Prevalence of cardiovascular disease among Asian, Pacific Islander and multi-race populations in Hawai'i and California.

BACKGROUND: Cardiovascular disease (CVD) remains the leading cause of death in the US. CVD incidence is influenced by many demographic, clinical, cultural, and psychosocial factors, including race and ethnicity. Despite recent research, there remain limitations on understanding CVD health among Asians and Pacific Islanders (APIs), particularly some subgroups and multi-racial populations. Combining diverse API populations into one study group and difficulties in defining API subpopulations and multi-race individuals have hampered efforts to identify and address health disparities in these growing populations. METHODS: The study cohort was comprised of all adult patients at Kaiser Permanente Hawai'i and Palo Alto Medical Foundation in California during 2014-2018 (n = 684,363). EHR-recorded ICD-9 and ICD-10 diagnosis codes were used to indicate coronary heart disease (CHD), stroke, peripheral vascular disease (PVD), and overall CVD. Self-reported race and ethnicity data were used to construct 12 mutually exclusive single and multi-race groups, and a Non-Hispanic White (NHW) comparison group. Logistic regression models were used to derive prevalence estimates, odds ratios, and confidence intervals for the 12 race/ethnicity groups. RESULTS: The prevalence of CHD and PVD varied 4-fold and stroke and overall CVD prevalence varied 3-fold across API subpopulations. Among Asians, the Filipino subgroup had the highest prevalence of all three CVD conditions and overall CVD. Chinese people had the lowest prevalence of CHD, PVD and overall CVD. In comparison to Native Hawaiians, Other Pacific Islanders had significantly higher prevalence of CHD. For the multi-race groups that included Native Hawaiians and Other Pacific Islanders, the prevalence of overall CVD was significantly higher than that for either single-race Native Hawaiians or Other Pacific Islanders. The multi-race Asian + White group had significantly higher overall CVD prevalence than both the NHW group and the highest Asian subgroup (Filipinos). CONCLUSIONS: Study findings revealed significant differences in overall CVD, CHD, stroke, and PVD among API subgroups. In addition to elevated risk among Filipino, Native Hawaiian, and Other Pacific Islander groups, the study identified particularly elevated risk among multi-race API groups. Differences in disease prevalence are likely mirrored in other cardiometabolic conditions, supporting the need to disaggregate API subgroups in health research.

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.

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.

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.

Treatment Initiation for New Episodes of Depression in Primary Care Settings.

BACKGROUND: Depression is prevalent and costly, but despite effective treatments, is often untreated. Recent efforts to improve depression care have focused on primary care settings. Disparities in treatment initiation for depression have been reported, with fewer minority and older individuals starting treatment. OBJECTIVE: To describe patient characteristics associated with depression treatment initiation and treatment choice (antidepressant medications or psychotherapy) among patients newly diagnosed with depression in primary care settings. DESIGN: A retrospective observational design was used to analyze electronic health record data. PATIENTS: A total of 241,251 adults newly diagnosed with depression in primary care settings among five health care systems from 2010 to 2013. MAIN MEASURES: ICD-9 codes for depression, following a 365-day period with no depression diagnosis or treatment, were used to identify new depression episodes. Treatment initiation was defined as a completed psychotherapy visit or a filled prescription for antidepressant medication within 90 days of diagnosis. Depression severity was measured with Patient Health Questionnaire (PHQ-9) scores on the day of diagnosis. KEY RESULTS: Overall, 35.7% of patients with newly diagnosed depression initiated treatment. The odds of treatment initiation among Asians, non-Hispanic blacks, and Hispanics were at least 30% lower than among non-Hispanic whites, controlling for all other variables. The odds of patients aged ≥ 60 years starting treatment were half those of patients age 44 years and under. Treatment initiation increased with depression severity, but was only 53% among patients with a PHQ-9 score of ≥ 10. Among minority patients, psychotherapy was initiated significantly more often than medication. CONCLUSIONS: Screening for depression in primary care is a positive step towards improving detection, treatment, and outcomes for depression. However, study results indicate that treatment initiation remains suboptimal, and disparities persist. A better understanding of patient factors, and particularly system-level factors, that influence treatment initiation is needed to inform efforts by heath care systems to improve depression treatment engagement and to reduce disparities.

