Dataset Information

Primary care clinicians' recognition and management of depression: a model of depression care in real-world primary care practice.

ABSTRACT:

Background

Depression is prevalent in primary care (PC) practices and poses a considerable public health burden in the United States. Despite nearly four decades of efforts to improve depression care quality in PC practices, a gap remains between desired treatment outcomes and the reality of how depression care is delivered.

Objective

This article presents a real-world PC practice model of depression care, elucidating the processes and their influencing conditions.

Design

Grounded theory methodology was used for the data collection and analysis to develop a depression care model. Data were collected from 70 individual interviews (60 to 70 min each), three focus group interviews (n = 24, 2 h each), two surveys per clinician, and investigators' field notes on practice environments. Interviews were audiotaped and transcribed for analysis. Surveys and field notes complemented interview data.

Participants

Seventy primary care clinicians from 52 PC offices in the Midwest: 28 general internists, 28 family physicians, and 14 nurse practitioners.

Key results

A depression care model was developed that illustrates how real-world conditions infuse complexity into each step of the depression care process. Depression care in PC settings is mediated through clinicians' interactions with patients, practice, and the local community. A clinician's interactional familiarity ("familiarity capital") was a powerful facilitator for depression care. For the recognition of depression, three previously reported processes and three conditions were confirmed. For the management of depression, 13 processes and 11 conditions were identified. Empowering the patient was a parallel process to the management of depression.

Conclusions

The clinician's ability to develop and utilize interactional relationships and resources needed to recognize and treat a person with depression is key to depression care in primary care settings. The interactional context of depression care makes empowering the patient central to depression care delivery.

SUBMITTER: Baik SY

PROVIDER: S-EPMC3797334 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Primary care clinicians' recognition and management of depression: a model of depression care in real-world primary care practice.

Baik Seong-Yi SY Crabtree Benjamin F BF Gonzales Junius J JJ

Journal of general internal medicine 20130507 11

<h4>Background</h4>Depression is prevalent in primary care (PC) practices and poses a considerable public health burden in the United States. Despite nearly four decades of efforts to improve depression care quality in PC practices, a gap remains between desired treatment outcomes and the reality of how depression care is delivered.<h4>Objective</h4>This article presents a real-world PC practice model of depression care, elucidating the processes and their influencing conditions.<h4>Design</h4>G ...[more]

PMID: 23649784

Similar Datasets

Project description:BACKGROUND: Most evidence on the effect of collaborative care for depression is derived in the selective environment of randomised controlled trials. In collaborative care, practice nurses may act as case managers. The Primary Care Services Improvement Project (PCSIP) aimed to assess the cost-effectiveness of alternative models of practice nurse involvement in a real world Australian setting. Previous analyses have demonstrated the value of high level practice nurse involvement in the management of diabetes and obesity. This paper reports on their value in the management of depression. METHODS: General practices were assigned to a low or high model of care based on observed levels of practice nurse involvement in clinical-based activities for the management of depression (i.e. percentage of depression patients seen, percentage of consultation time spent on clinical-based activities). Linked, routinely collected data was used to determine patient level depression outcomes (proportion of depression-free days) and health service usage costs. Standardised depression assessment tools were not routinely used, therefore a classification framework to determine the patient's depressive state was developed using proxy measures (e.g. symptoms, medications, referrals, hospitalisations and suicide attempts). Regression analyses of costs and depression outcomes were conducted, using propensity weighting to control for potential confounders. RESULTS: Capacity to determine depressive state using the classification framework was dependent upon the level of detail provided in medical records. While antidepressant medication prescriptions were a strong indicator of depressive state, they could not be relied upon as the sole measure. Propensity score weighted analyses of total depression-related costs and depression outcomes, found that the high level model of care cost more (95% CI: -$314.76 to $584) and resulted in 5% less depression-free days (95% CI: -0.15 to 0.05), compared to the low level model. However, this result was highly uncertain, as shown by the confidence intervals. CONCLUSIONS: Classification of patients' depressive state was feasible, but time consuming, using the classification framework proposed. Further validation of the framework is required. Unlike the analyses of diabetes and obesity management, no significant differences in the proportion of depression-free days or health service costs were found between the alternative levels of practice nurse involvement.

