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Inequalities in the provision of cardiovascular screening to people with severe mental illnesses in primary care
Schizophrenia Research 129 (2011) 104–110
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Schizophrenia Research j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / s c h r e s
Inequalities in the provision of cardiovascular screening to people with severe mental illnesses in primary care Cohort study in the United Kingdom THIN Primary Care Database 2000–2007 David P.J. Osborn a,b,⁎, Gianluca Baio c,d, Kate Walters e,f, Irene Petersen e,f, Heather Limburg e,f, Rosalind Raine c, Irwin Nazareth e,f a
Department of Mental Health Sciences, Royal Free Campus, University College London Medical School, Rowland Hill Street, London, NW3 2PF, UK Camden and Islington Mental Health and Social Care Trust, St. Pancras Way, London, NW1 OPE, UK c Health Care Evaluation Group, Department of Epidemiology and Public Health, University College London, Gower Street, London WC1E 6BT, UK d UCLH/UCL Comprehensive Biomedical Research Centre, 149 Tottenham Court Road, London W1T 7NF, UK e Department of Primary Care and Population Health, University College London Medical School, Rowland Hill Street, London, NW3 2PF, UK f MRC General Practice Research Framework, Stephenson House, 158–160 North Gower Street London, NW1 2ND, UK b
a r t i c l e
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Article history: Received 22 December 2010 Received in revised form 29 March 2011 Accepted 1 April 2011 Available online 8 May 2011 Keywords: Schizophrenia Bipolar affective disorder Cardiovascular disease Screening Primary care Risk factors
a b s t r a c t Background: People with severe mental illnesses (SMI), including schizophrenia, are at increased risk of cardiovascular disease (CVD). Guidelines recommend regular CVD screening and in the United Kingdom, since 2004, General Practitioners are remunerated for annual reviews. Objectives: To compare annual rates of CVD screening provision in people with and without SMI between 2000 and 2008. Method: We identified 18,696 people with SMI and 95,512 people without SMI in the UK The Health Improvement Network (THIN) primary care database. We compared the rates of measurement of blood pressure (BP), glucose, cholesterol and body mass index (BMI). Results: Prior to 2004, all people with SMI, were significantly less likely to receive each measurement, (including people above and below 60 years of age). In 2003; adjusted incidence rate ratios (95% CI) for screening in people with SMI under 60 years compared to people without SMI were: BMI: 0.62 (0.58–0.65); BP: 0.59 (0.56–0.62); glucose: 0.66 (0.61–0.70) and cholesterol: 0.54 (0.49–0.59). By 2007 people with SMI under 60 were equally likely receive a measurement of BMI: 1.00 (0.96–1.04), glucose: 1.00 (0.96–1.05) and cholesterol: 0.95 (0.90–1.0); the gap in screening for BP had narrowed 0.87 (0.83–0.90). However people with SMI over 60 years of age remained significantly less likely to be screened. There was little difference in screening according to social deprivation. Conclusions: In UK primary care, people with SMI over 60 years of age remain less likely than the general population to receive annual CVD screening despite higher risk of developing CVD. © 2011 Elsevier B.V. All rights reserved.
1. Introduction People with severe mental illnesses (SMI) such as schizophrenia and bipolar disorder die early from cardiovascular disease including myocardial infarction and stroke (Osborn et al., 2007a, 2007b; Tiihonen et al., 2009). There are several reasons for this including high rates of smoking and obesity, poor diet and lack of exercise
⁎ Corresponding author at: Department of Mental Health Sciences, Royal Free Campus, University College London Medical School, Rowland Hill Street, London, NW3 2PF, UK. Tel.: + 44 20 77940500x33950; fax: 44 20 78302808. E-mail addresses: [email protected], [email protected] (D.P.J. Osborn), [email protected] (G. Baio), [email protected] (K. Walters), [email protected] (I. Petersen), [email protected] (H. Limburg), [email protected] (R. Raine), [email protected] (I. Nazareth). 0920-9964/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2011.04.003
(Osborn et al., 2006, 2007a, 2007b). Antipsychotic and other psychiatric medications may increase weight and cause abnormalities in the regulation of serum glucose and lipids (Marder et al., 2004). The National Institute for Health and Clinical Excellence (2006, 2009) in England recommends that people with SMI have regular reviews of their physical health, with a focus on cardiovascular screening. International guidelines recommend that everyone prescribed antipsychotic medications should have regular measurement of cardiovascular risk factors including glucose, lipids and body mass index (Marder et al., 2004; Citrome and Yeomans, 2005). There is a consensus that the physical health care of people with SMI is primarily the responsibility of primary care services (National Institute for Health and Clinical Excellence, 2006, 2009). In the United Kingdom, the care of people with SMI is included in the General Medical Services GP contract (NHS Employers, 2005). This includes a
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Quality and Outcomes Framework (QOF), whereby practices receive remuneration for keeping a register of people who have a diagnosis of SMI and for offering them an annual review. The precise contents of this annual review are not specified under QOF. The indicators state that age-appropriate health promotion and prevention advice should be given during the review. Therefore, although best practice would include cardiovascular risk assessment, this is not part of the current national contract. A national consultation is currently underway, and there are proposals to specifically include CVD risk factor screening in QOF from 2011. There is small-scale evidence that CVD care and screening may be inferior in people with SMI. People with SMI are less likely to receive appropriate pharmacological interventions once they have developed coronary heart disease (Hippisley-Cox et al., 2007). They may also be less likely to be screened for cardiovascular risk factors before they develop CVD. A study of 195 people with schizophrenia from 22 UK General Practices revealed that people with SMI were significantly less likely to receive screening for all cardiovascular risk factors (Roberts et al., 2007). We do not know whether the introduction of QOF has improved cardiovascular screening in SMI or whether there is a need to more actively promote or incentivise CVD risk screening in this group. We aimed to explore national inequalities in the provision of cardiovascular screening to people with SMI in a large representative sample of patients in primary care and to assess whether provision of screening had improved over time and since the introduction of QOF in 2004. A secondary aim was to determine whether any inequalities in CVD screening for people with SMI were associated with social deprivation. We hypothesized that the competing demands of working with deprived populations would make it more difficult to meet standards of physical health care for people with SMI.
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the methods described by Dave and Petersen (2009) to identify all people with diagnoses of non-organic psychoses and bipolar affective disorders, schizophrenia, schizo-affective disorder, depressive psychosis, persistent delusional disorders and “psychoses not otherwise specified”. To improve validity of diagnosis we only included patients whose diagnosis was entered or re-entered after 1990.
2.4.2. People without SMI We selected six times the number of comparison patients, who did not have a SMI diagnosis. We frequency-matched by 5 year age bands, by practice and gender.
2.4.3. All patients We included patients with at least 6 months of follow-up data. To ensure data quality we only included data after the date at which each practice had reached pre-defined THIN quality standards for acceptable computer use and acceptable mortality recording (Maguire et al., 2009).
