Depression Screening Tool for A Primary Care Center

Introduction and Background

Major depressive disorder or MDD is identified by the American Psychiatric Association (2013) as a disorder that causes significant distress and inability to function while being associated with depressed mood, feelings of worthlessness, and some other symptoms. It is not clear what causes the disorder, but MDD is probably associated with dysfunctions of neurotransmitters (Stahl, 2013). MDD is extremely widespread, with at least 7% of US adults have experienced it; the figure is higher for younger people, and the economic burden of the disease is substantial. In other words, MDD requires the attention of modern-day health professionals, but to this day, it is reported by the American Psychiatric Association (2017) that MDD screening in primary care is not sufficient.

DNP Project Problem Statement

Consequently, the problem statement of this project can be made. Research shows that while screening on its own is not sufficient for positive outcomes when combined with treatment, it is critical for patient health (Ferenchick et al., 2019). Given the recommendation of ensuring standardized screening in primary care (American Psychiatric Association, 2016), it makes sense to consider individual clinics and their methods. For this project, Orlando primary care clinic is going to be considered, and a change will be offered for it, during which the clinic will be adopting a standardized screening tool, that is, PHQ questionnaires. Specifically, PHQ-2 and PHQ-9 are a system of questionnaires that help to screen for depression in primary care

Aims/goal of the project

The main aims of the project are to provide the clinic with a standardized tool and, subsequently, improve the well-being of its patients and community. However, it should also be pointed out that the PHQ questionnaires could benefit from additional research (Ferenchick et al., 2019; Munoz-Nevarro et al., 2017), which the proposed project can offer.


The population of the project is adults because they are most susceptible to MDD and because they constitute the majority of the patients of the clinic. The intervention follows from the problem statement, and it is an evidence-based solution to it, which is the PHQ. The comparison is care-as-usual, which, in the case of Orlando clinic, is the lack of a standardized tool. The outcome is the accuracy of diagnosing MDD, and the timeframe is the largest allowed by the project option, which is four weeks.

Action plan/ROL/Evidence

The review of literature that was carried out involved considering over 70 records, with 22 of them being overviewed fully. The results suggested that PHQ is a very reliable, valid, and sensitive tool that can and should be used in primary care (Arrieta et al., 2017; Ferenchick et al., 2019; Korenke et al., 2016; Levis et al., 2019; Levis et al., 2020; Munoz-Nevarro et al., 2017; Villarreal-Zegarra et al., 2019). Moreover, the review of literature helped to identify the models that could be used to develop an action plan, including Kurt Lewin’s model (Lewin & Gold, 1999), as well as the IOWA model (Iowa Model Collaborative et al., 2017). This slide presents how the two were blended, resulting in the stages of the IOWA model being divided into three parts. Overall, the project intends to use the unfreeze and change model while employing the specific steps of the IOWA model, including the identification of the issue, team formation, planning, and trialing. The process of refreezing, which, in IOWA terms, would include integrating the change, would not be included since that requires more time than the project can allocate. However, the grounds for refreezing will be created during the project with the help of its methodology.


The intervention, as was mentioned, is the PHQ questionnaire, which has high reliability, validity, specificity, and sensitivity. It can be pointed out that at least one study reported lower specificity for the tool than is usually observed (Munoz-Nevarro et al., 2017), but it is an outlier. The project intends to implement the intervention and test it with at least 30 patients who have already been visiting the clinic. They can include patients with depression, but they will be randomly selected for this project. Furthermore, all of the staff will be recruited to ensure their ability to study the PHQ questionnaire administration. The IRB will be cleared, and regular safeguards for participant safety and confidentiality will be implemented. The design itself will be partially similar to that of one of the reviewed studies.


To be more specific, the information about the patients’ depression status before the intervention, their PHQ scores, and their semi-structured interview scores will be recorded. The former will be compared to the PHQ scores to see if there are any changes in the accuracy of the diagnosis after the project’s implementation; the latter will be also compared to PHQ scores to validate them and establish if they are accurate. The analysis will most likely have to be non-parametric since the sample is unlikely to be very large, but the goal will be to check for statistically significant differences.