Project description:BACKGROUND:Burnout among primary care physicians, advanced practice clinicians (nurse practitioners and physician assistants [APCs]), and staff is common and associated with negative consequences for patient care, but the association of burnout with characteristics of primary care practices is unknown. OBJECTIVE:To examine the association between physician-, APC- and staff-reported burnout and specific structural, organizational, and contextual characteristics of smaller primary care practices. DESIGN:Cross-sectional analysis of survey data collected from 9/22/2015-6/19/2017. SETTING:Sample of smaller primary care practices in the USA participating in a national initiative focused on improving the delivery of cardiovascular preventive services. PARTICIPANTS:10,284 physicians, APCs and staff from 1380 primary care practices. MAIN MEASURE:Burnout was assessed with a validated single-item measure. KEY RESULTS:Burnout was reported by 20.4% of respondents overall. In a multivariable analysis, burnout was slightly more common among physicians and APCs (physician vs. non-clinical staff, adjusted odds ratio [aOR]?=?1.26; 95% confidence interval [CI], 1.05-1.49, APC vs. non-clinical staff, aOR?=?1.34, 95% CI, 1.10-1.62). Other multivariable correlates of burnout included non-solo practice (2-5 physician/APCs vs. solo practice, aOR?=?1.71; 95% CI, 1.35-2.16), health system affiliation (vs. physician/APC-owned practice, aOR?=?1.42; 95%CI, 1.16-1.73), and Federally Qualified Health Center status (vs. physician/APC-owned practice, aOR?=?1.36; 95%CI, 1.03-1.78). Neither the proportion of patients on Medicare or Medicaid, nor practice-level patient volume (patient visits per physician/APC per day) were significantly associated with burnout. In analyses stratified by professional category, practice size was not associated with burnout for APCs, and participation in an accountable care organization was associated with burnout for clinical and non-clinical staff. CONCLUSIONS:Burnout is prevalent among physicians, APCs, and staff in smaller primary care practices. Members of solo practices less commonly report burnout, while members of health system-owned practices and Federally Qualified Health Centers more commonly report burnout, suggesting that practice level autonomy may be a critical determinant of burnout.

Project description:BACKGROUND:Obesity is a major risk factor behind some of the most common problems encountered in primary care. Although effective models for obesity treatment have been developed, the 'reach' of these interventions is poor and only a small fraction of primary care patients receive evidence-based treatment. The purpose of this study is to identify factors that impact the uptake (reach) of an evidence-based obesity treatment program within the context of a pragmatic cluster randomized controlled trial comparing three models of care delivery. METHODS:Recruitment and reach were evaluated by the following measures: 1) mailing response rates, 2) referral sources among participants contacting the study team, 3) eligibility rates, 4) participation rates, and 5) representativeness based on demographics, co-morbid conditions, and healthcare utilization of 1432 enrolled participants compared to >?17,000 non-participants from the clinic-based patient populations. Referral sources and participation rates were compared across study arms and level of clinic engagement. RESULTS:The response rate to clinic-based mailings was 13.2% and accounted for 66% of overall program recruitment. An additional 22% of recruitment came from direct clinic referrals and 11% from media, family, or friends. Of those screened, 87% were eligible; among those eligible, 86% enrolled in the trial. Participation rates did not vary across the three care delivery arms, but were higher at clinics with high compared to low provider involvement. In addition, clinics with high provider involvement had a higher rate of in clinic referrals (33% versus 16%) and a more representative sample with regards to BMI, rurality, and months since last clinic visit. However, across clinics, enrolled participants compared to non-participants were older, more likely to be female, more likely to have had a joint replacement but less likely to have CVD or smoke, and had fewer hospitalizations. CONCLUSIONS:A combination of direct patient mailings and in-clinic referrals may enhance the reach of primary care behavioral weight loss interventions, although more proactive outreach is likely necessary for men, younger patients, and those at greater medial risk. Strategies are needed to enhance provider engagement in referring patients to behavioral weight loss programs. TRIAL REGISTRATION:clnicialtrials.gov NCT02456636. Registered May 28, 2015, https://www.clinicaltrials.gov/ct2/results?cond=&term=RE-POWER&cntry=&state=&city=&dist=.

Dataset Information

Primary care clinicians' recognition and management of depression: a model of depression care in real-world primary care practice.

Background

Objective

Design

Participants

Key results

Conclusions

Publications

Primary care clinicians' recognition and management of depression: a model of depression care in real-world primary care practice.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets