Changes in rates of recorded depression in English primary care 2003-2013: time trend analyses of effects of the economic recession, and the GP contract quality outcomes framework (QOF)

Tony Kendrick, Beth Stuart, Colin Newell, Adam W A Geraghty, Michael Moore

Abstract

Background: Depression may be increasing, particularly since the economic recession. Introduction of quality outcomes framework (QOF) performance indicators may have altered GP recording of depression.

Methods: Time trend analyses of GP recording of depression before and after the recession (from April 2008), and the QOF (from April 2006), were conducted on anonymised consultation data from 142 English practices contributing to the Clinical Practice Research Datalink, April 2003-March 2013.

Results: 293,596 patients had computer codes for depressive diagnoses or symptoms in the 10 years. Prevalence of depression codes fell from 44.6 (95% CI 44.2, 45.0) per 1000 person years at risk (PYAR) in 2003/2004 to 38.0 (37.7, 38.3) in 2008/2009, rising to 39.5 (39.2, 39.9) in 2012/2013. Incidence of first-ever depression codes fell from 11.9 (95% CI 11.7, 12.1) per 1000 PYAR in 2003/2004 to 9.5 (9.3, 9.7) in 2008/2009, rising to 10.0 (9.8, 10.2) in 2012/1203. Prevalence increased in men but not women following the recession, associated with increased unemployment. Following introduction of the QOF, GPs used more non-QOF-qualifying symptom or other codes than QOF-qualifying diagnostic codes for new episodes.

Limitations: Clinical data recording is probably incomplete. Participating practices were relatively large and not representative across English regions.

Conclusions: Rates of recorded depression in English general practices were falling prior to the economic recession but increased again subsequently, among men, associated with increased unemployment. GPs responded to the QOF by switching from diagnostic to symptom codes, removing most depressed patients from the denominator for measuring GP performance in assessing depression.

Key words: depression, prevalence, primary care, economic recession, pay for performance, QOF

Corresponding author:Professor Tony Kendrick MD FRCGP FRCPsychProfessor of Primary CarePrimary Care & Population SciencesUniversity of SouthamptonAldermoor Health CentreSouthampton SO16 5STTel: 02380 241083Fax: 02380 701125Email: A.R.Kendrick@Southampton.ac.uk

This is independent research funded by the National Institute for Health Research (NIHR) School for Primary Care Research (grant no. 214). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

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Background

Depression is very common, often chronic or relapsing, and costly, and is usually treated in primary care if it is treated at all. There is concern that depression might be increasing in prevalence worldwide, although the evidence is mixed. Epidemiological surveys suggest prevalence increased from the early 1990s up until 2004, at least in the USA (Hasin et al, 2005; Kessler et al, 2005; Eaton et al, 2007). Overall rates in the UK did not appear to have risen at least up until 2007 (Singleton et al, 2003; McManus et al, 2009), although there was limited evidence of an increase among women (Spiers et al, 2012). Major depressive disorder (MDD) moved up from 15 th to 11th in the ranking of disorders by disability adjusted life years between 1990 and 2010 (a 37% increase) (Murray et al, 2012), but this change in ranking was due to population growth and ageing - prevalence rates for MDD were found to have decreased slightly over the 20 year period (Ferrari et al, 2013). Nevertheless, the King’s Fund estimated that 1.45 million people in England would have depression by 2026, and the total cost to the nation would exceed GBP 12 billion per year, including prescriptions, inpatient and outpatient care, supported accommodation, social services, and lost employment (McCrone et al, 2008).

There are relatively few data on rates of depression in primary care compared to the large amount of epidemiological data from community surveys (Waraich et al, 2004). The diagnosis and treatment of depression in primary care is controversial, as on the one hand it has been found repeatedly that general practitioners (GPs) fail to recognise a proportion of disorders which might benefit from treatment (Kessler et al, 2002; Cepoui et al, 2008), while on the other they are accused of treating more and more people with antidepressants unnecessarily (Parker, 2007). Antidepressant use has been rising steadily since the early 1990s when the selective serotonin reuptake inhibitors were introduced, which could be due to more people being diagnosed year on year, but could be due to the prescribing of longer courses of treatment (Moore et al, 2009), or a combination of both.

Analysis of computerised medical record data from The Health Improvement Network (THIN) general practice database found that the prevalence of adults diagnosed with depression and treated with antidepressants roughly doubled between 1993 and 2004: prevalence among women increased from around 50 to around 100 per 1000 person-years at risk (PYAR), and among men from around 25 to around 50 (Morgan et al, 2008). We analysed computerised medical record data from the General Practice Research Database (GPRD) from 1993 to 2005 and also found that antidepressant prescribing approximately doubled during the study period (Moore et al, 2009). However this was due to a doubling in the average number of prescriptions given to each patient rather than an increase in the incidence of new cases of depression. The majority of antidepressant prescriptions were given as long term treatment or as intermittent treatment to patients with presumed multiple episodes of depression, and the recorded incidence of first-ever episodes actually declined over the period: in women from 15.8 per 1000 PYAR in 1993 to 10.1 in 2005, and in men from 7.8 per 1000 PYAR in 1993 to 6.0 in 2005 (Moore et al, 2009).

GPs do not usually use specific diagnostic criteria to characterise depression and they use symptoms as labels associated with antidepressant prescriptions as well as diagnostic labels. Furthermore, their use of labels seemed to be changing in the period up until 2006, perhaps as a consequence of being accused of over-diagnosis. A separate analysis of the THIN database found that the incidence of new episodes of diagnosed depression fell from 22.5 to 14.0 per 1000 PYAR between 1996 and 2006, but

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the incidence of new episodes of depressive symptoms rose threefold from 5.1 to 15.5 per 1000 PYAR, and the combined annual incidence of diagnoses and symptoms remained stable at around 29 per 1000 PYAR, suggesting that GPs were increasingly using symptom rather than diagnostic labels to record depression (Rait et al, 2009).

These studies predate the economic recession starting in April 2008, following which there was an increase in suicides in England (Barr et al, 2012) as in other western countries, associated with rising unemployment rates, particularly in men (Chang et al, 2013; Coope et al, 2014). Antidepressant use has continued to rise, doubling in the 10 years up to 2011 among the world’s richest nations (McCarthy, 2013) with a steeper trajectory in England since 2008 (Health & Social Care Information Centre, 2014) which may be due to an increased incidence of depression as well as more long-term prescribing.

The studies above also predate the introduction of performance indicators in the GP contract quality outcomes framework (QOF) which required the assessment with symptom questionnaires of the severity of depression in people diagnosed with categorical depressive disorders, at diagnosis from 2006 and also at follow-up from 2009 (BMA & NHS Employers, 2006; 2009). This may have affected GPs’ willingness to label people with categorical diagnoses and further encouraged the use of symptoms as medical record labels instead, from 2006 onwards.

We analysed data from the Clinical Practice Research Datalink (CPRD), a longitudinal anonymised research database derived from nearly 700 primary care practices in the UK, formerly known as the GPRD (Medicines and Healthcare Products Regulatory Agency (MHRA), 2014; Williams et al, 2012), to determine how GP rates of recording of depression changed in England between April 2003 and March 2013, exploring possible effects of the recession from April 2008 and the QOF from April 2006, using time trend analyses of quarterly rates.

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Methods

The study protocol was approved by the Independent Scientific Advisory Committee of the MHRA. Data were obtained from all general practices which were in the CPRD continuously from 2003 to 2013, whose recording of data was judged by the CPRD to be up to standard (UTS) (MHRA, 2014), and for whom the Index of Multiple Deprivation (IMD) deprivation score (for the practice address) was available, thereby excluding practices outside England. Only general practices continuously in the CPRD and UTS for the whole of the ten year period were included, to provide a relatively stable denominator for calculating rates of recording of depression. The available routinely collected anonymised GP consultation data included clinical events (symptoms and diagnoses), therapy events (prescriptions), and referral events (including mental health and other referrals).

Eligibility for inclusion

The inclusion criteria were all patients who between 1st April 2003 and 31st March 2013 had clinical or referral events recorded which included a Read code for non-psychotic depressive symptoms or diagnoses, or for assessment using depression symptom questionnaires. We excluded patients with psychotic diagnoses including bipolar disorder, psychotic depression, and schizoaffective psychosis, and patients prescribed antidepressants for other indications besides depression. The 179 Read codes we used as inclusion criteria were classified by us into four categories: diagnoses (n = 88); symptoms (40); questionnaire assessments (36); and others (15). (See Web Appendix for the list of Read codes used, and our classification.)

Anonymised data were obtained from the start of the patient’s registration with the practice, which in most cases predated the 10-year period during which they had to be labelled with a depression Read code to be included in the study. In addition to clinical, therapy, and referral events, the dataset included patients’ dates of birth, gender, marital status, family size, GP practice code (also anonymised), NHS Region, and IMD score for the practice address.

