Incidence of Lung Cancer Among Never-Smoking Asian American, Native Hawaiian, and Pacific Islander Females.

BACKGROUND: Although lung cancer incidence rates according to smoking status, sex, and detailed race/ethnicity have not been available, it is estimated that more than half of Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females with lung cancer have never smoked. METHODS: We calculated age-adjusted incidence rates for lung cancer according to smoking status and detailed race/ethnicity among females, focusing on AANHPI ethnic groups, and assessed relative incidence across racial/ethnic groups. We used a large-scale dataset that integrates data from electronic health records from 2 large health-care systems-Sutter Health in Northern California and Kaiser Permanente Hawai'i-linked to state cancer registries for incident lung cancer diagnoses between 2000 and 2013. The study population included 1 222 694 females (n = 244 147 AANHPI), 3297 of which were diagnosed with lung cancer (n = 535 AANHPI). RESULTS: Incidence of lung cancer among never-smoking AANHPI as an aggregate group was 17.1 per 100 000 (95% confidence interval [CI] = 14.9 to 19.4) but varied widely across ethnic groups. Never-smoking Chinese American females had the highest rate (22.8 per 100 000, 95% CI = 17.3 to 29.1). Except for Japanese American females, incidence among every never-smoking AANHPI female ethnic group was higher than that of never-smoking non-Hispanic White females, from 66% greater among Native Hawaiian females (incidence rate ratio = 1.66, 95% CI = 1.03 to 2.56) to more than 100% greater among Chinese American females (incidence rate ratio = 2.26, 95% CI = 1.67 to 3.02). CONCLUSIONS: Our study revealed high rates of lung cancer among most never-smoking AANHPI female ethnic groups. Our approach illustrates the use of innovative data integration to dispel the myth that AANHPI females are at overall reduced risk of lung cancer and demonstrates the need to disaggregate this highly diverse population.

Predicting suicide attempts and suicide deaths among adolescents following outpatient visits.

BACKGROUND: Few studies report on machine learning models for suicide risk prediction in adolescents and their utility in identifying those in need of further evaluation. This study examined whether a model trained and validated using data from all age groups works as well for adolescents or whether it could be improved. METHODS: We used healthcare data for 1.4 million specialty mental health and primary care outpatient visits among 256,823 adolescents across 7 health systems. The prediction target was 90-day risk of suicide attempt following a visit. We used logistic regression with least absolute shrinkage and selection operator (LASSO) and generalized estimating equations (GEE) to predict risk. We compared performance of three models: an existing model, a recalibrated version of that model, and a newly-learned model. Models were compared using area under the receiver operating curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: The AUC produced by the existing model for specialty mental health visits estimated in adolescents alone (0.796; [0.789, 0.802]) was not significantly different than the AUC of the recalibrated existing model (0.794; [0.787, 0.80]) or the newly-learned model (0.795; [0.789, 0.801]). Predicted risk following primary care visits was also similar: existing (0.855; [0.844, 0.866]), recalibrated (0.85 [0.839, 0.862]), newly-learned (0.842, [0.829, 0.854]). LIMITATIONS: The models did not incorporate non-healthcare risk factors. The models relied on ICD9-CM codes for diagnoses and outcome measurement. CONCLUSIONS: Prediction models already in operational use by health systems can be reliably employed for identifying adolescents in need of further evaluation.

Integrating Electronic Health Record, Cancer Registry, and Geospatial Data to Study Lung Cancer in Asian American, Native Hawaiian, and Pacific Islander Ethnic Groups.