2.4.4. Follow-up period The start date for each patient was the maximum (latest) of the following: date of registration at the practice or the date when practice met acceptable data quality standards above. The end date was either December 2007, or the date when the patient left the practice or died. Although we received some records from 2008; we were unable to use the data as we did not have access to the full calendar year. Exclusion criteria: People with pre-existing CVD and patients who registered but had no further record of attendance at the practice.
2. Methods 2.1. Study design Retrospective cohort study. 2.2. Setting/population Adults in the United Kingdom registered with a practice contributing to the primary care database The Health Improvement Network (THIN) during the Jan 2000–Dec 2007 period. 2.3. Data source THIN provides anonymized clinical data from 420 general practices in England, Scotland, Wales and Northern Ireland. The database includes around 6 million patients and is a powerful resource for epidemiological and health services research. Since most people with SMI are registered with primary care, it is highly suitable for studying these conditions. The validity of GP computer diagnoses of SMI has been established (Nazareth et al., 1993). THIN includes information for each individual on diagnoses, prescriptions, referrals, CVD risk factors including smoking, and local deprivation for an individual's postcode (using quintiles of Townsend score; see Section 2.5). Diagnoses, symptoms and lifestyle information are entered into the database by GPs and practice staff as Read codes (Dave and Petersen, 2009) as part of routine clinical care and the database is regularly updated. All practices were using Vision software. 2.4. Inclusion criteria 2.4.1. People with SMI All people aged over 18 years of age with a practice computer diagnosis of severe mental illness. We created Read code lists using
2.5. Data extracted 2.5.1. Main outcomes We recorded whether each patient had a recording of the following individual measurements during each calendar year. 1) Systolic and/or diastolic blood pressure 2) Body mass index, (including weight measurement if height had already been documented in a previous year) 3) Serum glucose (random or fasting) 4) Serum total cholesterol
2.5.2. Other variables We also extracted data regarding age, sex, time since initial diagnosis of SMI, mean annual consultation rate at the practice, and whether a patient had newly registered within each year. We included the latter variable, since screening is more likely to be performed as part of the baseline registration procedures at a new practice. THIN includes an area-based indicator of patients' socioeconomic circumstances. Each enumeration district (around 150 households) is assigned a Townsend Deprivation score (Townsend et al., 1986).These are divided into national quintiles and patients are assigned a quintile score according to the enumeration district in which they live. The Townsend score is made up of four deprivation indices for an area; the percentage unemployed; the percentage of households who own their home and own a car, and level of overcrowding. We also calculated an aggregate social deprivation score for each general practice by taking the mean individual Townsend score for all patients within that practice. We used this continuous variable to assess the importance of practice-level deprivation.
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2.6. Analysis First we determined the proportion of people who had received screening for BMI, BP, glucose and cholesterol in each calendar year from 2000 to 2007. We calculated the unadjusted proportions screened, comparing all people with and without SMI. We then stratified by sex, age-group and individual social deprivation (area postcode) to assess whether each of these variables influenced any differences in screening between SMI and non-SMI. Time trends in screening were explored graphically, plotting the proportions screened and their 95% confidence intervals. For the multivariable analysis we used random effects Poisson regression, to account for clustering by practice. To assess the significance of time trends in rates of screening we included an interaction term between calendar year and SMI status in the Poisson model and employed a likelihood ratio test to assess if the interaction term improved the fit of the model and therefore whether any increases in screening over time differed significantly between people with and without SMI. To determine the magnitude of any differences in rates of annual screening between people with and without SMI we calculated incidence rate ratios; IRRs. We built separate models and derived IRRs in four different calendar years, namely 2000 (baseline), 2003 (preQOF), 2005 (post QOF) and 2007 (the last complete year in the dataset). We adjusted for age, sex, social deprivation, consultation rate and newly registering with a practice. We assessed whether social deprivation affected provision of screening as follows. First we compared the proportions of people with and without SMI who were screened for each risk factor, stratified according to quintiles of Townsend deprivation score for their domestic postcode. We assessed the importance of practice level deprivation as follows: Separate Poisson regression models were built with each of the four CVD risk factors as the dependent outcomes. Once again we built these models for the years 2000 (baseline), 2003 (pre-QOF), 2005 (post-QOF) and 2007 (the last complete year in the dataset). To test the hypothesis that relative rates of screening would be more pronounced in practices with greater deprivation, we also included an interaction term between SMI and practice deprivation as a continuous variable and tested its significance with a likelihood ratio test. Due to the large numbers of patients in THIN studies, interaction terms may appear significant by chance. Therefore we imposed a significance threshold of p b 0.01 to determine whether an interaction term was important statistically. 2.7. Ethics The study had ethical approval from the London Research Ethics Committee. Reference number: 09/H0718/11. 3. Results 3.1. Sample We identified 18,696 people with SMI and 95,512 comparison patients without an SMI diagnosis. The characteristics of the two cohorts are described in Table 1. The mean follow-up was 5.7 years for people with SMI and 6.9 years for people without SMI. The majority of the SMI cohort had a diagnosis of schizophrenia, bipolar disorder or schizo-affective disorder. The unadjusted screening results can be viewed graphically in Figs. 1–4, and the proportions screened for each risk factor in each calendar year are reported in Appendices 1–2. Results were similar for age groups under 60, but were different for those aged 60 and over. Therefore all the analyses were stratified according to age, above and below 60.
Table 1 Characteristics of cohorts with and without severe mental illnesses. SMI N (%) Mean age (SD) % Female (SE) Mean follow up in years (SD) Mean time since diagnosis (SD) Diagnosis Schizophrenia/schizoaffective disorder (%) Bipolar disorder (%) Other psychosis (%) Mean consultation rate per annum (SD) New registered — (%) Deprivation — missing (%) Deprivation — 1st quintile: least deprived (%) Deprivation — 2nd quintile (%) Deprivation — 3rd quintile (%) Deprivation — 4th quintile (%) Deprivation — 5th quintile: most deprived (%) Mean practice level deprivation (SD) [range 1–5]
Non-SMI
18,696 52.1 49.48 5.7 5.6
(16.4) (18.7) (0.5) (2.4) (3.8)
6983 4586 7127 9.0 3411 885 2452 2660 3520 4432 4747 2.81
(37.4) (24.5) (38.1) (11.8) (18.2) (4.7) (13.1) (14.2) (18.9) (23.7) (25.4) (0.8)
95,512 53.2 52.6 7.0
(83.4) (19.0) (0.2) (2.1)
5.7 26,973 4016 19,854 18,328 19,435 18,795 15,084 2.80
(6.2) (28.2) (4.2) (20.8) (19.2) (20.4) (19.7) (15.8) (0.8)
SMI: severe mental Illness. SD: standard deviation.
