QUALITY IMPROVEMENT REPORT
Evaluation of a depression screening and treatment program in primary care for patients with diabetes mellitus: Insights and future directions Carrie Palmer, DNP, ANP (Clinical Assistant Professor)1 , Allison Vorderstrasse, DNSc, APRN (Associate Professor)2 , Amy Weil, MD (Associate Professor)3 , Cristin Colford, MD (Clinical Associate Professor)3 , & Diane Dolan-Soto, MSW, LCSW (Clinical Social Worker)3 1
School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina Duke University School of Nursing, Durham, North Carolina 3 School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 2
Keywords Depression; diabetes; primary care; collaboration. Correspondence Carrie Palmer, School of Nursing, University of North Carolina at Chapel Hill, 7460 Carrington Hall, Chapel Hill, NC 27599-7460. Tel: 919-966-5480, 919-219-4496; Fax: 919-843-9900; E-mail: [email protected], [email protected] Received: April 2012; accepted: December 2012 doi: 10.1002/2327-6924.12149
Abstract Purpose: To evaluate a collaborative depression care program by assessing adherence to the program by internal medicine clinic (IMC) staff, and the program’s effectiveness in treating depression in patients with diabetes mellitus. We also describe the rate of depression among patients with diabetes in the IMC. Data sources: Data for this program were obtained from a deidentified disease registry and included 1312 outpatient IMC visits in adult patients with diabetes between March 2011 and September 2011. Conclusions: Collaborative depression care results in high rates of screening for and identification of depression, high rates of antidepressant utilization, and improved depression scores; however, more focused interventions are needed to improve diabetes outcomes in patients with depression and diabetes. Implications for practice: The results indicate that the multidisciplinary IMC staff can work together with patients to identify and monitor depression within primary care. This study provides valuable information about models of depression care that can be implemented and evaluated in a clinical setting.
Introduction Adults in the United States face 7%–16% lifetime risk of developing depression (Bowser, Utz, Glick, Harmon, & Rovnyak, 2009; Egede & Ellis, 2010; O’Connor, Whitlock, Beil, & Gaynes, 2009). For adults with diabetes, the risk is much higher. Up to 33% of people with diabetes also carry a diagnosis of depression (Egede & Ellis, 2010). Depression care is suboptimal, particularly in minority and financially unstable populations and in those with chronic illnesses, such as diabetes (Gonzalez et al., 2010). Nurse practitioners (NPs) see these high risk patients every day and are poised to improve the delivery of care to this vulnerable population through innovative screening and treatment programs. Depressed patients with diabetes report poorer quality of life (Ali et al., 2010), have more complications and higher rates of mortality (Katon, Fan et al., 2008; Lin C 2014 American Association of Nurse Practitioners
et al., 2009, 2010), adhere less frequently to medical and self-care regimens (Egede & Ellis, 2008; Gonzalez et al., 2007, 2008), and incur up to 100% higher healthcare costs (Egede & Ellis, 2010; Simon et al., 2007) than patients without depression. Despite these welldocumented facts, depression in patients with diabetes is suboptimally treated within the primary care setting or via referral to mental health services (Vera et al., 2010). Numerous studies in adult populations have shown promising improvements in the treatment of depression using collaborative programs based in the primary care setting (Bogner & de Vries, 2010; Ell et al., 2010; Gilmer, Walker, Johnson, Philis-Tsimikas, & Unutzer, 2008; Katon et al., 2004; Kinder et al., 2006; Unutzer et al., 2002; Vera et al., 2010). Central to these trials was either the presence of a mental healthcare provider within the primary care office or one within the community 1
Evaluation of a depression screening and treatment program
who communicated directly with the patient’s primary care clinician. Over time, these programs demonstrated sustained improvement in patients’ depressive symptoms, lower rates of mortality, and cost neutrality or cost savings (Bogner, Morales, Post, & Bruce, 2007; Katon, Russo et al., 2008; Simon et al., 2007). Implementing innovative strategies to detect and treat depression in patients with diabetes could lead to improved outcomes by focusing on evidence-based depression care within the patient’s primary healthcare setting (Sinnema et al., 2011). There is some evidence that collaborative depression care may lead to improvement in diabetes outcomes through adequate treatment of depression, although this has not been consistently reported (Lin et al., 2006; Lustman, Griffith, Freedland, Kissel, & Clouse, 1998). The University of North Carolina at Chapel Hill (UNC) internal medicine clinic (IMC) recognized the impact of depression on chronic illness management, particularly in patients with diabetes mellitus. Using a multidisciplinary healthcare team of nurses, physicians, NPs, pharmacists, and physician assistants, a comprehensive depression care program was implemented in 2010 to address this often comorbid condition. Founded on the principles of the IMPACT (improving mood-promoting access to collaborative treatment) trial (Unutzer et al., 2002), this depression care program includes a formalized depression screening process for patients with diabetes, methods for documentation of the results of screening and treatment, and an avenue for the patients to receive problem solving treatment (PST), an evidence-based form of cognitive behavioral therapy (CBT), in the primary care setting (Unutzer et al., 2002). The objectives of this project were threefold: to evaluate adherence to the depression program by IMC staff, to determine the rate of depression among patients in the IMC, and to determine the program’s effectiveness in treating depression in patients with diabetes mellitus.
