Skip to main content
Full access
Brief Reports
Published Online: 31 October 2014

Effects of Staffing Choices on Collaborative Care for Depression at Primary Care Clinics in Minnesota

Abstract

Objective:

This study assessed associations between staffing of a collaborative care program for depression and enrollment in the program and remission rates.

Methods:

Data were collected from depression care registries at 63 primary care clinics that participated in the initiative through early 2012. Project leaders at the 12 medical groups that operate the clinics were surveyed about the background of care managers and clinic characteristics. Generalized linear mixed models assessed associations of care manager background and configuration of staffing with enrollment and remission rates.

Results:

Enrollment was higher (p=.050) and there was a trend toward higher remission rates (p=.105) at clinics where care managers were dedicated exclusively to depression care. No differences in outcomes were obtained by registered nurses versus certified medical assistants and licensed practical nurses.

Conclusions:

Hiring dedicated paraprofessional care managers may maximize the cost-effectiveness of collaborative care programs and should be supported by regulations and reimbursement policies.
Depression causes substantial suffering, health care expenditure, additional economic loss, and death through suicide and inferior self-care of other chronic diseases (1,2). Most depression treatment is administered in primary care settings, where diagnosis, medication selection and dosing, duration of treatment, and response to treatment failure are often suboptimal (3,4).
Designed to improve depression outcomes for primary care patients, collaborative care involves expanding primary care teams with the addition of two new roles. A psychiatrist conducts regular case reviews and advises on diagnosis and treatment. A care manager educates patients about depression, coordinates referrals, promotes behavior changes that decrease depression symptoms, supports adherence to treatment regimens, administers serial depression symptom questionnaires, and notifies primary care providers when responses to those questionnaires indicate inadequate improvement and a possible need to revise the treatment plan. On the basis of meta-analyses, researchers have concluded that collaborative care substantially improves depression outcomes (5,6). A randomized controlled trial involving primary care patients ages 60 years and older found that collaborative care generated substantial health care cost savings (7).
From 2008 to 2012, the Institute for Clinical Systems Improvement (ICSI) assisted 87 primary care clinics in implementing collaborative care through the Depression Improvement Across Minnesota, Offering a New Direction (DIAMOND) initiative (8). The clinics received similar training and support but varied in how they staffed and configured care manager positions. Some care managers were registered nurses (RNs), whereas others were certified medical assistants (CMAs) and licensed practical nurses (LPNs). Some were dedicated to depression care, but others had additional responsibilities. Some served patients at one clinic, whereas others served patients at multiple clinics in the same medical group. To inform future implementation of collaborative care, we analyzed associations between two key measures of program effectiveness—patient enrollment and six-month remission rates—with care manager background and clinic characteristics.

Methods

Between March 2008 and March 2010, a group of clinics began DIAMOND implementation every six months, for a total of five groups. A total of 87 clinics operated by 21 medical groups participated. This study focused on the 63 clinics, operated by 12 medical groups, that remained active through early 2012.
Staff of the participating clinics aimed to enroll all patients with ICD-9 diagnoses of 296.2X, 296.3X, or 300.4 and a score of ≥10 on the Patient Health Questionnaire–9 (PHQ-9), suggesting probable major depression or significant dysthymia (9). Patients were discharged from DIAMOND if they met criteria for remission, defined as having PHQ-9 scores of <5 on two consecutive occasions over a period of greater than two months.
Care managers were expected to collect PHQ-9 data from patients at every contact. They contacted patients weekly to monthly on the basis of the severity of depression symptoms. Monthly, clinic staff submitted deidentified data on service delivery and PHQ-9 scores for each enrolled patient. From these data, the ICSI calculated total enrollment and remission rates.
Throughout implementation, the ICSI tracked clinic progress and provided technical assistance. In early 2012, the ICSI surveyed project leaders at each active medical group about care manager and clinic characteristics. The data indicated whether the care manager was an RN, a CMA, or an LPN; whether the care manager was dedicated solely to depression care or had other duties; and whether the care manager provided depression services at one or multiple clinics. Of the 63 clinics, seven clinics indicated modifying their staffing models within two months of program launch, and the data reflect the final staffing model. Clinics located in or near the Twin Cities (in Hennepin or Ramsey County or adjacent counties) were classified as metropolitan, and the other clinics were classified as outstate. Complete data were obtained for all 63 active clinics.
We analyzed the relationship of care manager and clinic characteristics to rate of enrollment of eligible patients and rate of remission six months (±30 days) after the enrollment date. Generalized linear mixed models (GLMMs) were used to account for multiple sources of clustering within the data (10). We conducted two separate GLMMs, one using enrollment rates and one using remission rates as the binomial outcome variable. For each model, the independent variables were the three care manager variables and clinic location. A random-effects term accounted for medical group effect. A sequence effect term denoted the five different start dates. A term for number of enrolled patients controlled for clinic volume. We conducted the analysis with SAS, version 9.2 (11).
Informed consent was not obtained from patients, nor was institutional review board approval sought, because the project was a quality improvement initiative, and no protected health information was shared with the researchers.