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.

Cardiometabolic Risk Factors Among 1.3 Million Adults With Overweight or Obesity, but Not Diabetes, in 10 Geographically Diverse Regions of the United States, 2012-2013.

INTRODUCTION: Various phenotypes of overweight and obesity pose various health risks. The objective of this study was to determine the prevalence of 4 commonly measured cardiometabolic risk factors (CRFs) among adults with overweight or obesity, but not diabetes, at the time of the study. METHODS: We analyzed data for 1,294,174 adults (aged ≥20 y) who were members of one of 4 integrated health systems. Each cohort member had a body mass index in 2012 or 2013 that indicated overweight or obesity. We determined the presence of 4 CRFs within 1 year of the first BMI measurement: elevated blood pressure (systolic ≥130 mm Hg or diastolic >85 mm Hg or ICD-9-CM [International Classification of Diseases, Ninth Revision, Clinical Modification] diagnosis code 401.0-405.9); elevated triglycerides (≥150 mg/dL or ICD-9-CM 272.1); low high-density lipoprotein cholesterol (<40 mg/dL for men or <50 mg/dL for women or ICD-9-CM 272.5); and prediabetes (fasting glucose 100-125 mg/dL or HbA1c 5.7%-6.4% or ICD-9-CM 790.2x). We tested the risk of having 1 or more CRFs after adjusting for obesity class and demographic characteristics with multivariable logistic regression. RESULTS: Among participants with overweight (52.5% of the sample), 18.6% had none of the 4 CRFs. Among the 47.5% of participants with obesity, 9.6% had none; among participants with morbid obesity, 5.8% had none. Age was strongly associated with CRFs in multivariable analysis. CONCLUSION: Almost 10% of participants with obesity had no CRFs. Overweight or obesity increases cardiometabolic risk, but the number and type of CRFs varied substantially by age, even among participants with morbid obesity.

Medication Adherence Does Not Explain Black-White Differences in Cardiometabolic Risk Factor Control among Insured Patients with Diabetes.

BACKGROUND: Among patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence contribute to such disparities is not known. We examined whether medication adherence, controlling for treatment intensification, could explain differences in risk factor control between black and white patients with diabetes. METHODS: We identified three cohorts of black and white patients treated with oral medications and who had poor risk factor control at baseline (2009): those with glycated hemoglobin (HbA1c) >8 % (n = 37,873), low-density lipoprotein cholesterol (LDL-C) >100 mg/dl (n = 27,954), and systolic blood pressure (SBP) >130 mm Hg (n = 63,641). Subjects included insured adults with diabetes who were receiving care in one of nine U.S. integrated health systems comprising the SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) consortium. Baseline and follow-up risk factor control, sociodemographic, and clinical characteristics were obtained from electronic health records. Pharmacy-dispensing data were used to estimate medication adherence (i.e., medication refill adherence [MRA]) and treatment intensification (i.e., dose increase or addition of new medication class) between baseline and follow-up. County-level income and educational attainment were estimated via geocoding. Logistic regression models were used to test the association between race and follow-up risk factor control. Models were specified with and without medication adherence to evaluate its role as a mediator. RESULTS: We observed poorer medication adherence among black patients than white patients (p < 0.01): 50.6 % of blacks versus 39.7 % of whites were not highly adherent (i.e., MRA <80 %) to HbA1c oral medication(s); 58.4 % of blacks and 46.7 % of whites were not highly adherent to lipid medication(s); and 33.4 % of blacks and 23.7 % of whites were not highly adherent to BP medication(s). Across all cardiometabolic risk factors, blacks were significantly less likely to achieve control (p < 0.01): 41.5 % of blacks and 45.8 % of whites achieved HbA1c <8 %; 52.6 % of blacks and 60.8 % of whites achieved LDL-C <100; and 45.7 % of blacks and 53.6 % of whites achieved SBP <130. Adjusting for medication adherence/treatment intensification did not alter these patterns or model fit statistics. CONCLUSIONS: Medication adherence failed to explain observed racial differences in the achievement of HbA1c, LDL-C, and SBP control among insured patients with diabetes.