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sion in a primary care setting, but also to monitor depression over time. The tool has been found to be a reliable measure of depression in multiple populations, increasing the reliability of the findings in the heterogenous population in the IMC (Kroeke et al., 2001). The first step of the PHQ-9 is a two-question screen, the PHQ-2. If the score of the PHQ-2 is ࣙ3, the patient is more likely to have depression, and the full PHQ-9 is administered. Nursing staff were responsible for administering the PHQ-2 to patients at the point of triage, and utilized the PHQ-9 if initial scores were ࣙ3. Positive results were then reported to the clinician. Clinicians reviewed the PHQ-9 scores and initiated treatment based on the algorithmic protocol and their clinical judgment. The treatment algorithm was designed by IMC clinicians and includes medications, counseling, and follow-up care. Medication was recommended for all patients who were identified as severely depressed (PHQ-9 score ࣙ15). The PHQ-9 questionnaire was given at each subsequent visit to those with severe depression to assess the effectiveness of depression treatment. Patients were offered referral to the IMC counselor or encouraged to contact a local mental health provider. Patients who were moderately depressed (PHQ-9 score 10–14) were offered an informed decision tool, or “Decision Aid,” describing options for treatment of depression, along with the option of considering medication or a referral for counseling. Patients with no or mild depression (PHQ-9 score 15
−1.3596 0.0938 2.8182 5.3934
−2.1388 – 0.5805 −1.8775 – 2.0650 1.5781 – 4.0582 3.8452 – 6.9417
↑ ↓ ↓ ↓
No No No Yes
The IMC offered the services of a licensed clinical social worker (LCSW) who provided CBT and PST to patients within the IMC. The presence of the therapist within the clinic meant that patients did not have to initiate contact with a mental health provider outside the clinic or travel to an additional location.
Methods Setting UNC Health Care is an 803-bed academic medical center in the southeastern United States with 20 outpatient clinics (UNC Healthcare, 2012). The IMC, a Center for Excellence in Chronic Disease Care, uses a multidisciplinary team approach, supported by CAs and a diabetes registry, to provide comprehensive diabetes management services. Of the approximately 12,100 patients followed in the IMC, about 2800 have diabetes. Many of these patients are elderly, disabled, or financially disadvantaged. The ethnic make-up of this population is 45% African American, 46% Caucasian, and 4% Hispanic. Patients with diabetes make-up approximately 990 of the 3000 clinic visits per month in the IMC.
Design and data collection This study utilized program evaluation methodology. Data were collected retrospectively from the period of March 2011 to September 2011. Deidentified data were extracted from the EMR and provided to researchers. All data were stored on a password protected server behind a firewall. The UNC institutional review board granted approval to conduct this study.
Analysis Fidelity The primary objective of this project was an evaluation of the effectiveness of the depression program in the IMC. This first step in determining efficacy was to evaluate adherence to the protocol by clinic staff. The proportion of completed PHQ-9 questionnaires to the opportunities (prompts) to administer the questionnaire by the
nursing staff was evaluated and noted as a percentage. To evaluate clinician fidelity, the proportion of addressed PHQ-9 scores to the number of completed questionnaires was expressed as a percentage.
Depression outcomes The prevalence of depression was determined from percentages of scores in each depression category (no, mild, moderate, severe). Patients’ depression scores were monitored at initiation of the study period and again at 6 months. A reduction of five points in PHQ-9 scores was considered to be a clinically significant change (Lowe, Unutzer, Callahan, Perkins, & Kroenke, 2004). Depression scores before and after patients entered the depression treatment program were compared using repeated measures ANOVA. Percentages of patients in each depression category who were prescribed an antidepressant were obtained. Additionally, chi-square tests were used to examine the correlation of antidepressant prescriptions with depression severity.
Diabetes outcomes To examine the impact of collaborative depression care on chronic illness management, changes in hemoglobin A1c and body mass index (BMI) were compared at the beginning and end of the study period. Paired t-tests for dependent samples were used for these comparisons.
Results Fidelity The results showed high fidelity for compliance with the depression screening and treatment program. Nursing staff completed depression screening in 95% of opportunities during the study period. Clinicians acted on depression screening results in 80% of opportunities during the study period.
Depression scores The results showed a significant proportion of patients (29.3%) with clinically significant depression, 3
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Table 3 Comparison of the change in PHQ-9 depression scores between groups during the study period 95% Confidence Interval Depression Group
Comparison Group
No
Mild Moderate Severe No Moderate Severe No Mild Severe No Mild Moderate
Mild
Moderate
Severe
Mean Difference
Standard Error
Significance (p-value)
Lower Bound
Upper Bound
−1.45340 −4.17783* −6.75309* 1.45340 −2.72443* −5.29969* 4.17783* 2.72443* −2.57512* 6.75309* 5.29969* 2.57526*
0.98446 0.80790 0.78064 0.98466 1.09409 1.07412 0.80790 1.09409 0.91503 0.78064 1.07412 0.91503
.141 .000 .000 .141 .013 .000 .000 .013 .005 .000 .000 .005
−3.3920 −5.7688 −8.2903 −.4852 −4.8789 −7.4148 2.5869 .5699 −4.3771 5.2158 3.1845 .7734
0.4852 −2.5869 −5.2158 3.3920 −0.5699 −3.1845 5.7688 4.8789 −7734 8.2903 7.4148 4.43771
*p < .05.
either moderate or severe, on PHQ-9 (Table 1). Of the 1312 screenings during the data collection period, nearly 30% of patients had depression that would lead to either an initiation of treatment, augmentation of therapy, or referral for mental health services.
