van Steenbergen-Weijenburg in chronic medically ill patients

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1 Kirsten van Steenbergen-Weijenburg Depression in chronic medically ill patients

2 Depression In Chronic Medically Ill Patients. A thesis from the Netherlands Depression Initiative. Kirsten van Steenbergen-Weijenburg

3 The Collaborative Care study where this thesis was based on was conducted at the Trimbos-Institute in Utrecht, in cooperation with the Institute of Medical Technology Assessment (imta) in Rotterdam. It was part of the Depression Initiative, a national program aimed at supporting depression care in The Netherlands, which was funded by the Foundation for Innovation of Healthcare Insurers. Pro Persona, the Onze Lieve Vrouwe Gasthuis and the Ziekenhuis Groep Twente kindly provided financial support for the production of this thesis. English title: Depression In Chronic Medically Ill Patients. A thesis from the Netherlands Depression Initiative. Nederlandse titel: Depressie bij chronisch zieken. Een proefschrift vanuit het Depressie Initiatief. ISBN: Cover/poem: Printed by: Lay-out: De KaarsenDraagster, detail "De Trap naar Zolder" Harsolieverf en tempera op linnen 100 * 130 cm Paul Christiaan Bos - GVO Drukkers & Vormgevers B.V. Ponsen & Looijen Mike Reinten 2013 Kirsten van Steenbergen-Weijenburg, The Netherlands

4 Depression In Chronic Medically Ill Patients. A thesis from the Netherlands Depression Initiative. Depressie bij chronisch zieken. Een proefschrift vanuit het Depressie Initiatief. Proefschrift Ter verkrijging van de graad van doctor aan de Erasmus Universiteit Rotterdam Op gezag van de Rector magnificus Prof.dr. H.G. Schmidt En volgens besluit van het College voor Promoties. De openbare verdediging zal plaatsvinden op vrijdag 6 september 2013 om 9.30 uur Kirsten Mattanja van Steenbergen-Weijenburg Geboren te Bennekom

5 Promotiecommissie: Promotoren: Prof.dr. F.F.H. Rutten Prof.dr. C.M. van der Feltz-Cornelis Prof.dr. A.T.F. Beekman Overige leden: Prof.dr. J. van Busschbach Prof.dr. F.J. Snoek Prof.dr. W.B.F. Brouwer Co-promotor: Dr. L. Hakkaart-van Roijen

6 Contents Chapter 1: General introduction 7 Part 1: Prevalence and recognition of depression in diabetes patients Chapter 2: Prevalence of depression in diabetes patients 29 Chapter 3: Recognizing depression in diabetes patients 41 Part 2: A generic treatment model for depression in chronic medically ill patients: collaborative care Chapter 4: The effectiveness of a generic collaborative care model 57 for chronic medically ill patients Chapter 5: The cost-effectiveness of collaborative care in primary care 81 Chapter 6: The cost-effectiveness of a generic collaborative care model for chronic medically ill patients 101 Part 3: Implementation of collaborative care Chapter 7: Implementing collaborative care in primary care 121 Chapter 8: General discussion 141 Chapter 9: Addendum 9.1 Literature Summary Samenvatting Curriculum Vitae Dankwoord 205

7

8 Chapter 1. General introduction General Introduction 7

9 8 General Introduction

10 1.1 The prevalence and implications of co-morbid depression In the Netherlands, approximately 20.2% of the adult population experiences a mood disorder at least once in their lifetime and 6.1% have experienced it in the past year. Major depressive disorder (MDD) is one of the most prevalent mental disorders: 5.2% of the Netherlands population have experienced it in the past year (Bijl et al, 1998; de Graaf et al, 2011). A causal relationship between medical illnesses and depression has frequently been assumed, but rarely demonstrated. However, many studies document a positive relationship between medical illness and mental problems: the prevalence of co-morbid MDD is higher in chronic medically ill patients than in the general population (Anderson et al, 2001; Egede et al, 2002). The prevalence of chronic medically ill patients with diabetes and MDD ranges from 7-16% (Egede et al, 2002). This thesis focuses on patients with physical diseases and co-morbid depression. Co-morbidity can be defined as a clinical entity existing or occurring during the clinical course of the index illness (Feinstein, 1970). Patients with a mental index illness and co-morbid depression were excluded from our study. We assessed co-morbid depression in the following chronic medical diseases: diabetes, chronic obstructive pulmonary disorders (COPD) and cardiovascular disorders; more in specific patients with congestive heart failure (CHF), myocardial infarction (MI) and coronary artery disease (CAD). These diseases were chosen as they were the most prevalent co-morbid conditions found in the general hospital (van der Feltz-Cornelis et al, 2010a). Another large scale problem encountered in the general hospital is multimorbidity. Multimorbidity is defined as having a combination of two or more chronic medical illnesses, for example concordant conditions such as hypertension, coronary heart disease and diabetes (Mercer et al, 2012). Patients with multimorbidity were included in the studies in this thesis. General Introduction 9