BACKGROUND: A relatively high proportion of Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females with lung cancer have never smoked. We used an integrative data approach to assemble a large-scale cohort to study lung cancer risk among AANHPIs by smoking status with attention to representation of specific AANHPI ethnic groups. METHODS: We leveraged electronic health records (EHRs) from two healthcare systems-Sutter Health in northern California and Kaiser Permanente Hawai'i-that have high representation of AANHPI populations. We linked EHR data on lung cancer risk factors (i.e., smoking, lung diseases, infections, reproductive factors, and body size) to data on incident lung cancer diagnoses from statewide population-based cancer registries of California and Hawai'i for the period between 2000 and 2013. Geocoded address data were linked to data on neighborhood contextual factors and regional air pollutants. RESULTS: The dataset comprises over 2.2 million adult females and males of any race/ethnicity. Over 250,000 are AANHPI females (19.6% of the female study population). Smoking status is available for over 95% of individuals. The dataset includes 7,274 lung cancer cases, including 613 cases among AANHPI females. Prevalence of never-smoking status varied greatly among AANHPI females with incident lung cancer, from 85.7% among Asian Indian to 14.4% among Native Hawaiian females. CONCLUSION: We have developed a large, multilevel dataset particularly well-suited to conduct prospective studies of lung cancer risk among AANHPI females who never smoked. IMPACT: The integrative data approach is an effective way to conduct cancer research assessing multilevel factors on cancer outcomes among small populations.

Weighing the Association Between BMI Change and Suicide Mortality.

OBJECTIVE: Suicide rates continue to rise, necessitating the identification of risk factors. Obesity and suicide mortality rates have been examined, but associations among weight change, death by suicide, and depression among adults in the United States remain unclear. METHODS: Data from 387 people who died by suicide in 2000-2015 with a recorded body mass index (BMI) in the first and second 6 months preceding their death ("index date") were extracted from the Mental Health Research Network. Each person was matched with five people in a control group (comprising individuals who did not die by suicide) by age, sex, index year, and health care site (N=1,935). RESULTS: People who died by suicide were predominantly male (71%), White (69%), and middle aged (mean age=57 years) and had a depression diagnosis (55%) and chronic health issues (57%) (corresponding results for the control group: 71% male, 66% White, 14% with depression diagnosis, and 43% with chronic health issues; mean age=56 years). Change in BMI within the year before the index date statistically significantly differed between those who died by suicide (mean change=-0.72±2.42 kg/m2) and the control group (mean change=0.06±4.99 kg/m2) (p<0.001, Cohen's d=0.17). A one-unit BMI decrease was associated with increased risk for suicide after adjustment for demographic characteristics, mental disorders, and Charlson comorbidity score (adjusted odds ratio=1.11, 95% confidence interval=1.05-1.18, p<0.001). For those without depression, a BMI change was significantly associated with suicide (p<0.001). CONCLUSIONS: An increased suicide mortality rate was associated with weight loss in the year before a suicide after analyses accounted for general and mental health indicators.

Serious Suicide Attempts and Risk of Suicide Death.

Background: In the US, more than one million people attempt suicide each year. History of suicide attempt is a significant risk factor for death by suicide; however, there is a paucity of data from the US general population on this relationship. Aim: The objective of this study was to examine suicide attempts needing medical attention as a risk for suicide death. Method: We conducted a case-control study involving eight US healthcare systems. A total of 2,674 individuals who died by suicide from 2000 to 2013 were matched to 267,400 individuals by year and location. Results: Prior suicide attempt associated with a medical visit increases risk for suicide death by 39.1 times, particularly for women (OR = 79.2). However, only 11.3% of suicide deaths were associated with an attempt that required medical attention. The association was the strongest for children 10-14 years old (OR = 98.0). Most suicide attempts were recorded during the 20-week period prior to death. Limitations: Our study is limited to suicide attempts for which individuals sought medical care. Conclusion: In the US, prior suicide attempt is associated with an increased risk of suicide death; the risk is high especially during the period immediately following a nonlethal attempt.

Chronic pain diagnoses and opioid dispensings among insured individuals with serious mental illness.