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.

Trends in diabetes incidence among 7 million insured adults, 2006-2011: the SUPREME-DM project.

An observational cohort analysis was conducted within the Surveillance, Prevention, and Management of Diabetes Mellitus (SUPREME-DM) DataLink, a consortium of 11 integrated health-care delivery systems with electronic health records in 10 US states. Among nearly 7 million adults aged 20 years or older, we estimated annual diabetes incidence per 1,000 persons overall and by age, sex, race/ethnicity, and body mass index. We identified 289,050 incident cases of diabetes. Age- and sex-adjusted population incidence was stable between 2006 and 2010, ranging from 10.3 per 1,000 adults (95% confidence interval (CI): 9.8, 10.7) to 11.3 per 1,000 adults (95% CI: 11.0, 11.7). Adjusted incidence was significantly higher in 2011 (11.5, 95% CI: 10.9, 12.0) than in the 2 years with the lowest incidence. A similar pattern was observed in most prespecified subgroups, but only the differences for persons who were not white were significant. In 2006, 56% of incident cases had a glycated hemoglobin (hemoglobin A1c) test as one of the pair of events identifying diabetes. By 2011, that number was 74%. In conclusion, overall diabetes incidence in this population did not significantly increase between 2006 and 2010, but increases in hemoglobin A1c testing may have contributed to rising diabetes incidence among nonwhites in 2011.

Racial/Ethnic differences in health care visits made before suicide attempt across the United States.

BACKGROUND: Suicide is a public health concern, but little is known about the patterns of health care visits made before a suicide attempt, and whether those patterns differ by race/ethnicity. OBJECTIVES: To examine racial/ethnic variation in the types of health care visits made before a suicide attempt, when those visits occur, and whether mental health or substance use diagnoses were documented. RESEARCH DESIGN: Retrospective, longitudinal study, 2009-2011. PARTICIPANTS: 22,387 individuals who attempted suicide and were enrolled in the health plan across 10 health systems in the Mental Health Research Network. MEASURES: Cumulative percentage of different types of health care visits made in the 52 weeks before a suicide attempt, by self-reported racial/ethnicity and diagnosis. Data were from the Virtual Data Warehouse at each site. RESULTS: Over 38% of the individuals made any health care visit within the week before their suicide attempt and ∼95% within the preceding year; these percentages varied across racial/ethnic groups (P<0.001). White individuals had the highest percentage of visits (>41%) within 1 week of suicide attempt. Asian Americans were the least likely to make visits within 52 weeks. Hawaiian/Pacific Islanders had proportionally the most inpatient and emergency visits before an attempt, but were least likely to have a recorded mental health or substance use diagnosis. Overall, visits were most common in primary care and outpatient general medical settings. CONCLUSIONS: This study provides temporal evidence of racial/ethnic differences in health care visits made before suicide attempt. Health care systems can use this information to help focus the design and implementation of their suicide prevention initiatives.

Longitudinal associations between sex, diabetes self-care, and health-related quality of life among youth with type 1 or type 2 diabetes mellitus.