Change in depression scores There was no statistically significant change in overall depression scores. However, in post hoc analyses, a statistically significant change in depression scores was seen in the severely depressed group, with a mean reduction in PHQ-9 score of 5.4 points. In the moderately depressed group, a nonsignificant mean reduction of 2.8 points was detected. There was no significant change in groups with no or mild depression (Table 2). ANOVA statistics showed that higher depression scores were more likely to be decreased at the end of the study period compared to lower scores, F[3, 258] = 27.552; p = .000. Multiple comparison procedures showed that moderate and severe depression groups were significantly more likely to see decreased PHQ-9 scores than those with no or mild depression (Table 3).
Antidepressant prescriptions About one third of the patients without depression or with mild depression had a prescription for an antidepressant in their medication list. In the moderate and severe depression groups, about 85% of patients had an active antidepressant prescription (Table 4). Belonging to the moderate or severe depression groups was significantly associated with having an active prescription for antidepressant χ 2 [n = 967] = 157.666, df = 3, p = .0001.
4
Diabetes outcomes There was a statistically significant decrease in hemoglobin A1c during the study period. The initial mean hemoglobin A1c was 8.1%, SD 1.90. The followup mean hemoglobin A1c indicated significant change at 7.8%, SD 1.64; p < .0001. The relationship between depression score and hemoglobin A1c level was not statistically significant, p = .619. There was a statistically significant increase in BMI during the study period, from a baseline mean BMI of 32.8 to a mean of 34.7 at the end of the data collection period, t = 14.810; p = .000.
Discussion The collaborative depression model was successful in detecting, treating, and following depression in the primary care setting. There was a clinically significant reduction in depression scores in the patients with the most severe depression who were treated within this model. The most severely depressed patients were the most likely to receive antidepressant therapy. Although mean hemoglobin A1c values decreased over the study period, the results were not correlated with changes in depression scores. This finding indicates that collaborative depression care may not improve diabetes outcomes, but that confounding variables induced the change in hemoglobin A1c levels. The data collection period included warm weather months, during which glycemic control is often improved because of the availability of fresh fruits and vegetables and opportunities for physical activity. BMI increased during this study period. Increasing rates of identifying depression may have lead to increased rates of antidepressant use. The overall weight increase could
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Table 4 Percentage of patients in each depression severity group with an antidepressant prescription Depression Severity
No
Yes
Total
Percentage
None Mild Moderate Severe
485 21 10 14
252 43 64 78
737 64 74 92
34 33 86 85
be a side effect of antidepressants or improved glycemic control, both of which can cause weight gain.
Relation to other evidence The findings from this study support previous reports on collaborative depression care models. The rate of depression in this sample of IMC patients was about 30%, consistent with previous research that examined depression prevalence in a population of people with diabetes in various settings (Egede & Ellis, 2010). In this setting, the model does seem to increase identification of depression within primary care, though no previous studies were found that compared collaborative care to a standard of care for diagnosing depression. The overall trend was a reduction in depression scores, with the most severely depressed patients seeing the greatest reduction in PHQ-9 scores (Bogner et al., 2007). Also, consistent with other studies was the lack of improvement in diabetes outcomes associated with an improvement in depression care (Lin et al., 2006). A noteworthy concern with increased screening for depression is an increased identification of suicidal ideations and behaviors. Clinicians may be fearful of not only providing the safest care for a person who is suicidal, but also increasing suicidal ideation if the subject is broached (Feldman et al., 2007). There was a welldefined evidence-based protocol in place in the IMC should a clinician determine that a patient is in danger of suicidal behavior, including steps to initiate an involuntary psychiatric commitment. Clinic staff members, including physicians, social workers, and advanced practice nurses, were trained to support clinicians in handling suicidal ideation in the IMC. A suicidality protocol should be in place from the initiation of any process to detect or treat depression in any setting.
2004; Kinder et al., 2006; Unutzer et al., 2002; Vera et al., 2010). Providing mental health care within the primary care setting allowed for more comprehensive follow-up than simply identifying depression and referring patients to an outside practitioner. Validity of these findings is enhanced by the high fidelity rates of both nurses’ screening for depression and clinicians’ initiating treatment. Additionally, a large sample size with repeated measures was available for evaluation.
Limitations This evaluation was conducted in one clinical setting with a convenience sample of patients. Multiple clinical settings and comparison to a control group or prior standard of care would enhance the validity of the findings. The PHQ-9 was administered repeatedly within the data collection period. Although the PHQ-9 is validated to not only identify but to follow depression treatment in a clinical setting, there are no data on desensitization to this tool with repeated exposures. Additionally, the PHQ9 may not be a sensitive indicator of mood in patients with mobility issues or chronic illnesses with symptoms that can mimic those of depression. The IMC had a preexisting comprehensive diabetes management program in place. All patients with diabetes are followed through this program and have exposures to CAs and other practitioners outside of their primary care clinician, thus they encounter more opportunities to address depression. However, the diabetes management program preceded the depression program by more than a decade, indicating that the standard of care was evidently enhanced by this model. Economic analyses would be useful in determining long-term sustainability of this model. This evaluation was conducted in a large academic medical center with resources to house a therapist within a primary care office. This level of collaboration would be difficult to replicate in smaller primary care settings. In order to make this program feasible in a private office, relationships between clinicians and mental health providers in the community would have to be strengthened through consistent communication of treatment plans, changes in depression, and barriers to chronic illness and depression self-care.