BACKGROUND: Individuals with major depressive disorder (MDD) and bipolar disorder (BD) have particularly high rates of chronic non-cancer pain (CNCP) and are also more likely to receive prescription opioids for their pain. However, there have been no known studies published to date that have examined opioid treatment patterns among individuals with schizophrenia. METHODS: Using electronic medical record data across 13 Mental Health Research Network sites, individuals with diagnoses of MDD (N = 65,750), BD (N = 38,117) or schizophrenia or schizoaffective disorder (N = 12,916) were identified and matched on age, sex and Medicare status to controls with no documented mental illness. CNCP diagnoses and prescription opioid medication dispensings were extracted for the matched samples. Multivariate analyses were conducted to evaluate (1) the odds of receiving a pain-related diagnosis and (2) the odds of receiving opioids, by separate mental illness diagnosis category compared with matched controls, controlling for age, sex, Medicare status, race/ethnicity, income, medical comorbidities, healthcare utilization and chronic pain diagnoses. RESULTS: Multivariable models indicated that having a MDD (OR = 1.90; 95% CI = 1.85-1.95) or BD (OR = 1.71; 95% CI = 1.66-1.77) diagnosis was associated with increased odds of a CNCP diagnosis after controlling for age, sex, race, income, medical comorbidities and healthcare utilization. By contrast, having a schizophrenia diagnosis was associated with decreased odds of receiving a chronic pain diagnosis (OR = 0.86; 95% CI = 0.82-0.90). Having a MDD (OR = 2.59; 95% CI = 2.44-2.75) or BD (OR = 2.12; 95% CI = 1.97-2.28) diagnosis was associated with increased odds of receiving chronic opioid medications, even after controlling for age, sex, race, income, medical comorbidities, healthcare utilization and chronic pain diagnosis; having a schizophrenia diagnosis was not associated with receiving chronic opioid medications. CONCLUSIONS: Individuals with serious mental illness, who are most at risk for developing opioid-related problems, continue to be prescribed opioids more often than their peers without mental illness. Mental health clinicians may be particularly well-suited to lead pain assessment and management efforts for these patients. Future research is needed to evaluate the effectiveness of involving mental health clinicians in these efforts.

Substance use disorders and risk of suicide in a general US population: a case control study.

BACKGROUND: Prior research suggests that substance use disorders (SUDs) are associated with risk of suicide mortality, but most previous work has been conducted among Veterans Health Administration patients. Few studies have examined the relationship between SUDs and suicide mortality in general populations. Our study estimates the association of SUDs with suicide mortality in a general US population of men and women who receive care across eight integrated health systems. METHODS: We conducted a case-control study using electronic health records and claims data from eight integrated health systems of the Mental Health Research Network. Participants were 2674 men and women who died by suicide between 2000-2013 and 267,400 matched controls. The main outcome was suicide mortality, assessed using data from the health systems and confirmed by state death data systems. Demographic and diagnostic data on substance use disorders and other health conditions were obtained from each health system. First, we compared descriptive statistics for cases and controls, including age, gender, income, and education. Next, we compared the rate of each substance use disorder category for cases and controls. Finally, we used conditional logistic regression models to estimate unadjusted and adjusted odds of suicide associated with each substance use disorder category. RESULTS: All categories of substance use disorders were associated with increased risk of suicide mortality. Adjusted odds ratios ranged from 2.0 (CI 1.7, 2.3) for patients with tobacco use disorder only to 11.2 (CI 8.0, 15.6) for patients with multiple alcohol, drug, and tobacco use disorders. Substance use disorders were associated with increased relative risk of suicide for both women and men across all categories, but the relative risk was more pronounced in women. CONCLUSIONS: Substance use disorders are associated with significant risk of suicide mortality, especially for women, even after controlling for other important risk factors. Experiencing multiple substance use disorders is particularly risky. These findings suggest increased suicide risk screening and prevention efforts for individuals with substance use disorders are needed.

Association between suicide death and concordance with benzodiazepine treatment guidelines for anxiety and sleep disorders.

