Factors Associated With Increased Health Care Utilization for Patients With Dementia With Lewy Bodies: A Narrative Review.

Numerous studies have demonstrated that dementia is associated with increased utilization of health care services, which in turn results in increased costs of care. Dementia with Lewy bodies (DLB) is associated with greater costs of care relative to other forms of dementia due to higher rates of hospitalization and nursing home placement directly related to neuropsychiatric symptoms, parkinsonism, increased susceptibility to delirium, and elevated rates of caregiver burden. There is a critical need for researchers to identify potentially modifiable factors contributing to increased costs of care and poor clinical outcomes for patients with DLB, which may include comorbidities, polypharmacy/contraindicated medications, and access to specialty care. Previous research has utilized Medicare claims data, limiting the ability to study patients with early-onset (ie, prior to age 65) DLB. Integrated health systems offer the ability to combine electronic medical record data with Medicare, Medicaid, and commercial claims data and may therefore be ideal for utilization research in this population. The goals of this narrative review are to 1) synthesize and describe the current literature on health care utilization studies for patients with DLB, 2) highlight the current gaps in the literature, and 3) provide recommendations for stakeholders, including researchers, health systems, and policymakers. It is important to improve current understanding of potentially modifiable factors associated with increased costs of care among patients with DLB to inform public health policies and clinical decision-making, as this will ultimately improve the quality of patient care.

Improving Assessment of Adherence Behaviors and Drivers: Targeted Literature Review and Concept Elicitation Interviews in Multiple Countries and Disease Populations.

Purpose: Medication adherence is crucial for achieving clinical goals. Medication adherence drivers and behaviors were explored across multiple conditions, countries, and medication schedules/modalities to develop a conceptual model of medication adherence, which could later be used to support development of a patient-reported outcome (PRO) measure of adherence. Patients and Methods: Targeted review of qualitative literature identified important medication adherence concepts. Fifty-seven qualitative concept elicitation interviews were conducted (USA n=21, Spain n=18, Germany n=18). Participants were prescribed medication for: hypertension (n=9), asthma (n=8), multiple myeloma (n=8), psoriasis (n=8), diabetes (n=7), depression (n=7), multiple sclerosis (n=7), and/or schizophrenia (n=6). Thematic analysis of verbatim transcripts was performed. Expert clinicians (n=3) provided input throughout. Results: Nine qualitative articles were selected for review from 2168 screened abstracts. Forty-two medication adherence concepts were reported and grouped into 10 domains. Eight forms of medication adherence were reported during interviews, along with 27 drivers of non-adherence, all of which were incorporated into a conceptual model. Participants reported skipping medication doses (n=36/57; 63.2%) or taking medication later in the day than prescribed (n=29/57; 50.9%). Common drivers of non-adherence included forgetfulness (n=35/57; 61.4%), being out of the usual routine (n=31/57; 54.4%) and being busy (n=22/57; 38.6%). US participants were more likely to report non-adherence due to low perceived efficacy (n=6/21, 28.6%) and cost (n=5/21, 23.8%) than German (n=1/18, 5.6%; n=0/18, 0.0%) or Spanish (n=2/18, 11.1%; n=1/18, 5.6%) participants. Conclusion: Findings highlight the diverse forms and drivers of medication non-adherence, informing the development of a comprehensive conceptual model of medication adherence. The conceptual model builds on and advances previous models of medication adherence and can be used by healthcare professionals to understand and interpret barriers to medication adherence and how best to support patients in taking their medication as intended.

Medication adherence is the extent to which a patient takes their medication as prescribed. This paper describes a literature review and concept elicitation interviews to identify forms and drivers of medication adherence across a diverse sample of participants. Forms of non-adherence identified included: deviating from the prescription, skipping a dose, taking a different amount, and taking medication at a different time. Behaviours and drivers can vary by condition, treatment modality, and dosing schedule.This research highlights the variation in the prevalence of medication non-adherence, and the different forms and drivers of non-adherence, based on individuals' demographic and clinical characteristics. The conceptual model developed advances previous models of medication adherence and may support healthcare professionals in the management of patients and how they can be supported to take medication as intended. The research ultimately informed the development of the Adelphi Adherence Questionnaire (ADAQ^©), a novel generic patient-reported outcome measure.

