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      Equitability of Depression Screening After Implementation of General Adult Screening in Primary Care

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      , MD, MPH, MAS 1 , 2 , 3 , 4 , , , MD 5 , , PhD 4 , , MD, MPhil 3 , , PhD 1 , , MD, MAS 1 , 2 , 3
      JAMA Network Open
      American Medical Association

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          Key Points

          Question

          Is implementation of routine depression screening in primary care associated with improved screening rates for groups at risk for undertreatment of depression?

          Findings

          In this cohort study of 52 944 adult patients in primary care practices in a California health system, depression screening rates increased from 40.5% in 2017 to 88.8% in 2019 after implementation of a general screening policy. Initial statistically significant screening disparities among older patients, Black/African American and other English-speaking patients, and patients with language barriers disappeared by 2019, although disparities for men did not.

          Meaning

          These results suggest that implementation of depression screening may reduce disparities in screening and could improve recognition and appropriate treatment of depression for all patients.

          Abstract

          Importance

          Depression is a debilitating and costly medical condition that is often undertreated. Men, racial and ethnic minority individuals, older adults, and those with language barriers are at increased risk for undertreatment of depression. Disparities in screening may contribute to undertreatment.

          Objective

          To examine depression screening rates among populations at risk for undertreatment of depression during and after rollout of general screening.

          Design, Setting, and Participants

          This cohort study from September 1, 2017, to December 31, 2019, of electronic health record data from 52 944 adult patients at 6 University of California, San Francisco, primary care facilities assessed depression screening rates after implementation of a general screening policy. Patients were excluded if they had a baseline diagnosis of depression, bipolar disorder, schizophrenia, schizoaffective disorder, or dementia.

          Exposures

          Screening year, including rollout (September 1, 2017, to December 31, 2017) and each subsequent calendar year (January 1 to December 31, 2018, and January 1 to December 31, 2019).

          Main Outcomes and Measures

          Rates of depression screening performed by medical assistants using the Patient Health Questionnaire-2. Data collected included age, sex, race and ethnicity, and language preference (English vs non-English); to compare English and non-English language preference groups and also assess depression screening by race and ethnicity within the English-speaking group, a single language-race-ethnicity variable with non–English language preference and English language preference categories was created. In multivariable analyses, the likelihood of being screened was evaluated using annual logistic regression models for 2018 and 2019, examining sex, age, language-race-ethnicity, and comorbidities, with adjustment for primary care site.

          Results

          There were 52 944 unique, eligible patients with 1 or more visits in one of the 6 primary care practices during the entire study period (59% female; mean [SD] age, 48.9 [17.6] years; 178 [0.3%] American Indian/Alaska Native, 13 241 [25.0%] English-speaking Asian, 3588 [6.8%] English-speaking Black/African American, 4744 [9.0%] English-speaking Latino/Latina/Latinx, 760 [1.4%] Pacific Islander, 22 689 [42.9%] English-speaking White, 4857 [9.0%] English-speaking other [including individuals who indicated race and ethnicity as other and individuals for whom race and ethnicity data were missing or unknown], and 2887 [5.5%] with language barriers [non–English language preference]). Depression screening increased from 40.5% at rollout (2017) to 88.8% (2019). In 2018, the likelihood of being screened decreased with increasing age (adusted odds ratio [aOR], 0.89 [95% CI, 0.82-0.98] for ages 45-54 and aOR, 0.75 [95% CI, 0.65-0.85] for ages 75 and older compared with ages 18-30); and, except for Spanish-speaking patients, patients with limited English proficiency were less likely to be screened for depression than English-speaking White patients (Chinese language preference: aOR, 0.59 [95% CI, 0.51-0.67]; other non–English language preference: aOR, 0.55 [95% CI, 0.47-0.64]). By 2019, depression screening had increased dramatically for all at-risk groups, and for most, disparities had disappeared; the odds of screening were only still significantly lower for men compared with women (aOR, 0.87 [95% CI, 0.81 to 0.93]).

          Conclusions and Relevance

          In this cohort study in a large academic health system, full implementation of depression screening was associated with a substantial increase in screening rates among groups at risk for undertreatment of depression. In addition, depression screening disparities narrowed over time for most groups, suggesting that routine depression screening in primary care may reduce screening disparities and improve recognition and appropriate treatment of depression for all patients.

          Abstract

          This cohort study assesses rates of depression screening among groups at risk for undertreatment of depression after initiation of routine primary care screening for adults in a large health system.

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          Most cited references71

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          The PHQ-9: validity of a brief depression severity measure.