11 Most chronic medically ill patients are treated in the general hospital and a large part of them is treated at hospital outpatient clinics. Therefore, the studies as described in this thesis included patients of outpatient clinics of general hospitals located in the Netherlands. The largest outpatient departments in the participating hospitals were selected, as they were the most relevant disease categories for exploration of the collaborative care model we studied. For the treatment of depression there are several evidence-based guidelines, but the applicability for patients with co-morbid conditions is limited. Cost-effective treatment options for depression are mentioned in guidelines, such as antidepressant medication, cognitive behavioural therapy and physical therapy (Romeijnders et al, 2005). Unfortunately, most guidelines do not provide explicit guidance on the treatment of patients with co-morbidity, particularly for discordant combinations (Lugtenberg et al, 2011). It is important to establish if there is a treatment option suitable for these patients. Therefore, this thesis presents the results regarding collaborative care for patients with a medical illness and co-morbid depression in the general hospital setting. This thesis is part of the Depression Initiative, which was led by the Trimbos-Institute in collaboration with several partners and ran from 2006 until It was funded by the Dutch Innovation Fund of Healthcare Insurers. The aim was to improve the diagnosis and treatment of depression on a national scale in a diversity of health care settings and community settings in the Netherlands (van der Feltz-Cornelis et al, 2009; 2011c). In this chapter, an overview of the relevant literature concerning several aspects of depression in chronic medically ill patients will be given. Firstly, the prevalence and implications of the three main chronic medical illnesses will be presented. 10 General Introduction

12 Secondly, the diagnosis of depression in chronic medically ill patients will be discussed, and finally, the treatment options for depression in chronic medically ill patients, with a focus on collaborative care, will be showed Diabetes In patients with diabetes, the chance of having depression is twice as likely than in individuals without diabetes in the general population (Fisher et al, 2008; Baan et al, 2011). In a meta-analysis, performed by Anderson et al (2001), the odds of depression in patients with diabetes were doubled, compared with patients without diabetes. The prevalence of comorbid depression was significantly higher in clinical (32%) than in community (20%) samples. Functional limitations (physical, mental or developmental disabilities) may play an essential role in the development of depression in diabetes patients. Pouwer et al (2003) showed that due to the burden of having diabetes and co-morbid MDD, the patients' health-related quality of life was negatively influenced and this consequently contributed to the worsening of depression. A relationship between having depression and poor glycaemic control was shown in diabetes patients (Hassan et al, 2006; Lee et al, 2009; Lamers et al, 2010a). Diabetes and co-morbid depression was also associated with perceived lack of control and greater perceived burden of symptoms (Paschalides et al, 2004). In several studies considering diabetes patients, depression was also associated with decreased health-related quality of life (Eren et al, 2008; Moreira et al, 2009; Filipcic et al, 2010; Egede et al, 2010; Verma et al, 2010). Having a higher baseline level of depression was related to major depression in diabetes patients (Bot et al, 2010). Improving identification and treatment of depression in diabetes patients can lead to improvements in health related quality of life (Goldney et al, 2004; Schram et al, 2009; Ali et al, 2010). General Introduction 11

