Extending postpartum Medicaid coverage through the first year postpartum could mitigate excess morbidity and mortality among postpartum individuals, particularly those with behavioural health conditions.

Prevalence of Central Nervous System-Active Polypharmacy Among Older Adults With Dementia in the US.

Importance: Community-dwelling older adults with dementia have a high prevalence of psychotropic and opioid use. In these patients, central nervous system (CNS)-active polypharmacy may increase the risk for impaired cognition, fall-related injury, and death. Objective: To determine the extent of CNS-active polypharmacy among community-dwelling older adults with dementia in the US. Design, Setting, and Participants: Cross-sectional analysis of all community-dwelling older adults with dementia (identified by International Classification of Diseases, Ninth Revision, Clinical Modification or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis codes; N = 1 159 968) and traditional Medicare coverage from 2015 to 2017. Medication exposure was estimated using prescription fills between October 1, 2017, and December 31, 2018. Exposures: Part D coverage during the observation year (January 1-December 31, 2018). Main Outcomes and Measures: The primary outcome was the prevalence of CNS-active polypharmacy in 2018, defined as exposure to 3 or more medications for longer than 30 days consecutively from the following classes: antidepressants, antipsychotics, antiepileptics, benzodiazepines, nonbenzodiazepine benzodiazepine receptor agonist hypnotics, and opioids. Among those who met the criterion for polypharmacy, duration of exposure, number of distinct medications and classes prescribed, common class combinations, and the most commonly used CNS-active medications also were determined. Results: The study included 1 159 968 older adults with dementia (median age, 83.0 years [interquartile range {IQR}, 77.0-88.6 years]; 65.2% were female), of whom 13.9% (n = 161 412) met the criterion for CNS-active polypharmacy (32 139 610 polypharmacy-days of exposure). Those with CNS-active polypharmacy had a median age of 79.4 years (IQR, 74.0-85.5 years) and 71.2% were female. Among those who met the criterion for CNS-active polypharmacy, the median number of polypharmacy-days was 193 (IQR, 88-315 polypharmacy-days). Of those with CNS-active polypharmacy, 57.8% were exposed for longer than 180 days and 6.8% for 365 days; 29.4% were exposed to 5 or more medications and 5.2% were exposed to 5 or more medication classes. Ninety-two percent of polypharmacy-days included an antidepressant, 47.1% included an antipsychotic, and 40.7% included a benzodiazepine. The most common medication class combination included an antidepressant, an antiepileptic, and an antipsychotic (12.9% of polypharmacy-days). Gabapentin was the most common medication and was associated with 33.0% of polypharmacy-days. Conclusions and Relevance: In this cross-sectional analysis of Medicare claims data, 13.9% of older adults with dementia in 2018 filled prescriptions consistent with CNS-active polypharmacy. The lack of information on prescribing indications limits judgments about clinical appropriateness of medication combinations for individual patients.

Use of Medications for Treatment of Opioid Use Disorder Among US Medicaid Enrollees in 11 States, 2014-2018.

Importance: There is limited information about trends in the treatment of opioid use disorder (OUD) among Medicaid enrollees. Objective: To examine the use of medications for OUD and potential indicators of quality of care in multiple states. Design, Setting, and Participants: Exploratory serial cross-sectional study of 1 024 301 Medicaid enrollees in 11 states aged 12 through 64 years (not eligible for Medicare) with International Classification of Diseases, Ninth Revision (ICD-9 or ICD-10) codes for OUD from 2014 through 2018. Each state used generalized estimating equations to estimate associations between enrollee characteristics and outcome measure prevalence, subsequently pooled to generate global estimates using random effects meta-analyses. Exposures: Calendar year, demographic characteristics, eligibility groups, and comorbidities. Main Outcomes and Measures: Use of medications for OUD (buprenorphine, methadone, or naltrexone); potential indicators of good quality (OUD medication continuity for 180 days, behavioral health counseling, urine drug tests); potential indicators of poor quality (prescribing of opioid analgesics and benzodiazepines). Results: In 2018, 41.7% of Medicaid enrollees with OUD were aged 21 through 34 years, 51.2% were female, 76.1% were non-Hispanic White, 50.7% were eligible through Medicaid expansion, and 50.6% had other substance use disorders. Prevalence of OUD increased in these 11 states from 3.3% (290 628 of 8 737 082) in 2014 to 5.0% (527 983 of 10 585 790) in 2018. The pooled prevalence of enrollees with OUD receiving medication treatment increased from 47.8% in 2014 (range across states, 35.3% to 74.5%) to 57.1% in 2018 (range, 45.7% to 71.7%). The overall prevalence of enrollees receiving 180 days of continuous medications for OUD did not significantly change from the 2014-2015 to 2017-2018 periods (-0.01 prevalence difference, 95% CI, -0.03 to 0.02) with state variability in trend (90% prediction interval, -0.08 to 0.06). Non-Hispanic Black enrollees had lower OUD medication use than White enrollees (prevalence ratio [PR], 0.72; 95% CI, 0.64 to 0.81; P < .001; 90% prediction interval, 0.52 to 1.00). Pregnant women had higher use of OUD medications (PR, 1.18; 95% CI, 1.11-1.25; P < .001; 90% prediction interval, 1.01-1.38) and medication continuity (PR, 1.14; 95% CI, 1.10-1.17, P < .001; 90% prediction interval, 1.06-1.22) than did other eligibility groups. Conclusions and Relevance: Among US Medicaid enrollees in 11 states, the prevalence of medication use for treatment of opioid use disorder increased from 2014 through 2018. The pattern in other states requires further research.