OBJECTIVE: Guidelines for management of anxiety and sleep disorders emphasize antidepressant medications and/or psychotherapy as first/second-line and benzodiazepines as third-line treatments. We evaluated the association between suicide death and concordance with benzodiazepine guidelines. METHODS: Retrospective case-control study of patients with anxiety and/or sleep disorders from health systems across 8 U.S. states within the Mental Health Research Network. Suicide death cases were matched to controls on year and health system. Appropriate benzodiazepine prescribing defined as: no monotherapy, no long duration, and/or age < 65 years. The association between guideline concordance and suicide death was evaluated, adjusting for diagnostic and treatment covariates. RESULTS: Sample included 6960 patients with anxiety disorders (2363 filled benzodiazepine) and 6215 with sleep disorders (1237 filled benzodiazepine). Benzodiazepine guideline concordance was associated with reduced odds for suicide in patients with anxiety disorders (OR = 0.611, 95% CI = 0.392-0.953, p = 0.03) and was driven by shorter duration of benzodiazepine use with concomitant psychotherapy or antidepressant medication. The association of benzodiazepine guideline concordance with suicide death did not meet statistical significance in the sleep disorder group (OR = 0.413, 95% CI = 0.154-1.11, p = 0.08). CONCLUSIONS: We found reduced odds for suicide in those with anxiety disorders who filled benzodiazepines in short-moderate duration with concomitant psychotherapy or antidepressant treatment.

Variation in patterns of health care before suicide: A population case-control study.

BACKGROUND: The United States has experienced a significant rise in suicide. As decision makers identify how to address this national concern, healthcare systems have been identified as an optimal location for prevention. OBJECTIVE: To compare variation in patterns of healthcare use, by health setting, between individuals who died by suicide and the general population. DESIGN: Case-Control Study. SETTING: Eight healthcare systems across the United States. PARTICIPANTS: 2674 individuals who died by suicide between 2000 and 2013 along with 267,400 individuals matched on time-period of health plan membership and health system affiliation. MEASUREMENTS: Healthcare use in the emergency room, inpatient hospital, primary care, and outpatient specialty setting measured using electronic health record data during the 7-, 30-, 60-, 90-, 180-, and 365-day time periods before suicide and matched index date for controls. RESULTS: Healthcare use was more common across all healthcare settings for individuals who died by suicide. Nearly 30% of individuals had a healthcare visit in the 7-days before suicide (6.5% emergency, 16.3% outpatient specialty, and 9.5% primary care), over half within 30 days, and >90% within 365 days. Those who died by suicide averaged 16.7 healthcare visits during the year. The relative risk of suicide was greatest for individuals who received care in the inpatient setting (aOR = 6.23). There was both a large relative risk (aOR = 3.08) and absolute utilization rate (43.8%) in the emergency room before suicide. LIMITATIONS: Participant race/ethnicity was not available. The sample did not include uninsured individuals. CONCLUSIONS: This study provides important data about how care utilization differs for those who die by suicide compared to the general population and can inform decision makers on targeting of suicide prevention activities within health systems.

Diagnosed Mental Health Conditions and Risk of Suicide Mortality.

OBJECTIVE: Although mental health conditions are risk factors for suicide, limited data are available on suicide mortality associated with specific mental health conditions in the U.S. population. This study aimed to fill this gap. METHODS: This study used a case-control design. Patients in the case group were those who died by suicide between 2000 and 2013 and who were patients in eight health care systems in the Mental Health Research Network (N=2,674). Each was matched with 100 general population patients from the same system (N=267,400). Diagnostic codes for five mental health conditions in the year before death were obtained from medical records: anxiety disorders, attention deficit-hyperactivity disorder (ADHD), bipolar disorder, depressive disorders, and schizophrenia spectrum disorder. RESULTS: Among patients in the case group, 51.3% had a recorded psychiatric diagnosis in the year before death, compared with 12.7% of control group patients. Risk of suicide mortality was highest among those with schizophrenia spectrum disorder, after adjustment for age and sociodemographic characteristics (adjusted odds ratio [AOR]=15.0) followed by bipolar disorder (AOR=13.2), depressive disorders (AOR=7.2), anxiety disorders (AOR=5.8), and ADHD (AOR=2.4). The risk of suicide death among those with a diagnosed bipolar disorder was higher in women than men. CONCLUSIONS: Half of those who died by suicide had at least one diagnosed mental health condition in the year before death, and most mental health conditions were associated with an increased risk of suicide. Findings suggest the importance of suicide screening and providing an approach to improve awareness of mental health conditions.

