Psychometric evaluation and linking of the PHQ-9, QIDS-C, and VQIDS-C in a real-world population with major depressive disorder.

Purpose: Major depressive disorder (MDD) is a leading cause of disability worldwide. An accurate assessment of depressive symptomology is crucial for clinical management and research. This study assessed the convergent validity, reliability, and total scale score interconversion across the 9-item Patient Health Questionnaire (PHQ-9) self-report, the 16-item Quick Inventory of Depressive Symptomatology-clinician report (QIDS-C) (two widely used clinical ratings) and the 5-item Very Brief Quick Inventory of Depressive Symptoms-clinician report (VQIDS-C), which evaluate the core features of MDD. Patients and Methods: This study leveraged electronic health record (EHR)-derived, de-identified data from the NeuroBlu Database (Version 23R1), a longitudinal behavioural health real-world platform. Classical Test Theory (CTT) and Item Response Theory (IRT) analyses were used to evaluate the reliability, validity of, and conversions between the scales. The Test Information Function (TIF) was calculated for each scale, with greater test information reflecting higher precision and reliability in measuring depressive symptomology. IRT was also used to generate conversion tables so that total scores on each scale could be compared to the other. Results: The study sample (n = 2,156) had an average age of 36.4 years (standard deviation [SD] = 13.0) and 59.7% were female. The mean depression scores for the PHQ-9, QIDS-C, and VQIDS-C were 12.9 (SD = 6.6), 12.0 (SD = 4.9), and 6.18 (SD = 3.2), respectively. The Cronbach's alpha coefficients for PHQ-9, QIDS-C, and VQIDS-C were 0.9, 0.8, and 0.7, respectively, suggesting acceptable internal consistency. PHQ-9 (TIF = 30.3) demonstrated the best assessment of depressive symptomology, followed by QIDS-C (TIF = 25.8) and VQIDS-C (TIF = 17.7). Conclusion: Overall, PHQ-9, QIDS-C, and VQIDS-C appear to be reliable and convertible measures of MDD symptomology within a US-based adult population in a real-world clinical setting.

Associations of comorbid substance use disorders with clinical outcomes in schizophrenia using electronic health record data.

BACKGROUND AND HYPOTHESIS: Schizophrenia and comorbid substance use disorders (SUDs) are associated with poor treatment outcomes but differences between the associations of different SUDs with clinical outcomes are poorly characterized. This study examines the associations of comorbid SUDs with clinical outcomes in schizophrenia using a largescale electronic health record (EHR) database. DESIGN: Real-world data (RWD) analysis using the NeuroBlu database; de-identified EHR data were analysed. Multivariable logistic regression, Poisson and CoxPH models were used to compare the associations of specific comorbid SUDs with outcome variables. RESULTS: Comorbid SUD was significantly different on all outcome measures compared to no SUD (U = 1.44e7-1.81e7, all ps < .001), except number of unique antipsychotics (U = 1.61e7, p = .43). Cannabis (OR = 1.58, p < .001) and polysubstance (OR = 1.22, p = .007) use disorders were associated with greater CGI-S. Cannabis (IRR = 1.13, p = .003) and polysubstance (IRR = 1.08, p = .003) use disorders were associated with greater number of unique antipsychotics prescribed, while cocaine (HR = 1.87, p < .001), stimulants (HR = 1.64, p = .024), and polysubstance (HR = 1.46, p < .001) use disorders were associated with a shorter time to antipsychotic discontinuation. Conversely, alcohol use (IRR = 0.83, p < .001), cocaine use (IRR = 0.61, p < .001), opioid use (IRR = 0.61, p < .001), stimulant use (IRR = 0.57, p < .001) and polysubstance use (IRR = 0.87, p < .001) disorders were associated fewer inpatient days. CONCLUSION: Comorbid SUDs were generally associated with greater CGI-S and poorer clinical outcomes in patients with schizophrenia. Treatment strategies should target not only schizophrenia symptoms but also comorbid SUD to improve management of both conditions.

Early trajectory of clinical global impression as a transdiagnostic predictor of psychiatric hospitalisation: a retrospective cohort study.

