Envisioning the Future of Well-Being Efforts for Health Care Workers-Successes and Lessons Learned From the COVID-19 Pandemic.

Importance: The National Academy of Medicine's National Plan for Health Workforce Well-Being provides recommendations for supporting the mental health and well-being of health care workers. This article aims to guide implementation of National Academy of Medicine recommendations by describing 2 programs at Columbia University Irving Medical Center and the University of California, San Francisco (UCSF), designed early in the COVID-19 pandemic to respond to the behavioral health needs of the health care workforce. The development of these programs, their similarities and differences, and the key lessons learned are discussed. Observations: The well-being programs, CopeColumbia and UCSF Cope, shared key elements. Both efforts were led by their respective departments of psychiatry and used similar frameworks. Teams created strategic cross-university partnerships to share difficulties and successes across both programs. Moreover, both programs addressed compounding stressors of racial and political unrest, evaluated program components, and created resources for employee self-management. CopeColumbia and UCSF Cope differed in approaches to identifying high-risk employees and formal assessment and treatment pathways. From the authors' experience implementing these programs and having knowledge regarding health care workforce burnout, this article offers recommendations for the development of well-being programs. These include structural changes and resources to promote group and individual well-being emphasizing equity and justice, intentional involvement of psychiatry on well-being leadership teams, and bold efforts to destigmatize mental health care alongside clear paths to mental health treatment. Conclusions and Relevance: The impact of the COVID-19 pandemic revealed a need for institutions to support the mental health and emotional well-being of health care workers. By outlining the development and implementation of 2 well-being programs in large academic health care settings and making recommendations to promote workforce well-being, it is the authors' hope that leaders will be empowered to carry forward critical changes. Most importantly, implementing plans now will provide the resilience needed both for the long shadow of the pandemic and future crises.

Meeting the Behavioral Health Needs of Health Care Workers During COVID-19 by Leveraging Chatbot Technology: Development and Usability Study.

BACKGROUND: During the COVID-19 pandemic, health care systems were faced with the urgent need to implement strategies to address the behavioral health needs of health care workers. A primary concern of any large health care system is developing an easy-to-access, streamlined system of triage and support despite limited behavioral health resources. OBJECTIVE: This study provides a detailed description of the design and implementation of a chatbot program designed to triage and facilitate access to behavioral health assessment and treatment for the workforce of a large academic medical center. The University of California, San Francisco (UCSF) Faculty, Staff, and Trainee Coping and Resiliency Program (UCSF Cope) aimed to provide timely access to a live telehealth navigator for triage and live telehealth assessment and treatment, curated web-based self-management tools, and nontreatment support groups for those experiencing stress related to their unique roles. METHODS: In a public-private partnership, the UCSF Cope team built a chatbot to triage employees based on behavioral health needs. The chatbot is an algorithm-based, automated, and interactive artificial intelligence conversational tool that uses natural language understanding to engage users by presenting a series of questions with simple multiple-choice answers. The goal of each chatbot session was to guide users to services that were appropriate for their needs. Designers developed a chatbot data dashboard to identify and follow trends directly through the chatbot. Regarding other program elements, website user data were collected monthly and participant satisfaction was gathered for each nontreatment support group. RESULTS: The UCSF Cope chatbot was rapidly developed and launched on April 20, 2020. As of May 31, 2022, a total of 10.88% (3785/34,790) of employees accessed the technology. Among those reporting any form of psychological distress, 39.7% (708/1783) of employees requested in-person services, including those who had an existing provider. UCSF employees responded positively to all program elements. As of May 31, 2022, the UCSF Cope website had 615,334 unique users, with 66,585 unique views of webinars and 601,471 unique views of video shorts. All units across UCSF were reached by UCSF Cope staff for special interventions, with >40 units requesting these services. Town halls were particularly well received, with >80% of attendees reporting the experience as helpful. CONCLUSIONS: UCSF Cope used chatbot technology to incorporate individualized behavioral health triage, assessment, treatment, and general emotional support for an entire employee base (N=34,790). This level of triage for a population of this size would not have been possible without the use of chatbot technology. The UCSF Cope model has the potential to be scaled, adapted, and implemented across both academically and nonacademically affiliated medical settings.

Achieving Mental Health Equity: Collaborative Care.

The literature supports the effectiveness of systems-based integrated care models, particularly collaborative care, to improve access, quality of care, and health outcomes for behavioral health conditions. There is growing evidence for the promise of collaborative care to reduce behavioral health disparities for racial and ethnic, low-income, and other at-risk populations. Using rapid literature review, this article highlights what is known about how collaborative care may promote health equity for behavioral health conditions, by reducing disparities in access, quality, and outcomes of care. Further, it explores innovative intervention and engagement strategies to promote behavioral health equity for at-risk groups.

The Psychiatric Assessment and Brief Intervention Program: Partnering With Primary Care Providers.

OBJECTIVE: To present the structure and outcomes to date for the Psychiatric Assessment and Brief Intervention (PABI), a pilot program developed at University of California, San Francisco, to improve access of primary care patients to mental health services. PABI offers diagnostic evaluations and brief (up to 3 months) evidence-based treatment, including pharmacologic management and psychotherapy, to medical patients 18 years of age and older. Core PABI features are ensuring prompt access, actively partnering with patients and referring providers, and coordinating seamless transitions of care. METHODS: Demographic and clinical variables and outcome indicators were collected for all patients seen in PABI from October 2015 to June 2017. Descriptive statistics and mixed-effects linear models were used to analyze the data. RESULTS: During the study period, 139 patients (54% women, mean [SD] age of 48.2 [17.5] years) with a mean of 2 DSM-5 psychiatric diagnoses each (range, 1-5) were seen. Mean time to access was 8 days, with a mean length of stay in the program of 11 weeks. Compared to baseline, final behavioral health measure scores showed significant improvement: the mean Patient Health Questionnaire-9 score decreased by 5.9 points (95% CI, 4.6-7.2), and the mean 7-item Generalized Anxiety Disorder scale score was 4.4 points lower (95% CI, 3.2-5.6; both P values < .0001). CONCLUSIONS: This brief psychiatric treatment program provides prompt access to quality mental health care for patients with medical comorbidities. Results to date suggest that this program leads to significantly improved clinical outcomes. Further research is needed to determine its long-term sustainability and generalizability.

