Over the last two decades, opioid prescription and prevalence has increased to account for over 33,000 deaths per year (Soelberg, Brown, Du Vivier, Meyer & Ramachandran, 2017). This is not only due to overdose, but misuse, abuse, and addiction. The abrupt increase in prescriptions, pills dispensed, and opioid-related deaths have encouraged the involvement of multiple entities.

In 2016, the opioid crisis gained the attention of communities that released guidelines to regulate prescription of opioid pain management. Such entities include the Center for Disease Control and Prevention (CDC), National Institute on Drug Abuse, Agency for Healthcare Research and Quality (AHRQ), Arizona Department of Health Services (AZDHS), and Substance Abuse and Mental Health Services Administration (SAMHSA). Evidence shows that prescribing practices between providers vary. It also shows that providers lack knowledge of appropriate opioid prescribing and management. To address this problem, provider education on an opioid policy is the most effective way to uniform opioid prescribing.

Homeless individuals encounter barriers such as lack of health insurance, increased cost of care and unavailability of resources. They have increased risk of comorbid physical disease and poor mental health. Depression is a prevalent mental health disorder in the US linked to increased risk of mortality. Literature suggests depression screening can identify high-risk individuals with using the patient health questionnaire (PHQ-9).

The objective of this project is to determine if screening identifies depression in the homeless and how it impacts healthcare access. Setting is a local organization in Phoenix offering shelter to homeless individuals. An evidence-based project was implemented over two months in 2019 using convenience sampling. Intervention included depression screening using the PHQ-9, referring to primary care and tracking appointment times. IRB approval obtained from Arizona State University, privacy discussed, and consent obtained prior to data collection. Participants were assigned a random number to protect privacy.

A chart audit tool was used to obtain sociodemographics and insurance status. Descriptive statistics used and analyzed using Intellectus. Sample size was (n = 18), age (M = 35) most were White-non-Hispanic, 44% had a high school diploma and 78% were insured. Mean score was 7.72, three were previously diagnosed and not referred. Three were referred with a turnaround appointment time of one, two and seven days respectively. No significant correlation found between age and depression severity. A significant correlation found between previous diagnosis and depression severity. Attention to PHQ-9 varied among providers and not always addressed. Future projects should focus on improving collaboration between this facility and providers, increasing screening and ensuring adequate follow up and treatment.