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An Evaluation of Routine Screening, Assessment and Treatment of Depression for Patients on the Diabetes and / or Coronary Heart Disease Registers in a Primary Care Practice in Norfolk

Anna Marie Croxford[1], School of Medicine Health Policy and Practice, University of East Anglia



Depression is more common in patients with diabetes and coronary heart disease (CHD). Depression screening in these patients has been of interest since its inclusion in the 2006 Quality and Outcome Frameworks (QOF) contract.


To investigate if depression screening in patients with diabetes and/or CHD is performed in accordance with QOF guidance, and whether screening causes identification and treatment of new depression cases.


A retrospective audit of eligible patients on the diabetes and/or CHD registers at a rural general practice from 1 April 2007 to 31 March 2008. The percentages of patients screened, identified to have depression and subsequently treated were calculated.


148 of the 532 sample patients were excluded leaving 384 eligible patients. 47 eligible patients were excluded by healthcare staff, mostly for known depression. 303 (78.9%) were screened, of whom seven (2.3%) screened positively for depression; only two were assessed for severity. One scored for mild depression, the other for moderate/severe. No new treatment was initiated.


Current screening at this practice appears unnecessary or unsuccessful. Further research is required to investigate whether screening is adhered to and results in identification and treatment of new depression cases in other practices.

Keywords: Coronary heart disease, depression screening, diabetes, primary care, quality indicators


The aim of this study was to audit the screening, assessment and treatment of depression in eligible patients with diabetes and/or coronary heart disease (CHD) at a rural Primary Care Practice in Norfolk from 1 April 2007 to 31 March 2008. Screening and assessment was recorded in accordance with the General Medical Services (GMS) contract revision in March 2006. This introduced 8 new clinical Quality and Outcomes Framework (QOF) domains emphasising the management of long-term conditions in primary care, including screening and management of depression in patients with CHD and diabetes. (BMA, 2007). Hence the percentage of eligible patients for whom the procedures outlined below have been carried out was investigated. This should allow comment on the practice's performance in following the QOF guideline and the effectiveness of the guideline in facilitating identification and treatment of new depression cases.

  1. Patients should be screened for depression in a primary care setting in accordance with the following two-question depression screen recommended by NICE:
    1. 'During the last month, have you often been bothered by feeling down, depressed or hopeless?'
    2. 'During the last month, have you often been bothered by having little interest or pleasure in doing things?' (NICE, 2010)

An answer of 'yes' to either question is considered a positive indicator of depression and leads to the second indicator:

  1. When depression is detected, severity should be assessed using an assessment tool validated for use in primary care. (NICE, 2010)

Depression severity is assessed as mild, moderate or severe, using one of three NICE-accredited questionnaires; the 9-item Patient Health Questionnaire (PHQ-9), the Beck Depression Inventory Second Edition (BDI-II), and the Hospital Anxiety and Depression Score (HADS). (NICE, 2009; NICE, 2010; BMA, 2009) The PHQ-9 is used at the practice audited in this paper and is available online. (Kroenke et al., 2001)

  1. Following severity assessment, treatment should be offered in accordance with the stepped care model of depression treatment recommended by NICE (Appendix 1) (NICE, 2009).

Depression severity is judged by the patient's score (MacArthur Initiative, 2008) facilitating discussion of treatment options in accordance with the stepped care model of depression treatment recommended by NICE. Primary care practices are responsible for steps one to three of the guidance. These include assessment and treatment of mild, moderate or severe depression (Appendix 1) (NICE, October 2009). Practices are required to report the percentage of their patients on the CHD and diabetic registers that have been screened, providing an opportunity for audit. (BMA, 2009) At this practice screening is nurse-performed during annual diabetic and CHD reviews. Patients are referred to their General Practitioner (GP) for assessment and treatment if the nurse is concerned by their PHQ-9 score (Andy Gray, personal communication).

As part of clinical governance, National Health Service (NHS) organisations are required to improve their services by optimising clinical care. The General Medical Council (GMC) recommends doctors change their clinical practice as a result of audits (Michael, 2004). Audits are carried out within a cycle where current clinical practice is measured against established best practice criteria allowing understanding and change in practice if standards are not met. This cycle repeats to measure and sustain improvement (Cooper, 2004).