          While considerable attention has focused on improving the detection of depression, assessment of severity is also important in guiding treatment decisions. Therefore, we examined the validity of a brief, new measure of depression severity. The Patient Health Questionnaire (PHQ) is a self-administered version of the PRIME-MD diagnostic instrument for common mental disorders. The PHQ-9 is the depression module, which scores each of the 9 DSM-IV criteria as "0" (not at all) to "3" (nearly every day). The PHQ-9 was completed by 6,000 patients in 8 primary care clinics and 7 obstetrics-gynecology clinics. Construct validity was assessed using the 20-item Short-Form General Health Survey, self-reported sick days and clinic visits, and symptom-related difficulty. Criterion validity was assessed against an independent structured mental health professional (MHP) interview in a sample of 580 patients. As PHQ-9 depression severity increased, there was a substantial decrease in functional status on all 6 SF-20 subscales. Also, symptom-related difficulty, sick days, and health care utilization increased. Using the MHP reinterview as the criterion standard, a PHQ-9 score > or =10 had a sensitivity of 88% and a specificity of 88% for major depression. PHQ-9 scores of 5, 10, 15, and 20 represented mild, moderate, moderately severe, and severe depression, respectively. Results were similar in the primary care and obstetrics-gynecology samples. In addition to making criteria-based diagnoses of depressive disorders, the PHQ-9 is also a reliable and valid measure of depression severity. These characteristics plus its brevity make the PHQ-9 a useful clinical and research tool.
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            The PHQ-9

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              The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.

              Much biomedical research is observational. The reporting of such research is often inadequate, which hampers the assessment of its strengths and weaknesses and of a study's generalizability. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Initiative developed recommendations on what should be included in an accurate and complete report of an observational study. We defined the scope of the recommendations to cover 3 main study designs: cohort, case-control, and cross-sectional studies. We convened a 2-day workshop in September 2004, with methodologists, researchers, and journal editors, to draft a checklist of items. This list was subsequently revised during several meetings of the coordinating group and in e-mail discussions with the larger group of STROBE contributors, taking into account empirical evidence and methodological considerations. The workshop and the subsequent iterative process of consultation and revision resulted in a checklist of 22 items (the STROBE Statement) that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. Eighteen items are common to all 3 study designs and 4 are specific for cohort, case-control, or cross-sectional studies. A detailed Explanation and Elaboration document is published separately and is freely available at http://www.annals.org and on the Web sites of PLoS Medicine and Epidemiology. We hope that the STROBE Statement will contribute to improving the quality of reporting of observational studies.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                18 August 2022
                August 2022
                18 August 2022
                : 5
                : 8
                : e2227658
                Affiliations
                [1 ]Center for Aging in Diverse Communities, University of California, San Francisco, San Francisco
                [2 ]Multiethnic Health Equity Research Center, Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco
                [3 ]Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco
                [4 ]Implementation Science Training Program, Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco
                [5 ]Department of Psychiatry and Behavioral Sciences, University of California, Davis, Davis
                Author notes
                Article Information
                Accepted for Publication: July 4, 2022.
                Published: August 18, 2022. doi:10.1001/jamanetworkopen.2022.27658
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Garcia ME et al. JAMA Network Open.
                Corresponding Author: Maria E. Garcia, MD, MPH, MAS, UCSF Division of General Internal Medicine, 1701 Divisadero St, Room 536, San Francisco, CA 94143-1731 ( maria.garcia@ 123456ucsf.edu ).
                Author Contributions: Dr Garcia had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Garcia, Karliner.
                Acquisition, analysis, or interpretation of data: All authors.
                Drafting of the manuscript: Garcia, Neuhaus, Livaudais-Toman.
                Critical revision of the manuscript for important intellectual content: Garcia, Hinton, Neuhaus, Feldman, Karliner.
                Statistical analysis: Neuhaus, Livaudais-Toman.
                Obtained funding: Garcia.
                Administrative, technical, or material support: Garcia.
                Supervision: Garcia, Hinton, Feldman.
                Conflict of Interest Disclosures: Dr Neuhaus reported receiving grants from the National Institutes of Health during the conduct of the study. Dr Karliner reported receiving personal fees from the University of Illinois Chicago outside the submitted work. No other disclosures were reported.
                Funding/Support: This study was supported by National Institute on Minority Health and Health Disparities grant K23MD015115 (Dr Garcia) and National Institute on Aging grant K24AG067003 (Dr Karliner).
                Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Disclaimer: The content does not necessarily represent the official views of the NIMHD, NIA, or NIH.
                Additional Contributions: We thank Steve Gregorich, PhD, University of California (UCSF), San Francisco, San Francisco, for initial biostatistical consultations. We also wish to thank Maki Aoki, MD, Nicole Appelle, MD, and Emma Samuelson-Jones, MD, UCSF, for providing context for implementation of depression screening at UCSF Health. These individuals were not compensated beyond their usual salaries.
                Article
                zoi220786
                10.1001/jamanetworkopen.2022.27658
                9389351
                35980633
                80d2d527-7e6d-40c6-a0b7-c8731d4e59a6
                Copyright 2022 Garcia ME et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 17 March 2022
                : 4 July 2022
                Categories
                Research
                Original Investigation
                Online Only
                Diversity, Equity, and Inclusion

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