Assessing and Minimizing Re-identification Risk in Research Data Derived from Health Care Records.

BACKGROUND: Sharing of research data derived from health system records supports the rigor and reproducibility of primary research and can accelerate research progress through secondary use. But public sharing of such data can create risk of re-identifying individuals, exposing sensitive health information. METHOD: We describe a framework for assessing re-identification risk that includes: identifying data elements in a research dataset that overlap with external data sources, identifying small classes of records defined by unique combinations of those data elements, and considering the pattern of population overlap between the research dataset and an external source. We also describe alternative strategies for mitigating risk when the external data source can or cannot be directly examined. RESULTS: We illustrate this framework using the example of a large database used to develop and validate models predicting suicidal behavior after an outpatient visit. We identify elements in the research dataset that might create risk and propose a specific risk mitigation strategy: deleting indicators for health system (a proxy for state of residence) and visit year. DISCUSSION: Researchers holding health system data must balance the public health value of data sharing against the duty to protect the privacy of health system members. Specific steps can provide a useful estimate of re-identification risk and point to effective risk mitigation strategies.

The Mediating Effect of Sleep Disturbance on the Relationship Between Nonmalignant Chronic Pain and Suicide Death.

IMPORTANCE: Few studies have examined the relationship between nonmalignant chronic pain (NMCP) and suicide death, and even fewer have specifically explored what role sleep disturbance might play in the association between NMCP and suicide death. OBJECTIVE: To assess whether sleep disturbance mediates the relationship between NMCP and suicide death. DESIGN: This case-control study included 2,674 individuals who died by suicide between 2000 and 2013 (cases) and 267,400 matched individuals (controls). SETTING: Eight Mental Health Research Network (MHRN)-affiliated healthcare systems. PARTICIPANTS: All cases and matched controls were health plan members for at least 10 months during the year prior to the index date. MAIN OUTCOMES AND MEASURES: Sociodemographic data and diagnosis codes for NMCP and sleep disorders were extracted from the MHRN's Virtual Data Warehouse. Suicide mortality was identified using International Statistical Classification of Diseases and Related Health Problems (ICD)-10 codes from official government mortality records matched to health system records. RESULTS: After accounting for covariates, there was a significant relationship between NMCP and sleep disturbance; those who were diagnosed with NMCP were more likely to develop subsequent sleep disturbance. Similarly, sleep disturbance was significantly associated with suicide death. Finally, a significant indirect effect of NMCP on suicide death, through sleep disturbance, and a nonsignificant direct effect of NMCP on suicide death provide support for a fully mediated model. CONCLUSIONS AND RELEVANCE: There is a need for clinicians to screen for both sleep disturbance and suicidal ideation in NMCP patients and for health systems to implement more widespread behavioral treatments that address comorbid sleep problems and NMCP.

Self-Reported Suicidal Ideation as a Predictor of Suicidal Behavior Among Outpatients With Diagnoses of Psychotic Disorders.