Analysis

We used patient years at risk (PYAR) as the denominator to calculate the level of recording of depression, so someone who was registered in the CPRD for only one quarter of the year would contribute 0.25 years to the denominator. In order to be able to identify significant changes in the annual incidence or prevalence of depression, we calculated a minimum sample size which would be sufficient to estimate a rate of approximately 5 per 1000 PYAR with a 95% confidence interval of plus or minus 0.5 per 1000 PYAR. This required a sample of 19,112 patients per year, i.e. a total of at least 191,120 for the ten year period.

Rates per 1000 PYAR of recorded depression, defined in terms of the presence of the inclusion criteria Read codes, were calculated for each of the 10 years, and for each of the 40 quarters, of our study period, together with 95% confidence intervals. We identified three different numerators:

(i) prevalence of depression: which included all inclusion criteria Read codes recorded in the patients’ clinical or referral events file during the year, or quarter;

(ii) rate of new episodes of depression: a sub-set of the total recorded codes, limited to those patients who had no previous depression codes recorded within the previous four quarters;

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(iii) incidence of first-ever depression: a sub-set of the total recorded codes, limited to those patients who had no previous codes for depression diagnoses, symptoms or antidepressant treatment recorded within the 10 year study period, and no previous record of depression or antidepressant treatment recorded in their past history prior to April 2003. (We were unable to determine whether patients had had previous unrecorded depression, as the data were anonymised and so we could not ask the patient or their GP about any previous unrecorded episodes prior to their registration with a CPRD practice).

We analysed changes over time in the quarterly prevalence and incidence of first-ever depression codes for the total cohort, and broken down by gender; by age group (adolescent 16-17 years, younger working age 18-29, older working age 30-64, and retired 65 years and over); and by quintile of IMD deprivation score. We also subdivided new episodes of depression into those which had one or more diagnostic category codes which qualified patients for inclusion in the denominator for the QOF performance indicators, and those which had other depression codes (usually symptom only codes) which did not qualify patients for inclusion in the QOF.

We conducted time trend analyses to determine whether significant changes in the quarterly rates of GP recording of depression codes (for both prevalence and incidence of first-ever depression) were found following the economic recession from April 2008; and whether the rates correlated with subsequent unemployment rates from the Office of National Statistics (2014). We also analysed whether significant changes in the types of coding (QOF-qualifying versus non-QOF-qualifying codes) were found for new episodes of depression following the introduction of QOF indicators for the assessment of depression with severity questionnaires at diagnosis from April 2006. Quarterly time periods were chosen for the time series analyses because yearly periods would have given too few time periods to look at changes either side of the events in 2006 and 2008. We took into account seasonality as well as the underlying trend, as rates of depression are known to vary with the seasons of the year.

Data were analysed as an interrupted time series using segmented regression (Wagner et al, 2002). This divided the time series into two periods, before and after the event of interest, and tested whether there was a significant step change, or change in the slope of the line following the event. Our regression model was: Υt = β0 + β1 x timet + β2 x eventt + β3 x time after eventt + et where: β0 = the level of depression at the start of the observation period in 2003, β1 = the secular trend in level of depression, β2 = the change in the level of depression in the quarter of the event, β3 = the change in trend after the event, and et = the error term, which included an allowance for autocorrelation. We tested for autocorrelation using the Durbin-Watson statistic (Durbin and Watson, 1971) which indicated it was present, so the regression model was fitted using the Stata ‘prais’ command to fit a Cochrane-Orcutt transformation and control for seasonal effects.

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Results

The dataset included 142 practices, at which a total of 2,326,673 patients had been registered at some point during the study period April 2003 to March 2013 inclusive. Compared to national practice data (Health & Social Care Information Centre, 2011), participating practices were broadly representative in terms of age and gender profiles and levels of deprivation, but larger than the average for England and not representative regionally, being significantly over-represented in the North-West, and significantly under-represented in the North-East, Yorkshire and Humber, and East Midlands regions.

Prevalence of depression codes, and incidence of first-ever depression codes

A total of 293,596 registered patients (12.6%) had received at least one non-psychotic depression Read code during the 10 year study period. Annual prevalence of depression codes fell from 44.6 (95% CI 44.2, 45.0) per 1000 person years at risk (PYAR) in 2003/2004 to 38.0 (37.7, 38.3) in 2008/2009, rising to 39.5 (39.2, 39.9) in 2012/2013. Annual incidence of first-ever depression codes fell from 11.9 (95% CI 11.7, 12.1) per 1000 PYAR in 2003/2004 to 9.5 (9.3, 9.7) in 2008/2009, rising to 10.0 (9.8, 10.2) in 2012/1203. Annual rate of new episodes in patients with no record of depression in the preceding four quarters fell from 29.4 (95% CI 29.1, 29.7) per 1000 PYAR in 2004/2005 to 26.8 (26.5, 27.1) per 1000 PYAR in 2008/2009, rising to 29.2 (28.9, 29.5) in 2012/2013.

Figure 1 shows the quarterly prevalence of depression codes, and incidence of first-ever codes, per 1000 person quarters at risk (PQAR), over the 10 year study period (see Web Table 1 for detailed figures). We tested the hypothesis that the economic recession from April 2008 may have changed the trajectory of the prevalence of depression codes, and the incidence of first-ever depression codes, using time series analysis, also shown in Figure 1. Rates of prevalence and incidence showed a similar pattern. The trend prior to quarter 2 of 2008 was a statistically significant decline in both prevalence and incidence rates, but from that date, there was a significant change in the slope of the trend for prevalence (p<0.001), which was not significant for incidence (p= 0.074). There was no evidence of a significant step change but levels of both prevalence and incidence flattened out after April 2008 and the slopes were no longer significantly different from zero.

Quarterly prevalence of depression codes by gender

Figure 2 shows quarterly prevalence rates for depression codes per 1000 PQAR, by gender (see Web Table 2 for detailed figures). The interrupted time series models for both genders (Figure 2) showed a similar pattern as that for the total cohort prior to quarter 2 of 2008: levels of both prevalence and incidence of first-ever depression codes were declining. Following that time point, for prevalence in females the slope flattened and was not significantly different from zero. However for males the analysis showed a significant increase in the prevalence of depression codes. There were no significant changes to the slopes of the lines for incidence of first-ever depression codes for either gender (not shown).

Quarterly prevalence of depression codes by age group

Figure 3 shows the quarterly prevalence of depression codes and incidence of first-ever depression codes by age group (see Web Table 3 for details). Figure 3 also shows the interrupted time series models by age groups. The prevalence of depression codes, and incidence of first-ever depression

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codes, were falling prior to quarter 2 of 2008 in all age groups, except for the incidence of first-ever depression codes in 16-17 year olds. From that point onwards, there was a significant change in trend for the prevalence of depression codes in all age groups: the trajectory flattened, becoming not significantly different from zero. Changes in the incidence of first-ever depression codes varied between age groups, with 18-29 year olds showing a significant rise after Q2 2008, while the trend for 30-64 year olds flattened out, and trends for the 16-17 year olds, and 65 and over, age groups remained unchanged throughout.

Correlation with the unemployment rate

Figure 4 shows comparisons between levels of unemployment (Office of National Statistics, 2014) and the prevalence of depression codes for males and females respectively. There was an apparent increase in the unemployment rate after quarter 2 of 2008, which appeared to coincide with changes in trajectory for the prevalence of depression codes in both males and females. In the period prior to quarter 2 of 2008, there was a negative correlation between overall prevalence and unemployment (Figure 4). However after quarter 2 of 2008, the correlation was moderately positive and statistically significant. The relationship for males was very similar to the overall cohort, but for females there was no significant correlation after quarter 2 of 2008.

Relationship between changing prevalence of depression codes and levels of deprivation

Figure 5 shows the prevalence of depression codes by quintile of practice IMD deprivation score. Prevalence remained lowest in the practices in the most affluent IMD quintile throughout the period and highest in the least affluent quintile. Rates in the other three quintiles crossed over one another over the 10 year period. Prevalence rates in all five quintiles seemed to show a similar trend over time. Prior to Q2 2008, rates were falling and after this point there was a statistically significant change (Figure 5). The trajectory flattened and was not significantly different from zero in quintiles 1 to 4. However, in the least affluent quintile 5, the prevalence rate began to rise significantly.

Use of QOF-qualifying and non-QOF qualifying Read codes to label depression

Figure 6 shows the sub-division of the codes for new episodes of depression into those labelled by Read diagnostic category codes which qualified patients for inclusion in the denominator for the QOF performance indicators, and those with only non-qualifying Read symptom codes or other depression codes. It is apparent that prior to quarter 2 of 2006, when the QOF indicators were introduced, the use of QOF-qualifying diagnostic category labels was already declining, but this decline was accelerated by a step change following that event, such that the majority of new episodes were coded with non-QOF-qualifying codes. From April 2006 onwards there was a significant increase in the trajectory for non-QOF-qualifying codes, while the trajectory for QOF-qualifying codes remained flat, so that over time an increasing proportion of new episodes were coded with non-QOF qualifying codes.