OBJECTIVE: To examine the longitudinal associations between sex, diabetes self-care, and the health-related quality of life (HRQL) of children and adolescents with type 1 or type 2 diabetes. STUDY DESIGN: The sample included 910 participants with type 1 and 241 participants with type 2, ages 10-22 years at baseline, from the SEARCH for Diabetes in Youth Study, a longitudinal observational study. The primary outcome measure was the Pediatric Quality of Life Inventory. Repeated measures, mixed-model regression analysis was conducted with the use of data from baseline and at least one follow-up assessment, spanning approximately 4 years. RESULTS: HRQL was greater among those with type 1 versus type 2 diabetes. Among participants with type 1, greater (better) Pediatric Quality of Life Inventory total scores over time were related to greater parent education (P = .0007), lower glycated hemoglobin values (P < .0001), and greater physical activity during the past 7 days (P = .0001). There was a significant interaction between sex and age (P < .0001); girls' HRQL remained stable or decreased over time, whereas males' HRQL increased. For participants with type 2 diabetes, there was no significant interaction by age and sex, but lower total HRQL was related to being female (P = .011) and greater body mass index z-scores (P = .014). CONCLUSIONS: HRQL in this cohort varied by diabetes type. The interaction between sex and age for type 1 participants, coupled with poorer HRQL among female than male participants with type 2 diabetes, suggests the impacts of diabetes on HRQL differ by sex and should be considered in clinical management. Encouraging physical activity and weight control continue to be important in improving HRQL.

Prevalence of and disparities in barriers to care experienced by youth with type 1 diabetes.

OBJECTIVE: To describe the prevalence of access and process barriers to health care and to examine their relationship to sociodemographic and disease factors in a large and diverse cohort of US youth with type 1 diabetes. STUDY DESIGN: A cross-sectional analysis of 780 youth who participated in the SEARCH for Diabetes in Youth Study and were diagnosed with type 1 diabetes in 2002-2005. Experience of barriers to care was collected from parent report on questionnaires. Analyses included multivariate regression models to predict the presence of specific barriers to care. RESULTS: Overall, 81.7% of participants reported at least one barrier; the 3 most common were costs (47.5%), communication (43.0%), and getting needed information (48.4%). Problems with access to care, not having a regular provider, and receiving contextual care (care that takes into account personal and family context) were associated with poorer glycated hemoglobin levels. Adjusted multivariate models indicated that barriers related to access (regular provider, cost) were most likely for youth with low family income and those without public health insurance. Barriers associated with the processes of quality care (contextual care, communication) were more likely for Hispanic youth and those whose parents had less education. CONCLUSIONS: This study indicates that a large proportion of youth with type 1 diabetes experience substantial barriers to care. Barriers to access and those associated with processes of quality care differed by sociodemographic characteristics. Future investigators should expand knowledge of the systemic processes that lead to disparate outcomes for some youth with diabetes and assess potential solutions.

Health care contacts in the year before suicide death.

BACKGROUND: Suicide prevention is a public health priority, but no data on the health care individuals receive prior to death are available from large representative United States population samples. OBJECTIVE: To investigate variation in the types and timing of health services received in the year prior to suicide, and determine whether a mental health condition was diagnosed. DESIGN: Longitudinal study from 2000 to 2010 within eight Mental Health Research Network health care systems serving eight states. PARTICIPANTS: In all, 5,894 individuals who died by suicide, and were health plan members in the year before death. MAIN MEASURES: Health system contacts in the year before death. Medical record, insurance claim, and mortality records were linked via the Virtual Data Warehouse, a federated data system at each site. KEY RESULTS: Nearly all individuals received health care in the year prior to death (83 %), but half did not have a mental health diagnosis. Only 24 % had a mental health diagnosis in the 4-week period prior to death. Medical specialty and primary care visits without a mental health diagnosis were the most common visit types. The individuals more likely to make a visit in the year prior to death (p < 0.05) tended to be women, individuals of older age (65+ years), those where the neighborhood income was over $40,000 and 25 % were college graduates, and those who died by non-violent means. CONCLUSIONS: This study indicates that opportunities for suicide prevention exist in primary care and medical settings, where most individuals receive services prior to death. Efforts may target improved identification of mental illness and suicidal ideation, as a large proportion may remain undiagnosed at death.