Depression is a common and disabling condition. The World Health Organisation (WHO) has predicted that depression will be the highest-ranking cause of disease burden in 2020 (Murray and Lopez, 1996). Depression is characterised by low mood and associated emotional, cognitive, physical and behavioural symptoms, including lack of interest and enjoyment in activities. This may cause significant disability impacting upon personal, social and occupational activities, while burdening carers and dependants of those affected. Multiple morbidity and suicide are common and cause increased service use and economic costs. Depression is more common in patients with chronic health conditions than the general population (BMA, 2009). Egede found that patients with chronic disease in the USA were almost three times more likely to be depressed. Depression rates were double in diabetes, hypertension, coronary artery disease and heart failure and trebled in end-stage renal failure, chronic pulmonary obstructive disease and cerebro-vascular disease (Egede, 2007). Similar results were found in a WHO study including 60 countries; patients with two or more chronic disease diagnoses experienced a depression prevalence of 23% compared to 2% (Moussavi et al., 2007). When depression and physical disorder co-exist, disability is likely to be greater (NICE, 2009) and depression is often overlooked by healthcare professionals, especially in chronic disease where attention can shift to physical symptoms (Thompson et al., 2000; Ustun and Sartorius, 1995).

While depression has co-morbidity with many chronic physical conditions, the evidence for co-morbidity with CHD (Nemeroff et al., 2000) and diabetes (Anderson et al., 2001) is well documented (BMA, 2009). Depression is more common in people with CHD; up to 33% of patients develop depression post myocardial infarction (MI) (Davies et al., 2004). In this group, depression is associated with social isolation, increased use of healthcare resources and poorer treatment compliance and prognosis (Carney et al., 2003). A meta-analysis of 20 trials showed that depression is an independent risk factor for mortality in CHD patients (Barth et al., 2004). The lifetime prevalence of depression in diabetic patients (24%) is three times greater than the general population. A recent meta-analysis found depression to be clinically significant in one third of diabetic patients (Anderson et al., 2001). Depressed diabetic patients are less physically and socially active, suffer from more severe symptoms, have worse functional impairment and diabetic complications, and are less likely to adhere to physical health treatments than those without depression. Higher suicide risk has been reported (Tsang, 2004).

Recent evidence details the efficacy of treatment in both diabetic and CHD patients. Two Random Controlled Trials (RCTs) of Cochrane Grade A evidence demonstrated that Selective Serotonin Reuptake Inhibitor (SSRI) antidepressants reduce depression in CHD patients, especially those with severe symptoms or a past history of depression (Glassman et al., 2005). A non-randomised trial suggested that antidepressant treatment or Cognitive Behavioural Therapy (CBT) reduces death or recurrent MI (Lesperance et al., 2007). Evidence from five RCTs suggests treatment with antidepressants or CBT improves depression outcomes in diabetics. Treatment did not improve glycaemic control, but psychological well-being is an important management goal in the St Vincent Declaration, 1989. Non-UK evidence has shown that patients with diabetes or CHD and co-morbid depression accrue higher medical healthcare costs (NICE, 2009). This has been demonstrated for both diabetes (Ciechanowski et al., 2000; Egede et al., 2002) and CHD (Frasure-Smith et al., 2000). Hence healthcare resources should be used efficiently to treat depression in patients with chronic health conditions. It is reasonable to believe that if QOF is implemented as intended significant improvement in the management of depression in patients with diabetes and CHD will follow (BMA, 2009).

However, recent studies concluded that depression screening in general has no effect on prescribing (Boardman, 2009; Morrison et al., 2009; Alter, 2008) and does not alter practice (Dorwick et al., 1995). A recent Cochrane review compared the outcomes of a normal pattern of depression care with the introduction of routine screening. The authors concluded that depression screening questionnaires had little impact on the recognition, management and outcomes of depression. They recommended that GPs should resist incentives to screen patients routinely for depression without further research (Gilbody et al., 2009). Few studies focus solely upon depression screening and treatment outcomes in patients with diabetes and/or CHD. An audit conducted prior to the new QOF guidelines found that patients with higher severity scores were more likely to receive treatment, but there was variation between the HADS and PHQ-9 scores. Treatment rates were lower for older patients and those with chronic disease (Kendrick et al., 2009). An unpublished analysis of 38 practices using the PHQ-9 or HADS is outlined in the QOF Guidance 2009/2010. This showed that treatment and referral rates increased in line with higher depression scores. The PHQ-9 rated more people as severely depressed, but there was no difference between treatment rates with both scores, suggesting that clinicians do not choose drug treatment based on scores alone (BMA, 2009). Subramanian and Hopayian audited the treatment outcomes of the first year of depression screening under QOF 2006 guidelines in a semi-rural practice in Norfolk. They found only 1% of the 435 patient sample screened positive for depression and that no new depression treatment was initiated. They concluded that audits at other practices are required to investigate if screening leads to substantial improvement in the identification and treatment of high-risk patient groups (Subramanian and Hopayian, 2008). Hence this audit builds upon limited contradictory research regarding the implementation and outcome of depression screening in the target group.