OBJECTIVE: Individuals with psychotic disorders are at high risk of suicidal behavior. The study examined whether response to item 9 of the Patient Health Questionnaire (PHQ-9), which asks about thoughts of death or self-harm, predicts suicidal behavior among outpatients with diagnoses of psychotic disorders. METHODS: Electronic health records (EHRs) from seven large integrated health systems were used to identify all outpatient visits by adults with a diagnosis of schizophrenia spectrum psychosis or unspecified psychosis from January 1, 2009, to June 30, 2015, during which a PHQ-9 was completed (N=32,982 visits by 5,947 patients). Suicide attempts over the 90 days following each visit were ascertained from EHRs and insurance claims. Suicide deaths were ascertained from state death certificate files. RESULTS: Risk of suicide attempt within 90 days of an outpatient visit was .8% among patients reporting no thoughts of death or self-harm and 3.5% among those reporting such thoughts "nearly every day." Over 90 days of follow-up, 47% of suicide attempts occurred among those who reported any recent thoughts of death or self-harm at the sampled visit. Also, 59% of attempts occurred among those reporting thoughts of death or self-harm at the index visit or any visit in the prior year. The number of suicide deaths within 90 days (N=10) was too small to accurately assess the relationship between PHQ-9 item 9 response and subsequent suicide death. CONCLUSIONS: Among outpatients with psychotic disorders, response to item 9 of the PHQ-9 accurately identified those at increased short-term risk of a suicide attempt.

General Medical, Mental Health, and Demographic Risk Factors Associated With Suicide by Firearm Compared With Other Means.

OBJECTIVE: Mitigation of suicide risk by reducing access to lethal means, such as firearms and potentially lethal medications, is a highly recommended practice. To better understand groups of patients at risk of suicide in medical settings, the authors compared demographic and clinical risk factors between patients who died by suicide by using firearms or other means with matched patients who did not die by suicide (control group). METHODS: In a case-control study in 2016 from eight health care systems within the Mental Health Research Network, 2,674 suicide cases from 2010-2013 were matched to a control group (N=267,400). The association between suicide by firearm or other means and medical record information on demographic characteristics, general medical disorders, and mental disorders was assessed. RESULTS: The odds of having a mental disorder were higher among cases of suicide involving a method other than a firearm. Fourteen general medical disorders were associated with statistically significant (p<.001) greater odds of suicide by firearm, including traumatic brain injury (TBI) (odds ratio [OR]=23.53), epilepsy (OR=3.17), psychogenic pain (OR=2.82), migraine (OR=2.35), and stroke (OR=2.20). Fifteen general medical disorders were associated with statistically significant (p<.001) greater odds of suicide by other means, with particularly high odds for TBI (OR=7.74), epilepsy (OR=3.28), HIV/AIDS (OR=6.03), and migraine (OR=3.17). CONCLUSIONS: Medical providers should consider targeting suicide risk screening for patients with any mental disorder, TBI, epilepsy, HIV, psychogenic pain, stroke, and migraine. When suicide risk is detected, counseling on reducing access to lethal means should include both firearms and other means for at-risk groups.

Dermatologic Conditions and Risk of Suicide: A Case-Control Study.

BACKGROUND: Patients diagnosed with skin conditions have a higher risk of comorbid psychiatric conditions and suicide-related outcomes such as suicidal ideations and behaviors. There is paucity of evidence in the US general population about the risk of suicide death in patients with dermatologic conditions. METHODS: We conducted a retrospective case-control study to investigate the risk of suicide death in patients receiving care for dermatologic conditions. This study involved 8 US health systems. A total of 2674 individuals who died by suicide (cases) were matched with 267,400 general population control individuals. RESULTS: After adjusting for age, sex, and any mental health or substance use condition, we did not find an association between death by suicide and any skin condition including conditions where clinicians are generally concerned about the risk such as acne (adjusted odds ratio [aOR] = 1.04, p = 0.814), atopic dermatitis (aOR = 0.77, p = 0.28), and psoriasis (aOR = 0.91, p = 0.64). CONCLUSION: This case-control study provides no evidence of increased risk of death by suicide in individuals with major skin disorders in the US general population.

The impact of race and ethnicity on rates of return to psychotherapy for depression.