Conclusion Strengths The most important strength of this evaluation is the evidence-based protocol on which it is based. Collaborative depression care is a well-studied intervention shown to be useful in many populations (Bogner & de Vries, 2010; Ell et al., 2010; Gilmer et al., 2008; Katon et al.,
The United States Preventative Services Task Force (USPTSF) recommends routine depression screening when there is a reliable mechanism to ensure treatment (O’Connor et al., 2009). Adult patients with diabetes are particularly vulnerable to comorbid depression, and may especially benefit from increased 5
Evaluation of a depression screening and treatment program
depression detection and treatment. Collaborative depression care models provide mental health care in the patient’s primary care setting. In areas where mental health services are lacking or in low-income populations, implementing this service within the setting where patients receive most of their care can improve depression outcomes. Collaborative depression care may be insufficient to improve diabetes outcomes and more research is necessary to explore models that address both mental health issues and adherence to the diabetes self-care regimen.
References Ali, S., Stone, M., Skinner, T. C., Robertson, N., Davies, M., & Khunti, K. (2010). The association between depression and health-related quality of life in people with type 2 diabetes: A systematic literature review. Diabetes/Metabolism Research and Reviews, 26(2), 75–89. doi:10.1002/dmrr.1065 Bogner, H. R., & de Vries, H. F. (2010). Integrating type 2 diabetes mellitus and depression treatment among African Americans: A randomized controlled pilot trial. Diabetes Educator, 36(2), 284–292. doi:10.1177/0145721709356115 Bogner, H. R., Morales, K. H., Post, E. P., & Bruce, M. L. (2007). Diabetes, depression, and death: A randomized controlled trial of a depression treatment program for older adults based in primary care (PROSPECT). Diabetes Care, 30(12), 3005–3010. doi:10.2337/dc07-0974 Bowser, D. M., Utz, S., Glick, D., Harmon, R., & Rovnyak, V. (2009). The relationship between diabetes mellitus, depression, and missed appointments in a low-income uninsured population. Diabetes Educator, 35(6), 966–977. doi:10.1177/0145721709345164 Egede, L. E., & Ellis, C. (2008). The effects of depression on diabetes knowledge, diabetes self-management, and perceived control in indigent patients with type 2 diabetes. Diabetes Technology and Therapeutics, 10(3), 213–219. doi:10.1089/dia.2007.0278 Egede, L. E., & Ellis, C. (2010). Diabetes and depression: Global perspectives. Diabetes Research and Clinical Practice, 87(3), 302–312. doi:10.1016/j.diabres.2010.01.024 Ell, K., Katon, W., Xie, B., Lee, P. J., Kapetanovic, S., Guterman, J., & Chou, C. P. (2010). Collaborative care management of major depression among low-income, predominantly Hispanic subjects with diabetes: A randomized controlled trial. Diabetes Care, 33(4), 706–713. doi:dc09-1711[pii] 10.2337/dc09-1711 Feldman, M. D., Franks, P., Duberstein, P. R., Vannoy, S., Epstein, R., & Kravitz, R. L. (2007). Let’s not talk about it: suicide inquiry in primary care. Annals of Family Medicine, 5(5), 412–418. Gilmer, T. P., Walker, C., Johnson, E. D., Philis-Tsimikas, A., & Unutzer, J. (2008). Improving treatment of depression among Latinos with diabetes using Project Dulce and IMPACT. Diabetes Care, 31(7), 1324–1326. doi:10.2337/dc08-0307 Gonzalez, H. M., Vega, W. A., Williams, D. R., Tarraf, W., West, B. T., & Neighbors, H. W. (2010). Depression care in the United States: Too little for too few. Archives of General Psychiatry, 67(1), 37–46. doi:10.1001/archgenpsychiatry.2009.168 Gonzalez, J. S., Safren, S. A., Cagliero, E., Wexler, D. J., Delahanty, L., Wittenberg, E., . . . Grant, R. W. (2007). Depression, self-care, and medication adherence in type 2 diabetes: Relationships across the full range of symptom severity. Diabetes Care, 30(9), 2222–2227. doi:10.2337/dc07-0158 Gonzalez, J. S., Safren, S. A., Delahanty, L. M., Cagliero, E., Wexler, D. J., Meigs, J. B., & Grant, R. W. (2008). Symptoms of depression prospectively
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predict poorer self-care in patients with Type 2 diabetes. Diabetic Medicine, 25(9), 1102–1107. doi:10.1111/j.1464-5491.2008.02535.x Katon, W., Fan, M. Y., Unutzer, J., Taylor, J., Pincus, H., & Schoenbaum, M. (2008). Depression and diabetes: A potentially lethal combination. Journal of General Internal Medicine, 23(10), 1571–1575. doi:10.1007/s11606-008-0731-9 Katon, W. J., Russo, J. E., Von Korff, M., Lin, E. H., Ludman, E., & Ciechanowski, P. S. (2008). Long-term effects on medical costs of improving depression outcomes in patients with depression and diabetes. Diabetes Care, 31(6), 1155–1159. doi:10.2337/dc08-0032 Katon, W. J., Von Korff, M., Lin, E. H., Simon, G., Ludman, E., Russo, J., . . . Bush, T. (2004). The pathways study: A randomized trial of collaborative care in patients with diabetes and depression. Archives of General Psychiatry, 61(10), 1042–1049. doi:10.1001/archpsyc.61.10.1042 Kinder, L. S., Katon, W. J., Ludman, E., Russo, J., Simon, G., Lin, E. H. B., . . . Young, B. (2006). Improving depression care in patients with diabetes