Suicide attempts after bariatric surgery: comparison to a nonsurgical cohort of individuals with severe obesity.

BACKGROUND: The rate of suicide is higher among individuals following bariatric surgery compared with the general population; however, it is not clear whether risk is associated with bariatric surgery beyond having severe obesity. OBJECTIVE: To compare the risk of a suicide attempt among those who had bariatric surgery versus a nonsurgical cohort with severe obesity. SETTING: Aggregate count data were collected from 5 healthcare systems. METHODS: Individuals were identified in the surgical cohort if they underwent bariatric surgery between 2009 and 2017 (n = 35,522) and then were compared with a cohort of individuals with severe obesity who never had bariatric surgery (n = 691,752). Suicide attempts were identified after study enrollment date using International Classification of Diseases, Ninth and Tenth Editions (ICD-9 and ICD-10) diagnosis codes from 2009 to 2021. RESULTS: The relative risk of a suicide attempt was 64% higher in the cohort with bariatric surgery than that of the nonsurgical cohort (2.2% versus 1.3%; relative risk = 1.64; 95% CI, 1.53-1.76). Within the cohort with bariatric surgery, suicide attempts were more common among the 18- to 39-year age group (P < .001), women (P = .002), Hawaiian-Pacific Islanders (P < .001), those with Medicaid insurance (P < .001), and those with a documented mental health condition at baseline (in the previous 2 years; P < .001). CONCLUSIONS: The relative risk of suicide attempts was higher among those who underwent bariatric surgery compared with a nonsurgical cohort, though absolute risk remained low. Providers should be aware of this increased risk. Screening for suicide risk after bariatric surgery may be useful to identify high-risk individuals.

Differential Effects of an Intervention to Reduce Cardiovascular Risk for Patients With Bipolar Disorder, Schizoaffective Disorder, or Schizophrenia: A Randomized Clinical Trial.

Objective: To measure the impact of a clinical decision support (CDS) tool on total modifiable cardiovascular risk at 12 months separately for outpatients with 3 subtypes of serious mental illness (SMI) identified via ICD-9 and ICD-10 codes: bipolar disorder, schizoaffective disorder, and schizophrenia.Methods: This cluster-randomized pragmatic clinical trial was active from March 2016 to September 2018; data were analyzed from April 2021 to September 2022. Clinicians and patients from 78 primary care clinics participated. All 8,922 adult patients aged 18-75 years with diagnosed SMI, at least 1 cardiovascular risk factor not at goal, and an index and follow-up visit during the study period were included. The CDS tool provided a summary of modifiable cardiovascular risk and personalized treatment recommendations.Results: Intervention patients had 4% relative reduction in total modifiable cardiovascular risk at 12 months compared to controls (relative risk ratio = 0.96; 95% CI, 0.94 to 0.98), with similar intervention benefits for all 3 SMI subtypes. At index, 10-year cardiovascular risk was higher for patients with schizophrenia (mean [SD] = 11.3% [9.2%]) than for patients with bipolar disorder (8.5% [8.9%]) or schizoaffective disorder (9.4% [8.1%]), while 30-year cardiovascular risk was highest for patients with schizoaffective disorder (44% with 2 or more major cardiovascular risk factors, compared to 40% for patients with schizophrenia and 37% for patients with bipolar disorder). Smoking was highly prevalent (47%), and mean (SD) BMI was 32.7 (7.9).Conclusions: This CDS intervention produced a clinically and statistically significant 4% relative reduction in total modifiable cardiovascular risk for intervention patients versus controls at 12 months, an effect observed across all 3 SMI subtypes and attributable to the aggregate impact of small changes in multiple cardiovascular risk factors.Trial Registration: ClinicalTrials.gov Identifier: NCT02451670.

Cancer and psychiatric diagnoses in the year preceding suicide.

