The overall study sample included the 11,803 patients seen at the nine BCC clinics within the 2017 calendar year. The average age was 48 years old, 64.30% (n=7,584) of the study sample were female and 62.30% (n=7,358) of the sample identified as Hispanic (Table 1).

National rates of depression screening in primary care remain very low, with racial minorities half as likely to be screened compared with whites (Casey, 2013). In the current study, however, the overall screening rate with PHQ-2 was substantially higher at 67%, suggesting that implementation of EHR technology has likely enhanced routine screening at intake. Interetsingly, the odds of being screened was higher for Hispanic patients, yet they were less likely to actually be diagnosed with depression in comparison non-Hispanic patients, differences which may reflect language barriers in symptom measurement and persistent gaps in access to quality depression care and disparities in receipt of treatment (Akincigil & Matthews, 2017). Our previous work on symptom measurement among Hispanics in primary care characterized the specific manifestation of depression in a Hispanic population, with the single item related to fatigue showing the greatest varaition across groups (Killian, Sanchez, Eghaneyan, Cabassa, & Trivedi, 2021). It is important to note that while the PHQ-9 can be used to alert clinicians for evidence of disease, it cannot distinguish between differential depressive disorders nor can it confirm the diagnosis itself. Consideration of the use of additional screening tools, especially in Hispanic populations, could prove helpful for differentiating between disorders, such as anxiety, and may help shift clinical focus away from negative symtomotology to positive mental health (Guillot-Valdés et al., 2019; Teismann et al., 2019).

There was no significant difference between the portion of patients treated with antidepressants compared to behavioral health which is encouraging since patients with depression disorders often express a preference for counseling over pharmacological treatment (McHugh et al., 2013). However, more than half of patients with a depression diagnosis did not have a treatment plan recorded in the EHR. While it is possible that patients were referred to specialty care, that was not evident from the medical record. This finding is congruent with a recent analysis of depression treatment initiation patterns among primary care settings across five large, integrated US healthcare systems which reported only 35.70% of new episodes of diagnosed depression initiated antidepressant medication and/or psychotherapy, with all racial and ethnic minority groups having significantly lower odds of starting treatment, and the average delay in initiation of treatment being 6-8 years (Waitzfelder et al., 2018).

In the current analysis, Hispanic patients diagnosed with depression were more likely to use anti-depressants and had greater odds of behavioral health visits compared to non-Hispanic patients which contrasts with large health system data studies reporting that the odds of treatment initiation for Asians, non-Hispanic blacks, and Hispanics to be 30% lower than for non-Hispanic whites (Waitzfelder et al., 2018). Inclusion of the behavioral health provider on the primary care team can address significant barriers to treatment such as stigma, limited knowledge of mental health disorders, and treatment engagement and adherence, which disproportionately affect racial and ethnic minorities (Kahalnik et al., 2019; Siu et al., 2016), and was likely a factor in this study, though those gains may be limited in reach in low resource settings.

Only one-third of the patients with a depression diagnosis had a follow up PHQ-9 score recorded within six months of the first diagnosis, which reflects nonadherence to evidence-based treatment guidelines. Without proper documentation of regular quantitative assessment of symptoms and provider adjustment of the treatment plan in response to symptoms, trends in a single patient’s remission, relapse, and recovery cannot be assessed (Trombello et al., 2017). Even if a patient with depression reaches remission of depressive symptoms, they may have a relapse of symptoms or develop a new episode of depression. Further, the more failed treatment attempts a patient has, the higher the chances are of relapse. Active and routine measurement of depressed patients can help the clinician identify those at greatest risk for relapse (Lewis et al., 2019) and trends of the overall clinic population and depression management can be tracked.

Barriers to effective implementation of MBC include patient concerns about breach of confidentially, provider belief that measurement is inferior to clinical judgment, lack of resources for MBC training, and finally, competing clinical priorities (Kahalnik et al., 2019; Lewis et al., 2019). Opportunities for improving measurement include harmonizing EHRs and technology support to encourage MBC practices, prompts and reminders to set follow up appointments and to remind clinicians to collect follow up PHQ-9 scores within those appointments could be especially beneficial if integrated within EHR systems (Fortney et al., 2017).

This study has some limitations largely attributable to the data extracted from the EHR. Epic was implemented in the community clinics in 2017, so patient data prior to 2017 was not available. Additionally, data which may have been inaccurately documented, such as imbedded within clinician notes (primary and behavioral health), could not be extracted and accounted for in the analysis. In determining follow-up variables, it is possible that the patients failed to keep a scheduled appointment. In spite of these limitations, the EHR data revealed important depression screening, diagnosis, treatment and measurement patterns.

Over the past decade, robust research has demonstrated the gaps in care for low-income racial and ethnic minority groups in spite of incentives for primary care clinics with reimbursements for annual screening. Findings from this study demonstrate improved screening, diagnosis, and treatment initiation for patients with depression, however, there is substantial need for better implementation of MBC guidelines and consistent documentation of follow up PHQ-9 in the EHR. Routine measurement of depression symptoms should guide treatment decisions. Understanding the unique qualities, and potential reach, of behavioral health providers in community-based clinics has important implications for closing disparity gaps in depression treatment.

Future research should evaluate facilitators and barriers to implementing evidenced based interventions while incorporating technology solutions for decision support in the EHR. The practice transformation necessary for broad implementation of evidence-based depression screening and treatment guidelines into practice will require analysis of the contextual factors to overcome barriers, especially those related to organizational readiness and mechanisms to support implementation and sustain integrated behavioral health programs.