New persistent opioid use after acute opioid prescribing in pregnancy: a nationwide analysis.

OBJECTIVE: To evaluate the association between opioid prescribing during pregnancy and new persistent opioid use in the year following delivery. MATERIALS AND METHODS: This nationwide retrospective cohort study included patients aged 12-55 years in Optum's deidentified Clinformatics Data Mart Database who were undergoing vaginal delivery or cesarean delivery from 2008 to 2016, with continuous enrollment from 2 years before birth to 1 year postdischarge. Women were included if they were opioid naive in pregnancy (ie, did not fill an opioid prescription 2 years to 9 months before delivery) and did not undergo a procedure within the year after discharge. The exposure was filling an opioid prescription in pregnancy. The primary outcome was new persistent opioid use, defined as a pharmacy claim for ≥1 opioid prescription between 4 and 90 days postdischarge and ≥1 prescription between 91 and 365 days postdischarge. Clinical and demographic covariates were included. Analyses included descriptive statistics and multivariable logistic regression, adjusting for clinical and demographic covariates. RESULTS: Of 158,425 childbirths identified, 101,013 (63.8%) were by vaginal delivery and 57,412 (36.2%) cesarean delivery. Among all patients, 6.0% (9429) filled an opioid prescription during pregnancy. The factors associated with filling an opioid in pregnancy were having a nondelivery procedure in pregnancy (adjusted odds ratio, 9.60; 95% confidence interval, 8.81-10.47) and having an emergency room visit during pregnancy (adjusted odds ratio, 2.48; 95% confidence interval, 2.37-2.59). Of women who received an opioid in pregnancy, 4% (379) developed new persistent opioid use. The factors most associated with new persistent opioid use were receiving an opioid prescription during pregnancy (adjusted odds ratio, 3.45; 95% confidence interval, 3.04-3.92) and filling a peripartum opioid prescription (1 week prior to 3 days postdischarge) adjusted odds ratio, 2.28, 95% confidence interval (2.02-2.57). Though having a procedure during pregnancy was associated with increased receipt of an opioid prescription, it was also associated with reduced new persistent opioid use (adjusted odds ratio, 0.72; 95% confidence interval, 0.52-0.99). CONCLUSION: Women who receive an opioid prescription during pregnancy are more likely to experience new persistent opioid use. Maternity care providers must balance pain management in pregnancy with potential risks of opioids.

Financial Toll of Untreated Perinatal Mood and Anxiety Disorders Among 2017 Births in the United States.

Objectives. To estimate the economic burden of untreated perinatal mood and anxiety disorders (PMADs) among 2017 births in the United States.Methods. We developed a mathematical model based on a cost-of-illness approach to estimate the impacts of exposure to untreated PMADs on mothers and children. Our model estimated the costs incurred by mothers and their babies born in 2017, projected from conception through the first 5 years of the birth cohort's lives. We determined model inputs from secondary data sources and a literature review.Results. We estimated PMADs to cost $14 billion for the 2017 birth cohort from conception to 5 years postpartum. The average cost per affected mother-child dyad was about $31 800. Mothers incurred 65% of the costs; children incurred 35%. The largest costs were attributable to reduced economic productivity among affected mothers, more preterm births, and increases in other maternal health expenditures.Conclusions. The US economic burden of PMADs is high. Efforts to lower the prevalence of untreated PMADs could lead to substantial economic savings for employers, insurers, the government, and society.

Modeling smoking-attributable mortality among adults with major depression in the United States.