Use of antipsychotic medications in pediatric populations: what do the data say?

Recent reports of antipsychotic medication use in pediatric populations describe large increases in rates of use. Much interest in the increasing use has focused on potentially inappropriate prescribing for non-Food and Drug Administration-approved uses and use amongst youth with no mental health diagnosis. Different studies of antipsychotic use have used different time periods, geographic and insurance populations of youth, and aggregations of diagnoses. We review recent estimates of use and comment on the similarities and dissimilarities in rates of use. We also report new data obtained on 11 health maintenance organizations that are members of the Mental Health Research Network in order to update and extend the knowledge base on use by diagnostic indication. Results indicate that most use in pediatric populations is for disruptive behaviors and not psychotic disorders. Differences in estimates are likely a function of differences in methodology; however, there is remarkable consistency in estimates of use by diagnosis.

Evaluation of risk equations for prediction of short-term coronary heart disease events in patients with long-standing type 2 diabetes: the Translating Research into Action for Diabetes (TRIAD) study.

BACKGROUND: To evaluate the U.K. Prospective Diabetes Study (UKPDS) and Framingham risk equations for predicting short-term risk of coronary heart disease (CHD) events among adults with long-standing type 2 diabetes, including those with and without preexisting CHD. METHODS: Prospective cohort of U.S. managed care enrollees aged ≥ 18 years and mean diabetes duration of more than 10 years, participating in the Translating Research into Action for Diabetes (TRIAD) study, was followed for the first occurrence of CHD events from 2000 to 2003. The UKPDS and Framingham risk equations were evaluated for discriminating power and calibration. RESULTS: A total of 8303 TRIAD participants, were identified to evaluate the UKPDS (n = 5914, 120 events), Framingham-initial (n = 5914, 218 events) and Framingham-secondary (n = 2389, 374 events) risk equations, according to their prior CHD history. All of these equations exhibited low discriminating power with Harrell's c-index <0.65. All except the Framingham-initial equation for women and the Framingham-secondary equation for men had low levels of calibration. After adjsusting for the average values of predictors and event rates in the TRIAD population, the calibration of these equations greatly improved. CONCLUSIONS: The UKPDS and Framingham risk equations may be inappropriate for predicting the short-term risk of CHD events in patients with long-standing type 2 diabetes, partly due to changes in medications used by patients with diabetes and other improvements in clinical care since the Frmaingham and UKPDS studies were conducted. Refinement of these equations to reflect contemporary CHD profiles, diagnostics and therapies are needed to provide reliable risk estimates to inform effective treatment.

Construction of a multisite DataLink using electronic health records for the identification, surveillance, prevention, and management of diabetes mellitus: the SUPREME-DM project.

INTRODUCTION: Electronic health record (EHR) data enhance opportunities for conducting surveillance of diabetes. The objective of this study was to identify the number of people with diabetes from a diabetes DataLink developed as part of the SUPREME-DM (SUrveillance, PREvention, and ManagEment of Diabetes Mellitus) project, a consortium of 11 integrated health systems that use comprehensive EHR data for research. METHODS: We identified all members of 11 health care systems who had any enrollment from January 2005 through December 2009. For these members, we searched inpatient and outpatient diagnosis codes, laboratory test results, and pharmaceutical dispensings from January 2000 through December 2009 to create indicator variables that could potentially identify a person with diabetes. Using this information, we estimated the number of people with diabetes and among them, the number of incident cases, defined as indication of diabetes after at least 2 years of continuous health system enrollment. RESULTS: The 11 health systems contributed 15,765,529 unique members, of whom 1,085,947 (6.9%) met 1 or more study criteria for diabetes. The nonstandardized proportion meeting study criteria for diabetes ranged from 4.2% to 12.4% across sites. Most members with diabetes (88%) met multiple criteria. Of the members with diabetes, 428,349 (39.4%) were incident cases. CONCLUSION: The SUPREME-DM DataLink is a unique resource that provides an opportunity to conduct comparative effectiveness research, epidemiologic surveillance including longitudinal analyses, and population-based care management studies of people with diabetes. It also provides a useful data source for pragmatic clinical trials of prevention or treatment interventions.