Changes in screening rates for cardiovascular risk factors 2000– 2007. The annual screening rates increased for all four risk factors during the study period, both for people with and without SMI. Marked inequalities in screening provision were apparent early in the decade, but this gap narrowed considerably for all risk factors by 2007 (Figs. 1–4). These increases in annual rates of screening between 2000 and 2007 were significantly different for people with and without SMI; the rate of increase in screening was greater for people with SMI. In Poisson regression, interaction terms between calendar year and SMI status significantly improved the models for all four risk factors (likelihood ratio tests comparing models with and without the SMI × calendar year interaction term: all p values b 0.001, except glucose in the over-60s p = 0.002). 3.2. Comparison of screening rates between SMI and non-SMI For each risk factor, Poisson regression models better predicted screening when the following co-variates were included: age, sex, being newly registered at a practice and consultation rate. 3.2.1. BMI Fig. 1 shows time trends in screening for BMI. Proportions screened each year are compared according to sex and age-group. Before 2004, people with SMI under 60 were far less likely to be screened, but by 2007, they were equally likely to receive a BMI measurement as people without SMI. This was true for both males and females. However the over-60s with SMI were still less likely to receive a BMI recording, even by 2007 (Fig. 1). The results were similar in the adjusted analysis; in 2007, people with SMI over 60 were less likely to have a record of BMI (Table 2). 3.2.2. Blood pressure Between 2000 and 2007 there was a general increase in blood pressure measurement for people with SMI, however by 2007 people with SMI were still significantly less likely to have a blood pressure recording compared to people without SMI. This difference was particularly marked in the over-60s (Fig. 2 and Appendix 1). The adjusted analysis confirmed that even by 2007, blood pressure was less likely to be recorded in people with SMI, aged both below and above 60 (Table 2).
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Proportion screened for BMI - Female
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Fig. 1. Proportion of people with and without Severe Mental Illnesses (SMI) who received a BMI measurement in each year from 2000 to 2007. Unadjusted data.
Proportion screened for BP - Male
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Fig. 2. Proportion of people with and without Severe Mental Illnesses (SMI) who received a Blood pressure measurement in each year from 2000 to 2007. Unadjusted data.
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Proportion screened for Cholesterol - Male
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Fig. 3. Proportion of people with and without Severe Mental Illnesses (SMI) who received a cholesterol measurement in each year from 2000 to 2007. Unadjusted data.
3.2.3. Cholesterol A similar pattern emerged for cholesterol (Fig. 3). People with SMI were less likely to be screened early in the decade, but by 2007, this inequality had disappeared for people with SMI under 60, and their cholesterol was more likely to be measured. However once again, the over 60s with SMI were far less likely to receive cholesterol testing than their counterparts without SMI. This pattern was confirmed by the adjusted analysis; in 2007 people with SMI under 60 were equally likely to receive a cholesterol measurement, but those under 60 were less likely than their counterparts without SMI (IRR 0.65; 95% CI: 0.61–0.70. Table 2).
3.3.2. Practice level deprivation Practice level deprivation also exerted little influence on any inequalities in screening. Interaction terms were explored between SMI and practice deprivation for each of the four main risk factors, in 2000, 2003, 2005 and 2007. Separate Poisson models were built for the over and under 60s. None of the interaction terms were significant at p b 0.01, suggesting little difference in the relative rates of screening between people with and without SMI in areas with greater social deprivation.
3.2.4. Glucose Serum glucose testing also increased over time in all groups with SMI and by 2007, there was no significant gap between total proportions receiving a glucose measurement comparing those with and without SMI (Fig. 4). Once again, the over 60s were an exception; people with SMI in this age bracket were less likely to be screened than people over 60 without SMI. These 2007 findings remained the same after adjusting in the Poisson regression (Table 2).
There has been a yearly increase in the proportion of people with SMI who receive cardiovascular screening over the last decade in UK primary care. Since the introduction of financial incentives for GPs in the Quality and Outcomes Framework (QOF) policy in 2004 there has been an increase in recording of glucose, BMI, cholesterol and Blood pressure for people with SMI. Before 2004, there were marked inequalities and people with SMI were half as likely to be screened for CVD risk factors, compared to people without SMI. By 2007, people with SMI under 60 were equally likely to be screened for glucose, BMI and cholesterol. However, they remained significantly less likely to receive a blood pressure measurement. It is reassuring that younger people with SMI are now equally likely to be screened, given their propensity for developing early diabetes, lipid abnormalities and new onset CVD. However, in the UK NICE recommends that people with SMI have an annual cardiovascular risk check. In 2007, although inequalities had mostly disappeared for the under-60s, the majority of people with SMI did not have a primary care record for the four CVD risk factors we studied (Figs. 1–4). Care for people with SMI over 60 remains inferior to their counterparts without SMI, and there is no clinical or epidemiological
3.3. Inequalities in screening and social deprivation 3.3.1. Individual deprivation: Within SMI For each CVD risk factor, there was little consistent association between Townsend deprivation quintiles and the proportions of people with SMI who were screened each year (unadjusted data; Appendices 1 and 2). For instance, for blood pressure, the proportion screened in 2006 was 40.1% for people living in the least deprived post-codes and 40.7% for those living in the most deprived areas (Appendix 1). For glucose, the proportions from 2006 were 27.3% (least deprived) and 27.5% (most deprived).
4. Discussion
D.P.J. Osborn et al. / Schizophrenia Research 129 (2011) 104–110
Proportion screened for Glucose - Female
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Fig. 4. Proportion of people with and without Severe Mental Illnesses (SMI) who received a glucose measurement in each year from 2000 to 2007. Unadjusted data.
justification for this. People with SMI between 50 and 70 are twice as likely to develop heart disease as the general population (Osborn et al., 2007a, 2007b). The inequality in this older age group may reflect that the general population without SMI are much more likely to be screened once they pass the age of 60. In the United Kingdom, there are no specific schemes to remunerate general practitioners for assessing or managing elderly people. The QOF system is targeted at a number of chronic diseases rather than specific age groups. However there is some evidence that other groups of vulnerable elderly people may be served less well by QOF. A recent study compared care provision to elderly people living in the community and those in residential homes. Delivery of care was significantly poorer for those in residential homes, on a number of quality indicators such as the management of both heart disease and diabetes (Shah et al., 2011).