This study involved a retrospective audit of patient information collected by hand-searching electronic patient notes and Quality Management and Analysis System (QMAS) returns of all patients on the diabetic and/or CHD registers from 1 April 2007 to 31 March 2008. This was the entire previous year's QMAS returns. Electronic records are held on the 'Vision', version three, software system on the local IT server at the practice. A pilot of the first 50 patients on the registers was completed to familiarise with 'Vision', find the location(s) of information and to check the relevance of outcome measures and exclusion criteria. All patients over 18 years old, diagnosed with diabetes and/or CHD and eligible for depression screening and severity assessment were audited. Patients were excluded from the outcome measures for the following reasons:

(i) Depression diagnosis recorded before the annual recording period (01/04/07);

(ii) Recorded as unsuitable in last 15 months (table 2);

(iii) Informed dissent for screening in last 15 months;*

(iv) Patient deceased;

(v) Did not attend annual diabetic/CHD review;*

(vi) First diagnosis of diabetes/CHD in last 15 months.

Most exclusions were included in the QMAS returns. Those marked with an asterisk are detailed in QOF Guidance for GMS contract 2008/09 (DOH, 2008/2009). Outcome measure retrieval was completed in the order detailed below as each test should only be carried out for each patient if they answered positive for the previous test. Data corresponding to outcomes (A) and (B) were retrieved from the QMAS returns and checked against computerised patient notes. Outcomes (C) to (F) were retrieved from computerised patient notes.

Screening process

The number of patients on the diabetic and/or CHD registers who were recorded as screened using the two screening questions for depression.

(B) Of those patients who were screened, the number that answered positively for depression (BMA, 2009).

Assessment of severity of depression identified by screening

(C) The number of patients, who answered positively for depression, for whom a PHQ-9 score and depression severity was recorded (BMA, 2009).

Outcome of screening process

(D) The number of patients for whom depression treatment was offered and recorded.

(E) The number of patients for whom depression treatment offered corresponds with the NICE guidelines for depression management (NICE, 2009).

(F) The number of patients that declined treatment offered.

Ethical considerations

Patient recruitment, ethics committee and research and development approval are not required for an audit. Information relating to depression is private and sensitive. Patient-identifiable data were held securely on the practice IT server and the author respected the practice's confidentiality agreement (see Appendix 2). An audit should not negatively affect patient care. It may improve future outcomes through feedback and change in clinical practice, especially if standards are not met.

Data analysis

Data were recorded in an Excel spreadsheet and encoded for transfer into SPSS version 16 for analysis. The number and percentage of patients for whom each outcome measure was completed was calculated. Percentages were expressed as a proportion of patients who yielded a positive result from the previous outcome measure.


Of the 532 patients on the diabetes and CHD registers, 148 patients were excluded leaving 384 for analysis (figure 1). Sample characteristics of the eligible patients are shown in table 1. The median age of patients was 72 years (range 19-98). 63% of the patients were male. Type two diabetes and/or CHD were more prevalent than type one diabetes.

Qualifying condition(s) n (%)
Male Female Total
Type one diabetes 11 (4.5) 8 (5.6) 19 (4.9)
Type two diabetes 93 (38.5) 65 (45.8) 158 (41.1)
CHD 121 (50) 57 (40.1) 178 (46.6)
Type one diabetes & CHD 1 (0.4) 1 (0.7) 2 (0.5)
Type two diabetes & CHD 16 (6.6) 11 (7.7) 27 (7.0)
Total 242 (63) 142 (37) 384 (100)

Table 1: Sample characteristics

Reasons for exclusion are shown in table 2. 105 patients were excluded due to depression diagnosis before the QMAS reporting period; this exclusion is appropriate as the aim of screening is to identify new depression cases (Dr Chris Hand, personal communication). Screening patients with depression may have little effect on patient management at the practice as patients with depression are monitored through regular mental health review (Andy Gray, personal communication). It is interesting that 47 patients were recorded as unsuitable for screening by healthcare staff over the last 15 months (table 2). The appropriateness of these exclusions is considered in the discussion.

