Large language models outperform mental and medical health care professionals in identifying obsessive-compulsive disorder.

Despite the promising capacity of large language model (LLM)-powered chatbots to diagnose diseases, they have not been tested for obsessive-compulsive disorder (OCD). We assessed the diagnostic accuracy of LLMs in OCD using vignettes and found that LLMs outperformed medical and mental health professionals. This highlights the potential benefit of LLMs in assisting in the timely and accurate diagnosis of OCD, which usually entails a long delay in diagnosis and treatment.

Provision of Digital Health Technologies for Opioid Use Disorder Treatment by US Health Care Organizations.

Importance: Digital health technologies may expand organizational capacity to treat opioid use disorder (OUD). However, it remains unclear whether these technologies serve as substitutes for or complements to traditional substance use disorder (SUD) treatment resources in health care organizations. Objective: To characterize the use of patient-facing digital health technologies for OUD by US organizations with accountable care organization (ACO) contracts. Design, Setting, and Participants: This cross-sectional study analyzed responses to the 2022 National Survey of Accountable Care Organizations (NSACO), collected between October 1, 2021, and June 30, 2022, from US organizations with Medicare and Medicaid ACO contracts. Data analysis was performed between December 15, 2022, and January 6, 2023. Exposures: Treatment resources for SUD (eg, an addiction medicine specialist, sufficient staff to treat SUD, medications for OUD, a specialty SUD treatment facility, a registry to identify patients with OUD, or a registry to track mental health for patients with OUD) and organizational characteristics (eg, organization type, Medicaid ACO contract). Main Outcomes and Measures: The main outcomes included survey-reported use of 3 categories of digital health technologies for OUD: remote mental health therapy and tracking, virtual peer recovery support programs, and digital recovery support for adjuvant cognitive behavior therapy (CBT). Statistical analysis was conducted using descriptive statistics and multivariable logistic regression models. Results: Overall, 276 of 505 organizations responded to the NSACO (54.7% response rate), with a total of 304 respondents. Of these, 161 (53.1%) were from a hospital or health system, 74 (24.2%) were from a physician- or medical group-led organization, and 23 (7.8%) were from a safety-net organization. One-third of respondents (101 [33.5%]) reported that their organization used at least 1 of the 3 digital health technology categories, including remote mental health therapy and tracking (80 [26.5%]), virtual peer recovery support programs (46 [15.1%]), and digital recovery support for adjuvant CBT (27 [9.0%]). In an adjusted analysis, organizations with an addiction medicine specialist (average marginal effect [SE], 32.3 [4.7] percentage points; P < .001) or a registry to track mental health (average marginal effect [SE], 27.2 [3.8] percentage points; P < .001) were more likely to use at least 1 category of technology compared with otherwise similar organizations lacking these capabilities. Conclusions and Relevance: In this cross-sectional study of 276 organizations with ACO contracts, organizations used patient-facing digital health technologies for OUD as complements to available SUD treatment capabilities rather than as substitutes for unavailable resources. Future studies should examine implementation facilitators to realize the potential of emerging technologies to support organizations facing health care practitioner shortages and other barriers to OUD treatment delivery.

Practices for monitoring and responding to incoming data on self-injurious thoughts and behaviors in intensive longitudinal studies: A systematic review.

Advancements in the understanding and prevention of self-injurious thoughts and behaviors (SITBs) are urgently needed. Intensive longitudinal data collection methods-such as ecological momentary assessment-capture fine-grained, "real-world" information about SITBs as they occur and thus have the potential to narrow this gap. However, collecting real-time data on SITBs presents complex ethical and practical considerations, including about whether and how to monitor and respond to incoming information about SITBs from suicidal or self-injuring individuals during the study. We conducted a systematic review of protocols for monitoring and responding to incoming data in previous and ongoing intensive longitudinal studies of SITBs. Across the 61 included unique studies/samples, there was no clear most common approach to managing these ethical and safety considerations. For example, studies were fairly evenly split between either using automated notifications triggered by specific survey responses (e.g., indicating current suicide risk) or monitoring and intervening upon (generally with a phone-based risk assessment) incoming responses (36%), using both automated notifications and monitoring/intervening (35%), or neither using automated notifications nor monitoring/intervening (29%). Certain study characteristics appeared to influence the safety practices used. Future research that systematically evaluates optimal, feasible strategies for managing risk in real-time monitoring research on SITBs is needed.