and multiple complications. Journal of General Internal Medicine, 21(10), 1036–1041. doi:10.1111/j.1525-1497.2006.00552.x Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613. Lin, E. H., Heckbert, S. R., Rutter, C. M., Katon, W. J., Ciechanowski, P., Ludman, E. J., . . . Von Korff, M. (2009). Depression and increased mortality in diabetes: Unexpected causes of death. Annals of Family Medicine, 7(5), 414–421. doi:10.1370/afm.998 Lin, E. H., Katon, W., Rutter, C., Simon, G. E., Ludman, E. J., Von Korff, M., . . . Walker, E. (2006). Effects of enhanced depression treatment on diabetes self-care. Annals of Family Medicine, 4(1), 46–53. doi:10.1370/afm.423 Lin, E. H., Rutter, C. M., Katon, W., Heckbert, S. R., Ciechanowski, P., Oliver, M. M., . . . Von Korff, M. (2010). Depression and advanced complications of diabetes: A prospective cohort study. Diabetes Care, 33(2), 264–269. doi:10.2337/dc09-1068 Lowe, B., Unutzer, J., Callahan, C. M., Perkins, A. J., & Kroenke, K. (2004). Monitoring depression treatment outcomes with the patient health questionnaire-9. Medical Care, 42(12), 1194–1201. Lustman, P. J., Griffith, L. S., Freedland, K. E., Kissel, S. S., & Clouse, R. E. (1998). Cognitive behavior therapy for depression in type 2 diabetes mellitus: A randomized, controlled trial. Annals of Internal Medicine, 129(8), 613–621. O’Connor, E. A., Whitlock, E. P., Beil, T. L., & Gaynes, B. N. (2009). Screening for depression in adult patients in primary care settings: A systematic evidence review. Annals of Internal Medicine, 151(11), 793–803. doi:10.1059/0003-4819-151-11-200912010-00007 Sacco, W. P., Malone, J. I., Morrison, A. D., Friedman, A., & Wells, K. (2009). Effect of a brief, regular telephone intervention by paraprofessionals for type 2 diabetes. Journal of Behavioral Medicine, 32(4), 349–359. doi:10.1007/s10865-009-9209-4 Simon, G. E., Katon, W. J., Lin, E. H., Rutter, C., Manning, W. G., Von Korff, M., . . . Young, B. A. (2007). Cost-effectiveness of systematic depression treatment among people with diabetes mellitus. Archives of General Psychiatry, 64(1), 65–72. doi:64/1/65[pii]10.1001/archpsyc.64.1.65 Sinnema, H., Franx, G., Volker, D., Majo, C., Terluin, B., Wensing, M., & von Balker, A. (2011). Randomised controlled trial of tailored interventions to improve the management of anxiety and depressive disorders in primary care. Implementation Science, 6(1), 1–8. doi:10.1186/1748-5908-6-75 UNC Healthcare. (2012). About us: What is UNC health care? Retrieved from http://www.unchealthcare.org/site/aboutus Unutzer, J., Katon, W., Callahan, C. M., Williams, J. W., Jr., Hunkeler, E., Harpole, L., . . . Langston, C. (2002). Collaborative care management of late-life depression in the primary care setting: A randomized controlled trial. Journal of the American Medical Association, 288(22), 2836–2845. Vera, M., Perez-Pedrogo, C., Huertas, S. E., Reyes-Rabanillo, M. L., Juarbe, D., Huertas, A., . . . Chaplin, W. (2010). Collaborative care for depressed patients with chronic medical conditions: A randomized trial in Puerto Rico. Psychiatric Services, 61(2), 144–150. doi:10.1176/appi.ps.61.2.144
Evaluation of a depression screening and treatment program in primary care for patients with diabetes mellitus: Insights and future directions Carrie Palmer, DNP, ANP (Clinical Assistant Professor)1 , Allison Vorderstrasse, DNSc, APRN (Associate Professor)2 , Amy Weil, MD (Associate Professor)3 , Cristin Colford, MD (Clinical Associate Professor)3 , & Diane Dolan-Soto, MSW, LCSW (Clinical Social Worker)3 1
School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina Duke University School of Nursing, Durham, North Carolina 3 School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 2
Keywords Depression; diabetes; primary care; collaboration. Correspondence Carrie Palmer, School of Nursing, University of North Carolina at Chapel Hill, 7460 Carrington Hall, Chapel Hill, NC 27599-7460. Tel: 919-966-5480, 919-219-4496; Fax: 919-843-9900; E-mail: [email protected], [email protected] Received: April 2012; accepted: December 2012 doi: 10.1002/2327-6924.12149
Abstract Purpose: To evaluate a collaborative depression care program by assessing adherence to the program by internal medicine clinic (IMC) staff, and the program’s effectiveness in treating depression in patients with diabetes mellitus. We also describe the rate of depression among patients with diabetes in the IMC. Data sources: Data for this program were obtained from a deidentified disease registry and included 1312 outpatient IMC visits in adult patients with diabetes between March 2011 and September 2011. Conclusions: Collaborative depression care results in high rates of screening for and identification of depression, high rates of antidepressant utilization, and improved depression scores; however, more focused interventions are needed to improve diabetes outcomes in patients with depression and diabetes. Implications for practice: The results indicate that the multidisciplinary IMC staff can work together with patients to identify and monitor depression within primary care. This study provides valuable information about models of depression care that can be implemented and evaluated in a clinical setting.