Our study has a number of strengths, including the large size and representative nature of the national sample, as well as the ability to control for other factors which might predict inequalities in screening especially consultation rate and deprivation. We took a thorough but conservative approach to exploring the effects of deprivation, using both practice and individual levels of deprivation, although personal postcode is still a proxy for individual deprivation. The exploration of deprivation effects involved building multiple Poisson regression models for each risk factor in four calendar years. Therefore we looked for consistent patterns in any interaction terms across 4 years within the decade, across the risk factors. We were deliberately conservative in interpretation of interaction terms, because the large sample size and multiple tests could lead to spurious significant findings occurring by chance. However there was
Table 2 Results from Poisson regression. Adjusted incidence rate ratios for being screened for body mass index, blood pressure, cholesterol and glucose in people with SMI, compared with people without SMI. 2000–2007. People aged 18–59
BMI: Adj IRR for BMI in SMI BP: Adj IRR for BP in SMI Cholesterol: Adj IRR for cholesterol in SMI Glucose: Adj IRR for glucose in SMI People aged 60 and above
BMI: Adj IRR for BMI in SMI BP: Adj IRR for BP in SMI Cholesterol: Adj IRR for cholesterol in SMI Glucose: Adj IRR for glucose in SMI
2000
2003
IRR
95% CI
0.599 0.579 0.477 0.643
0.546 0.539 0.404 0.576
0.657 0.622 0.563 0.717
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2005
IRR
95% CI
0.615 0.591 0.540 0.655
0.578 0.562 0.492 0.613
0.653 0.622 0.591 0.701
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IRR
95% CI
0.571 0.557 0.440 0.697
0.490 0.501 0.364 0.607
0.666 0.620 0.532 0.799
2007
IRR
95% CI
0.793 0.709 0.750 0.825
0.756 0.679 0.704 0.782
0.833 0.739 0.801 0.870
2005
IRR
95% CI
0.553 0.618 0.477 0.645
0.499 0.573 0.429 0.589
0.613 0.667 0.529 0.705
IRR
95% CI
0.995 0.866 0.949 1.004
0.955 0.833 0.899 0.957
1.037 0.900 1.002 1.052
2007
IRR
95% CI
0.657 0.678 0.566 0.754
0.607 0.634 0.523 0.703
0.711 0.724 0.612 0.809
IRR
95% CI
0.808 0.778 0.653 0.815
0.759 0.732 0.612 0.767
0.861 0.826 0.697 0.868
BMI: body mass index; BP: blood pressure. IRR: incidence rate ratio. All results adjusted for age, sex, social deprivation, consultation rate and newly registering with a practice.
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little evidence to support our hypothesis that people with SMI might receive less CVD screening in more deprived areas. The aims of our study were deliberately focussed, to avoid multiple testing of hypotheses. Therefore we did not address questions relating to sub-groups who might require more intensive screening such as those prescribed antipsychotics, those with different mental health conditions or those with existing risk factors such as diabetes and smoking. Future studies might explore the management of CVD risk factors which are identified by screening people with SMI. Although there has been improvement in CVD screening over the last decade, in particular for those under 60 years of age, our findings suggest that specific financial incentives for annual reviews of cholesterol, blood pressure, glucose and BMI measurement would improve physical health care for people with SMI. Furthermore, primary care services should ensure that they target all people with SMI including the over-60s who currently receive inferior care. The UK NICE guidance on schizophrenia treatment recommends that this screening takes place in primary care, but also that results are communicated to secondary care mental health services. Although improved screening was temporally related to the introduction of UK QOF, we cannot conclude that this policy was the only driver for change in practice. There has also been an increased awareness of the poor physical health of people with SMI over the last decade. Furthermore, the propensity of some antipsychotics to increase weight and to influence glucose regulation has also been publicized widely. Our results may reflect this awareness; inequalities in BMI and glucose measurement have narrowed while differences in screening for blood pressure and cholesterol remain. There is some evidence that the implementation of the UK QOF improved quality of care in other areas of medicine in the UK. Campbell et al. (2009) explored quality of care in 42 UK general practices for three chronic conditions, namely asthma, coronary heart disease and diabetes. They showed that between 2003 and 2005, quality of care improved for these conditions, but the increases plateaued up to 2007. In our data, increases in cardiovascular screening continued until 2007 (Figs. 1–4), suggesting that improvements were not merely a consequence of financial incentives for GPs and those factors other than QOF may be responsible for the improvements, such as increased awareness amongst health professionals of guidelines regarding cardiovascular screening in SMI. Alternatively, the ongoing increase in screening may reflect a delay in some general practitioners adopting the QOF recommendations. It is reassuring that the provision of cardiovascular screening for people with SMI is not influenced by social deprivation of either the individual's area or the practice. Our study showed that relative rates of screening were independent of the level of deprivation. In other areas of medicine there is some evidence of narrowing in inequalities in care between affluent and deprived areas since the introduction of QOF (Doran et al., 2008). We found no differences in relative rates of screening in the most deprived areas. Therefore, our main finding, of marked inequalities in screening for older people with SMI holds true in all practices irrespective of their level of deprivation. Screening is only the first step in reducing the burden of CVD in people with SMI and we lack evidence regarding the effective reduction of risk in this population. Future studies will need to look in detail at the provision of interventions for people with SMI who have identified risk factors for CVD. The effectiveness of such interventions in real clinical settings is a key question regarding health inequalities for people with SMI and could be explored in future studies utilizing primary care databases.
Supplementary materials related to this article can be found online at doi:10.1016/j.schres.2011.04.003. Role of funding source GB was funded by the UCLH/UCL Comprehensive Biomedical Research Centre. The funder had no role in the study design, data extraction, analysis or interpretation of the data, in the writing of the report or the decision to submit the paper for publication. Contributors DO, IN, IP, RR, and KW designed the study. HL wrote the analysis plan, extracted and cleaned the data. GB performed the data analysis, with input and data interpretation from all authors. DO and GB wrote the first draft of the manuscript and all authors commented extensively and approved the final draft. Conflict of interest All authors confirm that they have no conflicts of interest that could influence the work in this manuscript. Acknowledgements None.