Telerehabilitation in Psychiatry.

The COVID-19 pandemic has interrupted the usual mechanisms of healthcare delivery and exacerbated symptoms of mental illnesses. Telemedicine has morphed from niche service to essential platform, with newly released guidelines that cover various aspects of tele-mental health delivery. Rehabilitation services, which incorporate a range of psychosocial interventions and liaison services, have been significantly impacted too. They are currently more institute-based than community-based in India. However, recent legislation has mandated that community-based rehabilitation options be available. While a large treatment gap for mental health issues has always existed, telemedicine provides an opportunity to scale services up to minimize this gap. Community-based rehabilitation can be delivered over various platforms, from text to phone to videoconferencing, and various devices. Telemedicine is cost-effective, and enables delivery of services where existing services are inadequate. The recent guidelines allow other healthcare workers to be involved in mental health service delivery. Hence, in addition to direct delivery of services, telerehabilitation can facilitate task-shifting, with mental health professionals mentoring and supervising existing human resources, such as ASHA workers, VRWs, DMHP programme staff, and others. Tele-rehabilitation also poses challenges - not all needs can be met; access and privacy can be a problem in resource-scarce settings; liaison with existing services is required; and organisations need to plan appropriately and re-allocate resources. Digital access to welfare benefits and interventions must be expanded without disadvantaging those without internet access. Yet, many rehabilitation interventions can be adapted to telemedicine platforms smoothly, and task-shifting can broaden access to care for persons with disability.

Generating value with mental health apps.

BACKGROUND: Although apps are increasingly being used to support the diagnosis, treatment and management of mental illness, there is no single means through which costs associated with mental apps are being reimbursed. Furthermore, different apps are amenable to different means of reimbursement as not all apps generate value in the same way. AIMS: To provide insights into how apps are currently generating value and being reimbursed across the world, with a particular focus on the situation in the USA. METHOD: An international team performed secondary research on how apps are being used and on common pathways to remuneration. RESULTS: The uses of apps today and in the future are reviewed, the nature of the value delivered by apps is summarised and an overview of app reimbursement in the USA and other countries is provided. Recommendations regarding how payments might be made for apps in the future are discussed. CONCLUSIONS: Currently, apps are being reimbursed through channels with other original purposes. There may be a need to develop an app-specific channel for reimbursement which is analogous to the channels used for devices, drugs and laboratory tests.

The power of capturing and using information at the point of care.

Historically, the process of scientific discovery and the process of clinical delivery have been poorly integrated. As a result of the Decade of Health Information Technology (2004-2014), many of the former barriers to capturing, processing, and retrieving medical information at the point of care have been surmounted. This change has the potential to both transform how new medical discoveries are made and how evidence-based medicine is put into practice. To illustrate the impact of this ongoing change, several examples are provided of institutions which have innovatively used information at the point of care.

To Use or Not? Evaluating ASPECTS of Smartphone Apps and Mobile Technology for Clinical Care in Psychiatry.

In this commentary, we discuss smartphone apps for psychiatry and the lack of resources to assist clinicians in evaluating the utility, safety, and efficacy of apps. Evaluating an app requires new considerations that are beyond those employed in evaluating a medication or typical clinical intervention. Based on our software engineering, informatics, and clinical knowledge and experiences, we propose an evaluation framework, "ASPECTS," to spark discussion about apps and aid clinicians in determining whether an app is Actionable, Secure, Professional, Evidence-based, Customizable, and TranSparent. Clinicians who use the ASPECTS guide will be more informed and able to make more thorough evaluations of apps.