BACKGROUND: Identifying patients most at risk of psychiatric hospitalisation is crucial to improving service provision and patient outcomes. Existing predictors focus on specific clinical scenarios and are not validated with real-world data, limiting their translational potential. This study aimed to determine whether early trajectories of Clinical Global Impression Severity are predictors of 6 month risk of hospitalisation. METHODS: This retrospective cohort study used data from the NeuroBlu database, an electronic health records network from 25 US mental health-care providers. Patients with an ICD-9 or ICD-10 code of major depressive disorder, bipolar disorder, generalised anxiety disorder, post-traumatic stress disorder, schizophrenia or schizoaffective disorder, ADHD, or personality disorder were included. Using this cohort, we assessed whether clinical severity and instability (operationalised using Clinical Global Impression Severity measurements) during a 2-month period were predictors of psychiatric hospitalisation within the next 6 months. FINDINGS: 36 914 patients were included (mean age 29·7 years [SD 17·5]; 21 156 [57·3%] female, 15 748 [42·7%] male; 20 559 [55·7%] White, 4842 [13·1%] Black or African American, 286 [0·8%] Native Hawaiian or other Pacific Islander, 300 [0·8%] Asian, 139 [0·4%] American Indian or Alaska Native, 524 (1·4%) other or mixed race, and 10 264 [27·8%] of unknown race). Clinical severity and instability were independent predictors of risk of hospitalisation (adjusted hazard ratio [HR] 1·09, 95% CI 1·07-1·10 for every SD increase in instability; 1·11, 1·09-1·12 for every SD increase in severity; p<0·0001 for both). These associations were consistent across all diagnoses, age groups, and in both males and females, as well as in several robustness analyses, including when clinical severity and clinical instability were based on the Patient Health Questionnaire-9 rather than Clinical Global Impression Severity measurements. Patients in the top half of the cohort for both clinical severity and instability were at an increased risk of hospitalisation compared with those in the bottom half along both dimensions (HR 1·45, 95% CI 1·39-1·52; p<0·0001). INTERPRETATION: Clinical instability and severity are independent predictors of future risk of hospitalisation, across diagnoses, age groups, and in both males and females. These findings could help clinicians make prognoses and screen patients who are most likely to benefit from intensive interventions, as well as help health-care providers plan service provisions by adding additional detail to risk prediction tools that incorporate other risk factors. FUNDING: National Institute for Health and Care Research, National Institute for Health and Care Research Oxford Health Biomedical Research Centre, Medical Research Council, Academy of Medical Sciences, and Holmusk.

Factors That Affect Patient Attrition in Buprenorphine Treatment for Opioid Use Disorder: A Retrospective Real-World Study Using Electronic Health Records.

PURPOSE: To describe attrition patterns of opioid use disorder (OUD) patients treated with buprenorphine (BUP) and to assess how clinical, sociodemographic, or BUP medication dosing features are associated with attrition. PATIENTS AND METHODS: Electronic health records of adults (16+ year-olds) with OUD treated with BUP from 23 different substance use or mental health care programs across 11 US states were examined for one year following BUP initiation in inpatient (IP), intensive outpatient (IOP), or outpatient (OP) settings. Treatment attrition was declared at >37 days following the last recorded visit. Survival analyses and predictive modelling were used. RESULTS: Retention was consistently 2-3 times higher following BUP initiation in OP (n = 2409) than in IP/IOP (n = 2749) settings after 2 (50% vs 25%), 6 (27% vs 9%) and 12 months (14% vs 4%). Retention was higher for females, whites (vs blacks), and those with less severe OUD, better global function, or not using non-psychotropic medications. Comorbid substance use, other psychiatric disorders, and the number of psychotropic medications were variously related to retention depending on the setting in which BUP was initiated. Predictive modelling revealed that a higher global assessment of functioning and a smaller OUD severity based on the Clinical Global Impression - Severity led to longer retentions, a higher initial BUP dose led to higher retention in a few cases, an OP setting of BUP initiation led to longer retentions, and a lower total number of psychotropic and non-psychotropic medications led to longer retentions. These were the most important parameters in the model, which identified 75.2% of patients who left BUP treatment within three months post-initiation, with a precision of 90.5%. CONCLUSION: Of all the OUD patients who began BUP, 50-75% left treatment within three months, and most could be accurately identified. This could facilitate patient-centered management to better retain OUD patients in BUP treatment.