BACKGROUND: There are many limitations with the evidence base for the role of race and ethnicity in continuation of psychotherapy for depression. METHODS: The study sample consisted of 242,765 patients ≥ 18 years old from six healthcare systems in the Mental Health Research Network (MHRN) who had a new episode of psychotherapy treatment for depression between 1/1/2010 and 12/31/2013. Data were from electronic medical records and organized in a Virtual Data Warehouse (VDW). The odds of racial and ethnic minority patients returning for a second psychotherapy visit within 45 days of the initial session were examined using multilevel regression. RESULTS: The sample was primarily middle aged (68%, 30-64 years old), female (68.5%), and non-Hispanic white (50.7%), had commercial insurance (81.4%), and a low comorbidity burden (68.8% had no major comorbidities). Return rates within 45 days of the first psychotherapy visit were 47.6%. Compared to their non-Hispanic white counterparts, racial and ethnic minority patients were somewhat less likely to return to psychotherapy for a second visit (adjusted odds ratios [aORs] ranged from 0.80 to 0.90). Healthcare system was a much stronger predictor of return rates (aORs ranged from 0.89 to 5.53), while providers accounted for 21.1% of the variance in return rates. CONCLUSIONS: Provider and healthcare system variation were stronger predictors of patient return to psychotherapy than race and ethnicity. More research is needed to understand why providers and healthcare systems determine psychotherapy return rates for patients of all racial and ethnic groups.

Major Physical Health Conditions and Risk of Suicide.

INTRODUCTION: Most individuals make healthcare visits before suicide, but many do not have a diagnosed mental health condition. This study seeks to investigate suicide risk among patients with a range of physical health conditions in a U.S. general population sample and whether risk persists after adjustment for mental health and substance use diagnoses. METHODS: This study included 2,674 individuals who died by suicide between 2000 and 2013 along with 267,400 controls matched on year and location in a case-control study conducted in 2016 across eight Mental Health Research Network healthcare systems. A total of 19 physical health conditions were identified using diagnostic codes within the healthcare systems' Virtual Data Warehouse, including electronic health record and insurance claims data, during the year before index date. RESULTS: Seventeen physical health conditions were associated with increased suicide risk after adjustment for age and sex (p<0.001); nine associations persisted after additional adjustment for mental health and substance use diagnoses. Three conditions had a more than twofold increased suicide risk: traumatic brain injury (AOR=8.80, p<0.001); sleep disorders; and HIV/AIDS. Multimorbidity was present in 38% of cases versus 15.5% of controls, and represented nearly a twofold increased risk for suicide. CONCLUSIONS: Although several individual conditions, for example, traumatic brain injury, were associated with high risk of suicide, nearly all physical health conditions increased suicide risk, even after adjustment for potential confounders. In addition, having multiple physical health conditions increased suicide risk substantially. These data support suicide prevention based on the overall burden of physical health.

ANTIDEPRESSANT ADHERENCE ACROSS DIVERSE POPULATIONS AND HEALTHCARE SETTINGS.

BACKGROUND: Early adherence is key to successful depression treatment, but nearly 60% of patients discontinue antidepressants within 3 months. Our study aimed to determine factors associated with poor early adherence to antidepressants in a large diverse sample of patients. METHODS: Six Mental Health Research Network healthcare systems contributed data for adults with depression and a new antidepressant start, defined by a washout period of at least 270 days, between January 1, 2010 and December 31, 2012. Pharmacy fill and self-reported race/ethnicity data were obtained from the electronic medical record. Patients had early adherence if they had a second antidepressant fill within 180 days of the first. We used logistic regression to investigate the relationship between early adherence and patient characteristics. RESULTS: A total of 177,469 adult patients had 184,967 new episodes of depression with a filled antidepressant prescription. Patients refilled their antidepressants within 180 days in 71% of episodes. Race/ethnicity was a strong predictor of early adherence, with patients from racial/ethnic minorities other than Native Americans/Alaskan Natives less likely (adjusted odd ratios 0.50-0.59) to refill their antidepressants than non-Hispanic whites. Age, neighborhood education, comorbidity burden, provider type and engagement in psychotherapy were also associated with adherence. Other apparent predictors of early adherence, including neighborhood income, gender, and prior mental health hospitalizations, were no longer significant in the fully adjusted model. CONCLUSIONS: Race/ethnicity was a robust predictor of early antidepressant adherence, with minority groups other than Native Americans/Alaskan Natives less likely to be adherent. Further research is needed to determine whether early nonadherence in specific minority populations is intentional, due to side effects or patient preference, or unintentional and appropriate for targeted interventions to improve adherence.

