Improving Depression and Anxiety Care in the Post-COVID Population

Background: The coronavirus pandemic has left countless individuals with lingering symptoms, both mental and physical. Anxiety and depression were among some of the top complaints reported by patients, causing an increased need for mental health care in the post-COVID patient population. Adequate screening and referral are crucial to ensure proper management of these conditions. Local Problem: Patients seen in the Comprehensive COVID-19 Clinic in Salt Lake City, Utah were being screened for anxiety and depression using the Generalized Anxiety Disorder Scale (GAD-7) and Patient Health Questionnaire (PHQ-9). However, there was no standardized practice on when patients should be referred to social work, leaving many individuals without needed care. A social work algorithm and patient/provider toolkit were implemented to help increase social work referral rates and provide resources for clinic staff and patients. Methods: A pre/post-intervention design was used. Data on the total number of patients seen in the clinic, total number of patients screened using the PHQ-9 and GAD-7, aggregate patient scores on the PHQ-9 and GAD-7 instruments, and number of social work referrals written were collected and compared to evaluate if any changes were seen with the intervention. In addition, pre/post-surveys were conducted to evaluate provider knowledge and the usability, feasibility, and satisfaction of the algorithm and toolkit. Interventions: A social work referral algorithm was implemented to help guide providers on when to offer a social work referral based on PHQ-9 and GAD-7 scores. Keyboard shortcuts were also created to help streamline charting for providers and a self-care guide document was generated that was given to patients upon discharge from the clinic. Results: Post-intervention, the study found a 28.6 percent increase in social work referrals over a 3-month period. High usability, feasibility, and satisfaction were also reported by all staff members (n=4) with all reporting the intent to continue using the algorithm and toolkit after the completion of the project. Conclusion: The algorithm and the toolkit appear to be valuable resources to help increase social work referral rates and improve mental health care in this patient population. Replication of this quality improvement project is needed to determine if similar results occur with other patient populations.