Stakeholders, Cost-risk benefits

The stakeholders of the project range from the clinic to the community, with the former receiving a helpful tool for improved care, and the latter potentially benefiting from the outcomes. The risks are not going to be significant since the project will only involve testing a screening tool. However, it is taken into account that patients with suicidal thoughts might be present in the sample, and they will be treated according to the clinic’s policy, with the data being removed if incomplete. Patient privacy will be of primary importance, too. The anticipated benefits of improved screening, especially if coupled with treatment, are likely to overshadow the possible risks.


Based on the literature review, the results should be positive, with PHQ being more accurate than practice-as-usual. However, with the small sample and only four weeks for the project, the data may be insufficient to make conclusive statements. In any case, however, the project will start a change at the clinic, and it will leave the clinic with the means of finalizing it.


In summary, MDD is a serious issue, the screening of which remains deficient. Based on the existing recommendations and literature PHQ questionnaires should be a worthy intervention that can improve screening accuracy. The presented project will aim to provide the target clinic with this evidence-based tool while also improving the well-being of the patients and the community, and it will achieve that with the help of a quantitative project that will compare PHQ scores to pre-intervention records and semi-structured interviews. The risks are mostly not very significant or are controlled, and the potential outcomes can be very positive, which makes this project feasible.


American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorder (5th ed). Washington, DC: American Psychiatric Publishing.

American Psychiatric Association. (2016). Practice guidelines for the psychiatric evaluation of adults (3rd ed). Washington, DC: American Psychiatric Publishing.

American Psychiatric Association. (2017). Web.

Arrieta, J., Aguerrebere, M., Raviola, G., Flores, H., Elliott, P., Espinosa, A.,… Franke, M. F. (2017). Validity and utility of the Patient Health Questionnaire (PHQ)‐2 and PHQ‐9 for screening and diagnosis of depression in rural Chiapas, Mexico: A cross‐sectional study. Journal of Clinical Psychology, 73(9), 1076-1090. Web.

CDC. (2018). Mental health. Web.

Denson, B., & Kim, R. (2018). Evaluation of provider response to positive depression screenings and physician attitudes on integrating psychiatric pharmacist services in primary care settings. Mental Health Clinician, 8(1), 28-32. Web.

Ferenchick, E., Ramanuj, P., & Pincus, H. (2019). Depression in primary care: part 1—screening and diagnosis. BMJ, 365(1794), l794. Web.

Hartung, T. J., Friedrich, M., Johansen, C., Wittchen, H. U., Faller, H., Koch, U., … Mehnert, A. (2017). Cancer, 123(21), 4236–4243. Web.

Indu, P. S., Anilkumar, T. V., Vijayakumar, K., Kumar, K. A., Sarma, P. S., Remadevi, S., Andrade, C. (2018). Asian Journal of Psychiatry, 37(1), 10–14. Web.

Iowa Model Collaborative, Buckwalter, K. C., Cullen, L., Hanrahan, K., Kleiber, C., McCarthy, A. M.,… Tucker, S. (2017). Iowa model of evidence-based practice: Revisions and validation. Worldviews on Evidence-Based Nursing, 14(3), 175-182. Web.

Levis, B., Benedetti, A., & Thombs, B.D. (2019). Accuracy of Patient Health Questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis. BMJ, 365, l1781. Web.

Levis, B., Sun, Y., He, C., Wu, Y., Krishnan, A., Bhandari, P. M., … Thombs, B. D. (2020). Journal of the American Medical Association, 323(22), 2290–2300. Web.

Lewin, K., & Gold, M. (1999). The complete social scientist: a Kurt Lewin reader. Washington, DC: American Psychological Association.

Muñoz-Navarro, R., Cano-Vindel, A., Medrano, L. A., Schmitz, F., Ruiz-Rodríguez, P., Abellán-Maeso, C.,… Hermosilla-Pasamar, A. M. (2017). Utility of the PHQ-9 to identify major depressive disorder in adult patients in Spanish primary care centres. BMC Psychiatry, 17(1), 291. Web.

Stahl, S. M. (2013). Web.

SAMHSA. (2020). Web.

Villarreal-Zegarra, D., Copez-Lonzoy, A., Bernabé-Ortiz, A., Melendez-Torres, G., & Bazo-Alvarez, J. (2019). Valid group comparisons can be made with the Patient Health Questionnaire (PHQ-9): A measurement invariance study across groups by demographic characteristics. PLOS ONE, 14(9), e0221717. Web.

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