Results

Of 55,594 eligible patients, 9,179 patients enrolled in DIAMOND as of early 2012, for a 17% enrollment rate across all clinics. Enrollment rates varied from 1% to 55% across the participating clinics. The model in Table 1 indicates the association between enrollment and remission rates and clinic characteristics after the analyses accounted for medical group–level effects. Clinics with a dedicated care manager had higher enrollment rates than clinics in which the care manager had multiple roles (odds ratio [OR]=2.65, p=.050). There were no significant differences in enrollment on the basis of care manager licensure (RN versus CMA or LPN), number of clinics served, or clinic location.
Table 1 Association of enrollment in collaborative care for depression and rates of remission at 63 primary care clinics, by clinic characteristic
 EnrollmentRemission
VariableOR95% CIpOR95% CIp
Care manager      
 Registered nurse (reference: CMA or LPN)a1.06.35–3.04ns1.23.56–2.69ns
 Dedicated role (reference: multiple roles)2.651.02–6.91<.051.96.83–4.72ns
 Served a single site (reference: multiple sites)1.61.41–6.84ns1.07.37–3.07ns
Metropolitan location (reference: outstate)1.23.44–3.62ns.69.32–1.52ns
Group start date (reference: March 2010)b      
 March 20081.571.40–1.77<.011.921.63–2.25<.01
 September 20081.171.02–1.33<.051.701.44–2.00<.01
 March 20091.201.04–1.39<.054.243.20–5.64<.01
 September 2009.90.78–1.04ns.83.62–1.12ns
Eligible patients (per 1,000).87.83–.92<.01   
Enrolled patients (per 100)   1.111.05–1.18<.05
a
CMA, certified medical assistant. LPN, licensed practical nurse
b
A group of clinics began DIAMOND implementation every six months, for a total of five groups.
Across the clinic sites, 7,438 enrolled patients were eligible for six-month PHQ-9 follow up. Of these patients, 2,323 attained remission at six months, yielding an overall remission rate of 31%. Six-month remission rates varied from 3% to 46% across the clinics. As shown in Table 1, the independent variables had no significant effects on remission rates. There was a trend for sites with a dedicated care manager to have higher remission rates (OR=1.96, p=.105).
Clinics that were among the first three groups to implement DIAMOND had higher enrollment and remission rates. Enrollment rates were significantly lower at larger versus smaller clinics, but remission rates were significantly higher at larger clinics.

Discussion

The U.S. Preventive Services Task Force (USPSTF) recommends depression screening in primary care settings only “when staff-assisted depression care supports are in place to assure accurate diagnosis, effective treatment, and follow-up” (12). Collaborative care clearly comprises the most effective supports.
Under the DIAMOND initiative, as the clinics implemented collaborative care, they varied in how they staffed the care manager role. Our analysis found no differences in outcomes obtained by RNs, CMAs, and LPNs, who had completed the same training. Our analysis also found that staffing by a dedicated care manager was associated with significantly greater enrollment and, possibly, superior treatment outcomes compared with staffing by a care manager with multiple duties, even when dedicated staff were shared across multiple clinics.
A possible explanation for the superior performance of the clinics in the first three groups to implement DIAMOND may be related to selection effects. Earlier-participating clinics may have been most ready and motivated to initiate the program. The association between volume of patients served and better outcomes may indicate that managers with dedicated time are more ready and motivated to develop their skills.
One limitation of the study was its focus on clinics that were still implementing collaborative care two to four years later. The data did not identify the factors that may have been associated with program discontinuation. Additional limitations were the retrospective nature of the analyses, which were possibly confounded by differences in implementation that were not measured and by the effects of idiosyncratic practices at the clinics studied. Furthermore, the study design allowed conclusions about association, not causation, given that decisions about staffing of care manager positions could have influenced service delivery or vice versa.
The findings of this study support the “teamlet” model of primary care, in which medical assistants are trained to execute health coaching functions (13). A larger prospective study would provide more definitive guidance on how best to configure and staff collaborative care programs.
Even if clinical data suggest how to optimize staffing, decisions about staffing must take into account the regulatory environment and financing opportunities. Regulations governing which individuals may deliver collaborative care may vary across states. In Minnesota, for example, paraprofessionals are permitted to deliver collaborative care, and major commercial payers honor a billing code for paraprofessional-administered collaborative care (14). This type of flexibility and financing is lacking in other states. Currently, Medicare reimburses for depression care only when depression care supports are in place, consistent with USPSTF recommendations. However, it does not reimburse for ongoing collaborative care. Thus most primary care settings cannot finance collaborative care through fee-for-service reimbursement.

Conclusions

Increasingly, health care providers are rewarded for delivering value rather than services, for example, as part of accountable care organizations. Research has documented a positive return on investment for collaborative care, which should help drive dissemination (7). As collaborative care spreads, patients and health care purchasers will benefit, especially if staffing decisions and relevant regulations are based on research findings rather than traditional role concepts.