Exclusion criterion n %
Depression diagnosis recorded prior to 01/04/07 105 58.3
Patient recorded unsuitable in last 15 months 50 27.8
Informed dissent for screening in last 15 months 12 6.7
Patient deceased 6 3.3
Did not attend annual diabetic/CHD review 4 2.2
First diagnosis of diabetes/CHD recorded in last 15 months 3 1.7
Total 180* 100

Table 2: Reasons for exclusion from the sample population (*some patients were excluded for more than one reason).

Reason for unsuitability n %
Dementia 25 50
Frail, in nursing home 2 4
GP encodes inappropriate - pre-existing depression 2 4
Impaired glucose tolerance rather than diabetes 1 2
Housebound, unable to get to surgery 1 2
Recent bereavement 1 2
Exempt from diabetic review - treated in secondary care 2 4
Other mental health disorder (bipolar) 1 2
Excluded from pre-existing audit: reason not specified 15 30
Total 50* 100

Table 3: Why healthcare professionals recorded patients as unsuitable for screening (*some patients were excluded for more than one reason).

A sequential analysis of the completion of each outcome measure is shown in figure 1. The number and percentage of patients for whom each outcome measure was completed is shown; percentages are expressed as a proportion of patients who yielded a positive result from the previous outcome measure. 303 (72.2%) of the sample population were screened for depression, compared to 77.8% reported by the annual QMAS returns for the practice (Appendix 3). Of the 303 patients screened for depression, seven responded positive to the screening questions. Three of the seven patients were given a PHQ-9 to complete, but they did not return it. Another two of the seven were questioned using a PHQ-9; one scored for minimal depression and the other, moderate / severe depression. Neither of these two patients was started on new treatment for depression; however the second patient declined computerized CBT or medication. There was no mention of any action, such as watchful waiting, as a result of screening in the first patient's notes. These contrast with the QMAS returns, which stated that 93.4% of patients identified as depressed were assessed using a PHQ-9 (Appendix 3). This is discussed later. There were insufficient depression diagnoses to analyse treatment provision against NICE guidelines (NICE, 2009). The practice offers pharmacological treatment, computerized CBT and consultations with the Link worker who offers self-help leaflets such as 'Depression. An information leaflet' (Norfolk NHS, 2006) or 'Finding your way: Information for older people living in Norfolk with mental health problems' (Norfolk County Council, 2006). Those with moderate / severe depression are assessed for secondary care referral by the link worker. Funding for NHS counseling, CBT and behavioural therapy has been withdrawn from the practice, hence they recommend a list of private practitioners. Antidepressants and computerized CBT are the mainstay of treatment (Andy Gray, personal communication).

Figure 1

Figure 1: Numbers (%) of patients for whom screening questions were completed.


Data were extracted for 532 patients on the CHD and/or diabetic register: 148 patients were excluded, leaving 348 patients in the audit. 303 patients (78.9% of the sample) were screened for depression. Seven of these yielded a result positive for depression (2.3% of the sample). A depression severity assessment was performed in two of these patients (0.5% of the sample). One patient scored for mild depression, and the other for moderate / severe depression. No identified patients were started on new treatment. Overall the results of this audit of screening appear to demonstrate that screening in its current form is unnecessary or unsuccessful (table four). Possible reasons for the low identification of new depression cases are considered later.

  1. 47 patients were recorded as not eligible for screening by their GP.
  2. Despite screening according to guidelines only 0.6% were identified as suffering from depression.
  3. Of those 7 who recorded positive for depression, only 2 had a recorded PHQ-9.
  4. No new treatment was initiated as a result of screening at this practice.

Table 4: Summary of main findings.