BACKGROUND: Patients with cancer are known to be at increased risk for suicide but little is known about the interaction between cancer and psychiatric diagnoses, another well-documented risk factor. METHODS: Electronic medical records from nine healthcare systems participating in the Mental Health Research Network were aggregated to form a retrospective case-control study, with ICD-9 codes used to identify diagnoses in the 1 year prior to death by suicide for cases (N = 3330) or matching index date for controls (N = 297,034). Conditional logistic regression was used to assess differences in cancer and psychiatric diagnoses between cases and controls, controlling for sex and age. RESULTS: Among patients without concurrent psychiatric diagnoses, cancer at disease sites with lower average 5-year survival rates were associated with significantly greater relative risk, while cancer disease sites with survival rates of >70% conferred no increased risk. Patients with most psychiatric diagnoses were at higher risk, however, there was no additional risk conferred to these patients by a concurrent cancer diagnosis. CONCLUSION: We found no evidence of a synergistic effect between cancer and psychiatric diagnoses. However, cancer patients with a concurrent psychiatric illness remain at the highest relative risk for suicide, regardless of cancer disease site, due to strong independent associations between psychiatric diagnoses and suicide. For patients without a concurrent psychiatric illness, cancer disease sites associated with worse prognoses appeared to confer greater suicide risk.

30-year Cardiovascular Disease Risk for Young Adults with Serious Mental Illness.

Objective: To estimate 30-year CVD risk and modifiable risk factors in young adults with serious mental illness (SMI) versus those without, and assess variations in CVD risk by race, ethnicity, and sex. Method: In this cross-sectional study, we estimated and compared the Framingham 30-year CVD risk score and individual modifiable CVD risk factors in young adult (20-39 years) primary care patients with and without SMI at two US healthcare systems (January 2016-Septemeber 2018). Interaction terms assessed whether the SMI-risk association differed across demographic groups. Results: Covariate-adjusted 30-year CVD risk was significantly higher for those with (n=4228) versus those without (n=155,363) SMI (RR 1.28, 95% CI [1.26, 1.30]). Patients with SMI had higher rates of hypertension (OR 2.02 [1.7, 2.39]), diabetes (OR 3.14 [2.59, 3.82]), obesity (OR 1.93 [1.8, 2.07]), and smoking (OR 4.94 [4.6, 5.36]). The increased 30-year CVD risk associated with SMI varied significantly by race and sex: there was an 8% higher risk in Black compared to White patients (RR 1.08, [1.04, 1.12]) and a 9% lower risk in men compared to women (RR 0.91 [0.88, 0.94]). Conclusions: Young adults with SMI are at increased 30-year risk of CVD, and further disparities exist for Black individuals and women.

Bolstering the Business Case for Adoption of Shared Decision-Making Systems in Primary Care: Randomized Controlled Trial.

BACKGROUND: Limited budgets may often constrain the ability of health care delivery systems to adopt shared decision-making (SDM) systems designed to improve clinical encounters with patients and quality of care. OBJECTIVE: This study aimed to assess the impact of an SDM system shown to improve diabetes and cardiovascular patient outcomes on factors affecting revenue generation in primary care clinics. METHODS: As part of a large multisite clinic randomized controlled trial (RCT), we explored the differences in 1 care system between clinics randomized to use an SDM intervention (n=8) versus control clinics (n=9) regarding the (1) likelihood of diagnostic coding for cardiometabolic conditions using the 10th Revision of the International Classification of Diseases (ICD-10) and (2) current procedural terminology (CPT) billing codes. RESULTS: At all 24,138 encounters with care gaps targeted by the SDM system, the proportion assigned high-complexity CPT codes for level of service 5 was significantly higher at the intervention clinics (6.1%) compared to that in the control clinics (2.9%), with P<.001 and adjusted odds ratio (OR) 1.64 (95% CI 1.02-2.61). This was consistently observed across the following specific care gaps: diabetes with glycated hemoglobin A1c (HbA1c)>8% (n=8463), 7.2% vs 3.4%, P<.001, and adjusted OR 1.93 (95% CI 1.01-3.67); blood pressure above goal (n=8515), 6.5% vs 3.7%, P<.001, and adjusted OR 1.42 (95% CI 0.72-2.79); suboptimal statin management (n=17,765), 5.8% vs 3%, P<.001, and adjusted OR 1.41 (95% CI 0.76-2.61); tobacco dependency (n=7449), 7.5% vs. 3.4%, P<.001, and adjusted OR 2.14 (95% CI 1.31-3.51); BMI >30 kg/m2 (n=19,838), 6.2% vs 2.9%, P<.001, and adjusted OR 1.45 (95% CI 0.75-2.8). Compared to control clinics, intervention clinics assigned ICD-10 diagnosis codes more often for observed cardiometabolic conditions with care gaps, although the difference did not reach statistical significance. CONCLUSIONS: In this randomized study, use of a clinically effective SDM system at encounters with care gaps significantly increased the proportion of encounters assigned high-complexity (level 5) CPT codes, and it was associated with a nonsignificant increase in assigning ICD-10 codes for observed cardiometabolic conditions. TRIAL REGISTRATION: ClinicalTrials.gov NCT02451670; https://clinicaltrials.gov/ct2/show/NCT02451670.