References Campbell, S.M., Reeves, D., Kontopantelis, E., Sibbald, B., Roland, M., 2009. Effects of payfor-performance on the quality of primary care in England. The New England Journal of Medicine 361, 368–378. Citrome, L., Yeomans, D., 2005. Do guidelines for severe mental illness promote physical health and well-being? Journal of psychopharmacology 19 (6 Suppl), 102–109. Dave, S., Petersen, I., 2009. Creating medical and drug code lists to identify cases in primary care databases. Pharmacoepidemiology and Drug Safety 18 (8), 704–707. Doran, T., Fullwood, C., Kontopantelis, E., Reeves, D., 2008. Effect of financial incentives on inequalities in the delivery of primary clinical care in England: analysis of clinical activity indicators for the quality and outcomes framework. Lancet 372 (9640), 728–736. Hippisley-Cox, J., Parker, C., Coupland, C., Vinogradova, Y., 2007. Inequalities in the primary care of patients with coronary heart disease and serious mental health problems: a cross-sectional study. Heart 93, 1256–1262. Maguire, A., Blak, B.T., Thompson, M., 2009. The importance of defining periods of complete mortality reporting for research using automated data from primary care. Pharmacoepidemiology and Drug Safety 18, 76–83. Marder, S.R., Essock, S.M., Miller, A.L., Buchanan, R.W., Casey, D.E., Davis, J.M., Kane, J.M., Lieberman, J.A., Schooler, N.R., Covell, N., Stroup, S., Weissman, E.M., Wirshing, D.A., Hall, C.S., Pogach, L., Pi-Sunyer, X., Bigger Jr., J.T., Friedman, A., Kleinberg, D., Yevich, S.J., Davis, B., Shon, S., 2004. Physical health monitoring of patients with schizophrenia. The American Journal of Psychiatry 161, 1334–1349. National Institute for Health and Clinical Excellence, 2006. National Institute for Health and Clinical Excellence. http://www.nice.org.uk/Guidance/CG38. National Institute for Health and Clinical Excellence, 2009. Clinical Guideline. Schizophrenia(update) http://www.nice.org.uk/CG082. Nazareth, I., King, M., Haines, A., Rangel, L., Myers, S., 1993. Accuracy of diagnosis of psychosis on general practice computer system. British Medical Journal 307, 32–34. NHS Employers, 2005. Revisions to the GMS contract for 2006–7, stage 1: the new QOF areas and indicators. www.nhsemployers.org. Osborn, D.P.J., Nazareth, I., King, M.B., 2006. Risk for coronary heart disease in people with severe mental illness: cross-sectional comparative study in primary care. The British Journal of Psychiatry 188, 271–277. Osborn, D.P.J., Levy, G., Nazareth, I., Petersen, I., Islam, A., King, M., 2007a. Relative risk of cardiovascular and cancer mortality in people with severe mental illness from the UK General Practice Research Database. Archives of General Psychiatry 64, 242–249. Osborn, D.P.J., King, M.B., Nazareth, I., 2007b. Physical activity, dietary habits and coronary heart disease risk factor knowledge amongst people with severe mental illness. A cross sectional comparative study in primary care. Social Psychiatry and Psychiatric Epidemiology 42 (10), 787–793. Roberts, L., Roalfe, A., Wilson, S., Lester, H., 2007. Physical health care of patients with schizophrenia in primary care: a comparative study. Family Practice 24 (1), 34–40. Shah, S., Carey, I.M., Harris, T., DeWilde, S., Cook, D.G., 2011. Quality of chronic disease care for older people in care homes and the community in a primary care pay for performance system: retrospective study. British Medical Journal 342, doi:10.1136/ bmj.d912. Tiihonen, J., Lönnqvist, J., Wahlbeck, K., et al., 2009. 11-year follow-up of mortality in patients with schizophrenia: a population-based cohort study (FIN11 study). Lancet 374, 620–627. Townsend, P., Phillimore, P., Beattie, A., 1986. Inequalities in health in the northern region. Newcastle upon Tyne: Northern Regional Health Authority and University of Bristol.
Contents lists available at ScienceDirect
Schizophrenia Research j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / s c h r e s
Inequalities in the provision of cardiovascular screening to people with severe mental illnesses in primary care Cohort study in the United Kingdom THIN Primary Care Database 2000–2007 David P.J. Osborn a,b,⁎, Gianluca Baio c,d, Kate Walters e,f, Irene Petersen e,f, Heather Limburg e,f, Rosalind Raine c, Irwin Nazareth e,f a
Department of Mental Health Sciences, Royal Free Campus, University College London Medical School, Rowland Hill Street, London, NW3 2PF, UK Camden and Islington Mental Health and Social Care Trust, St. Pancras Way, London, NW1 OPE, UK c Health Care Evaluation Group, Department of Epidemiology and Public Health, University College London, Gower Street, London WC1E 6BT, UK d UCLH/UCL Comprehensive Biomedical Research Centre, 149 Tottenham Court Road, London W1T 7NF, UK e Department of Primary Care and Population Health, University College London Medical School, Rowland Hill Street, London, NW3 2PF, UK f MRC General Practice Research Framework, Stephenson House, 158–160 North Gower Street London, NW1 2ND, UK b
a r t i c l e
i n f o
Article history: Received 22 December 2010 Received in revised form 29 March 2011 Accepted 1 April 2011 Available online 8 May 2011 Keywords: Schizophrenia Bipolar affective disorder Cardiovascular disease Screening Primary care Risk factors
a b s t r a c t Background: People with severe mental illnesses (SMI), including schizophrenia, are at increased risk of cardiovascular disease (CVD). Guidelines recommend regular CVD screening and in the United Kingdom, since 2004, General Practitioners are remunerated for annual reviews. Objectives: To compare annual rates of CVD screening provision in people with and without SMI between 2000 and 2008. Method: We identified 18,696 people with SMI and 95,512 people without SMI in the UK The Health Improvement Network (THIN) primary care database. We compared the rates of measurement of blood pressure (BP), glucose, cholesterol and body mass index (BMI). Results: Prior to 2004, all people with SMI, were significantly less likely to receive each measurement, (including people above and below 60 years of age). In 2003; adjusted incidence rate ratios (95% CI) for screening in people with SMI under 60 years compared to people without SMI were: BMI: 0.62 (0.58–0.65); BP: 0.59 (0.56–0.62); glucose: 0.66 (0.61–0.70) and cholesterol: 0.54 (0.49–0.59). By 2007 people with SMI under 60 were equally likely receive a measurement of BMI: 1.00 (0.96–1.04), glucose: 1.00 (0.96–1.05) and cholesterol: 0.95 (0.90–1.0); the gap in screening for BP had narrowed 0.87 (0.83–0.90). However people with SMI over 60 years of age remained significantly less likely to be screened. There was little difference in screening according to social deprivation. Conclusions: In UK primary care, people with SMI over 60 years of age remain less likely than the general population to receive annual CVD screening despite higher risk of developing CVD. © 2011 Elsevier B.V. All rights reserved.
1. Introduction People with severe mental illnesses (SMI) such as schizophrenia and bipolar disorder die early from cardiovascular disease including myocardial infarction and stroke (Osborn et al., 2007a, 2007b; Tiihonen et al., 2009). There are several reasons for this including high rates of smoking and obesity, poor diet and lack of exercise
⁎ Corresponding author at: Department of Mental Health Sciences, Royal Free Campus, University College London Medical School, Rowland Hill Street, London, NW3 2PF, UK. Tel.: + 44 20 77940500x33950; fax: 44 20 78302808. E-mail addresses: [email protected], [email protected] (D.P.J. Osborn), [email protected] (G. Baio), [email protected] (K. Walters), [email protected] (I. Petersen), [email protected] (H. Limburg), [email protected] (R. Raine), [email protected] (I. Nazareth). 0920-9964/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.schres.2011.04.003
(Osborn et al., 2006, 2007a, 2007b). Antipsychotic and other psychiatric medications may increase weight and cause abnormalities in the regulation of serum glucose and lipids (Marder et al., 2004). The National Institute for Health and Clinical Excellence (2006, 2009) in England recommends that people with SMI have regular reviews of their physical health, with a focus on cardiovascular screening. International guidelines recommend that everyone prescribed antipsychotic medications should have regular measurement of cardiovascular risk factors including glucose, lipids and body mass index (Marder et al., 2004; Citrome and Yeomans, 2005). There is a consensus that the physical health care of people with SMI is primarily the responsibility of primary care services (National Institute for Health and Clinical Excellence, 2006, 2009). In the United Kingdom, the care of people with SMI is included in the General Medical Services GP contract (NHS Employers, 2005). This includes a
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Quality and Outcomes Framework (QOF), whereby practices receive remuneration for keeping a register of people who have a diagnosis of SMI and for offering them an annual review. The precise contents of this annual review are not specified under QOF. The indicators state that age-appropriate health promotion and prevention advice should be given during the review. Therefore, although best practice would include cardiovascular risk assessment, this is not part of the current national contract. A national consultation is currently underway, and there are proposals to specifically include CVD risk factor screening in QOF from 2011. There is small-scale evidence that CVD care and screening may be inferior in people with SMI. People with SMI are less likely to receive appropriate pharmacological interventions once they have developed coronary heart disease (Hippisley-Cox et al., 2007). They may also be less likely to be screened for cardiovascular risk factors before they develop CVD. A study of 195 people with schizophrenia from 22 UK General Practices revealed that people with SMI were significantly less likely to receive screening for all cardiovascular risk factors (Roberts et al., 2007). We do not know whether the introduction of QOF has improved cardiovascular screening in SMI or whether there is a need to more actively promote or incentivise CVD risk screening in this group. We aimed to explore national inequalities in the provision of cardiovascular screening to people with SMI in a large representative sample of patients in primary care and to assess whether provision of screening had improved over time and since the introduction of QOF in 2004. A secondary aim was to determine whether any inequalities in CVD screening for people with SMI were associated with social deprivation. We hypothesized that the competing demands of working with deprived populations would make it more difficult to meet standards of physical health care for people with SMI.