Patient engagement programs for recognition and initial treatment of depression in primary care: a randomized trial.

IMPORTANCE: Encouraging primary care patients to address depression symptoms and care with clinicians could improve outcomes but may also result in unnecessary treatment. OBJECTIVE: To determine whether a depression engagement video (DEV) or a tailored interactive multimedia computer program (IMCP) improves initial depression care compared with a control without increasing unnecessary antidepressant prescribing. DESIGN, SETTING, AND PARTICIPANTS: Randomized clinical trial comparing DEV, IMCP, and control among 925 adult patients treated by 135 primary care clinicians (603 patients with depression and 322 patients without depression, defined by Patient Health Questionnaire-9 [PHQ-9] score) conducted from June 2010 through March 2012 at 7 primary care clinical sites in California. INTERVENTIONS: DEV targeted to sex and income, an IMCP tailored to individual patient characteristics, and a sleep hygiene video (control). MAIN OUTCOMES AND MEASURES: Among depressed patients, superiority assessment of the composite measure of patient-reported antidepressant drug recommendation, mental health referral, or both (primary outcome); depression at 12-week follow-up, measured by the PHQ-8 (secondary outcome). Among nondepressed patients, noninferiority assessment of clinician- and patient-reported antidepressant drug recommendation (primary outcomes) with a noninferiority margin of 3.5%. Analyses were cluster adjusted. RESULTS: Of the 925 eligible patients, 867 were included in the primary analysis (depressed, 559; nondepressed, 308). Among depressed patients, rates of achieving the primary outcome were 17.5% for DEV, 26% for IMCP, and 16.3% for control (DEV vs control, 1.1 [95% CI, -6.7 to 8.9], P = .79; IMCP vs control, 9.9 [95% CI, 1.6 to 18.2], P = .02). There were no effects on PHQ-8 measured depression score at the 12-week follow-up: DEV vs control, -0.2 (95% CI, -1.2 to 0.8); IMCP vs control, 0.9 (95% CI, -0.1 to 1.9). Among nondepressed patients, clinician-reported antidepressant prescribing in the DEV and IMCP groups was noninferior to control (mean percentage point difference [PPD]: DEV vs control, -2.2 [90% CI, -8.0 to 3.49], P = .0499 for noninferiority; IMCP vs control, -3.3 [90% CI, -9.1 to 2.4], P = .02 for noninferiority); patient-reported antidepressant recommendation did not achieve noninferiority (mean PPD: DEV vs control, 0.9 [90% CI, -4.9 to 6.7], P = .23 for noninferiority; IMCP vs control, 0.3 [90% CI, -5.1 to 5.7], P = .16 for noninferiority). CONCLUSIONS AND RELEVANCE: A tailored IMCP increased clinician recommendations for antidepressant drugs, a mental health referral, or both among depressed patients but had no effect on mental health at the 12-week follow-up. The possibility that the IMCP and DEV increased patient-reported clinician recommendations for an antidepressant drug among nondepressed patients could not be excluded. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01144104.

Improving care for minorities: can quality improvement interventions improve care and outcomes for depressed minorities? Results of a randomized, controlled trial.

OBJECTIVE: Ethnic minority patients often receive poorer quality care and have worse outcomes than white patients, yet practice-based approaches to reduce such disparities have not been identified. We determined whether practice-initiated quality improvement (QI) interventions for depressed primary care patients improve care across ethnic groups and reduce outcome disparities. STUDY SETTING: The sample consists of 46 primary care practices in 6 U.S. managed care organizations; 181 clinicians; 398 Latinos, 93 African Americans, and 778 white patients with probable depressive disorder. STUDY DEIGN: Matched practices were randomized to usual care or one of two QI programs that trained local experts to educate clinicians; nurses to educate, assess, and follow-up with patients; and psychotherapists to conduct Cognitive Behavioral Therapy. Patients and physicians selected treatments. Interventions featured modest accommodations for minority patients (e.g., translations, cultural training for clinicians). DATA EXTRACTION METHODS: Multilevel logistic regression analyses assessed intervention effects within and among ethnic groups. PRINCIPAL FINDINGS: At baseline, all ethnic groups Latino, African American, white) had low to moderate rates of appropriate care and the interventions significantly improved appropriate care at six months (by 8-20 percentage points) within each ethnic group, with no significant difference in response by ethnic group. The interventions significantly decreased the likelihood that Latinos and African Americans would report probable depression at months 6 and 12; the white intervention sample did not differ from controls in reported probable depression at either follow-up. While the intervention significantly improved the rate of employment for whites and not for minorities, precision was low for comparing intervention response on this outcome. It is important to note that minorities remained less likely to have appropriate care and more likely to be depressed than white patients. CONCLUSIONS: Implementation of quality improvement interventions that have modest accommodations for minority patients can improve quality of care for whites and underserved minorities alike, while minorities may be especially likely to benefit clinically. Further research needs to clarify whether employment benefits are limited to whites and if so, whether this represents a difference in opportunities. Quality improvement programs appear to improve quality of care without increasing disparities, and may offer an approach to reduce health disparities.