Acknowledgments

Dr. Brown is the owner and CEO of Wellsys, LLC, which helps health care settings and workplaces implement behavioral screening and intervention. The other authors report no competing interests.

References

1.
Williams JW, Jr, Noël PH, Cordes JA, et al: Is this patient clinically depressed? JAMA 287:1160–1170, 2002
2.
Moussavi S, Chatterji S, Verdes E, et al: Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet 370:851–858, 2007
3.
Kessler RC, Chiu WT, Demler O, et al: Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 62:617–627, 2005
4.
Unützer J, Katon W, Callahan CM, et al: Collaborative care management of late-life depression in the primary care setting: a randomized controlled trial. JAMA 288:2836–2845, 2002
5.
Archer J, Bower P, Gilbody S, et al: Collaborative care for depression and anxiety problems. Cochrane Database of Systematic Reviews 10:CD006525, 2012
6.
Thota AB, Sipe TA, Byard GJ, et al: Collaborative care to improve the management of depressive disorders: a community guide systematic review and meta-analysis. American Journal of Preventive Medicine 42:525–538, 2012
7.
Unutzer J, Katon WJ, Fan MY, et al: Long-term cost effects of collaborative care for late-life depression. American Journal of Managed Care 14:95–100, 2008
8.
Williams MD, Jaeckels N, Rummans TA, et al: Creating value in depression management. Quality in Primary Care 18:327–333, 2010
9.
Kroenke K, Spitzer RL, Williams JB, et al: The Patient Health Questionnaire Somatic, Anxiety and Depression Symptom Scales: a systematic review. General Hospital Psychiatry 32:345–359, 2010
10.
Breslow NE, Clayton DG: Approximate inference in generalized linear mixed models. Journal of the American Statistical Association 88:9–25, 1993
11.
SAS/STAT 9.2: User’s Guide. Cary, NC, SAS Institute, 2008
12.
Recommendations for Adults. Rockville, Md, US Preventive Services Task Force. Available at www.uspreventiveservicestaskforce.org/adultrec.htm. Accessed Sept 26, 2013
13.
Rodriguez HP, Giannitrapani KF, Stockdale S, et al: Teamlet structure and early experiences of medical home implementation for veterans. Journal of General Internal Medicine 29(suppl 2):S623–S631, 2014
14.
O’Donnell AN, Williams M, Kilbourne AM: Overcoming roadblocks: current and emerging reimbursement strategies for integrated mental health services in primary care. Journal of General Internal Medicine 28:1667–1672, 2013

Information & Authors

Information

Published In

Go to Psychiatric Services
Go to Psychiatric Services

Cover: In the Loge, by Mary Cassatt, circa 1879. Pastel and metallic paint on canvas prepared with a pastel ground. Gift of Mrs. Sargent McKean, 1950 (1950-52-1), the Philadelphia Museum of Art. Photo credit: the Philadelphia Museum of Art/Art Resources, New York.

Psychiatric Services
Pages: 101 - 103
PubMed: 25269565

History

Published ahead of print: 31 October 2014
Published in print: January 01, 2015
Published online: 2 January 2015

Authors

Details

Pamela B. Pietruszewski, M.A.
Ms. Pietruszewski and Ms. Hadzic are with the Institute for Clinical Systems Improvement, Bloomington, Minnesota. Dr. Mundt and Dr. Brown are with the Department of Family Medicine, University of Wisconsin School of Medicine and Public Health, Madison. Send correspondence to Dr. Brown (e-mail: [email protected]).
Marlon P. Mundt, Ph.D.
Ms. Pietruszewski and Ms. Hadzic are with the Institute for Clinical Systems Improvement, Bloomington, Minnesota. Dr. Mundt and Dr. Brown are with the Department of Family Medicine, University of Wisconsin School of Medicine and Public Health, Madison. Send correspondence to Dr. Brown (e-mail: [email protected]).
Senka Hadzic, M.P.H.
Ms. Pietruszewski and Ms. Hadzic are with the Institute for Clinical Systems Improvement, Bloomington, Minnesota. Dr. Mundt and Dr. Brown are with the Department of Family Medicine, University of Wisconsin School of Medicine and Public Health, Madison. Send correspondence to Dr. Brown (e-mail: [email protected]).
Richard L. Brown, M.D., M.P.H.
Ms. Pietruszewski and Ms. Hadzic are with the Institute for Clinical Systems Improvement, Bloomington, Minnesota. Dr. Mundt and Dr. Brown are with the Department of Family Medicine, University of Wisconsin School of Medicine and Public Health, Madison. Send correspondence to Dr. Brown (e-mail: [email protected]).

Metrics & Citations

Metrics

Citations

Export Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format
Citation style
Style
Copy to clipboard

View Options

View options

PDF/EPUB

View PDF/EPUB

Get Access

Login options

Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.

Personal login Institutional Login Open Athens login
Purchase Options

Purchase this article to access the full text.

PPV Articles - Psychiatric Services

PPV Articles - Psychiatric Services

Not a subscriber?

Subscribe Now / Learn More

PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.

Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).

Media

Figures

Other

Tables

Share

Share

Share article link

Share