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Discussion

Main findings

Prevalence rates of recorded Read codes for depression in English general practices contributing to the CPRD were falling prior to the economic downturn of 2008 but increased again after that, at least in younger working age adults. The increase after April 2008 was not statistically significant in women but was in men, among whom it correlated significantly with rising male unemployment nationally. The rise in prevalence from April 2008 was statistically significant only for the most socio-economically deprived quintile of practices according to practice address IMD score, but there were significant changes in trend for prevalence across the other four IMD quintiles, flattening out from a downward trend prior to the recession.

GPs appeared to respond to the introduction of the QOF in April 2006 by using relatively fewer diagnostic category codes and more symptom and other codes to record new episodes of depression over time, thereby putting relatively few patients into the denominator for assessing their performance in measuring the severity of depression with symptom questionnaires. Although prior to April 2006 GPs were already using fewer diagnostic category codes year on year, and tending to use more symptom codes instead, there was a step change from April 2006 which meant that in the event the majority of patients with new episodes of depressive symptoms were not actually included in the denominator for the QOF.

Strengths of the study

The large sample size of nearly 300,000 patients with depression was sufficient to allow the estimation of relatively precise incidence and prevalence rates for depression codes as well as calculation of the significance of changes in rates over the 40 quarters through the time series analyses. The inclusion of records of all patients registered in the practices means the study was not subject to recruitment bias, unlike studies which rely on patients attending the practice and volunteering to be screened.

Limitations

The participating practices, while broadly representative of all practices in England in terms of age and gender and deprivation profiles, were larger than average, and not representative in terms of distribution across the regions. This is a recognised limitation of the CPRD, which is not based on a random sample of practices but includes only those that have contracted to use the Vision computer system (Copyright © In Practice Systems Ltd) and provide anonymised data to the database (Campbell et al, 2013). This may have limited our analysis of associations between prevalence of depression and unemployment, which was based on national unemployment rates, rather than regional rates.

Routinely collected medical record data may over- or under-represent the true level of depression in patients, as GP diagnoses made in relatively brief consultations are unlikely to accord entirely with diagnoses made through longer interviews using specific diagnostic criteria. Patients and practices remained strictly anonymous, which meant we were unable to interview patients or GPs to explore the accuracy of recording of diagnoses and symptoms, or the possible reasons for the changes in rates found over time.

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We may have overestimated the incidence of first-ever cases of depression because patients may have had previous episodes of depression prior to registering with the CPRD practices, and past episodes may not always be recorded at registration.

Comparison with other studies

The prevalence rates we found of around 80 per 1000 PYAR in women and 35 in men in 2004 are somewhat lower than the rates found in the THIN database in 2004 of around 100 per 1000 PYAR in women and around 50 in men (Morgan et al, 2008), which may be due to differences in patient populations between practices contributing to the two studies, or differences in the number and type of Read codes used as inclusion criteria. The prevalence rates are considerably lower than the rates found in 25 UK practices in 2004-2005, for major depression according to DSM-IV criteria at diagnostic interview following screening, of 13.2% in women and 12.7% in men (King et al, 2008). However, the patients screened in King et al’s (2008) study were a relatively small sample of practice attenders who volunteered to be screened, and may not have been representative, being more likely to be depressed than registered patients who did not attend the participating practices during the study period.

It is likely nevertheless that GPs either fail to diagnose a proportion of cases of depression, or fail to record a proportion of their diagnoses. There is evidence that relying on diagnostic codes alone underestimates GP recognition of depression, as GPs sometimes record symptoms only in the free text part of the record, and sometimes record only antidepressant prescriptions and not the diagnoses associated with the prescriptions (Joling et al, 2011). In this study we did include symptom codes as well as diagnostic codes, but we did not analyse free text entries as these are not available from the CPRD, due to the threat that uncoded entries pose to patient and practice confidentiality. We did not count antidepressant prescriptions as evidence of GP recognition in the absence of depression diagnosis or symptom codes, because antidepressants are often used for other indications besides depression. Diagnoses of depression may be perceived as stigmatising, and can affect patients’ chances of obtaining insurance or employment, which, along with an understandable wariness of ‘medicalising unhappiness’ (Dowrick and Francis, 2013), may have led GPs to use diagnostic codes more sparingly.

We found annual rates of around 26 to 29 per 1000 PYAR for new episodes in patients with no depression in the previous year, which are remarkably close to the rate of 29 per 1000 PYAR found in the THIN database (Rait et al, 2009), despite differences in the patient samples between the two studies, which is likely to be due to our inclusion of symptom codes as well as diagnostic codes, as Rait and colleagues recommended. The annual rates we found for first-ever recorded depression, of around 9 to 11 per 1000 PYAR, are broadly consistent with the rates we found previously in the GPRD in 2005 of around 10 per 1000 PYAR in women and 6 per 1000 PYAR in men (Moore et al, 2009). The previous GPRD sample included practices outside England and is not directly comparable to the present CPRD sample. Also more symptom codes were added to the inclusion criteria for the present study than we used in the GPRD study, which may explain the slightly higher incidence rate in this study. It was not possible to determine the degree to which the two samples overlapped due to the requirement to maintain practice and patient anonymity. The decline in incidence of first-ever recorded depression we found from 2003 to 2008 in this study is also consistent with the decline we found in the GPRD study from 2001 to 2005 (Moore et al, 2009).

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The relationship of changes in prevalence to the economic recession are consistent with studies of suicide which have shown increases following the onset of the recession in England as in other western countries, and have also been found to be associated with rising unemployment rates, particularly in men (Barr et al, 2012; Chang et al, 2013).

The change in GP use of Read codes, away from diagnostic category codes and towards symptom codes through the course of our 10 year study period, is consistent with the changes in the types of codes that were found in the THIN database from 1996 to 2006 (Rait et al, 2009), suggesting that the advent of the QOF was not the only reason for the change, although it appears from our data to have accelerated it. It is possible that GPs were already moving away from using diagnostic codes because of the potential negative implications for patients, increasing recognition that the presence of depression symptoms does not automatically qualify patients for formal diagnoses, and increasing recognition that their diagnoses may be inaccurate when compared with psychiatrists’.

Implications for clinicians and policymakers

We found that the economic recession was followed by an increase in the prevalence of depressive diagnoses and symptoms in English primary care, consistent with previous findings for suicide (Barr et al, 2012; Coope et al, 2014). The rise in first–ever depression was seen in younger adults, presumably because the onset of depression is mainly in young adulthood, while the effect in older people was seen more in the prevalence rate, presumably because episodes in older people were more likely to be recurrences rather than first-onset episodes. Chang et al (2013) found increases in suicide related to the recession were highest among men aged 15-24 in Europe, while in American countries men aged 45-64 showed the largest increase. Coope et al (2014) found no clear evidence of an association between trends in female suicide rates and indicators of economic recession, but described a halt in the downward trend in suicide rates among men aged 16-34 years, beginning before the recession, while among men aged 35-44 years increased suicide rates mirrored recession-related unemployment. They suggested increased debt and house repossessions might contribute to suicides in younger adulthood while unemployment was more important in the older age range (Coope et al, 2014). However youth unemployment, particularly in men, was a feature of the 2008 economic recession (Bell & Blanchflower, 2011), and given the association we found with the national unemployment rate in men, and the associations found by Barr et al (2012) between regional unemployment and suicide rates, we agree with Barr and colleagues that policies to promote re-employment should be pursued, targeting the most socio-economically deprived areas.

The shift away from recording diagnostic codes could be perceived as ‘gaming’ as it meant that the QOF requirement to use symptom questionnaires to assess severity was bypassed for the majority of patients with new episodes of symptoms of depression. Our findings are consistent with qualitative studies which found that some GPs reported altering their coding in order to remove the need to assess patients with depression severity questionnaires (Dowrick et al, 2009; Mitchell et al, 2011). Some GPs considered their clinical judgment more important than scores on questionnaires, and were concerned that questionnaires reduced the human element of the consultation and were a threat to the GP’s professionalism (Dowrick et al, 2009; Leydon et al, 2011). However, qualitative research has shown that there are additional factors which influence coding decisions, including avoiding stigmatisation and the medicalisation of psychological distress (Mitchell et al, 2011). Mild depression may not be coded using diagnostic codes as GPs are not intending to prescribe

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antidepressants, in line with guideline recommendations, whereas in more severe cases the decision to prescribe might be backed up by the use of a diagnostic code (Mitchell et al, 2011).