Tobacco-related health disparities disproportionately affect smokers with major depression (MD). Although tobacco simulation models have been applied to general populations, to date they have not considered populations with a comorbid mental health condition. We developed and calibrated a simulation model of smoking and MD comorbidity for the US adult population using the 2005-2018 National Surveys on Drug Use and Health. We use this model to evaluate trends in smoking prevalence, smoking-attributable mortality and life-years lost among adults with MD, and changes in smoking prevalence by mental health status from 2018 to 2060. The model integrates known interaction effects between smoking initiation and cessation, and MD onset and recurrence. We show that from 2018 to 2060, smoking prevalence will continue declining among those with current MD. In the absence of intervention, people with MD will be increasingly disproportionately affected by smoking compared to the general population; our model shows that the smoking prevalence ratio between those with current MD and those without a history of MD increases from 1.54 to 2.42 for men and from 1.81 to 2.73 for women during this time period. From 2018 to 2060, approximately 484,000 smoking-attributable deaths will occur among adults with current MD, leading to 11.3 million life-years lost. Ambitious tobacco control efforts could alter this trajectory. With aggressive public health efforts, up to 264,000 of those premature deaths could be avoided, translating into 7.5 million life years gained. This model can compare the relative health gains across different intervention strategies for smokers with MD.

Perinatal mood and anxiety disorders, serious mental illness, and delivery-related health outcomes, United States, 2006-2015.

BACKGROUND: National estimates of perinatal mood and anxiety disorders (PMAD) and serious mental illness (SMI) among delivering women over time, as well as associated outcomes and costs, are lacking. The prevalence of perinatal mood and anxiety disorders and serious mental illness from 2006 to 2015 were estimated as well as associated risk of adverse obstetric outcomes, including severe maternal morbidity and mortality (SMMM), and delivery costs. METHODS: The study was a serial, cross-sectional analysis of National Inpatient Sample data. The prevalence of PMAD and SMI was estimated among delivering women as well as obstetric outcomes, healthcare utilization, and delivery costs using adjusted weighted logistic with predictive margins and generalized linear regression models, respectively. RESULTS: The study included an estimated 39,025,974 delivery hospitalizations from 2006 to 2015 in the U.S. PMAD increased from 18.4 (95% CI 16.4-20.0) to 40.4 (95% CI 39.3-41.6) per 1000 deliveries. SMI also increased among delivering women over time, from 4.2 (95% CI 3.9-4.6) to 8.1 (95% CI 7.9-8.4) per 1000 deliveries. Medicaid covered 72% (95% CI 71.2-72.9) of deliveries complicated by SMI compared to 44% (95% CI 43.1-45.0) and 43.5% (95% CI 42.5-44.5) among PMAD and all other deliveries, respectively. Women with PMAD and SMI experienced higher incidence of SMMM, and increased hospital transfers, lengths of stay, and delivery-related costs compared to other deliveries (P < .001 for all). CONCLUSION: Over the past decade, the prevalence of both PMAD and SMI among delivering women increased substantially across the United States, and affected women had more adverse obstetric outcomes and delivery-related costs compared to other deliveries.

The Cost-Effectiveness of Cognitive Behavioral Therapy Versus Second-Generation Antidepressants for Initial Treatment of Major Depressive Disorder in the United States: A Decision Analytic Model.

Background: Most guidelines for major depressive disorder recommend initial treatment with either a second-generation antidepressant (SGA) or cognitive behavioral therapy (CBT). Although most trials suggest that these treatments have similar efficacy, their health economic implications are uncertain. Objective: To quantify the cost-effectiveness of CBT versus SGA for initial treatment of depression. Design: Decision analytic model. Data Sources: Relative effectiveness data from a meta-analysis of randomized controlled trials; additional clinical and economic data from other publications. Target Population: Adults with newly diagnosed major depressive disorder in the United States. Time Horizon: 1 to 5 years. Perspectives: Health care sector and societal. Intervention: Initial treatment with either an SGA or group and individual CBT. Outcome Measures: Costs in 2014 U.S. dollars, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. Results of Base-Case Analysis: In model projections, CBT produced higher QALYs (3 days more at 1 year and 20 days more at 5 years) with higher costs at 1 year (health care sector, $900; societal, $1500) but lower costs at 5 years (health care sector, -$1800; societal, -$2500). Results of Sensitivity Analysis: In probabilistic sensitivity analyses, SGA had a 64% to 77% likelihood of having an incremental cost-effectiveness ratio of $100 000 or less per QALY at 1 year; CBT had a 73% to 77% likelihood at 5 years. Uncertainty in the relative risk for relapse of depression contributed the most to overall uncertainty in the optimal treatment. Limitation: Long-term trials comparing CBT and SGA are lacking. Conclusion: Neither SGAs nor CBT provides consistently superior cost-effectiveness relative to the other. Given many patients' preference for psychotherapy over pharmacotherapy, increasing patient access to CBT may be warranted. Primary Funding Source: Department of Veterans Affairs, National Institute of Mental Health.