13 For example, cognitive behaviour therapy is effective in the treatment of depression in Type 2 diabetes patients, both in reducing depressive symptoms and improving glycaemic control (Snoek et al, 2002). Patients with major depression and diabetes have, in addition to significantly more functional limitations, increased healthcare utilization and more losses in productivity (Egede, 2007). Therefore, patients with co-morbid depression have high healthcare expenditures (Ciechanowski et al, 2000; De Groot et al, 2001; Egede et al, 2002; Gonzalez et al, 2007; Kosten van ziekten, 2011). Annually, about one million Euros has been spend on medication, hospital care and other forms of healthcare, in total 1.4% of the Dutch healthcare costs (Kosten van ziekten, 2011). An international study in primary care in the US showed that participants with diabetes or heart failure, in combination with depression, caused significantly higher healthcare costs than those without depression ($20,046 vs. $11,956) (Unutzer et al, 2009). This was explained by the fact that patients with diabetes and depressive symptoms had on average more hospitalisation days, higher ambulatory care use and used more medication prescriptions than those patients without depression (Subramaniam et al, 2009). In a recent study of Le et al (2011) it was found that patients with diabetes and depression had a high resource burden, consisting of the use of multiple medication and healthcare services. Healthcare costs were $8470 higher compared to patients without depression; a significant difference COPD Co-morbid depression and anxiety are common in patients with COPD (Mikkelsen et al, 2004; Kunik et al, 2005). Yohannes et al (2006) found that the prevalence of depression in elderly patients with COPD was approximately 40%. Patients with COPD and co-morbid depression have a significantly higher risk of COPD exacerbations and had a worse health status and dyspnoea (Felker et al, 2010; Dalal et al, 2011). 12 General Introduction

14 The health-related quality of life as well as respiratory-specific quality of life of these patients can be negatively influenced by the presence of comorbid MDD (Omachi et al, 2009). The number of interventions to improve the quality of life of COPD patients with co-morbid depression is limited but results are promising. Even so, further research is needed as the recognition of co-morbid MDD in COPD patients can be difficult due to an overlap of symptoms (Lamers et al, 2010a; Baraniak et al, 2011). The costs of COPD are reported by The National Health Service of the United Kingdom and are estimated at per annum, with a further loss of 24 million working days and 30,000 deaths per annum (Chief Medical Officer, 2004). In the Netherlands, the costs for COPD were estimated in 2000 at ; the costs per patient were on average 900 per year, mainly caused by the high number of hospital admissions and medication prescriptions (Hoogendoorn et al, 2004). In 2005, the estimated costs for COPD increased to and were 1.2% of the total healthcare budget in the Netherlands (Poos et al, 2008) Cardiac disorders Between 31-45% of the patients with coronary artery disease (CAD) or myocardial infarction (MI) suffer from depressive symptoms and 15-20% of the patients have a Major Depressive Disorder (Lesperance et al, 2000; Thombs et al, 2006; Thombs et al, 2008; Carney et al, 2008). In hospitalised cardiac patients, this prevalence even increases to almost 50% (Ziegelstein et al, 2001). Several large scale studies were performed to indicate the implications of co-morbid depression in patients with heart diseases. In patients with congestive heart failure (CHF) and MI, depression was associated with a large amount of negative symptoms and poor health status (de Jonge et al, 2006; Bekelman et al, 2007). General Introduction 13

15 Depressive symptoms also significantly undermine the health-related quality of life: post-mi depression was significantly associated with the severity of left ventricular dysfunction and morbidity (van Melle et al, 2004; van Melle et al, 2005). Depression may also be triggered by the severity of the MI (Spijkerman et al, 2005). Therefore, de Jonge et al (2006) suggest that efforts to improve health status after MI should include standard assessment and guideline based treatment of depression. In patients with CAD and co-morbid depression, despite successful medical and surgical management, quality of life is low. In patients with CHF, having depression was associated with decreased functional limitations and decreased quality of life (Goyal et al, 2005; Stafford et al, 2007a; Shimizu et al, 2011). In the medical psychology and especially in the field of cardiovascular disorders, the concept of type D personality was introduced by Denollet et al (1998). Type D personality was defined as the joint tendency towards negative affectivity and social inhibition and can be related to depression outcomes in cardiac patients (Denollet, 2000; Denollet, 2005). In a study by Denollet et al (1996), there was found that type D personality was a significant predictor of long-term mortality in patients with established CHD. This was confirmed by a review by Pedersen et al (2003). They showed that cardiac patients with type D personality were not only at increased risk for cardiovascular morbidity and morbidity, but also for psychological distress and impaired quality of life. A more recent study by Svansdottir et al (2012), showed that type D personality was associated with psychological distress in cardiac patients. Also, patients with heart failure and type D personality showed an inadequate response to social stress (Kupper et al, 2013). As the recognition of depression in patients with cardiac diseases can be difficult, it is important that screening and adequate mechanisms for management and referral are structural imbedded in the treatment of these patients (Lesperance et al, 2000; Celano et al, 2011). 14 General Introduction