The upturn in rates of depression in younger men in England since the recession is likely to have contributed at least in part to the year on year rise in antidepressant prescribing, the trajectory of which increased from 2008 onwards (Health & Social Care Information Centre, 2014). However, prescriptions increased by around 50% between 2008 and 2012 (Spence et al, 2014) which cannot be explained by the 10% or so rise in prevalence of depression in this study. It is likely that the continuing increase is due in large part to more longer-term prescribing year on year (Moore et al, 2009), and we are proceeding to analyse changes in the length of antidepressant treatment in this sample to see if this was so up until 2013. The attention of clinicians and policymakers needs to shift away from the initial decision to prescribe antidepressants, towards examining the appropriateness of longer-term prescribing and whether patients on long-term medication should be reviewed with a view to discontinuation.

Implications for further research

Researchers need to be aware that GP coding of depression has varied over time. More symptom codes and relatively fewer diagnostic codes have been used, so studies of routinely collected data need to include symptom and other codes to include all patients presenting with depressive symptoms.

The year on year increase in antidepressant prescribing does not seem to be fully explained by an increased incidence or prevalence of depression. Further research is needed to explore whether it is explained by longer courses of treatment over time.

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Figure 1: Quarterly prevalence of depression codes, and incidence of first-ever depression codes, per 1000 person quarters at risk 2003-2013, with time series analysis of changes from quarter 2 2008

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prevalence of depression codes incidence of first-ever depression codes

Prevalence of depression codes Coefficient (95% CI) SignificanceSecular trend -0.14 (-0.20, -0.08) P<0.001Change in level in Q2 2008 0.28 (-0.49, 1.05) P=0.468Change in trend after Q2 2008 0.18 (0.09, 0.26) P<0.001Trend after Q2 2008 0.03 (-0.02, 0.08) P=0.205Incidence of first ever depression codes

Coefficient (95% CI) Significance

Secular trend -0.03 (-0.05, -0.002) P=0.034Change in level in Q2 2008 0.03 (-0.27, 0.32) P=0.851Change in trend after Q2 2008 0.03 (-0.003, 0.06) P=0.074Trend after Q2 2008 0.004 (-0.02, 0.02) P=0.675

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Figure 2: Quarterly prevalence of depression codes per 1000 person years at risk, by gender, and time series analysis of changes after quarter 2 of 2008

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males females

Prevalence of codes – females Coefficient (95% CI) SignificanceSecular trend -0.20 (-0.29, -0.11) P=0.001Change in level in Q2 2008 0.46 (-0.67, 1.59) P=0.414Change in trend after Q2 2008 0.20 (0.07, 0.32) P=0.003Trend after Q2 2008 -0.004 (-0.08, 0.07) P=0.904Prevalence of codes – malesSecular trend -0.09 (-0.12, -0.05) P<0.001Change in level in Q2 2008 0.07 (-0.41, 0.54) P=0.782Change in trend after Q2 2008 0.15 (0.10, 0.20) P<0.001Trend after Q2 2008 0.07 (0.04, 0.10) P<0.001

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Figure 3: Quarterly prevalence of depression codes, and incidence of first-ever depression codes per 1000 person quarters at risk, by age group, with time series analysis of changes after quarter 2 of 2008

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16-17 years 18-29 years

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Prevalence of depression codes - 16-17 year olds

Coefficient (95% CI) Significance

Secular trend -0.14 (-0.27, 0.004) P=0.056Change in level in Q2 2008 -0.35 (-2.00, 1.31) P=0.672Change in trend after Q2 2008 0.24 (0.05, 0.44) P=0.016Trend after Q2 2008 0.11 (-0.01, 0.22) P=0.065Prevalence of depression codes - 18-29 year oldsSecular trend -0.25 (-0.33, -0.17) P<0.001Change in level in Q2 2008 1.17 (0.06, 2.30) P=0.040Change in trend after Q2 2008 0.31 (0.21, 0.42) P<0.001Trend after Q2 2008 0.06 (-0.01, 0.13) P=0.073Prevalence of depression codes - 30-64 year oldsSecular trend -0.18 (-0.26, -0.10) P<0.001Change in level in Q2 2008 0.45 (-0.61, 1.51) P=0.398Change in trend after Q2 2008 0.25 (0.13, 0.36) P<0.001Trend after Q2 2008 0.06 (-0.01, 0.13) P=0.072Prevalence of depression codes - 65 years and overSecular trend -0.09 (-0.12, -0.05) P<0.001Change in level in Q2 2008 -0.57 (-1.09, -0.06) P=0.031Change in trend after Q2 2008 0.07 (0.02, 0.11) P=0.009Trend after Q2 2008 -0.02 (-0.05, 0.01) P=0.171Incidence of first ever codes -16-17 year olds

Coefficient (95% CI) Significance

Secular trend 0.02 (-0.04, 0.08) 0.512Change in level in Q2 2008 -0.15 (-1.05, 0.75) 0.739Change in trend after Q2 2008 0.07 (-0.01, 0.15) 0.101Trend after Q2 2008 0.09 (0.03, 0.14) 0.003Incidence of first ever codes -18-29 year oldsSecular trend -0.05 (-0.08, -0.01) P=0.009Change in level in Q2 2008 0.36 (-0.12, 0.85) P=0.135Change in trend after Q2 2008 0.08 (0.03, 0.13) P=0.002Trend after Q2 2008 0.03 (0.004, 0.06) P=0.029Incidence of first ever codes -30-64 year oldsSecular trend -0.03 (-0.06, -0.01) P=0.009Change in level in Q2 2008 0.01 (-0.30, 0.32) P=0.955Change in trend after Q2 2008 0.03 (-0.001, 0.07) P=0.060Trend after Q2 2008 -0.001 (-0.02, 0.02) P=0.922Incidence of first ever codes -65 years and overSecular trend -0.02 (-0.06, 0.02) P=0.302Change in level in Q2 2008 -0.13 (-0.59, 0.34) P=0.581Change in trend after Q2 2008 0.001 (-0.05, 0.05) P=0.984Trend after Q2 2008 -0.02 (-0.05, 0.01) P=0.225

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Figure 4: Comparison between percentage level of unemployment and prevalence of depression codes per 1000 person quarters at risk, for males and for females

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prevalence of depression codes per 1000 person quarters - males % unemployment - males

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prevalence of depression codes per 1000 person quarters - females % unemployment - females

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Prevalence of depression codes

Pre-quarter 2 of 2008Pearson's rho (significance)

Post-quarter 2 of 2008Pearson’s rho (significance)

Total cohort -0.48 (p=0.0342) 0.68 (p=0.0009)Males -0.29 (p=0.2164) 0.59 (p=0.0063)Females -0.59 (p=0.0057) 0.40 (p=0.0795)

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Figure 5: Prevalence of depression codes per 1000 person quarters at risk, by Index of Multiple Deprivation ranking (quintiles 1 to 5: quintile 1 is least deprived), and time series analysis of changes after quarter 2 of 2008

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IMD quintile 1 IMD quintile 2

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Prevalence of depression codes – IMD 1 Coefficient (95% CI) SignificanceSecular trend -0.18 (-0.22, -0.14) P<0.0001Change in level in Q2 2008 0.32 (-0.31, 0.95) P=0.310Change in trend after Q2 2008 0.20 (0.14, 0.26) P<0.0001Trend after Q2 2008 0.02 (-0.02, 0.06) P=0.398Prevalence of depression codes – IMD 2Secular trend -0.12 (-0.21, -0.04) P=0.005Change in level in Q2 2008 0.13 (-0.77, 1.03) P=0.775Change in trend after Q2 2008 0.15 (0.03, 0.26) P=0.016Trend after Q2 2008 0.02 (-0.04, 0.09) P=0.472Prevalence of depression codes – IMD 3Secular trend -0.14 (-0.22, -0.06) P=0.002Change in level in Q2 2008 0.39 (-0.65, 1.43) P=0.448Change in trend after Q2 2008 0.17 (0.05, 0.28) P=0.005Trend after Q2 2008 0.03 (-0.04, 0.10) P=0.369Prevalence of depression codes – IMD 4Secular trend -0.12 (-0.20, -0.03) P=0.007Change in level in Q2 2008 -0.33 (-1.44, 0.77) P=0.542Change in trend after Q2 2008 0.12 (0.01, 0.23) P=0.036Trend after Q2 2008 0.01 (-0.06, 0.08) P=0.864Prevalence of depression codes – IMD 5Secular trend -0.15 (-0.22, -0.09) P<0.0001Change in level in Q2 2008 0.75 (-0.13, 1.63) P=0.092Change in trend after Q2 2008 0.23 (0.14, 0.32) P<0.0001Trend after Q2 2008 0.07 (0.02, 0.13) P=0.012

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Figure 6: Levels of QOF-qualifying and non-QOF qualifying Read codes used to record new episodes of depression, and time series analysis of changes after quarter 2 of 2006

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QOF qualifying codes Non- QOF qualifying codes

Rates of new episodes of depression: QOF qualifying codes

Coefficient (95% CI) Significance

Secular trend -0.06 (-0.11, -0.01) P=0.013Change in level in Q2 2006 -0.39 (-0.70, -0.09) P=0.013Change in trend after Q2 2006 0.05 (0.002, 0.10) P=0.042Trend after Q2 2006 -0.01 (-0.02, 0.001) P=0.080Rates of new episodes of depression: non-QOF qualifying codes

Coefficient (95% CI) p-value

Secular trend 0.01 (-0.04, 0.06) P=0.733Change in level in Q2 2006 0.34 (0.03, 0.64) P=0.030Change in trend after Q2 2006 0.02 (-0.03, 0.07) P=0.327Trend after Q2 2006 0.03 (0.02, 0.04) P<0.0001

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WEB TABLES

Prevalence of codes per 1000 PQAR (95% C.I.)