As discussed in the introduction, current research regarding the outcome of depression screening in patients with diabetes and/or CHD is limited and divided in their conclusions. However, Subramanian and Hopayian (2008) found similar results in an audit of a semi-rural practice in Norfolk; 1% of the 435 patient sample screened positive for depression and no new depression treatment was initiated. Reasons screening may have little effect on depression outcomes have been discussed. Kendrick et al. (2009) suggested older patients may be screened to achieve QOF points rather than for treatment consideration. GPs may discount depression revealed through screening to avoid medicalising transient stress or from concerns regarding drug side effects on co-morbid physical conditions (Kendrick et al., 2009). Dowrick et al. (2009) investigated patients' and doctors' opinions on routine screening for depression severity. They found that patients viewed these questionnaires more favorably than GPs. Most GPs felt clinical judgment was more important than screening, which should be part of a holistic approach. Score manipulation was discussed as some patients answered dishonestly to avoid depression diagnosis or treatment, while some GPs avoided using depression reporting codes in notes to avoid performing an assessment (Dowrick et al., 2009). The accuracy and utility of screening has been questioned. Screening tests usually overestimate depression prevalence. Only 50% of patients who score as depressed actually have the condition so patients may be incorrectly labeled as depressed (Gilbody et al., 2009). Screening is one of many potential approaches to optimise depression care (Gilbody et al., 2009). It has been suggested that screening may have a greater effect on management when combined with GP educational programmes and an integrated care system to provide access to appropriate treatment (Kessler and Sharp, 2005; Boardman, 2009; Gilbody et al., 2009). GPs may feel not best equipped to deal with emotional disorders highlighting the need for education (Gilbody et al., 2009). Piloting of QOF indicators to assess their effect on patients has been suggested (Dowrick et al., 2009). Evidence also suggests that optimising treatment for patients suffering from depression is more appropriate than identifying new cases (Kessler and Sharp, 2005). Lepine et al. demonstrated 28% of patients prescribed an antidepressant by their GP never redeemed their prescription or did so only on one occasion (Lepine et al., 2007). Given the very small number of patients found by screening in this audit, it may be useful to see whether management of known depression cases is optimal. A nationwide lack of provision for psychological therapies and research showing their efficacy (Boardman, 2009) led to calls for improvement in provision of psychological treatments for common mental health problems (Layard, 2006). Hence the Department of Health (DOH) introduced the Increasing Access to Psychological Therapy (IAPT) schemes which will offer therapy programmes of varying intensities (DOH, 2008). This may help optimise treatment for depression (Boardman, 2009).

It is possible that there were very few cases of unidentified depression in this population giving a true effect, that screening in its existing form has a very low detection rate or that results reflect a systematic error in data collection or factors specific to the sample population. Data were collected through hand searching of patient notes using clear outcome measure definitions decided during a pilot audit. Multiple checks were included in different locations within the notes to ensure all required data were found. Data were retrieved for all patients on the diabetic and/or CHD registers over a given time period ensuring that the effect seen reflects information recorded in the notes for this population. Care may have been provided, but not recorded, giving an underestimation. This is the most plausible reason why only 78.9% were recorded as screened for depression, especially as the first year of QOF reporting was audited. However, it is less likely that recording would be omitted in the case of positive findings as this could be interpreted as negligence. It is also possible that the author did not find all relevant data, as some data were difficult to locate. Those patients who screened positive for depression were not listed in the QMAS returns as eligible for depression severity assessment, so data retrieval was from patient notes. The author is unable to explain this discrepancy between this audit and the QMAS returns. The possible systematic error of 5.5% difference in completion of the first screening question between the QMAS returns and this audit does not account for the low number of new depression cases found by screening. No other discrepancies were noted. 100% completion of each screening question is the gold standard. If this is not achieved an underestimate of the number of patients who yield a positive result for the next measure will occur. This may have skewed results as only 78.9% of the sample was screened. It was suggested that few new depression cases were identified as patients with depression were already known to their GP due to good continuity of care (Andy Gray, personal communication). It has been noted that accuracy of depression diagnosis increases with patient contact over 3-12 months rather than one-off contact (Mitchell et al., 2009). It is possible for the practice to have a high detection rate for depression independent of the screening, but the practice has no unique system for doing so. However, 10% of the total sample population (532) were either known to suffer from depression or identified as depressed during screening. This rate is higher than previously demonstrated in general primary care patients (6.6%), (Simon and VonKorff, 1995) and 1% less than the lower end of the estimate for those with diabetes (11-22%) (Anderson et al., 2001) and less than those with CHD (17%) (Hance et al., 1996). Even though 54% of the sample were diagnosed with diabetes, it is still likely that the sample was atypical. Hence these results are probably not generalisable to other populations, especially busy city practices and younger patients. Screening may uncover new depression cases if used at large polyclinics as suggested in the Darzi report (Stockport, 2008; Darzi, 2008) as less continuity of care will be provided by such services (DOH, 2008).