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the methods described by Dave and Petersen (2009) to identify all people with diagnoses of non-organic psychoses and bipolar affective disorders, schizophrenia, schizo-affective disorder, depressive psychosis, persistent delusional disorders and “psychoses not otherwise specified”. To improve validity of diagnosis we only included patients whose diagnosis was entered or re-entered after 1990.
2.4.2. People without SMI We selected six times the number of comparison patients, who did not have a SMI diagnosis. We frequency-matched by 5 year age bands, by practice and gender.
2.4.3. All patients We included patients with at least 6 months of follow-up data. To ensure data quality we only included data after the date at which each practice had reached pre-defined THIN quality standards for acceptable computer use and acceptable mortality recording (Maguire et al., 2009).
2.4.4. Follow-up period The start date for each patient was the maximum (latest) of the following: date of registration at the practice or the date when practice met acceptable data quality standards above. The end date was either December 2007, or the date when the patient left the practice or died. Although we received some records from 2008; we were unable to use the data as we did not have access to the full calendar year. Exclusion criteria: People with pre-existing CVD and patients who registered but had no further record of attendance at the practice.
2. Methods 2.1. Study design Retrospective cohort study. 2.2. Setting/population Adults in the United Kingdom registered with a practice contributing to the primary care database The Health Improvement Network (THIN) during the Jan 2000–Dec 2007 period. 2.3. Data source THIN provides anonymized clinical data from 420 general practices in England, Scotland, Wales and Northern Ireland. The database includes around 6 million patients and is a powerful resource for epidemiological and health services research. Since most people with SMI are registered with primary care, it is highly suitable for studying these conditions. The validity of GP computer diagnoses of SMI has been established (Nazareth et al., 1993). THIN includes information for each individual on diagnoses, prescriptions, referrals, CVD risk factors including smoking, and local deprivation for an individual's postcode (using quintiles of Townsend score; see Section 2.5). Diagnoses, symptoms and lifestyle information are entered into the database by GPs and practice staff as Read codes (Dave and Petersen, 2009) as part of routine clinical care and the database is regularly updated. All practices were using Vision software. 2.4. Inclusion criteria 2.4.1. People with SMI All people aged over 18 years of age with a practice computer diagnosis of severe mental illness. We created Read code lists using
2.5. Data extracted 2.5.1. Main outcomes We recorded whether each patient had a recording of the following individual measurements during each calendar year. 1) Systolic and/or diastolic blood pressure 2) Body mass index, (including weight measurement if height had already been documented in a previous year) 3) Serum glucose (random or fasting) 4) Serum total cholesterol
2.5.2. Other variables We also extracted data regarding age, sex, time since initial diagnosis of SMI, mean annual consultation rate at the practice, and whether a patient had newly registered within each year. We included the latter variable, since screening is more likely to be performed as part of the baseline registration procedures at a new practice. THIN includes an area-based indicator of patients' socioeconomic circumstances. Each enumeration district (around 150 households) is assigned a Townsend Deprivation score (Townsend et al., 1986).These are divided into national quintiles and patients are assigned a quintile score according to the enumeration district in which they live. The Townsend score is made up of four deprivation indices for an area; the percentage unemployed; the percentage of households who own their home and own a car, and level of overcrowding. We also calculated an aggregate social deprivation score for each general practice by taking the mean individual Townsend score for all patients within that practice. We used this continuous variable to assess the importance of practice-level deprivation.
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2.6. Analysis First we determined the proportion of people who had received screening for BMI, BP, glucose and cholesterol in each calendar year from 2000 to 2007. We calculated the unadjusted proportions screened, comparing all people with and without SMI. We then stratified by sex, age-group and individual social deprivation (area postcode) to assess whether each of these variables influenced any differences in screening between SMI and non-SMI. Time trends in screening were explored graphically, plotting the proportions screened and their 95% confidence intervals. For the multivariable analysis we used random effects Poisson regression, to account for clustering by practice. To assess the significance of time trends in rates of screening we included an interaction term between calendar year and SMI status in the Poisson model and employed a likelihood ratio test to assess if the interaction term improved the fit of the model and therefore whether any increases in screening over time differed significantly between people with and without SMI. To determine the magnitude of any differences in rates of annual screening between people with and without SMI we calculated incidence rate ratios; IRRs. We built separate models and derived IRRs in four different calendar years, namely 2000 (baseline), 2003 (preQOF), 2005 (post QOF) and 2007 (the last complete year in the dataset). We adjusted for age, sex, social deprivation, consultation rate and newly registering with a practice. We assessed whether social deprivation affected provision of screening as follows. First we compared the proportions of people with and without SMI who were screened for each risk factor, stratified according to quintiles of Townsend deprivation score for their domestic postcode. We assessed the importance of practice level deprivation as follows: Separate Poisson regression models were built with each of the four CVD risk factors as the dependent outcomes. Once again we built these models for the years 2000 (baseline), 2003 (pre-QOF), 2005 (post-QOF) and 2007 (the last complete year in the dataset). To test the hypothesis that relative rates of screening would be more pronounced in practices with greater deprivation, we also included an interaction term between SMI and practice deprivation as a continuous variable and tested its significance with a likelihood ratio test. Due to the large numbers of patients in THIN studies, interaction terms may appear significant by chance. Therefore we imposed a significance threshold of p b 0.01 to determine whether an interaction term was important statistically. 2.7. Ethics The study had ethical approval from the London Research Ethics Committee. Reference number: 09/H0718/11. 3. Results 3.1. Sample We identified 18,696 people with SMI and 95,512 comparison patients without an SMI diagnosis. The characteristics of the two cohorts are described in Table 1. The mean follow-up was 5.7 years for people with SMI and 6.9 years for people without SMI. The majority of the SMI cohort had a diagnosis of schizophrenia, bipolar disorder or schizo-affective disorder. The unadjusted screening results can be viewed graphically in Figs. 1–4, and the proportions screened for each risk factor in each calendar year are reported in Appendices 1–2. Results were similar for age groups under 60, but were different for those aged 60 and over. Therefore all the analyses were stratified according to age, above and below 60.