First-ever incidence of codes per 1000 PQAR (95% C.I.)

Q2 2003 14.62 (14.39,14.81) 2.74 (2.64,2.83)Q3 2003 14.71 (14.54,14.97) 2.88 (2.79,2.98)Q4 2003 15.10 (14.85,15.28) 2.97 (2.87,3.06)Q1 2004 16.50 (16.23,16.68) 3.27 (3.15,3.36)Q2 2004 14.42 (14.21,14.63) 2.67 (2.57,2.75)Q3 2004 14.39 (14.14,14.56) 2.67 (2.58,2.76)Q4 2004 14.14 (13.95,14.37) 2.71 (2.63,2.81)Q1 2005 14.52 (14.29,14.71) 2.55 (2.46,2.64)Q2 2005 14.07 (13.80,14.22) 2.57 (2.48,2.66)Q3 2005 13.70 (13.53,13.93) 2.49 (2.39,2.57)Q4 2005 13.54 (13.31,13.71) 2.35 (2.26,2.43)Q1 2006 14.91 (14.64,15.07) 2.68 (2.59,2.77)Q2 2006 12.51 (12.35,12.74) 2.32 (2.24,2.41)Q3 2006 12.92 (12.72,13.12) 2.50 (2.40,2.58)Q4 2006 13.67 (13.42,13.83) 2.75 (2.66,2.85)Q1 2007 14.76 (14.60,15.02) 3.23 (3.12,3.32)Q2 2007 13.06 (12.85,13.25) 2.57 (2.48,2.66)Q3 2007 12.95 (12.72,13.11) 2.43 (2.35,2.53)Q4 2007 12.59 (12.41,12.79) 2.37 (2.27,2.44)Q1 2008 13.05 (12.86,13.25) 2.47 (2.40,2.57)Q2 2008 12.01 (11.85,12.23) 2.20 (2.11,2.28)Q3 2008 12.17 (11.99,12.37) 2.20 (2.12,2.29)Q4 2008 12.61 (12.38,12.76) 2.41 (2.33,2.50)Q1 2009 13.81 (13.64,14.05) 2.67 (2.58,2.76)Q2 2009 12.97 (12.78,13.17) 2.46 (2.36,2.54)Q3 2009 12.93 (12.73,13.11) 2.41 (2.33,2.50)Q4 2009 13.25 (13.09,13.48) 2.61 (2.51,2.68)Q1 2010 14.35 (14.14,14.55) 2.75 (2.66,2.85)Q2 2010 13.80 (13.56,13.96) 2.57 (2.48,2.65)Q3 2010 13.75 (13.60,13.99) 2.47 (2.39,2.56)Q4 2010 13.19 (12.98,13.36) 2.38 (2.30,2.47)Q1 2011 14.35 (14.17,14.57) 2.70 (2.60,2.78)Q2 2011 13.18 (12.98,13.37) 2.41 (2.32,2.50)Q3 2011 13.04 (12.81,13.19) 2.34 (2.25,2.42)Q4 2011 13.38 (13.19,13.58) 2.53 (2.44,2.62)Q1 2012 14.45 (14.26,14.66) 2.81 (2.71,2.89)Q2 2012 13.31 (13.07,13.45) 2.51 (2.42,2.60)Q3 2012 13.27 (13.12,13.50) 2.37 (2.28,2.45)Q4 2012 13.51 (13.29,13.67) 2.62 (2.53,2.71)Q1 2013 13.60 (13.41,13.80) 2.57 (2.49,2.67)

Web table 1 Quarterly prevalence of depression codes, and incidence of first-ever depression codes, per 1000 person quarters at risk (PQAR)

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Web table 2 Quarterly prevalence of depression codes, and incidence of first-ever depression codes, per 1000 person quarters at risk (PQAR), by gender

Prevalence of codes per 1000 PQAR(95% C.I.)

First-ever codes per 1000 PQAR(95% C.I.)

Males Females Males FemalesQ2 2003 8.82 (8.58,9.05) 20.33 (19.93,20.64) 2.06 (1.95,2.18) 3.41 (3.25,3.55)Q3 2003 9.03 (8.75,9.23) 20.29 (19.81,20.51) 2.18 (2.05,2.28) 3.58 (3.45,3.75)Q4 2003 9.19 (8.94,9.42) 20.91 (20.49,21.20) 2.15 (2.02,2.25) 3.77 (3.64,3.95)Q1 2004 9.95 (9.77,10.28) 22.95 (22.69,23.45) 2.46 (2.33,2.58) 4.07 (3.88,4.20)Q2 2004 8.61 (8.31,8.78) 20.14 (19.94,20.65) 1.90 (1.79,2.01) 3.43 (3.26,3.55)Q3 2004 8.77 (8.60,9.07) 19.93 (19.68,20.38) 1.94 (1.83,2.05) 3.38 (3.25,3.55)Q4 2004 8.63 (8.33,8.79) 19.57 (19.07,19.76) 2.00 (1.89,2.11) 3.42 (3.29,3.59)Q1 2005 8.91 (8.75,9.23) 20.03 (19.81,20.52) 1.94 (1.82,2.04) 3.16 (3.02,3.31)Q2 2005 8.32 (8.14,8.60) 19.74 (19.45,20.15) 1.81 (1.72,1.94) 3.32 (3.16,3.45)Q3 2005 8.28 (8.07,8.53) 19.04 (18.73,19.41) 1.91 (1.81,2.03) 3.06 (2.95,3.23)Q4 2005 8.26 (8.09,8.55) 18.74 (18.51,19.19) 1.71 (1.62,1.83) 2.98 (2.83,3.10)Q1 2006 9.06 (8.87,9.35) 20.67 (20.40,21.12) 2.00 (1.90,2.12) 3.37 (3.25,3.54)Q2 2006 7.37 (7.19,7.61) 17.58 (17.28,17.93) 1.74 (1.64,1.85) 2.91 (2.78,3.05)Q3 2006 8.06 (7.85,8.29) 17.69 (17.37,18.01) 1.87 (1.76,1.97) 3.13 (2.98,3.26)Q4 2006 8.64 (8.46,8.92) 18.62 (18.38,19.04) 2.21 (2.09,2.33) 3.30 (3.16,3.44)Q1 2007 9.27 (9.07,9.55) 20.17 (19.87,20.56) 2.64 (2.51,2.76) 3.81 (3.64,3.95)Q2 2007 7.81 (7.59,8.02) 18.23 (17.88,18.54) 1.93 (1.83,2.05) 3.21 (3.10,3.38)Q3 2007 7.81 (7.57,8.00) 18.02 (17.64,18.28) 1.84 (1.74,1.95) 3.02 (2.90,3.17)Q4 2007 7.68 (7.48,7.91) 17.41 (17.10,17.74) 1.79 (1.70,1.91) 2.95 (2.83,3.10)Q1 2008 7.98 (7.69,8.13) 18.04 (17.57,18.22) 1.87 (1.76,1.97) 3.08 (2.93,3.20)Q2 2008 7.28 (7.02,7.44) 16.66 (16.26,16.89) 1.65 (1.55,1.75) 2.75 (2.61,2.87)Q3 2008 7.40 (7.14,7.55) 16.85 (16.43,17.05) 1.61 (1.50,1.70) 2.80 (2.65,2.90)Q4 2008 7.66 (7.42,7.84) 17.48 (17.11,17.74) 1.85 (1.74,1.95) 2.97 (2.82,3.09)Q1 2009 8.56 (8.28,8.73) 18.97 (18.53,19.20) 2.06 (1.94,2.16) 3.27 (3.16,3.45)Q2 2009 8.03 (7.88,8.32) 17.81 (17.37,18.01) 1.96 (1.87,2.09) 2.95 (2.83,3.10)Q3 2009 8.01 (7.84,8.28) 17.77 (17.32,17.95) 1.87 (1.77,1.98) 2.95 (2.82,3.08)Q4 2009 8.33 (8.06,8.50) 18.07 (17.68,18.32) 2.07 (1.97,2.19) 3.15 (3.02,3.29)Q1 2010 9.03 (8.87,9.33) 19.56 (19.09,19.76) 2.13 (2.02,2.25) 3.38 (3.23,3.52)Q2 2010 8.42 (8.23,8.68) 19.07 (18.87,19.54) 1.96 (1.85,2.07) 3.19 (3.03,3.31)Q3 2010 8.77 (8.56,9.00) 18.63 (18.41,19.06) 2.02 (1.90,2.12) 2.93 (2.81,3.08)Q4 2010 8.30 (8.11,8.54) 17.98 (17.55,18.18) 1.90 (1.78,2.00) 2.87 (2.72,2.98)Q1 2011 9.11 (8.86,9.32) 19.46 (19.23,19.90) 2.20 (2.1,2.33) 3.19 (3.07,3.35)Q2 2011 8.26 (8.01,8.44) 17.98 (17.73,18.36) 1.85 (1.75,1.96) 2.96 (2.83,3.10)Q3 2011 8.29 (8.13,8.57) 17.66 (17.39,18.01) 1.93 (1.82,2.04) 2.74 (2.61,2.86)Q4 2011 8.69 (8.42,8.86) 17.94 (17.73,18.37) 2.06 (1.95,2.17) 3.01 (2.87,3.14)Q1 2012 9.55 (9.35,9.82) 19.21 (18.86,19.51) 2.32 (2.22,2.46) 3.29 (3.17,3.45)Q2 2012 8.66 (8.50,8.94) 17.84 (17.56,18.19) 2.09 (1.96,2.18) 2.93 (2.77,3.04)Q3 2012 8.92 (8.74,9.19) 17.50 (17.21,17.83) 2.06 (1.96,2.18) 2.68 (2.57,2.82)Q4 2012 9.14 (8.85,9.30) 17.76 (17.51,18.14) 2.22 (2.12,2.35) 3.02 (2.91,3.18)Q1 2013 9.39 (9.19,9.65) 17.70 (17.36,17.98) 2.19 (2.08,2.31) 2.96 (2.83,3.10)