The appropriateness of reasons why patients were deemed unsuitable for screening by healthcare staff requires consideration. Exclusion due to recent diagnosis with a chronic health condition or difficult life event, such as recent bereavement, is appropriate as these patients may experience transient depression (Gilbody and Shelton, 2006). Considering that a significant proportion of patients with dementia are also suffering from depression and that screening in this group is recommended (Kessler and Sharp, 2005), what level of dementia is too advanced for screening? Some patients were excluded for economic reasons. Patients unable to attend the surgery could be offered a home visit and those who receive their diabetic care elsewhere or did not attend their diabetic/CHD review could be invited for screening by letter. If these patients were non-representative of the sample population this could have skewed the results; it is possible that they had a higher depression rate due to their additional co-morbidities. The 12 patients who refused screening are also a source of uncertainty; they may have refused in order to avoid a probable depression diagnosis. These uncertainties may have increased the percentage of depressed patients in the sample group nearer to the aforementioned documented percentages.

This audit raises the issue of improvement in QOF reporting at the practice studied. This may include screening of some patients who were deemed unsuitable, completion of PHQ-9 questionnaires on site to ensure completion, and education to ensure that all patients who are identified as depressed either receive a severity assessment, or the reasons for not doing so are recorded. The author cannot suggest why these assessments were not completed or not recorded in the notes. Discussion of the level of dementia that is too advanced to screen may be useful. Discrepancies between this audit and the QMAS returns at the practice studied should be investigated. Whilst beyond the scope of this project, it is important to re-audit annually to investigate the affect of altered clinical practice on outcomes (Rawlins, 2004). Since completion of this audit a third depression indicator has been included in the revised QOF guidance 2008/2009: the percentage of patients identified as depressed through screening who had a further severity assessment 5-12 weeks after the initial depression severity recording. Both assessments should be completed using an assessment tool validated for use in primary care. (BMA, 2009). One may question the cost-benefit analysis of this indicator at the practice studied as only two new cases were identified.

While this audit appears to demonstrate that screening in its current form is unnecessary or ineffective in identifying new depression cases for treatment initiation, further study is required to substantiate or revoke this. A large-scale study of a variety of UK general practices would be useful to improve generalisability, especially including busy city practices and large polyclinics, and may allow discussion of the appropriateness of treatment offered. Gilbody concluded that further establishment of sensitivity, specificity and predictive values of depression screening questionnaires, comparison of treatment outcomes between routine care for depression and those identified by screening, and finally cost benefit analysis of screening require investigation (Gilbody et al., 2009). It will be interesting to see the results of future research in this field.


I would like to thank my supervisor Professor Christopher Hand for supporting this audit, and Andy Gray, the practice manager at the general practice audited, for guidance regarding the Vision system. I also thank David Croxford for proof reading this document.

List of Illustrations

Figure 1: Number (%) of patients for whom each screening question was completed.

List of Tables

Table 1: Sample characteristics.

Table 2: Reasons for exclusion from the sample population.

Table 3: Why healthcare professionals recorded patients as unsuitable for screening.

Table 4: Summary of main findings.

Appendix 1

NICE Model for Depression Treatment (NICE, 2009)

Appendix 1

Appendix 2

Confidentiality Agreement

Appendix 2

Appendix 3

Annual QMAS Returns

[click on image for full-size version]

Appendix 3


[1] Anna Marie Croxford studied Medicine at the University of East Anglia. Since graduation she has been a Foundation Doctor at the Norfolk and Norwich University Hospital and a Research Assistant under Dr Julian Beezhold, consultant in emergency psychiatry at Hanser House, Hellesdon hospital in Norwich.


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To cite this paper please use the following details: Croxford, A. (2010), 'An Evaluation of Routine Screening, Assessment and Treatment of Depression for Patients on the Diabetes and / or Coronary Heart Disease Registers in a Primary Care Practice in Norfolk', Reinvention: a Journal of Undergraduate Research, Volume 3, Issue 1, Date accessed [insert date]. If you cite this article or use it in any teaching or other related activities please let us know by e-mailing us at Reinventionjournal at warwick dot ac dot uk