Introduction Adults in the United States face 7%–16% lifetime risk of developing depression (Bowser, Utz, Glick, Harmon, & Rovnyak, 2009; Egede & Ellis, 2010; O’Connor, Whitlock, Beil, & Gaynes, 2009). For adults with diabetes, the risk is much higher. Up to 33% of people with diabetes also carry a diagnosis of depression (Egede & Ellis, 2010). Depression care is suboptimal, particularly in minority and financially unstable populations and in those with chronic illnesses, such as diabetes (Gonzalez et al., 2010). Nurse practitioners (NPs) see these high risk patients every day and are poised to improve the delivery of care to this vulnerable population through innovative screening and treatment programs. Depressed patients with diabetes report poorer quality of life (Ali et al., 2010), have more complications and higher rates of mortality (Katon, Fan et al., 2008; Lin C 2014 American Association of Nurse Practitioners
et al., 2009, 2010), adhere less frequently to medical and self-care regimens (Egede & Ellis, 2008; Gonzalez et al., 2007, 2008), and incur up to 100% higher healthcare costs (Egede & Ellis, 2010; Simon et al., 2007) than patients without depression. Despite these welldocumented facts, depression in patients with diabetes is suboptimally treated within the primary care setting or via referral to mental health services (Vera et al., 2010). Numerous studies in adult populations have shown promising improvements in the treatment of depression using collaborative programs based in the primary care setting (Bogner & de Vries, 2010; Ell et al., 2010; Gilmer, Walker, Johnson, Philis-Tsimikas, & Unutzer, 2008; Katon et al., 2004; Kinder et al., 2006; Unutzer et al., 2002; Vera et al., 2010). Central to these trials was either the presence of a mental healthcare provider within the primary care office or one within the community 1
Evaluation of a depression screening and treatment program
who communicated directly with the patient’s primary care clinician. Over time, these programs demonstrated sustained improvement in patients’ depressive symptoms, lower rates of mortality, and cost neutrality or cost savings (Bogner, Morales, Post, & Bruce, 2007; Katon, Russo et al., 2008; Simon et al., 2007). Implementing innovative strategies to detect and treat depression in patients with diabetes could lead to improved outcomes by focusing on evidence-based depression care within the patient’s primary healthcare setting (Sinnema et al., 2011). There is some evidence that collaborative depression care may lead to improvement in diabetes outcomes through adequate treatment of depression, although this has not been consistently reported (Lin et al., 2006; Lustman, Griffith, Freedland, Kissel, & Clouse, 1998). The University of North Carolina at Chapel Hill (UNC) internal medicine clinic (IMC) recognized the impact of depression on chronic illness management, particularly in patients with diabetes mellitus. Using a multidisciplinary healthcare team of nurses, physicians, NPs, pharmacists, and physician assistants, a comprehensive depression care program was implemented in 2010 to address this often comorbid condition. Founded on the principles of the IMPACT (improving mood-promoting access to collaborative treatment) trial (Unutzer et al., 2002), this depression care program includes a formalized depression screening process for patients with diabetes, methods for documentation of the results of screening and treatment, and an avenue for the patients to receive problem solving treatment (PST), an evidence-based form of cognitive behavioral therapy (CBT), in the primary care setting (Unutzer et al., 2002). The objectives of this project were threefold: to evaluate adherence to the depression program by IMC staff, to determine the rate of depression among patients in the IMC, and to determine the program’s effectiveness in treating depression in patients with diabetes mellitus.
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sion in a primary care setting, but also to monitor depression over time. The tool has been found to be a reliable measure of depression in multiple populations, increasing the reliability of the findings in the heterogenous population in the IMC (Kroeke et al., 2001). The first step of the PHQ-9 is a two-question screen, the PHQ-2. If the score of the PHQ-2 is ࣙ3, the patient is more likely to have depression, and the full PHQ-9 is administered. Nursing staff were responsible for administering the PHQ-2 to patients at the point of triage, and utilized the PHQ-9 if initial scores were ࣙ3. Positive results were then reported to the clinician. Clinicians reviewed the PHQ-9 scores and initiated treatment based on the algorithmic protocol and their clinical judgment. The treatment algorithm was designed by IMC clinicians and includes medications, counseling, and follow-up care. Medication was recommended for all patients who were identified as severely depressed (PHQ-9 score ࣙ15). The PHQ-9 questionnaire was given at each subsequent visit to those with severe depression to assess the effectiveness of depression treatment. Patients were offered referral to the IMC counselor or encouraged to contact a local mental health provider. Patients who were moderately depressed (PHQ-9 score 10–14) were offered an informed decision tool, or “Decision Aid,” describing options for treatment of depression, along with the option of considering medication or a referral for counseling. Patients with no or mild depression (PHQ-9 score 15
−1.3596 0.0938 2.8182 5.3934
−2.1388 – 0.5805 −1.8775 – 2.0650 1.5781 – 4.0582 3.8452 – 6.9417
↑ ↓ ↓ ↓
No No No Yes
The IMC offered the services of a licensed clinical social worker (LCSW) who provided CBT and PST to patients within the IMC. The presence of the therapist within the clinic meant that patients did not have to initiate contact with a mental health provider outside the clinic or travel to an additional location.