Table 1 Characteristics of cohorts with and without severe mental illnesses. SMI N (%) Mean age (SD) % Female (SE) Mean follow up in years (SD) Mean time since diagnosis (SD) Diagnosis Schizophrenia/schizoaffective disorder (%) Bipolar disorder (%) Other psychosis (%) Mean consultation rate per annum (SD) New registered — (%) Deprivation — missing (%) Deprivation — 1st quintile: least deprived (%) Deprivation — 2nd quintile (%) Deprivation — 3rd quintile (%) Deprivation — 4th quintile (%) Deprivation — 5th quintile: most deprived (%) Mean practice level deprivation (SD) [range 1–5]
Non-SMI
18,696 52.1 49.48 5.7 5.6
(16.4) (18.7) (0.5) (2.4) (3.8)
6983 4586 7127 9.0 3411 885 2452 2660 3520 4432 4747 2.81
(37.4) (24.5) (38.1) (11.8) (18.2) (4.7) (13.1) (14.2) (18.9) (23.7) (25.4) (0.8)
95,512 53.2 52.6 7.0
(83.4) (19.0) (0.2) (2.1)
5.7 26,973 4016 19,854 18,328 19,435 18,795 15,084 2.80
(6.2) (28.2) (4.2) (20.8) (19.2) (20.4) (19.7) (15.8) (0.8)
SMI: severe mental Illness. SD: standard deviation.
Changes in screening rates for cardiovascular risk factors 2000– 2007. The annual screening rates increased for all four risk factors during the study period, both for people with and without SMI. Marked inequalities in screening provision were apparent early in the decade, but this gap narrowed considerably for all risk factors by 2007 (Figs. 1–4). These increases in annual rates of screening between 2000 and 2007 were significantly different for people with and without SMI; the rate of increase in screening was greater for people with SMI. In Poisson regression, interaction terms between calendar year and SMI status significantly improved the models for all four risk factors (likelihood ratio tests comparing models with and without the SMI × calendar year interaction term: all p values b 0.001, except glucose in the over-60s p = 0.002). 3.2. Comparison of screening rates between SMI and non-SMI For each risk factor, Poisson regression models better predicted screening when the following co-variates were included: age, sex, being newly registered at a practice and consultation rate. 3.2.1. BMI Fig. 1 shows time trends in screening for BMI. Proportions screened each year are compared according to sex and age-group. Before 2004, people with SMI under 60 were far less likely to be screened, but by 2007, they were equally likely to receive a BMI measurement as people without SMI. This was true for both males and females. However the over-60s with SMI were still less likely to receive a BMI recording, even by 2007 (Fig. 1). The results were similar in the adjusted analysis; in 2007, people with SMI over 60 were less likely to have a record of BMI (Table 2). 3.2.2. Blood pressure Between 2000 and 2007 there was a general increase in blood pressure measurement for people with SMI, however by 2007 people with SMI were still significantly less likely to have a blood pressure recording compared to people without SMI. This difference was particularly marked in the over-60s (Fig. 2 and Appendix 1). The adjusted analysis confirmed that even by 2007, blood pressure was less likely to be recorded in people with SMI, aged both below and above 60 (Table 2).
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Proportion screened for BMI - Female
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Fig. 1. Proportion of people with and without Severe Mental Illnesses (SMI) who received a BMI measurement in each year from 2000 to 2007. Unadjusted data.
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Fig. 2. Proportion of people with and without Severe Mental Illnesses (SMI) who received a Blood pressure measurement in each year from 2000 to 2007. Unadjusted data.
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Proportion screened for Cholesterol - Male
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Fig. 3. Proportion of people with and without Severe Mental Illnesses (SMI) who received a cholesterol measurement in each year from 2000 to 2007. Unadjusted data.
3.2.3. Cholesterol A similar pattern emerged for cholesterol (Fig. 3). People with SMI were less likely to be screened early in the decade, but by 2007, this inequality had disappeared for people with SMI under 60, and their cholesterol was more likely to be measured. However once again, the over 60s with SMI were far less likely to receive cholesterol testing than their counterparts without SMI. This pattern was confirmed by the adjusted analysis; in 2007 people with SMI under 60 were equally likely to receive a cholesterol measurement, but those under 60 were less likely than their counterparts without SMI (IRR 0.65; 95% CI: 0.61–0.70. Table 2).
3.3.2. Practice level deprivation Practice level deprivation also exerted little influence on any inequalities in screening. Interaction terms were explored between SMI and practice deprivation for each of the four main risk factors, in 2000, 2003, 2005 and 2007. Separate Poisson models were built for the over and under 60s. None of the interaction terms were significant at p b 0.01, suggesting little difference in the relative rates of screening between people with and without SMI in areas with greater social deprivation.
3.2.4. Glucose Serum glucose testing also increased over time in all groups with SMI and by 2007, there was no significant gap between total proportions receiving a glucose measurement comparing those with and without SMI (Fig. 4). Once again, the over 60s were an exception; people with SMI in this age bracket were less likely to be screened than people over 60 without SMI. These 2007 findings remained the same after adjusting in the Poisson regression (Table 2).
There has been a yearly increase in the proportion of people with SMI who receive cardiovascular screening over the last decade in UK primary care. Since the introduction of financial incentives for GPs in the Quality and Outcomes Framework (QOF) policy in 2004 there has been an increase in recording of glucose, BMI, cholesterol and Blood pressure for people with SMI. Before 2004, there were marked inequalities and people with SMI were half as likely to be screened for CVD risk factors, compared to people without SMI. By 2007, people with SMI under 60 were equally likely to be screened for glucose, BMI and cholesterol. However, they remained significantly less likely to receive a blood pressure measurement. It is reassuring that younger people with SMI are now equally likely to be screened, given their propensity for developing early diabetes, lipid abnormalities and new onset CVD. However, in the UK NICE recommends that people with SMI have an annual cardiovascular risk check. In 2007, although inequalities had mostly disappeared for the under-60s, the majority of people with SMI did not have a primary care record for the four CVD risk factors we studied (Figs. 1–4). Care for people with SMI over 60 remains inferior to their counterparts without SMI, and there is no clinical or epidemiological
3.3. Inequalities in screening and social deprivation 3.3.1. Individual deprivation: Within SMI For each CVD risk factor, there was little consistent association between Townsend deprivation quintiles and the proportions of people with SMI who were screened each year (unadjusted data; Appendices 1 and 2). For instance, for blood pressure, the proportion screened in 2006 was 40.1% for people living in the least deprived post-codes and 40.7% for those living in the most deprived areas (Appendix 1). For glucose, the proportions from 2006 were 27.3% (least deprived) and 27.5% (most deprived).