Web table 3 Quarterly prevalence of depression codes, and incidence of first-ever depression codes, per 1000 person quarters at risk (PQAR), by age group

24

Prevalence of codes per 1000 PQAR (95% CI) First-ever codes per 1000 PQAR (95% CI)16-17 18-29 30-64 65+ 16-17 18-29 30-64 65+

Q2 2003 9.43

(8.26,10.65)

21.12 (20.42,21.83)

19.15 (18.8,19.50)

12.03 (11.56,12.51)

3.33 (2.66,4.08)

5.62 (5.26,5.99)

2.99 (2.85,3.13)

2.26 (2.06,2.47)

Q3 2003 9.02

(7.89,10.21)

21.97 (21.26,22.69)

19.34 (18.99,19.69)

11.31 (10.86,11.77)

3.88 (3.16,4.68)

5.90 (5.53,6.28)

3.05 (2.91,3.19)

2.63 (2.42,2.86)

Q4 2003 10.37

(9.17,11.64)

22.16 (21.44,22.88)

20.10 (19.74,20.45)

11.04 (10.59,11.49)

4.08 (3.34,4.89)

5.81 (5.45,6.19)

3.27 (3.12,3.41)

2.40 (2.19,2.61)

Q1 2004 13.81

(12.42,15.27)

25.27 (24.51,26.05)

21.68 (21.31,22.05)

11.60 (11.14,12.07)

5.42 (4.56,6.36)

6.59 (6.20,7.00)

3.62 (3.47,3.77)

2.29 (2.08,2.50)

Q2 2004 9.58

(8.42,10.80)

21.27 (20.57,21.98)

19.09 (18.74,19.43)

10.94 (10.5,11.39)

3.44 (2.76,4.19)

5.55 (5.19,5.91)

2.97 (2.83,3.11)

1.95 (1.77,2.15)

Q3 2004 9.46

(8.32,10.66)21.39 (20.7,22.1)

18.91 (18.57,19.25)

11.37 (10.92,11.83)

3.89 (3.17,4.68)

5.84 (5.47,6.21)

2.86 (2.73,3.00)

2.06 (1.87,2.26)

Q4 2004 9.31

(8.19,10.49)

21.06 (20.37,21.76)

18.67 (18.32,19.01)

10.68 (10.25,11.13)

4.36 (3.60,5.19)

5.87 (5.50,6.24)

2.94 (2.81,3.08)

1.83 (1.66,2.02)

Q1 2005 9.76

(8.61,10.98)

22.27 (21.55,22.99)

19.06 (18.71,19.41)

10.74 (10.3,11.19)

3.67 (2.97,4.44)

5.68 (5.31,6.05)

2.75 (2.62,2.88)

1.69 (1.51,1.87)

Q2 2005 8.11

(7.06,9.21)

20.49 (19.81,21.18)

18.72 (18.38,19.06)

10.86 (10.42,11.3)

3.55 (2.87,4.31)

5.32 (4.97,5.69)

2.87 (2.74,3.01)

1.79 (1.61,1.97)

Q3 2005 6.88

(5.92,7.89)

19.98 (19.32,20.66)

18.38 (18.04,18.71)

10.41 (9.98,10.84)

3.31 (2.66,4.04)

5.20 (4.86,5.55)

2.78 (2.65,2.92)

1.85 (1.67,2.04)

Q4 2005 6.89

(5.95,7.90)

19.40 (18.74,20.06)

18.23 (17.89,18.57)

10.23 (9.81,10.66)

3.23 (2.59,3.94)

5.02 (4.68,5.37)

2.62 (2.49,2.75)

1.56 (1.39,1.73)

Q1 2006 8.57

(7.50,9.70)

22.26 (21.55,22.97)

19.87 (19.52,20.23)

10.81 (10.37,11.26)

3.92 (3.20,4.70)

5.60 (5.24,5.97)

2.93 (2.79,3.07)

1.93 (1.75,2.12)

Q2 2006 6.84

(5.90,7.84)

17.61 (16.99,18.24)

16.69 (16.37,17.02)

10.03 (9.61,10.46)

3.06 (2.44,3.75)

4.67 (4.35,5.01)

2.49 (2.36,2.61)

2.02 (1.84,2.22)

Q3 2006 7.10

(6.15,8.11)

18.72 (18.09,19.37)

17.06 (16.73,17.38)

10.46 (10.04,10.89)

3.89 (3.19,4.66)

4.90 (4.57,5.24)

2.76 (2.63,2.90)

2.02 (1.84,2.22)

Q4 2006 8.76

(7.71,9.88)

19.17 (18.53,19.82)

18.28 (17.94,18.61)

10.82 (10.38,11.25)

4.23 (3.50,5.02)

5.50 (5.15,5.86)

3.06 (2.93,3.20)

2.13 (1.94,2.33)

Q1 2007 10.45

(9.29,11.67)

21.39 (20.71,22.08)

19.67 (19.32,20.02)

11.01 (10.57,11.46)

5.73 (4.87,6.66)

6.31 (5.94,6.70)

3.35 (3.20,3.50)

3.08 (2.84,3.32)

Q2 2007 7.98

(6.98,9.04)

18.88 (18.24,19.52)

17.38 (17.05,17.71)

10.13 (9.71,10.55)

4.38 (3.63,5.18)

5.37 (5.02,5.72)

2.71 (2.58,2.84)

2.08 (1.89,2.28)

Q3 2007 7.25

(6.30,8.26)

18.74 (18.12,19.38)

17.33 (17.01,17.66)

9.99 (9.58,10.41)

4.21 (3.49,5.00)

5.08 (4.75,5.42)

2.65 (2.52,2.78)

1.80 (1.63,1.99)

Q4 2007 7.95

(6.96,9.00)

17.74 (17.13,18.36)

16.99 (16.67,17.31)

9.45 (9.05,9.85)

4.43 (3.69,5.23)

4.86 (4.54,5.20)

2.58 (2.46,2.71)

1.71 (1.54,1.88)

Q1 2008 9.54

(8.45,10.69)

20.10 (19.45,20.76)

17.16 (16.83,17.48)

9.41 (9.01,9.82)

4.89 (4.10,5.73)

5.48 (5.14,5.84)

2.55 (2.43,2.68)

1.70 (1.53,1.88)

Q2 2008 6.29

(5.42,7.23)

17.58 (16.97,18.19)

16.14 (15.82,16.45)

8.94 (8.55,9.33)

3.19 (2.57,3.88)

4.89 (4.56,5.23)

2.33 (2.21,2.46)

1.58 (1.42,1.75)

Q3 2008 5.87

(5.04,6.77)

18.65 (18.03,19.27)

16.18 (15.87,16.49)

9.00 (8.61,9.39)

3.16 (2.55,3.84)

5.08 (4.75,5.42)

2.32 (2.20,2.44)

1.61 (1.45,1.79)