Qualitative Interviews to Support Development and Cognitive Debriefing of the Adelphi Adherence Questionnaire (ADAQ©): A Patient-Reported Measure of Medication Adherence Developed for Use in a Range of Diseases, Treatment Modalities, and Countries.

Purpose: The Adelphi Adherence Questionnaire (ADAQ©) is a newly developed generic patient-reported outcome (PRO) assessment of medication adherence. The aim was to assess its content validity by conducting cognitive debriefing (CD) interviews with patients prescribed medication(s) of various treatment modalities in a range of therapy areas. Materials and Methods: Targeted literature/instrument review and concept elicitation interviews informed development of the ADAQ©. CD interviews were conducted with 57 adults from the United States of America (USA; n = 21), Spain (n = 18), and Germany (n = 18) who prescribed medication for hypertension, diabetes, depression, schizophrenia, asthma, multiple myeloma, psoriasis, and/or multiple sclerosis. Interviews were conducted in two rounds to explore the relevance and understanding of the item wording, instructions, recall period and response options. Verbatim transcripts were analysed in ATLAS.Ti using thematic analysis. Three expert clinicians provided guidance throughout the study. Results: ADAQ© items/instructions were well understood and relevant to participants. Key modifications following round 1 included revising instructions to refer to current medication(s) for one condition to reduce cognitive burden, removing two items with lower relevance (specifically those assessing running out of medication and social discouragement), and adding a response option for participants to indicate if they had stopped taking a medication. Minor wording modifications were made following round 2. Subgroup differences in item relevance were explored based on clinical characteristics. Cost of medication was more relevant amongst US participants. Conclusion: Content validity of the ADAQ© was confirmed in demographically and clinically diverse participants. Psychometric properties of the ADAQ© will be explored in future studies.

Detecting and distinguishing indicators of risk for suicide using clinical records.

Health systems are essential for suicide risk detection. Most efforts target people with mental health (MH) diagnoses, but this only represents half of the people who die by suicide. This study seeks to discover and validate health indicators of suicide death among those with, and without, MH diagnoses. This case-control study used statistical modeling with health record data on diagnoses, procedures, and encounters. The study included 3,195 individuals who died by suicide from 2000 to 2015 and 249,092 randomly selected matched controls, who were age 18+ and affiliated with nine Mental Health Research Network affiliated health systems. Of the 202 indicators studied, 170 (84%) were associated with suicide in the discovery cohort, with 148 (86%) of those in the validation cohort. Malignant cancer diagnoses were risk factors for suicide in those without MH diagnoses, and multiple individual psychiatric-related indicators were unique to the MH subgroup. Protective effects across MH-stratified models included diagnoses of benign neoplasms, respiratory infections, and utilization of reproductive services. MH-stratified latent class models validated five subgroups with distinct patterns of indicators in both those with and without MH. The highest risk groups were characterized via high utilization with multiple healthcare concerns in both groups. The lowest risk groups were characterized as predominantly young, female, and high utilizers of preventive services. Healthcare data include many indicators of suicide risk for those with and without MH diagnoses, which may be used to support the identification and understanding of risk as well as targeting of prevention in health systems.