16 Cardiac disorders are very expensive disorders in terms of healthcare related costs in the Netherlands. In 2007, the costs were 1807 million, 2.4% of the total healthcare costs in the Netherlands. Most costs were due to hospital care (63%) and medication (24%) Multimorbidity A study of Spangenberg et al (2011) showed that depression was significantly more frequent in multimorbid respondents. Multimorbidity was associated with higher negative somatic symptoms and higher depression severity levels as compared to patients without multimorbidity. Gunn et al (2012) showed a negative relationship between the number of chronic medical illnesses and the prevalence of depression: the prevalence increased from 23% for having 1 illness to 41% for having 5 or more illnesses. Multimorbidity is common; a Netherlands study by Van Oostrom et al (2011) showed that almost 37% of the patients, aged 55 years and older, had 2 or more chronic diseases. Disease pairs that occurred more frequently than expected were coronary heart disease and heart failure, and COPD and heart failure. Multimorbidity in combination with co-morbid depression can result in several negative implications for normal daily life. When medical illnesses lead to pain, disability and disruption, co-morbid depression can exacerbate these negative outcomes and consequently, there is a decrease in quality of life (Gaynes et al, 2002). In a study by Agborsangaya et al (2012), quality of life and healthcare utilization in patients with multimorbidity was studied. They found that all chronic conditions reduced the health-related quality of life, most specific was the subject of pain/discomfort. Patients with multimorbidity also were twice as likely to being hospitalised or have an emergency department visit. Managing these patients demands complex interventions and challenges the protocolled healthcare. General Introduction 15

17 The treatment of these patients requires empathy, trust and therapeutic alliance with healthcare professionals (Mercer et al, 2012). As evidence on the care of patients with multimorbidity is limited, clearly a need exists to identify these patients and lead them to specially targeted interventions to improve their health outcomes (Smith et al, 2012). In this thesis, we focus on the most prevalent chronic medical illnesses: diabetes, chronic obstructive pulmonary disorders (COPD) and cardiovascular disorders (congestive heart failure (CHF), myocardial infarction (MI) and coronary artery disease (CAD)) (van der Feltz-Cornelis et al, 2010a). Patients with multimorbidity were also included and in chapter 2, a study concerning diabetes patients with multimorbidity will be presented. 16 General Introduction

18 1.2 The diagnosis of co-morbid depression Recognition by healthcare professionals When depression can be prevented or treated at an early stage, this can minimize negative consequences for the patient and lower healthcare related costs (Smit et al, 2006; Beekman et al, 2010). However, depression is not always recognized. Under-recognition has several causes. Firstly, the recognition of depression in chronically ill patients can be hampered due to the fact that some depressive symptoms have great similarities with medical symptoms and are therefore hard to distinguish (Whooley et al, 2000; Van der Feltz-Cornelis et al, 2010a). For example fatigue, loss of appetite and problems with concentration can be caused by depression, as well as a medical illness. Table 1 shows symptoms that can both be caused by depression and by a medical illness, based on the DSM-IV criteria for diagnosing depressive disorder (American Psychiatric Association, 2000). Secondly, general healthcare professionals do not always have the time, knowledge and access to the necessary resources to pay attention to mental disorders. In a study by Koenig (2007), the reference rates of older patients were examined. 37% of the physicians did not refer depressed patients for counselling and 40% did not refer depressed patients to a psychiatrist. Common reasons for not treating these patients were perceived resistance to treatment, lack of time, uncertainty of depression diagnosis, belief that patients could not afford treatment, and concern about medication/disease interactions. Pouwer et al (2006), concluded in their study that registration-rates of emotional problems by diabetes nurses were low and in patients with acute myocardial infarction, depression was recognized in fewer than 1 in 3 patients (Smolderen et al, 2009). General Introduction 17