Methods Setting UNC Health Care is an 803-bed academic medical center in the southeastern United States with 20 outpatient clinics (UNC Healthcare, 2012). The IMC, a Center for Excellence in Chronic Disease Care, uses a multidisciplinary team approach, supported by CAs and a diabetes registry, to provide comprehensive diabetes management services. Of the approximately 12,100 patients followed in the IMC, about 2800 have diabetes. Many of these patients are elderly, disabled, or financially disadvantaged. The ethnic make-up of this population is 45% African American, 46% Caucasian, and 4% Hispanic. Patients with diabetes make-up approximately 990 of the 3000 clinic visits per month in the IMC.
Design and data collection This study utilized program evaluation methodology. Data were collected retrospectively from the period of March 2011 to September 2011. Deidentified data were extracted from the EMR and provided to researchers. All data were stored on a password protected server behind a firewall. The UNC institutional review board granted approval to conduct this study.
Analysis Fidelity The primary objective of this project was an evaluation of the effectiveness of the depression program in the IMC. This first step in determining efficacy was to evaluate adherence to the protocol by clinic staff. The proportion of completed PHQ-9 questionnaires to the opportunities (prompts) to administer the questionnaire by the
nursing staff was evaluated and noted as a percentage. To evaluate clinician fidelity, the proportion of addressed PHQ-9 scores to the number of completed questionnaires was expressed as a percentage.
Depression outcomes The prevalence of depression was determined from percentages of scores in each depression category (no, mild, moderate, severe). Patients’ depression scores were monitored at initiation of the study period and again at 6 months. A reduction of five points in PHQ-9 scores was considered to be a clinically significant change (Lowe, Unutzer, Callahan, Perkins, & Kroenke, 2004). Depression scores before and after patients entered the depression treatment program were compared using repeated measures ANOVA. Percentages of patients in each depression category who were prescribed an antidepressant were obtained. Additionally, chi-square tests were used to examine the correlation of antidepressant prescriptions with depression severity.
Diabetes outcomes To examine the impact of collaborative depression care on chronic illness management, changes in hemoglobin A1c and body mass index (BMI) were compared at the beginning and end of the study period. Paired t-tests for dependent samples were used for these comparisons.
Results Fidelity The results showed high fidelity for compliance with the depression screening and treatment program. Nursing staff completed depression screening in 95% of opportunities during the study period. Clinicians acted on depression screening results in 80% of opportunities during the study period.
Depression scores The results showed a significant proportion of patients (29.3%) with clinically significant depression, 3
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Table 3 Comparison of the change in PHQ-9 depression scores between groups during the study period 95% Confidence Interval Depression Group
Comparison Group
No
Mild Moderate Severe No Moderate Severe No Mild Severe No Mild Moderate
Mild
Moderate
Severe
Mean Difference
Standard Error
Significance (p-value)
Lower Bound
Upper Bound
−1.45340 −4.17783* −6.75309* 1.45340 −2.72443* −5.29969* 4.17783* 2.72443* −2.57512* 6.75309* 5.29969* 2.57526*
0.98446 0.80790 0.78064 0.98466 1.09409 1.07412 0.80790 1.09409 0.91503 0.78064 1.07412 0.91503
.141 .000 .000 .141 .013 .000 .000 .013 .005 .000 .000 .005
−3.3920 −5.7688 −8.2903 −.4852 −4.8789 −7.4148 2.5869 .5699 −4.3771 5.2158 3.1845 .7734
0.4852 −2.5869 −5.2158 3.3920 −0.5699 −3.1845 5.7688 4.8789 −7734 8.2903 7.4148 4.43771
*p < .05.
either moderate or severe, on PHQ-9 (Table 1). Of the 1312 screenings during the data collection period, nearly 30% of patients had depression that would lead to either an initiation of treatment, augmentation of therapy, or referral for mental health services.
Change in depression scores There was no statistically significant change in overall depression scores. However, in post hoc analyses, a statistically significant change in depression scores was seen in the severely depressed group, with a mean reduction in PHQ-9 score of 5.4 points. In the moderately depressed group, a nonsignificant mean reduction of 2.8 points was detected. There was no significant change in groups with no or mild depression (Table 2). ANOVA statistics showed that higher depression scores were more likely to be decreased at the end of the study period compared to lower scores, F[3, 258] = 27.552; p = .000. Multiple comparison procedures showed that moderate and severe depression groups were significantly more likely to see decreased PHQ-9 scores than those with no or mild depression (Table 3).
Antidepressant prescriptions About one third of the patients without depression or with mild depression had a prescription for an antidepressant in their medication list. In the moderate and severe depression groups, about 85% of patients had an active antidepressant prescription (Table 4). Belonging to the moderate or severe depression groups was significantly associated with having an active prescription for antidepressant χ 2 [n = 967] = 157.666, df = 3, p = .0001.