Depression and cardiovascular risk in primary care patients.

OBJECTIVE: This study assessed the relationship of both depression diagnosis and clinically significant depressive symptoms with individual cardiovascular risk factors and estimated total cardiovascular risk in primary care patients. METHODS: This study used a cross-sectional and retrospective design. Patients who had a primary care encounter between January 2016 and September 2018 and completed depression screening (PHQ-9) during the year prior to their appointment (N = 70,980) were included in this study. Data examining estimated total cardiovascular risk, specific cardiovascular risk factors, and relevant clinical diagnoses (including depression diagnosis) were extracted from the electronic health record. Patients were categorized into three groups: no depression (PHQ-9 < 10 and no depression diagnosis), controlled depression (PHQ-9 < 10 with previous depression diagnosis), and current depression (PHQ-9 ≥ 10). Groups were compared on estimated total risk and specific cardiovascular risk factors (e.g., body mass index [BMI], smoking status, lipids, blood pressure, and glucose). RESULTS: In adjusted analyses, patients with current depression (n = 18,267) demonstrated significantly higher 10-year and 30-year cardiovascular risk compared to patients with controlled depression (n = 33,383; 10-year: b = 0.59 [95% CI = 0.44,0.74]; 30-year: OR = 1.32 [95% CI = 1.26,1.39]) and patients without depression (n = 19,330; 10-year: b = 0.55 [95% CI = 0.37,0.73]; 30-year: OR = 1.56 [95% CI = 1.48,1.65]). Except for low-density lipoprotein (LDL), patients with current depression had the greatest cardiovascular risk across specific risk factors. CONCLUSIONS: Individuals who had a depression diagnosis and clinically significant depressive symptoms had the greatest cardiovascular risk. Pathways to prevent cardiovascular disease in those with depression might focus on treating depressive symptoms as well as specific uncontrolled cardiovascular risk factors.

Cardiovascular Risk for Patients With and Without Schizophrenia, Schizoaffective Disorder, or Bipolar Disorder.

Background To compare estimated 10-year and 30-year cardiovascular risk in primary care patients with and without serious mental illness (SMI; bipolar disorder, schizophrenia, or schizoaffective disorder). Methods and Results All patients aged 18 to 75 years with a primary care visit in January 2016 to September 2018 were included and were grouped into those with and without SMI using diagnosis codes. Ten-year cardiovascular risk was estimated using atherosclerotic cardiovascular disease scores for patients aged 40 to 75 years without cardiovascular disease; 30-year cardiovascular risk was estimated using Framingham risk scores for patients aged 18 to 59 years without cardiovascular disease. Demographic, vital sign, medication, diagnosis, and health insurance data were collected from the electronic health record by a clinical decision support system. Descriptive statistics examined unadjusted differences, while general linear models examined differences for continuous variables and logistic regression models for categorical variables. Models were then adjusted for age, sex, race, ethnicity, and insurance type. A total of 11 333 patients with SMI and 579 924 patients without SMI were included. After covariate adjustment, 10-year cardiovascular risk was significantly higher in patients with SMI (mean, 9.44%; 95% CI, 9.29%-9.60%) compared with patients without SMI (mean, 7.99%; 95% CI, 7.97-8.02). Similarly, 30-year cardiovascular risk was significantly higher in those with SMI (25% of patients with SMI in the highest-risk group compared with 11% of patients without SMI; P<0.001). The individual cardiovascular risk factors contributing most to increased risk for those with SMI were elevated body mass index and smoking. Among SMI subtypes, patients with bipolar disorder had the highest 10-year cardiovascular risk, while patients with schizoaffective disorder had the highest 30-year cardiovascular risk. Conclusions The significantly increased cardiovascular risk associated with SMI is evident even in young adults. This suggests the importance of addressing uncontrolled major cardiovascular risk factors in those with SMI at as early an age as possible. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02451670.

