Increasing access to mental health supports for healthcare workers during the COVID-19 pandemic and beyond through a novel coaching program.

The COVID-19 pandemic led to heightened anxiety, distress, and burnout among healthcare workers and faculty in academic medicine. Penn Medicine launched Coping First Aid (CFA) in March 2020 in response to the pandemic. Informed by Psychological First Aid principles and therapeutic micro skills, CFA was designed as a tele-mental healthcare service for health system employees and their families delivered by trained lay volunteer coaches under the supervision of licensed mental health clinicians. We present an overview of the model, feasibility and utilization data, and preliminary implementation and effectiveness outcomes based on cross sectional coach (n = 22) and client (n = 57) self-report surveys with a subset of program users in the first year. A total of 44 individuals completed training and were certified to coach. Over the first 24 months of the program, 513 sessions occurred with 273 clients (119 sessions were no-shows or canceled). Follow-up appointments were recommended in 52.6% (n = 270) of sessions and 21.2% (n = 109) of clients were referred for professional mental health care. Client survey respondents reported CFA was helpful; 60% were very or extremely satisfied, and 74% indicated they would recommend the program. Our preliminary findings suggest that CFA was feasible to implement and most clients found the service beneficial. CFA provides a model for rapidly developing and scaling mental health supports during and beyond the pandemic.

Behavioral Health Needs of a Commercially Insured Adult Population with Type 2 Diabetes

Background: There is an increasing appreciation of the interconnection between chronic illnesses such as type-2 diabetes and behavioral health conditions such as depression and anxiety, as well as more serious behavioral health conditions. The separation of practice and payment for medical and behavioral conditions is ripe for disruption. This is of particular importance for risk-bearing entities. Methods: Level2 is a virtual accountable care organization taking total cost-of-care risk for a commercially insured population. Using a de-identified administrative claims research database, we estimated the behavioral health profile of our enrolled population by examining the prescribing of common behavioral health medications. Results: In our enrolled population of 7,361 members, the average age was 54.4 years, and the M:F ratio was 53:47. Prescriptions for behavioral health medications were demonstrated in 26.2% of the population. Medications for depression and anxiety were most common (20.0% and 8.0% respectively) , while antipsychotics were prescribed in 0.1% of attributed members. Twenty-four months of enrollment (November 2019- November 2021) showed stable prescribing patterns. Conclusion: The movement towards provider risk bearing, and a more sophisticated understanding of the relationship between physical and behavioral health, necessitate a more comprehensive and integrated approach to care for patients. While this intersection may be evident to providers in their daily activities, the analysis of a population of nearly 7,400 members gives a broader insight into this challenge and calls for clinical service redesign, the application of new methodologies and measurements, and over time, new payment models. Of note, the prescribing data spans the COVID and pre-COVID periods and was stable over time, so the high use of behavioral health medications is not COVID-attributable.

COBALT: Supporting the mental well-being of the health care workforce with technology-facilitated care during Covid-19 and beyond.

Two-thirds of health professionals facing the clinical demands of responding to the Covid-19 pandemic experience psychiatric symptoms, including post-traumatic stress, anxiety, substance use, depression, insomnia, and suicide.1,2 Compounding matters, access to mental health services is poor, quality is variable, and stigma is prevalent. COBALT, a digital mental health and wellness platform developed at Penn Medicine, was designed to support health care workers, offering a combination of self-directed resources, virtual group sessions, and individual appointments with a stepped care model of providers, including peers, resilience coaches, psychotherapists, and psychiatrists. In COBALT's first 11 months, the platform saw approximately 10,000 users, 200,000 page views, 1,400 one-on-one appointment bookings, over 1,000 group appointment reservations, and 158 interceptions of employees contemplating self-harm. COBALT reveals the unmet demand for mental health support among health professionals and provides a model for both expanding the supply of and streamlining access to services.

A call for open data to develop mental health digital biomarkers.

Digital biomarkers of mental health, created using data extracted from everyday technologies including smartphones, wearable devices, social media and computer interactions, have the opportunity to revolutionise mental health diagnosis and treatment by providing near-continuous unobtrusive and remote measures of behaviours associated with mental health symptoms. Machine learning models process data traces from these technologies to identify digital biomarkers. In this editorial, we caution clinicians against using digital biomarkers in practice until models are assessed for equitable predictions ('model equity') across demographically diverse patients at scale, behaviours over time, and data types extracted from different devices and platforms. We posit that it will be difficult for any individual clinic or large-scale study to assess and ensure model equity and alternatively call for the creation of a repository of open de-identified data for digital biomarker development.