19 Table 1. Depressive symptoms that can also be caused by a physical disease, as mentioned in the DSM-IV criteria (American Psychiatric Association, 2000). Markedly diminished interest or pleasure in all, or almost all, activities most of the day, nearly every day (as indicated by either subjective account or observation made by others) Significant weight loss when not dieting or weight gain (e.g., a change of more than 5% of body weight in a month), or decrease or increase in appetite nearly every day. Insomnia or Hypersomnia nearly every day Psychomotor agitation or retardation nearly every day (observable by others, not merely subjective feelings of restlessness or being slowed down) Fatigue or loss of energy nearly every day Feelings of worthlessness or excessive or inappropriate guilt (which may be delusional) nearly every day (not merely self-reproach or guilt about being sick) Diminished ability to think or concentrate, or indecisiveness, nearly every day (either by subjective account or as observed by others) In a focus group study by Van Rijkswijk (2009), 23 family physicians (FPs) were interviewed about the recognition of mental disorders. The FPs valued recognising, diagnosing and managing depressive and anxiety disorders as important primary care tasks, but they identified several factors that could hamper the diagnosis: insufficient understanding of the mental health problems and no access to tools for assessment and monitoring. Thirdly, patients with depressive symptoms do not always seek help or recognize depressive symptoms themselves. 18 General Introduction

20 Roness et al (2005) founded that 13% of the patients who were diagnosed with depression did not seek help. Reasons for not seeking help were causal attributions and perceived stigma or lack of need for help (Wrigley et al, 2006; Prins et al, 2011) Recognition by the use of screening questionnaires Under-recognition of depression can lead to under-treatment. Therefore, it is important to improve the recognition of depression, for example by means of screening questionnaires. The Beck Depression Inventory (BDI) was developed in 1974 and validated for depression (Beck et al, 1974). In 1977, the Hamilton Rating Scale for Depression was validated for screening depression in the general population. It showed a high correlation (0-89) between the Hamilton score and a psychiatrist's global rating (Knesevich et al, 1977). Also in 1977, the Centre for Epidemiologic Studies Depression Scale (CES-D) was developed (Weismann et al). This questionnaire also revealed good results with regard to sensitivity and specificity. But as all these questionnaires were validated for screening depression in the general population, there was a need for questionnaires for the screening of depression in hospital patients. For that reason, the Hospital Anxiety and Depression Scale (HADS) was developed (Zigmond et al, 1983). However, there was a need for a quick, simple screening questionnaire. In 2001, this led to the popularity of the Patient Health Questionnaire (PHQ-9) being validated in primary care clinics (Kroenke et al, 2001). In nine questions, the PHQ-9 uses the DSM-IV criteria to define depressive symptoms. In this thesis, we have used the PHQ-9 questionnaire to identify and screen patients for MDD. Chapter 3 will provide a validation study of this instrument in diabetes patients with co-morbid Major Depressive Disorder in the general hospital setting. General Introduction 19

21 1.3 The treatment of co-morbid depression Treatment options for co-morbid depression Although there are several suitable screening questionnaires for depression, they are only useful when those who have screened positive are offered adequate treatment. In a meta-analysis, Gilbody et al (2008) showed that screening for depression in clinical practice is not enough, because if used alone, case-finding or screening questionnaires for depression appear to have little or no impact in the detection and management of depression by clinicians. Providing the right treatment for depression is therefore necessary (Gilbody et al, 2008). The treatment of depression in chronically ill patients can be difficult. Treating co-morbid depression may require a different approach in patients with a chronic medical illness (Goldman et al, 1999). For example 'running therapy' can be impossible to do for chronically ill patients, due to physical impairments. Furthermore, taking antidepressant medication can be contra-indicated when patients already use several other medications. It is therefore important to define a treatment programme that takes the physical possibilities of these patients into account Disease management for patients with co-morbid depression Several studies have shown that integrated management programmes for depression are more effective than care as usual (Neumeyer-Gromen, 2004). Systematic reviews showed that disease management programmes for patients suffering from depression were superior compared to care as usual in terms of depression severity, mental health quality of life, keeping one s job, and adherence to medication (for at least 90 days) (Goldman et al, 1999; Neumeyer-Gromen, 2004). Disease management improved patient satisfaction, patient and provider adherence, and disease control regarding chronic conditions such as depression, diabetes mellitus, coronary artery disease, COPD, and heart failure (Goldman et al, 1999; Neumeyer-Gromen et al, 2004; Ofman et al, 2004). 20 General Introduction

