Literature Collection

PURPOSE OF REVIEW: Attention-deficit and hyperactivity disorder (ADHD) often presents with comorbid substance use disorders (SUD). Due to similarities in key symptoms of both disorders and suboptimal efficacy of the available treatments, clinicians are faced with difficulties in the diagnosis and treatment of these patients with both disorders. This review addresses recent publications between 2017 and 2019 on the etiology, prevalence, diagnosis and treatment of co-occurring ADHD and SUD. RECENT FINDINGS: ADHD is diagnosed in 15-20% of SUD patients, mostly as ADHD with combined (hyperactive/inattentive) presentation. Even during active substance use, screening with the Adult ADHD Self-Report Scale (ASRS) is useful to address whether further diagnostic evaluation is needed. After SUD treatment, the diagnosis of ADHD generally remains stable, but ADHD subtype presentations are not. Some evidence supports pharmacological treatment with long-acting stimulants in higher than usual dosages. Studies on psychological treatment remain scarce, but there are some promising findings on integrated cognitive behaviour therapy. SUMMARY: Diagnosis and treatment of patients with comorbid ADHD and SUD remain challenging. As ADHD presentations can change during active treatment, an active follow-up is warranted to provide treatment to the individuals' personal strengths and weaknesses.

INTRODUCTION: The general practitioners' (GP) approach to diagnosing depression has not yet been included in depression questionnaires. Therefore, the 'Questionnaire for the assessment of DEpression SYmptoms in Primary Care' (DESY-PC) has been developed. The DESY-PC consists of two parts, comprising the patient's perspective and psychiatric diagnostic criteria (DESY-PAT), and additionally the GP's heuristics and knowledge of patients (DESY-GP). The aim was to investigate the diagnostic accuracy and factor structure of the DESY-PC. METHODS: A multicentre diagnostic accuracy study was conducted in ten practices. Patients completed the DESY-PAT and PHQ-9 (Patient Health Questionnaire-9), while their GPs completed the DESY-GP. The Structured Clinical Interview for DSM-V disorders (SCID-V-CV) was used as reference standard. Sensitivity, specificity, receiver operating characteristic curves (ROC) and area under the curve (AUC) values were calculated to determine the diagnostic accuracy of the DESY-PC and PHQ-9. Factorial validity was assessed. RESULTS: 435 patients (mean age 47.6 years, 60.1% female, prevalence of depression 15.9%) were analysed. The diagnostic accuracy of the DESY-PAT (AUC=0.862, 95% Confidence Interval 0.815-0.908) was significantly higher (p<0.001) than that of PHQ-9 (AUC=0.821, 0.764-0.878). The diagnostic accuracy increased further when DESY-PAT was combined with DESY-GP for the overall questionnaire DESY-PC (AUC=0.874, 0.834-0.914). Goodness of fit indices indicated a plausible fit for the DESY-PC. CONCLUSIONS: Incorporating the GP's heuristics, judgement and knowledge of the patient contributes to a more accurate diagnosis. The DESY-PC integrates the GP's perspective, patient-specific factors, and psychiatric criteria into the diagnostic assessment, which might contribute to improved diagnostic decision-making in primary care.

INTRODUCTION: More health systems are implementing strategies to understand and address patient social health, also known as social health integration. We examine the impact of a pilot social health integration program in two primary care clinics in an integrated health care system on health care costs. METHODS: We randomized 534 patients who reported any social need between October 2022 - January 2023 to receive support from a centralized Connections Call Center (CCC) or clinic-based Community Resource Specialists (CRS). We used administrative and claims data to compare costs between programs incurred by the health care system over 9 months. Using an intent-to-treat approach, we used two-part models to estimate costs for behavioral health, emergency department, inpatient admissions, and urgent care. We estimated single-part models using generalized linear models for primary care, specialty care, and total costs. Our secondary as-treated analyses compared costs among those who received support from CRS to those who did not. RESULTS: Unadjusted results showed no significant differences between CRS and CCC participants. Adjusted findings showed that CRS participants had $286 higher primary care costs than CCC participants (95% CI: $63.61, $508.89). As-treated findings showed that those who received CRS assistance had $2,356 more specialty care costs (95% CI: $229, $4,482) than those who did not. CONCLUSIONS: Observed changes in primary and specialty care costs may be a result of increasing engagement with the health system that could support patients in managing their health and prevent avoidable utilization in the long-term. These findings can help inform others who are interested in adopting similar primary care interventions.

INTRODUCTION: The aim of this study was to assess differences in utilization outcomes among patients with social needs as part of a pilot social health integration program in 2 clinics in an integrated health system in the Pacific Northwest. METHODS: Patients who reported social needs between October 2022 and January 2023 were randomized to receive support from either local, clinic-based community resource specialists or a centralized Connections Call Center. The authors used administrative and claims data for 534 participants to compare the following utilization outcomes between arms over 9 months after randomization: primary care encounters, specialty care encounters, behavioral health encounters, emergency department encounters, inpatient admissions, urgent care encounters, and secure patient messages. Using an intent-to-treat approach, the authors used negative binomial regression models to compare visit counts and logistic regression to estimate differences in the probability of any emergency department visit or inpatient admissions between groups. The authors conducted secondary as-treated analyses comparing participants who received resource information from community resource specialists with those who did not. RESULTS: Unadjusted results showed no statistically significant differences between community resource specialists and Connections Call Center. Adjusted results showed that community resource specialist participants received 1.04 more primary care encounters than Connections Call Center participants (95% CI=0.336, 1.746). As-treated results showed that participants who received support from community resource specialists had higher counts of primary care encounters, specialty care encounters, and patient messages than those who did not. CONCLUSIONS: Beyond social needs navigation, clinic-based supports may be better integrated with care teams to provide ongoing support for patients' medical needs. Findings from this primary care social health pilot program showed that local, clinic-based support was associated with greater outpatient utilization than a call center support.