Predicting adolescent alcohol and other drug problems using electronic health records data.

IMPORTANCE: Alcohol and other drug (AOD) use problems may cause significant burden on affected adolescents and their families, yet treatment providers often do not identify these problems early enough. OBJECTIVE: To develop, and internally and externally validate a multivariable prediction model of adolescent AOD problems using child- and maternal-level predictors before age 12, and child-level predictors between ages 12 to 18, as recorded in the electronic health records (EHR). DESIGN: A retrospective cohort study conducted time-to-event analyses using Cox proportional hazards models. SETTING AND PARTICIPANTS: 41,172 children born between 1997 and 2000 at four health plans (Kaiser Permanente Hawaii, KPHI; Kaiser Permanente Northern California, KPNC; Geisinger Clinic, GC; and Henry Ford Health System, HFHS) who had continuous membership since birth and linkable maternal records in the health plan. OUTCOMES: AOD use problems between ages 12 to 18, defined as either: 1) having a contact with the AOD treatment program or 2) receiving a non-tobacco AOD diagnosis in an inpatient or outpatient encounter. EXPOSURES: Candidate predictor variables include demographics, socioeconomic status, and clinical diagnoses of the children and the mothers. RESULTS: Overall, 1400 (3.4%) adolescents had an AOD disorder between ages 12 to 18; the median follow-up time post-age 12 was 5.3 years. The research team developed two final prediction models: a "baseline" model of 10 child-level and 7 maternal-level predictors before age 12, and a more comprehensive "time-varying" model, which incorporated child risk factors after age 12 as time-varying covariates in addition to the baseline model predictors. Model performance evaluation showed good discrimination performance of the models, with the concordance index improved for the time-varying model, especially for prediction of AOD events in late adolescence. CONCLUSIONS AND RELEVANCE: This study identified a number of child and maternal characteristics and diagnoses routinely available in EHR data as predictive of risk for developing AOD problems in adolescence. Further, we found that risk of developing problems varies significantly by the timing and persistence of the risk factors. Findings may have potential clinical implications for prevention and identification of adolescent AOD problems, but more research is needed, especially across additional health systems.

Health Service Utilization Among Children and Adolescents with Posttraumatic Stress Disorder: A Case-Control Study.

OBJECTIVE: Trauma exposure is widely prevalent, with more than 60% of adolescents having experienced at least 1 traumatic event and a third of those at high risk to develop posttraumatic stress disorder (PTSD). Data are scarce and out of date on the services children and adolescents with PTSD receive, impeding efforts to improve care and outcomes. This study examines health service use for a large and diverse sample of children and adolescents with and without a diagnosis of PTSD. METHOD: Using a matched case-control study, we gathered information from 4 large health care systems participating in the Mental Health Research Network. Data from each site's electronic medical records on diagnoses, health care encounters, and demographics were analyzed. Nine hundred fifty-five 4- to 18-year-olds with a diagnosis of PTSD were identified and matched on a 1:5 ratio to 4770 controls. We compared cases with controls on frequency of service use in outpatient primary care, medical specialty care, acute care, and mental health care. We also assessed psychotropic medication use. RESULTS: Children and adolescents diagnosed with PTSD used nearly all physical and mental health service categories at a higher rate than controls. However, one-third of children and adolescents did not receive even 1 outpatient mental health visit (36.86%) during the year-long sampling window. CONCLUSION: Our findings suggest that children and adolescents diagnosed with PTSD may have unmet mental health needs. They are high utilizers of health services overall, but lower utilizers of the sectors that may be most helpful in resolving their symptoms.