4. Discussion
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Proportion screened for Glucose - Female
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year
Fig. 4. Proportion of people with and without Severe Mental Illnesses (SMI) who received a glucose measurement in each year from 2000 to 2007. Unadjusted data.
justification for this. People with SMI between 50 and 70 are twice as likely to develop heart disease as the general population (Osborn et al., 2007a, 2007b). The inequality in this older age group may reflect that the general population without SMI are much more likely to be screened once they pass the age of 60. In the United Kingdom, there are no specific schemes to remunerate general practitioners for assessing or managing elderly people. The QOF system is targeted at a number of chronic diseases rather than specific age groups. However there is some evidence that other groups of vulnerable elderly people may be served less well by QOF. A recent study compared care provision to elderly people living in the community and those in residential homes. Delivery of care was significantly poorer for those in residential homes, on a number of quality indicators such as the management of both heart disease and diabetes (Shah et al., 2011).
Our study has a number of strengths, including the large size and representative nature of the national sample, as well as the ability to control for other factors which might predict inequalities in screening especially consultation rate and deprivation. We took a thorough but conservative approach to exploring the effects of deprivation, using both practice and individual levels of deprivation, although personal postcode is still a proxy for individual deprivation. The exploration of deprivation effects involved building multiple Poisson regression models for each risk factor in four calendar years. Therefore we looked for consistent patterns in any interaction terms across 4 years within the decade, across the risk factors. We were deliberately conservative in interpretation of interaction terms, because the large sample size and multiple tests could lead to spurious significant findings occurring by chance. However there was
Table 2 Results from Poisson regression. Adjusted incidence rate ratios for being screened for body mass index, blood pressure, cholesterol and glucose in people with SMI, compared with people without SMI. 2000–2007. People aged 18–59
BMI: Adj IRR for BMI in SMI BP: Adj IRR for BP in SMI Cholesterol: Adj IRR for cholesterol in SMI Glucose: Adj IRR for glucose in SMI People aged 60 and above
BMI: Adj IRR for BMI in SMI BP: Adj IRR for BP in SMI Cholesterol: Adj IRR for cholesterol in SMI Glucose: Adj IRR for glucose in SMI
2000
2003
IRR
95% CI
0.599 0.579 0.477 0.643
0.546 0.539 0.404 0.576
0.657 0.622 0.563 0.717
2000
2005
IRR
95% CI
0.615 0.591 0.540 0.655
0.578 0.562 0.492 0.613
0.653 0.622 0.591 0.701
2003
IRR
95% CI
0.571 0.557 0.440 0.697
0.490 0.501 0.364 0.607
0.666 0.620 0.532 0.799
2007
IRR
95% CI
0.793 0.709 0.750 0.825
0.756 0.679 0.704 0.782
0.833 0.739 0.801 0.870
2005
IRR
95% CI
0.553 0.618 0.477 0.645
0.499 0.573 0.429 0.589
0.613 0.667 0.529 0.705
IRR
95% CI
0.995 0.866 0.949 1.004
0.955 0.833 0.899 0.957
1.037 0.900 1.002 1.052
2007
IRR
95% CI
0.657 0.678 0.566 0.754
0.607 0.634 0.523 0.703
0.711 0.724 0.612 0.809
IRR
95% CI
0.808 0.778 0.653 0.815
0.759 0.732 0.612 0.767
0.861 0.826 0.697 0.868
BMI: body mass index; BP: blood pressure. IRR: incidence rate ratio. All results adjusted for age, sex, social deprivation, consultation rate and newly registering with a practice.
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little evidence to support our hypothesis that people with SMI might receive less CVD screening in more deprived areas. The aims of our study were deliberately focussed, to avoid multiple testing of hypotheses. Therefore we did not address questions relating to sub-groups who might require more intensive screening such as those prescribed antipsychotics, those with different mental health conditions or those with existing risk factors such as diabetes and smoking. Future studies might explore the management of CVD risk factors which are identified by screening people with SMI. Although there has been improvement in CVD screening over the last decade, in particular for those under 60 years of age, our findings suggest that specific financial incentives for annual reviews of cholesterol, blood pressure, glucose and BMI measurement would improve physical health care for people with SMI. Furthermore, primary care services should ensure that they target all people with SMI including the over-60s who currently receive inferior care. The UK NICE guidance on schizophrenia treatment recommends that this screening takes place in primary care, but also that results are communicated to secondary care mental health services. Although improved screening was temporally related to the introduction of UK QOF, we cannot conclude that this policy was the only driver for change in practice. There has also been an increased awareness of the poor physical health of people with SMI over the last decade. Furthermore, the propensity of some antipsychotics to increase weight and to influence glucose regulation has also been publicized widely. Our results may reflect this awareness; inequalities in BMI and glucose measurement have narrowed while differences in screening for blood pressure and cholesterol remain. There is some evidence that the implementation of the UK QOF improved quality of care in other areas of medicine in the UK. Campbell et al. (2009) explored quality of care in 42 UK general practices for three chronic conditions, namely asthma, coronary heart disease and diabetes. They showed that between 2003 and 2005, quality of care improved for these conditions, but the increases plateaued up to 2007. In our data, increases in cardiovascular screening continued until 2007 (Figs. 1–4), suggesting that improvements were not merely a consequence of financial incentives for GPs and those factors other than QOF may be responsible for the improvements, such as increased awareness amongst health professionals of guidelines regarding cardiovascular screening in SMI. Alternatively, the ongoing increase in screening may reflect a delay in some general practitioners adopting the QOF recommendations. It is reassuring that the provision of cardiovascular screening for people with SMI is not influenced by social deprivation of either the individual's area or the practice. Our study showed that relative rates of screening were independent of the level of deprivation. In other areas of medicine there is some evidence of narrowing in inequalities in care between affluent and deprived areas since the introduction of QOF (Doran et al., 2008). We found no differences in relative rates of screening in the most deprived areas. Therefore, our main finding, of marked inequalities in screening for older people with SMI holds true in all practices irrespective of their level of deprivation. Screening is only the first step in reducing the burden of CVD in people with SMI and we lack evidence regarding the effective reduction of risk in this population. Future studies will need to look in detail at the provision of interventions for people with SMI who have identified risk factors for CVD. The effectiveness of such interventions in real clinical settings is a key question regarding health inequalities for people with SMI and could be explored in future studies utilizing primary care databases.
Supplementary materials related to this article can be found online at doi:10.1016/j.schres.2011.04.003. Role of funding source GB was funded by the UCLH/UCL Comprehensive Biomedical Research Centre. The funder had no role in the study design, data extraction, analysis or interpretation of the data, in the writing of the report or the decision to submit the paper for publication. Contributors DO, IN, IP, RR, and KW designed the study. HL wrote the analysis plan, extracted and cleaned the data. GB performed the data analysis, with input and data interpretation from all authors. DO and GB wrote the first draft of the manuscript and all authors commented extensively and approved the final draft. Conflict of interest All authors confirm that they have no conflicts of interest that could influence the work in this manuscript. Acknowledgements None.
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