Q4 7.88 19.18 16.95 8.67 4.72 5.49 2.51 1.57

25

2008(6.91,8.90)

(18.56,19.82)

(16.63,17.27) (8.29,9.05) (3.97,5.54) (5.15,5.84) (2.39,2.64) (1.41,1.74)

Q1 2009 9.58

(8.50,10.72)

21.11 (20.44,21.78)

18.51 (18.17,18.85)

9.27 (8.88,9.67)

5.01 (4.23,5.86)

6.03 (5.67,6.40)

2.80 (2.67,2.94)

1.66 (1.49,1.84)

Q2 2009 7.13

(6.22,8.11)

19.06 (18.44,19.69)

17.47 (17.15,17.8)

9.34 (8.95,9.74)

3.95 (3.27,4.70)

5.36 (5.02,5.71)

2.65 (2.52,2.78)

1.53 (1.37,1.70)

Q3 2009 7.04

(6.14,8.00)

20.03 (19.39,20.67)

17.36 (17.04,17.69)

8.89 (8.51,9.27)

3.55 (2.91,4.25)

5.89 (5.54,6.26)

2.52 (2.40,2.65)

1.41 (1.26,1.57)

Q4 2009 9.46

(8.42,10.56)

19.46 (18.84,20.09)

17.97 (17.64,18.3)

8.97 (8.59,9.36)

6.07 (5.23,6.97)

5.70 (5.35,6.06)

2.74 (2.61,2.87)

1.62 (1.45,1.78)

Q1 2010 10.14

(9.05,11.28)

21.64 (20.98,22.31)

19.49 (19.15,19.84)

9.06 (8.68,9.45)

5.92 (5.08,6.81)

6.26 (5.89,6.64)

2.85 (2.71,2.99)

1.55 (1.39,1.71)

Q2 2010 9.91

(8.84,11.04)

20.83 (20.18,21.48)

18.47 (18.14,18.81)

9.49 (9.10,9.88)

5.66 (4.84,6.53)

5.84 (5.48,6.20)

2.66 (2.53,2.79)

1.57 (1.41,1.74)

Q3 2010 7.61

(6.68,8.59)

21.05 (20.40,21.70)

18.62 (18.29,18.96)

9.24 (8.85,9.62)

4.08 (3.39,4.82)

5.97 (5.62,6.34)

2.54 (2.42,2.67)

1.55 (1.39,1.71)

Q4 2010 8.63

(7.64,9.67)

20.15 (19.52,20.79)

17.91 (17.59,18.24)

8.55 (8.19,8.92)

5.44 (4.64,6.28)

5.58 (5.23,5.93)

2.46 (2.33,2.58)

1.38 (1.24,1.54)

Q1 2011 10.98

(9.86,12.16)

21.88 (21.21,22.55)

19.21 (18.86,19.55)

9.69 (9.3,10.09)

6.93 (6.02,7.89)

6.46 (6.09,6.85)

2.62 (2.49,2.75)

1.52 (1.37,1.69)

Q2 2011 7.91

(6.96,8.90)

19.56 (18.94,20.19)

17.95 (17.62,18.28)

8.97 (8.59,9.35)

3.83 (3.17,4.55)

5.48 (5.14,5.83)

2.51 (2.39,2.64)

1.49 (1.34,1.65)

Q3 2011 7.69

(6.76,8.66)19.87 (19.24,20.5)

17.72 (17.39,18.04)

8.86 (8.49,9.23)

4.68 (3.95,5.46)

5.64 (5.30,6.00)

2.41 (2.29,2.54)

1.38 (1.23,1.53)

Q4 2011 8.52

(7.55,9.54)

20.19 (19.56,20.83)

18.20 (17.87,18.53)

8.99 (8.62,9.36)

5.43 (4.65,6.28)

6.01 (5.65,6.38)

2.59 (2.46,2.72)

1.50 (1.35,1.66)

Q1 2012 9.72

(8.67,10.82)

22.21 (21.54,22.88)

19.64 (19.3,19.99)

9.27 (8.90,9.65)

6.13 (5.29,7.02)

6.60 (6.23,6.99)

2.85 (2.72,2.99)

1.56 (1.4,1.72)

Q2 2012 8.55

(7.57,9.57)

19.9 (19.28,20.54)

18.18 (17.85,18.51)

8.94 (8.58,9.32)

5.47 (4.68,6.32)

6.00 (5.64,6.37)

2.54 (2.41,2.67)

1.50 (1.35,1.66)

Q3 2012 7.49

(6.58,8.45)

19.65 (19.04,20.27)

18.29 (17.96,18.62)

8.99 (8.62,9.36)

4.33 (3.64,5.09)

5.64 (5.29,5.99)

2.49 (2.36,2.62)

1.43 (1.28,1.58)

Q4 2012 9.66

(8.63,10.74)

20.49 (19.87,21.13)

18.59 (18.26,18.92)

8.44 (8.09,8.79)

5.82 (5.01,6.69)

6.24 (5.88,6.61)

2.71 (2.58,2.85)

1.36 (1.22,1.51)

Q1 2013 10.82

(9.71,11.98)

21.05 (20.41,21.70)

18.57 (18.24,18.91)

8.33 (7.98,8.68)

6.71 (5.83,7.66)

6.16 (5.80,6.53)

2.59 (2.46,2.72)

1.26 (1.12,1.40)