Racial-Ethnic Differences in Psychiatric Diagnoses and Treatment Across 11 Health Care Systems in the Mental Health Research Network.

OBJECTIVE: The objective of this study was to characterize racial-ethnic variation in diagnoses and treatment of mental disorders in large not-for-profit health care systems. METHODS: Participating systems were 11 private, not-for-profit health care organizations constituting the Mental Health Research Network, with a combined 7,523,956 patients age 18 or older who received care during 2011. Rates of diagnoses, prescription of psychotropic medications, and total formal psychotherapy sessions received were obtained from insurance claims and electronic medical record databases across all health care settings. RESULTS: Of the 7.5 million patients in the study, 1.2 million (15.6%) received a psychiatric diagnosis in 2011. This varied significantly by race-ethnicity, with Native American/Alaskan Native patients having the highest rates of any diagnosis (20.6%) and Asians having the lowest rates (7.5%). Among patients with a psychiatric diagnosis, 73% (N=850,585) received a psychotropic medication. Non-Hispanic white patients were significantly more likely (77.8%) than other racial-ethnic groups (odds ratio [OR] range .48-.81) to receive medication. In contrast, only 34% of patients with a psychiatric diagnosis (N=548,837) received formal psychotherapy. Racial-ethnic differences were most pronounced for depression and schizophrenia; compared with whites, non-Hispanic blacks were more likely to receive formal psychotherapy for their depression (OR=1.20) or for their schizophrenia (OR=2.64). CONCLUSIONS: There were significant racial-ethnic differences in diagnosis and treatment of psychiatric conditions across 11 U.S. health care systems. Further study is needed to understand underlying causes of these observed differences and whether processes and outcomes of care are equitable across these diverse patient populations.

Adherence to common cardiovascular medications in patients with schizophrenia vs. patients without psychiatric illness.

OBJECTIVE: The purpose of the study was to examine whether individuals with diagnoses of schizophrenia were differentially adherent to their statin or angiotensin-converting enzyme inhibitor/angiotensin receptor blocker (ACEI/ARB) medications compared to individuals without psychiatric illness. METHOD: Using electronic medical record data across 13 Mental Health Research Network sites, individuals with diagnoses of schizophrenia or schizoaffective disorder receiving two or more medication dispensings of a statin or an ACEI/ARB in 2011 (N=710) were identified and matched on age, sex and Medicare status to controls with no documented mental illness and two or more medication dispensings of a statin in 2011 (N=710). Medication adherence, and sociodemographic and clinical characteristics of the study population were assessed. RESULTS: Multivariable models indicated that having a schizophrenia diagnosis was associated with increased odds of statin medication adherence; the odds ratio suggested a small effect. After adjustment for medication regimen, schizophrenia no longer showed an association with statin adherence. Having a schizophrenia diagnosis was not associated with ACEI/ARB medication adherence. CONCLUSIONS: Compared to patients without any psychiatric illness, individuals with schizophrenia were marginally more likely to be adherent to their statin medications. Given that patterns of adherence to cardioprotective medications may be different from patterns of adherence to antipsychotic medications, improving adherence to the former may require unique intervention strategies.