Effect of Clinical Decision Support on Cardiovascular Risk Among Adults With Bipolar Disorder, Schizoaffective Disorder, or Schizophrenia: A Cluster Randomized Clinical Trial.

IMPORTANCE: Adults with schizophrenia, schizoaffective disorder, or bipolar disorder, collectively termed serious mental illness (SMI), have shortened life spans compared with people without SMI. The leading cause of death is cardiovascular (CV) disease. OBJECTIVE: To assess whether a clinical decision support (CDS) system aimed at primary care clinicians improves CV health for adult primary care patients with SMI. DESIGN, SETTING, AND PARTICIPANTS: In this cluster randomized clinical trial conducted from March 2, 2016, to September 19, 2018, restricted randomization assigned 76 primary care clinics in 3 Midwestern health care systems to receive or not receive a CDS system aimed at improving CV health among patients with SMI. Eligible clinics had at least 20 patients with SMI; clinicians and their adult patients with SMI with at least 1 modifiable CV risk factor not at the goal set by the American College of Cardiology/American Heart Association guidelines were included. Statistical analysis was conducted on an intention-to-treat basis from January 10, 2019, to December 29, 2021. INTERVENTION: The CDS system assessed modifiable CV risk factors and provided personalized treatment recommendations to clinicians and patients. MAIN OUTCOMES AND MEASURES: Patient-level change in total modifiable CV risk over 12 months, summed from individual modifiable risk factors (smoking, body mass index, low-density lipoprotein cholesterol level, systolic blood pressure, and hemoglobin A1c level). RESULTS: A total of 80 clinics were randomized; 4 clinics were excluded for having fewer than 20 eligible patients, leaving 42 intervention clinics and 34 control clinics. A total of 8937 patients with SMI (4922 women [55.1%]; mean [SD] age, 48.4 [13.5] years) were enrolled. There was a 4% lower rate of increase in total modifiable CV risk among intervention patients relative to control patients (relative rate ratio [RR], 0.96; 95% CI, 0.94-0.98). The intervention favored patients who were 18 to 29 years of age (RR, 0.89; 95% CI, 0.81-0.98) or 50 to 59 years of age (RR, 0.93; 95% CI, 0.90-0.96), Black (RR, 0.93; 95% CI, 0.88-0.98), or White (RR, 0.96; 95% CI, 0.94-0.98). Men (RR, 0.96; 95% CI, 0.94-0.99) and women (RR, 0.95; 95% CI, 0.92-0.97), as well as patients with any SMI subtype (bipolar disorder: RR, 0.96; 95% CI, 0.94-0.99; schizoaffective disorder: RR, 0.94; 95% CI, 0.90-0.98; schizophrenia: RR, 0.92; 95% CI, 0.85-0.99) also benefited from the intervention. Despite treatment effects favoring the intervention, there were no significant differences in individual modifiable risk factors. CONCLUSIONS AND RELEVANCE: This CDS intervention resulted in a rate of change in total modifiable CV risk that was 4% lower among intervention patients compared with control patients. Results were driven by the cumulative effects of incremental and mostly nonsignificant changes in individual modifiable risk factors. These findings emphasize the value of using CDS to prompt early primary care intervention for adults with SMI. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02451670.

Screening for Cognitive Impairment in Older Adults: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force.