26

Web Appendix

Read code Read term Type of code

E2B..00 Depressive disorder NEC

Diagnosis

1BT..11 Low mood SymptomE200300 Anxiety with

depressionDiagnosis

Eu32z11 [X]Depression NOS

Diagnosis

1B17.00 Depressed Symptom1465 H/O: depression Diagnosis1B17.11 C/O - feeling

depressedSymptom

9H92.00 Depression interim review

Diagnosis

Eu32.00 [X]Depressive episode

Diagnosis

E204.00 Neurotic depression reactive type

Diagnosis

1BT..00 Depressed mood Symptom1B1U.00 Symptoms of

depressionSymptom

388P.00 HAD scale: depression score

Questionnaire

E204.11 Postnatal depression

Diagnosis

2257 O/E - depressed Symptom

Eu32100 [X]Moderate depressive episode

Diagnosis

E113.11 Endogenous depression - recurrent

Diagnosis

Eu32z00 [X]Depressive episode, unspecified

Diagnosis

1BO..00 Mood swings SymptomEu32z14 [X] Reactive

depression NOSDiagnosis

E112.13 Endogenous depression first episode

Diagnosis

E112.14 Endogenous depression

Diagnosis

1B1J.11 Emotional upset Symptom

27

E2B1.00 Chronic depression

Diagnosis

E112.11 Agitated depression

Diagnosis

E112.00 Single major depressive episode

Diagnosis

E135.00 Agitated depression

Diagnosis

E113700 Recurrent depression

Diagnosis

Eu32000 [X]Mild depressive episode

Diagnosis

1B1J.00 Emotional problem

Symptom

Eu33.00 [X]Recurrent depressive disorder

Diagnosis

Eu41200 [X]Mixed anxiety and depressive disorder

Diagnosis

1S4..00 Mood observations

Symptom

Eu32200 [X]Severe depressive episode without psychotic symptoms

Diagnosis

ZRLr.12 HADS - Hospital anxiety and depression scale

Questionnaire

1B1U.11 Depressive symptoms

Symptom

R007z14 [D]Work stress SymptomEu43000 [X]Acute stress

reactionSymptom

E11z100 Rebound mood swings

Symptom

E113.00 Recurrent major depressive episode

Diagnosis

388J.00 Hospital anxiety and depression scale

Questionnaire

Eu32z12 [X]Depressive disorder NOS

Diagnosis

9k4..00 Depression - enhanced services

Other

28

administrationEu3..00 [X]Mood -

affective disorders

Diagnosis

E112.12 Endogenous depression first episode

Diagnosis

Eu32400 [X]Mild depression

Diagnosis

9H90.00 Depression annual review

Other

9H91.00 Depression medication review

Other

Eu32.11 [X]Single episode of depressive reaction

Diagnosis

9HA0.00 On depression register

Other

E113200 Recurrent major depressive episodes, moderate

Diagnosis

Eu34100 [X]Dysthymia DiagnosisZRBY.11 EPDS - Edinburgh

postnatal depression scale

Questionnaire

E28z.00 Acute stress reaction NOS

Symptom

E112200 Single major depressive episode, moderate

Diagnosis

Eu32.13 [X]Single episode of reactive depression

Diagnosis

9k40.00 Depression - enhanced service completed

Other

E112100 Single major depressive episode, mild

Diagnosis

Eu33100 [X]Recurrent depressive disorder, current episode moderate

Diagnosis

Eu34114 [X]Persistent anxiety depression

Diagnosis

ZRLr.00 Hospital anxiety Questionnaire

29

and depression scale

Eu41211 [X]Mild anxiety depression

Diagnosis

E290.00 Brief depressive reaction

Symptom

Eu53011 [X]Postnatal depression NOS

Diagnosis

Eu43.00 [X]Reaction to severe stress, and adjustment disorders

Symptom

Eu33.13 [X]Recurrent episodes of reactive depression

Diagnosis

1BQ..00 Loss of capacity for enjoyment

Symptom

E11z200 Masked depression

Diagnosis

Eu33z00 [X]Recurrent depressive disorder, unspecified

Diagnosis

388g.00 Beck depression inventory second edition score

Questionnaire

ZRL6.00 Geriatric depression scale

Questionnaire

Eu34113 [X]Neurotic depression

Diagnosis

Eu33.11 [X]Recurrent episodes of depressive reaction

Diagnosis

ZRBY.00 Edinburgh postnatal depression scale

Questionnaire

ZRLr.11 HAD - Hospital anxiety and depression scale

Questionnaire

E112z00 Single major depressive episode NOS

Diagnosis

E291.00 Prolonged depressive reaction

Symptom

Eu43012 [X]Acute reaction to stress

Symptom

Eu32y00 [X]Other depressive

Diagnosis

30

episodesE113z00 Recurrent major

depressive episode NOS

Diagnosis

Eu43z00 [X]Reaction to severe stress, unspecified

Symptom

E112300 Single major depressive episode, severe, without psychosis

Diagnosis

8O82.00 Emotional and psychosocial support and advice

Other

1BT..12 Sad mood SymptomEu33200 [X]Recurr depress

disorder cur epi severe without psyc sympt

Diagnosis

Eu33000 [X]Recurrent depressive disorder, current episode mild

Diagnosis

1JJ..00 Suspected depression

Symptom

E113100 Recurrent major depressive episodes, mild

Diagnosis

388K.00 Geriatric depression scale

Questionnaire

Eu32212 [X]Single episode major depression w'out psychotic symptoms

Diagnosis

Eu34111 [X]Depressive neurosis

Diagnosis

Eu32700 [X]Major depression, severe without psychotic symptoms

Diagnosis

E113300 Recurrent major depressive episodes, severe, no psychosis

Diagnosis

E112000 Single major depressive episode,

Diagnosis

31

unspecifiedEu32600 [X]Major

depression, moderately severe

Diagnosis

ZR2A.00 Beck depression inventory

Questionnaire

Eu33211 [X]Endogenous depression without psychotic symptoms

Diagnosis

1BP0.00 Loss of interest in previously enjoyable activity

Symptom

ZR8..00 Depression self rating scale

Questionnaire

ZRLU.00 Hamilton rating scale for depression

Questionnaire

Eu33.12 [X]Recurrent episodes of psychogenic depression

Diagnosis

Eu4..00 [X]Neurotic, stress - related and somatoform disorders

Symptom

9ONA.00 Stress monitoring check done

Other

E113600 Recurrent major depressive episodes, in full remission

Diagnosis

Eu33400 [X]Recurrent depressive disorder, currently in remission

Diagnosis

Eu3z.00 [X]Unspecified mood affective disorder

Diagnosis

Eu32.12 [X]Single episode of psychogenic depression

Diagnosis

ZRL6.11 GDS - Geriatric depression scale

Questionnaire

Eu32z13 [X]Prolonged single episode of reactive depression

Diagnosis

ZR2A.11 BDI - Beck Questionnaire

32

depression inventory

1BU..00 Loss of hope for the future

Symptom

E113000 Recurrent major depressive episodes, unspecified

Diagnosis

Eu32500 [X]Major depression, mild

Diagnosis

Eu32y11 [X]Atypical depression

Diagnosis

E112500 Single major depressive episode, partial or unspec remission

Diagnosis

Eu33212 [X]Major depression, recurrent without psychotic symptoms

Diagnosis

Eu53012 [X]Postpartum depression NOS

Diagnosis

ZRL6.12 Geriatric depression score

Questionnaire

1S40.00 Dysphoric mood SymptomE284.00 Stress reaction

causing mixed disturbance of emotion/conduct

Symptom

ZV11100 [V]Personal history of affective disorder

Diagnosis

ZRLU.11 HAMD - Hamilton rating scale for depression

Questionnaire

E113500 Recurrent major depressive episodes, partial/unspec remission

Diagnosis

ZR2G.00 Behaviour and mood disturbance scale

Questionnaire

E11y200 Atypical depressive disorder

Diagnosis

Eu3y111 [X]Recurrent brief depressive episodes

Diagnosis

33

Eu33y00 [X]Other recurrent depressive disorders

Diagnosis

Eu43y00 [X]Other reactions to severe stress

Symptom

E112600 Single major depressive episode, in full remission

Diagnosis

ZRaH.00 Mood affective checklist

Questionnaire

Eu32211 [X]Single episode agitated depressn w'out psychotic symptoms

Diagnosis

Eu34.00 [X]Persistent mood affective disorders

Diagnosis

ZR7..00 Depression anxiety scale

Questionnaire

ZR2h.00 Brief depression rating scale

Questionnaire

E290z00 Brief depressive reaction NOS

Symptom

E292.00 Adjustment reaction, predominant disturbance other emotions

Symptom

ZRby.00 Profile of mood states

Questionnaire

E283z00 Other acute stress reaction NOS

Symptom

Eu92.11 [X]Emotional behavioural problems

Symptom

Eu3y.00 [X]Other mood affective disorders

Diagnosis

Eu3y000 [X]Other single mood affective disorders

Diagnosis

E283.00 Other acute stress reactions

Symptom

E292400 Adjustment reaction with

Symptom

34

anxious moodEu32y12 [X]Single episode

of masked depression NOS

Diagnosis

ZRrc.00 Zung self-rating depression scale

Questionnaire

9ON4.00 Stress monitoring 1st letter

Other

E2C4.00 Mixed disturbance of conduct and emotion

Symptom

ZRLn.00 Hopelessness scale

Questionnaire

Eu3y100 [X]Other recurrent mood affective disorders

Diagnosis

E292z00 Adjustment reaction with disturbance of other emotion NOS

Symptom

Eu34z00 [X]Persistent mood affective disorder, unspecified

Diagnosis

E2C4z00 Mixed disturbance of conduct and emotion NOS

Symptom

Eu32213 [X]Single episode vital depression w'out psychotic symptoms

Diagnosis

E294.00 Adjustment reaction with disturbance emotion and conduct

Symptom

E292y00 Adjustment reaction with mixed disturbance of emotion

Symptom

Eu33z11 [X]Monopolar depression NOS

Diagnosis

Eu3yy00 [X]Other specified mood affective disorders

Diagnosis

35

ZR2B.00 Beck hopelessness scale

Questionnaire

Eu32B00 [X]Antenatal depression

Diagnosis

ZRVM.00 Leeds scale for the self-assessment of anxiety & depression

Questionnaire

ZRLfH00 Health of the Nation Outcome Scale item 7 - depressed mood

Questionnaire

9ONZ.00 Stress monitoring admin. NOS

Other

Eu33214 [X]Vital depression, recurrent without psychotic symptoms

Diagnosis

ZR8..11 DSRS - Depression self rating scale

Questionnaire

ZRLU.12 HRSD - Hamilton rating scale for depression

Questionnaire

Eu34y00 [X]Other persistent mood affective disorders

Diagnosis

ZRrc.11 SDS - Zung self-rating depression scale

Questionnaire

9ON8.00 Stress monitoring phone invite

Other

9ON3.00 Stress monitoring default

Other

ZRaH.11 MACL - Mood affective checklist

Questionnaire

ZRrY.00 WHO depression scale

Questionnaire

9ON7.00 Stress monitoring verbal inv.

Other

ZRby.11 POMS - Profile of mood states

Questionnaire

9ON5.00 Stress monitoring 2nd letter

Other

9ON9.00 Stress monitoring deleted

Other

36

ZRbS.00 Positive and negative affect schedule

Questionnaire

ZRLfI00 Health of the Nation Outcome Scale item 7 - depressed mood

Questionnaire

ZRrI.00 Wakefield self-assessment depression inventory

Questionnaire

9ON6.00 Stress monitoring 3rd letter

Other

37

Highlights

The prevalence of GP recorded Read codes for depressive diagnoses and symptoms was falling in England prior to the economic recession, but rose again after April 2008

Increasing prevalence of depression after the recession was recorded among men, but not women, and was significantly related to the national unemployment rate in men.

Increasing depression after the recession was recorded among working age adults but not adolescents or older patients

A statistically significant increase in prevalence following the recession was found only in the most socioeconomically deprived quintile of practices, but the downward trend prior to the recession flattened out in the other four quintiles

Following the introduction of the GP contract quality outcome framework (QOF), GPs used more symptom codes than diagnostic codes to record depression

GP Read coding preferences meant the majority of patients with new depressive symptoms were not included in the QOF denominator for measuring GP performance in assessing depression

38