22 It also was cost-effective, compared to other well-accepted medical interventions (Badamgarav et al, 2003; Ofman et al, 2004). In the US, Katon et al (2002) developed the Improving Mood-Promoting Access to Collaborative Treatment (IMPACT) intervention. This disease management intervention consisted of a behavioural activation intervention, problem-solving treatment and antidepressant medication. In two-third of the patients, the long-term effect of this collaborative care intervention was associated with sustained improvement after 12 months (Katon et al, 2002). It resulted in less depression severity over time and higher satisfaction with care, compared with patients receiving care as usual. In 2006, Katon et al evaluated the collaborative care model in patients with diabetes and depression. The intervention was associated with an increase in depression-free days and a decrease in healthcare costs. Based on these positive results, in 2006 we decided to develop a collaborative care model for the treatment of depression in chronic medically ill patients in the Netherlands, based on the IMPACT intervention (van der Feltz-Cornelis et al, 2009). Most collaborative care studies have focussed on the treatment of depression in patients with a specific medical illness, but in order to develop a generic model for patients with multimorbidity, we focussed on patients with the most prevalent chronic diseases such as diabetes, COPD and cardiac disorders. The effectiveness and cost-effectiveness of this collaborative care treatment of co-morbid depression in chronic medically patients will be the topic of this thesis. General Introduction 21

23 1.4 The Netherlands collaborative care intervention Design of the study In the Netherlands, the Depression Initiative has been launched to integrate treatment for depressive disorder on a nationwide level, according to the principles of disease management (van der Feltz-Cornelis et al, 2009; 2011a; 2011c). Three collaborative care studies were initiated in three different settings: primary care (Huijbregts et al, 2012), occupational healthcare (Vlasveld et al, 2012) and hospital care (van Steenbergen-Weijenburg et al, submitted). In this thesis, the study of the cost-effectiveness of collaborative care in the general hospital will be presented: Collaborative Care: Depression Initiative in the Medical setting (CC:DIM). In 2006, the study started at the Onze Lieve Vrouwe Gasthuis (OLVG hospital) in Amsterdam and after that it was expanded to five outpatient clinics in the Netherlands. Patients who were diagnosed with a chronic medical illness such (e.g. diabetes, COPD or heart failure) were screened for depression with the PHQ-9 (Kroenke et al, 2001). For each question, a range from 0 (no complaints) to 3 (nearly every day complaints) was scored. A total score of < 5 was considered as no depression, a score of 5-10 as mild depression, as moderate depression and 15 as severe Major Depressive Disorder. A cut-off score of 10 was used to define patients with a moderate depression, after which the MIni Neuropsychiatric Interview (M.I.N.I.) (Sheehan et al, 1998) was used to diagnose Major Depressive Disorder (MDD). Included patients diagnosed with MDD were randomised into the intervention group or care as usual group. Patients in the intervention group received collaborative care, patients in the care as usual group were advised to seek help with their physician if the complaints continued. The physician treated these patients according to the Dutch Multidisciplinary guidelines for depression. 22 General Introduction

24 During one year, the patients received three-monthly questionnaires containing questions about physical and psychological wellbeing, healthcare usage, and quality of life Design of the intervention Patients in the collaborative care group had weekly consultations with a Psychiatric Nurse at the hospital outpatient clinic. During these consultations, the nurse used Problem Solving Treatment (PST) to help manage daily problems. PST is a brief form of evidence-based psychotherapy that was originally developed in the UK for use by medical professionals in primary care. Mynors-Wallis et al (1995) concluded that PST was effective, feasible and acceptable for patients with major depression. The nurse followed seven steps: problem orientation, recognising and identifying problems, selecting and defining a clear problem, generating solutions, decision making, creating and implementing a SMART action plan and reviewing progress. By solving relatively easy problems in daily life, patients felt they could manage these situations. Eventually, this could reduce the depressive symptoms. Hassink-Franke et al (2011) studied the effectiveness of PST in Dutch general practices. They concluded that patients treated with PST improved significantly more than care as usual patients on social functioning, emotional problems and general health perception. Besides PST, patients received a self-help care book about depression. In this book, there was information about the disease and exercises to improve mood. The exercises in the book were developed in a way that patients with a severe chronic disease could perform them. For the collaborative care intervention, an antidepressant medication algorithm was developed (medication was optional). To evaluate if the depressive symptoms were reduced, the progress was monitored bi-weekly with the PHQ-9 (Kroenke et al, 2001). General Introduction 23

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