Importance: Early identification of cognitive impairment may improve patient and caregiver health outcomes. Objective: To systematically review the test accuracy of cognitive screening instruments and benefits and harms of interventions to treat cognitive impairment in older adults (≥65 years) to inform the US Preventive Services Task Force. Data Sources: MEDLINE, PubMed, PsycINFO, and Cochrane Central Register of Controlled Trials through January 2019, with literature surveillance through November 22, 2019. Study Selection: Fair- to good-quality English-language studies of cognitive impairment screening instruments, and pharmacologic and nonpharmacologic treatments aimed at persons with mild cognitive impairment (MCI), mild to moderate dementia, or their caregivers. Data Extraction and Synthesis: Independent critical appraisal and data abstraction; random-effects meta-analyses and qualitative synthesis. Main Outcomes and Measures: Sensitivity, specificity; patient, caregiver, and clinician decision-making; patient function, quality of life, and neuropsychiatric symptoms; caregiver burden and well-being. Results: The review included 287 studies with more than 280 000 older adults. One randomized clinical trial (RCT) (n = 4005) examined the direct effect of screening for cognitive impairment on patient outcomes, including potential harms, finding no significant differences in health-related quality of life at 12 months (effect size, 0.009 [95% CI, -0.063 to 0.080]). Fifty-nine studies (n = 38 531) addressed the accuracy of 49 screening instruments to detect cognitive impairment. The Mini-Mental State Examination was the most-studied instrument, with a pooled sensitivity of 0.89 (95% CI, 0.85 to 0.92) and specificity of 0.89 (95% CI, 0.85 to 0.93) to detect dementia using a cutoff of 23 or less or 24 or less (15 studies, n = 12 796). Two hundred twenty-four RCTs and 3 observational studies including more than 240 000 patients or caregivers addressed the treatment of MCI or mild to moderate dementia. None of the treatment trials were linked with a screening program; in all cases, participants were persons with known cognitive impairment. Medications approved to treat Alzheimer disease (donepezil, galantamine, rivastigmine, and memantine) improved scores on the ADAS-Cog 11 by 1 to 2.5 points over 3 months to 3 years. Psychoeducation interventions for caregivers resulted in a small benefit for caregiver burden (standardized mean difference, -0.24 [95% CI, -0.36 to -0.13) over 3 to 12 months. Intervention benefits were small and of uncertain clinical importance. Conclusions and Relevance: Screening instruments can adequately detect cognitive impairment. There is no empirical evidence, however, that screening for cognitive impairment improves patient or caregiver outcomes or causes harm. It remains unclear whether interventions for patients or caregivers provide clinically important benefits for older adults with earlier detected cognitive impairment or their caregivers.

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.

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.

Pragmatic trial design of an intervention to reduce cardiovascular risk in people with serious mental illness.

BACKGROUND: Cardiovascular (CV) disease is the leading cause of death for people with serious mental illness (SMI), but clinicians are often slow to address this risk. METHODS/DESIGN: 78 Midwestern primary care clinics were randomized to receive or not receive access to a clinical decision support (CDS) tool. Between March 2016 and September 2018, primary care clinicians (PCPs) received CDS alerts during visits with adult patients with SMI who met minimal inclusion criteria and had at least one CV risk factor not at goal. The PCP CDS included a summary of six modifiable CV risk factors and patient-specific treatment recommendations. Psychiatrists received CDS alerts during their next visit with an eligible patient with SMI that alerted them to an elevated body mass index or recent weight gain and the presence of an obesogenic SMI medication. Study outcomes include total modifiable CV risk, six modifiable CV risk factors, and use of obesogenic SMI medications. DISCUSSION: This cluster-randomized pragmatic trial allowed PCPs and psychiatrists the opportunity to improve CV risk in a timely manner for patients with SMI. Effectiveness will be assessed using an intent-to-treat analysis, and outcomes will be assessed largely through electronic health record data harvested by the CDS tool itself. In total, 10,347 patients with SMI had an index primary care visit in a randomized clinic, and 8937 patients had at least one follow-up visit. Analyses are ongoing, and trial results are expected in mid-2020. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02451670.

Prevalence and treatment of opioid use disorders among primary care patients in six health systems.

