Literature Collection

Background: Screening for unhealthy drug use is now recommended for adult primary care patients, but primary care providers (PCPs) generally lack the time and knowledge required to screen and deliver an intervention during the medical visit. To address these barriers, we developed a tablet computer-based 'Substance Use Screening and Intervention Tool (SUSIT)'. Using the SUSIT, patients self-administer screening questionnaires prior to the medical visit, and results are presented to the PCP at the point of care, paired with clinical decision support (CDS) that guides them in providing a brief intervention (BI) for unhealthy drug use. Methods: PCPs and their patients with moderate-risk drug use were recruited from primary care and HIV clinics. A pre-post design compared a control 'screening only' (SO) period to an intervention 'SUSIT' period. Unique patients were enrolled in each period. In both conditions, patients completed screening and identified their drug of most concern (DOMC) before the visit, and completed a questionnaire about BI delivery by the PCP after the visit. In the SUSIT condition only, PCPs received the tablet with the patient's screening results and CDS. Multilevel models with random intercepts and patients nested within PCPs examined the effect of the SUSIT intervention on PCP delivery of BI. Results: 20 PCPs and 79 patients (42 SO, 37 SUSIT) participated. Most patients had moderate-risk marijuana use (92.4%), and selected marijuana as the DOMC (68.4%). Moderate-risk use of drugs other than marijuana included cocaine (15.2%), hallucinogens (12.7%), and sedatives (12.7%). Compared to the SO condition, patients in SUSIT had higher odds of receiving any BI for drug use, with an adjusted odds ratio of 11.59 (95% confidence interval: 3.39, 39.25), and received more elements of BI for drug use. Conclusions: The SUSIT significantly increased delivery of BI for drug use by PCPs during routine primary care encounters.

BACKGROUND: Incorporation of cognitive screening into the busy primary care will require the development of highly efficient screening tools. We report the convergence validity of a very brief, self-administered, computerized assessment protocol against one of the most extensively used, clinician-administered instruments-the Montreal Cognitive Assessment (MoCA). METHOD: Two hundred six participants (mean age = 67.44, standard deviation [SD] = 11.63) completed the MoCA and the computerized test. Three machine learning algorithms (ie, Support Vector Machine, Random Forest, and Gradient Boosting Trees) were trained to classify participants according to the clinical cutoff score of the MoCA (ie, /=26, n = 165), suggesting greater sensitivity to age-related changes in cognitive functioning. CONCLUSION: Future studies should examine ways to improve the sensitivity of the computerized test by expanding the cognitive domains it measures without compromising its efficiency.

Integrated health care includes joint, outpatient delivery of medical and behavioral health services. Traditional patient satisfaction measures might fail to capture the discrete delivery approaches in this model. To identify patient satisfaction measures used in integrated health care settings, a systematic review was conducted of US-based studies conducted in adult outpatient integrated care settings from 1999 through 2020. Study quality was assessed using standards recommended by the COSMIN guidelines. The review yielded a sample of 23 studies, consisting of 10 standardized measures and 6 self-developed tools. All studies/measures met at least one of the identified COSMIN guidelines, demonstrating quality of the measures. While most measures evaluated key elements of integration, including access, communication, and relationships, only one standardized measure evaluated elements of care specific to practice in integrated care. Findings suggest a need for a comprehensive patient satisfaction measure that captures important aspects of the integrated health care experience.