4
Diabetes outcomes There was a statistically significant decrease in hemoglobin A1c during the study period. The initial mean hemoglobin A1c was 8.1%, SD 1.90. The followup mean hemoglobin A1c indicated significant change at 7.8%, SD 1.64; p < .0001. The relationship between depression score and hemoglobin A1c level was not statistically significant, p = .619. There was a statistically significant increase in BMI during the study period, from a baseline mean BMI of 32.8 to a mean of 34.7 at the end of the data collection period, t = 14.810; p = .000.
Discussion The collaborative depression model was successful in detecting, treating, and following depression in the primary care setting. There was a clinically significant reduction in depression scores in the patients with the most severe depression who were treated within this model. The most severely depressed patients were the most likely to receive antidepressant therapy. Although mean hemoglobin A1c values decreased over the study period, the results were not correlated with changes in depression scores. This finding indicates that collaborative depression care may not improve diabetes outcomes, but that confounding variables induced the change in hemoglobin A1c levels. The data collection period included warm weather months, during which glycemic control is often improved because of the availability of fresh fruits and vegetables and opportunities for physical activity. BMI increased during this study period. Increasing rates of identifying depression may have lead to increased rates of antidepressant use. The overall weight increase could
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Table 4 Percentage of patients in each depression severity group with an antidepressant prescription Depression Severity
No
Yes
Total
Percentage
None Mild Moderate Severe
485 21 10 14
252 43 64 78
737 64 74 92
34 33 86 85
be a side effect of antidepressants or improved glycemic control, both of which can cause weight gain.
Relation to other evidence The findings from this study support previous reports on collaborative depression care models. The rate of depression in this sample of IMC patients was about 30%, consistent with previous research that examined depression prevalence in a population of people with diabetes in various settings (Egede & Ellis, 2010). In this setting, the model does seem to increase identification of depression within primary care, though no previous studies were found that compared collaborative care to a standard of care for diagnosing depression. The overall trend was a reduction in depression scores, with the most severely depressed patients seeing the greatest reduction in PHQ-9 scores (Bogner et al., 2007). Also, consistent with other studies was the lack of improvement in diabetes outcomes associated with an improvement in depression care (Lin et al., 2006). A noteworthy concern with increased screening for depression is an increased identification of suicidal ideations and behaviors. Clinicians may be fearful of not only providing the safest care for a person who is suicidal, but also increasing suicidal ideation if the subject is broached (Feldman et al., 2007). There was a welldefined evidence-based protocol in place in the IMC should a clinician determine that a patient is in danger of suicidal behavior, including steps to initiate an involuntary psychiatric commitment. Clinic staff members, including physicians, social workers, and advanced practice nurses, were trained to support clinicians in handling suicidal ideation in the IMC. A suicidality protocol should be in place from the initiation of any process to detect or treat depression in any setting.
2004; Kinder et al., 2006; Unutzer et al., 2002; Vera et al., 2010). Providing mental health care within the primary care setting allowed for more comprehensive follow-up than simply identifying depression and referring patients to an outside practitioner. Validity of these findings is enhanced by the high fidelity rates of both nurses’ screening for depression and clinicians’ initiating treatment. Additionally, a large sample size with repeated measures was available for evaluation.
Limitations This evaluation was conducted in one clinical setting with a convenience sample of patients. Multiple clinical settings and comparison to a control group or prior standard of care would enhance the validity of the findings. The PHQ-9 was administered repeatedly within the data collection period. Although the PHQ-9 is validated to not only identify but to follow depression treatment in a clinical setting, there are no data on desensitization to this tool with repeated exposures. Additionally, the PHQ9 may not be a sensitive indicator of mood in patients with mobility issues or chronic illnesses with symptoms that can mimic those of depression. The IMC had a preexisting comprehensive diabetes management program in place. All patients with diabetes are followed through this program and have exposures to CAs and other practitioners outside of their primary care clinician, thus they encounter more opportunities to address depression. However, the diabetes management program preceded the depression program by more than a decade, indicating that the standard of care was evidently enhanced by this model. Economic analyses would be useful in determining long-term sustainability of this model. This evaluation was conducted in a large academic medical center with resources to house a therapist within a primary care office. This level of collaboration would be difficult to replicate in smaller primary care settings. In order to make this program feasible in a private office, relationships between clinicians and mental health providers in the community would have to be strengthened through consistent communication of treatment plans, changes in depression, and barriers to chronic illness and depression self-care.
Conclusion Strengths The most important strength of this evaluation is the evidence-based protocol on which it is based. Collaborative depression care is a well-studied intervention shown to be useful in many populations (Bogner & de Vries, 2010; Ell et al., 2010; Gilmer et al., 2008; Katon et al.,
The United States Preventative Services Task Force (USPTSF) recommends routine depression screening when there is a reliable mechanism to ensure treatment (O’Connor et al., 2009). Adult patients with diabetes are particularly vulnerable to comorbid depression, and may especially benefit from increased 5
Evaluation of a depression screening and treatment program
depression detection and treatment. Collaborative depression care models provide mental health care in the patient’s primary care setting. In areas where mental health services are lacking or in low-income populations, implementing this service within the setting where patients receive most of their care can improve depression outcomes. Collaborative depression care may be insufficient to improve diabetes outcomes and more research is necessary to explore models that address both mental health issues and adherence to the diabetes self-care regimen.
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