BACKGROUND: The U.S. experienced nearly 48,000 opioid overdose deaths in 2017. Treatment of opioid use disorder (OUD) with buprenorphine is a recommended part of primary care, yet little is known about current U.S. practices in this setting. This observational study reports the prevalence of documented OUD and OUD treatment with buprenorphine among primary care patients in six large health systems. METHODS: Adults with ≥2 primary care visits during a three-year period (10/1/2013-9/30/2016) in six health systems were included. Data were obtained from electronic health record and claims data, with measures, assessed over the three-year period, including indicators for documented OUD from ICD 9 and 10 codes and OUD treatment with buprenorphine. The prevalence of OUD treatment was adjusted for age, gender, race/ethnicity, and health system. RESULTS: Among 1,368,604 primary care patients, 13,942 (1.0 %) had documented OUD, and among these, 21.0 % had OUD treatment with buprenorphine. For those with documented OUD, the adjusted prevalence of OUD treatment with buprenorphine varied across demographic and clinical subgroups. OUD treatment was lower among patients who were older, women, Black/African American and Hispanic (compared to white), non-commercially insured, and those with non-cancer pain, mental health disorders, greater comorbidity, and more opioid prescriptions, emergency department visits or hospitalizations. CONCLUSIONS: Among primary care patients in six health systems, one in five with an OUD were treated with buprenorphine, with disparities across demographic and clinical characteristics. Less buprenorphine treatment among those with greater acute care utilization highlights an opportunity for systems-level changes to increase OUD treatment.

Priorities Wizard: Multisite Web-Based Primary Care Clinical Decision Support Improved Chronic Care Outcomes with High Use Rates and High Clinician Satisfaction Rates.

INTRODUCTION: Priorities Wizard is an electronic health record-linked, web-based clinical decision support (CDS) system designed and implemented at multiple Health Care Systems Research Network (HCSRN) sites to support high quality outpatient chronic disease and preventive care. The CDS system (a) identifies patients who could substantially benefit from evidence-based actions; (b) presents prioritized evidence-based treatment options to both patient and clinician at the point of care; and (c) facilitates efficient ordering of recommended medications, referrals or procedures. METHODS: The CDS system extracts relevant data from electronic health records (EHRs), processes the data using Web-based clinical decision support algorithms, and displays the CDS output seamlessly on the EHR screen for use by the clinician and patient. Through a series of National Institutes of Health-funded projects led by HealthPartners Institute and the HealthPartners Center for Chronic Care Innovation and HCSRN partners, Priorities Wizard has been evaluated in cluster-randomized trials and expanded to include over 20 clinical domains. RESULTS: Cluster-randomized trials show that this CDS system significantly improved glucose and blood pressure control in diabetes patients, reduced 10-year cardiovascular (CV) risk in high-CV risk adults without diabetes, improved management of smoking in dental patients, and improved high blood pressure identification and management in adolescents. CDS output was used at 71-77 percent of targeted visits, 85-98 percent of clinicians were satisfied with the CDS system, and 94 percent reported they would recommend it to colleagues. CONCLUSIONS: Recently developed EHR-linked, Web-based CDS systems have significantly improved chronic disease care outcomes and have high use rates and primary care clinician satisfaction.

Opioid Use During Pregnancy, Observations of Opioid Use, and Secular Trend From 2006 to 2014 at HealthPartners Medical Group.

OBJECTIVES: To determine the prevalence of opioid use before, during, and after pregnancy and describe its use based on patient-specific characteristics. Determine secular trend of opioid use 2006 to 2014. MATERIALS AND METHODS: Retrospective cohort study. A large Upper Midwest integrated health care system and insurer. Female individuals age 10 to 50 years with a delivery diagnosis from July 1, 2006 through June 30, 2014. MAIN OUTCOME MEASURE: prevalence of opioid use before, during, and after pregnancy; description of opioid use during these time periods. RESULTS: From 11,565 deliveries among 9690 unique women, 862 (7.5%) deliveries were associated with significant opioid use. Significant opioid use was associated with single marital status, Cesarean section, Medicaid coverage, tobacco use, depression, anxiety, bipolar disorder, substance use disorder, nonopioid analgesic use, and referral to physical therapy, psychotherapy, or pain specialists. From 2006 to 2014 opioid use decreased from 9% to 6% before, during, and after pregnancy with a rate of change per year of -0.2%. DISCUSSION: Known risk factors including tobacco and alcohol use, mental health diagnoses, substance use disorder, or Medicaid enrollment may enable enhanced assessments and targeted interventions to reduce unnecessary prescribing and use of opioids among pregnant women and those who might become pregnant. Strategies to decrease opioid use during pregnancy should be considered by health care systems and health plans to reduce opioid prescribing in this patient population.