International Journal of Cardiology 171 (2014) 346–350
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Reversing social disadvantage in secondary prevention of coronary heart disease Michael V. Jelinek a,b,c,⁎, John D. Santamaria a,b, James D. Best a,b, David R. Thompson c, Andrew M. Tonkin d, Margarite J. Vale b,1 a
St Vincent's Hospital, Melbourne, Australia The University of Melbourne, Department of Medicine, St Vincent's Hospital, Melbourne, Australia Cardiovascular Research Centre, Australian Catholic University, East Melbourne, Australia d Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia b c
a r t i c l e
i n f o
Article history: Received 2 August 2013 Received in revised form 4 November 2013 Accepted 12 December 2013 Available online 24 December 2013 Keywords: Secondary prevention Coronary disease Risk factors Telephone Rehabilitation
a b s t r a c t Background: To compare and contrast the coronary heart disease (CHD) risk factors of lower socio-economic status public hospital patients with those of privately insured CHD patients before and after six months of telephone delivered coaching using The COACH Program. Methods: A retrospective observational study which contrasts the lifestyle and biomedical coronary risk factor status of 2256 public hospital patients with the same risk factors of 3278 patients who had private health insurance. All patients received an average of 5 coach sessions over 6 months. Results: The public hospital patients were four years younger and had multiple measures confirming their lower socio-economic status than their private hospital counterparts. At entry to the program, the public hospital patients had worse risk factor levels than the privately insured patients for total and LDL-cholesterol, triglycerides, fasting glucose, smoking and physical activity levels (P b 0.0001) but better status for systolic and diastolic blood pressures and alcohol intake. At exit from the program, many of these differences had diminished or disappeared. The public hospital patients had greater improvements in their risk factor status for total and LDL-cholesterol, fasting glucose, body weight, smoking status and physical activity level than did the privately insured patients (P b 0.05). Conclusions: This paper demonstrates that a program of initiating contact with patients with CHD, identifying treatment gaps in their management and coaching to achieve guideline recommended risk factor targets can help reduce health inequalities in such patients and thus benefit all patients in the context of ongoing secondary prevention. © 2013 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Coronary heart disease (CHD) is a lifelong condition which results in a very large burden of death, disability, and health care costs. Whilst some patients die in the initial clinical episode, most will survive to leave hospital and a program of secondary prevention will be recommended. Exercise based cardiac rehabilitation has been the method recommended by authorities to educate the patient and reduce the risk of recurrence of CHD events and premature mortality [1–5]. Systematic review of best practice exercise based cardiac rehabilitation has shown that such programs reduce all-cause and cardiovascular mortality,
⁎ Corresponding author at: St Vincent's Hospital, Melbourne, Australia. E-mail address: [email protected] (M.V. Jelinek). 1 Margarite J Vale is the director of The COACH Program. The data used in this study is not owned by The COACH Program. The data used in this study is owned by each health organisation using The COACH Program. The data was collected by each organisation as part of the usual care of delivering The COACH Program and not for study purposes. 0167-5273/$ – see front matter © 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijcard.2013.12.022
decrease hospital readmissions, and improve coronary risk factors [6,7]. However, despite widespread recommendations for the use of exercise based cardiac rehabilitation, only 10–30% of eligible patients attend these programs. This poor attendance has remained steady for at least 20 years despite major attempts to raise the profile and attendance at cardiac rehabilitation [8–11]. Most disturbing has been the finding that non-attenders at cardiac rehabilitation are typically older, are more likely to be female, have lower health literacy and worse coronary risk factors (particularly smoking), more complications of vascular disease and poorer left ventricular function. They are also more likely to be socio-economically disadvantaged [12,13]. There have been several responses to the problem of poor attendance of the neediest groups of patients. Some have recommended home based cardiac rehabilitation programs [14,15]. Others have recommended the use of practice nurses [16]. We have developed The COACH Program, a coaching program delivered by telephone and mail outs for patients with CHD in which a health professional coach trains patients to vigorously pursue the target levels for their particular coronary risk factors whilst working in partnership with the patient's own doctors.
M.V. Jelinek et al. / International Journal of Cardiology 171 (2014) 346–350
The benefits of The COACH Program have been demonstrated in two randomised controlled trials [17,18]. Furthermore, the improvements in coronary risk factor status achieved at six months are sustained for at least the next 18 months after cessation of coaching [19]. The program has been introduced to the public health system in all Australian states, financed by the state government health departments, and also most health insurance organisations which support patients discharged from private hospitals. All Australian citizens are entitled to hospital care funded in part by a taxation levy based on their annual income. Nearly one-half of Australians have additional health insurance which entitles them to the doctor and hospital of their choice, and the timing of an elective procedure. Private health insurance costs the average working Australian around 5% of their annual income. The lower an individual's personal income, the higher the proportion of that income which is spent on private medical care. Hence patients in private hospitals are usually of higher socio-economic status than those treated in the public hospital systems. On this background we aimed to compare the impact of The COACH Program on the coronary risk factor status in public and private health systems. In turn, this has allowed us to see whether this telephone assisted management could impact on the more disadvantaged patient who might not attend a typical exercise based cardiac rehabilitation program. 2. Methods 2.1. The COACH Program Coaching sessions are provided by a series of telephone calls and mail outs after the patient has been discharged from hospital, usually over a period of six months. A distinguishing feature of The COACH Program is that coaches identify and assist patients to close treatment gaps in the management of their lifestyle and biomedical risk factors. These ‘treatment gaps’ are gaps between the evidence based guideline recommended treatments patients should be receiving as against what they are actually receiving. Progress towards achieving risk factor targets is regularly monitored by the coach, who provides a structured written report that is a summary of each verbal coaching session. The written report is followed by a risk factor chart which lists the coronary risk factors, the actual risk factors levels for the patient, how they compare to the guideline recommended target levels and whether the targets have been achieved. The COACH Program is applicable to all patients with recent CHD hospitalisation, but in particular is appropriate for those patients with short stay admissions nowadays seen after percutaneous coronary interventions who may or may not have suffered myocardial infarction. The COACH Program is also especially useful for patients living in remote locations where access to cardiac rehabilitation or even primary medical care may be difficult. 2.2. The patients The patients reported in this study were either managed in public hospital systems run by two large Australian states or derived from any one of four private health funds throughout Australia. The coaches were dietitians or nurses who had been formally trained in The COACH Program methodology and in the use of the appropriate software. Patients were recruited either in-hospital or after discharge from hospital after an admission for CHD. The duration of involvement in The COACH Program for each patient was up to six months. We report here on all the patients enrolled by either public or private hospitals between March 21st 2007 and December 16th 2011. 2.3. Socio-economic status Objective support for our hypothesis that public hospital patients were, on average, more socially disadvantaged than private hospital patients was obtained by asking the patients for the highest level of education that they had achieved, and by using postcode derived measures of social advantage or disadvantage derived from data from the Australian Bureau of Statistics Socio-Economic Indexes for Areas (SEIFA) [20]. SEIFA is a suite of four summary measures that have been created from 2006 Census information. The indexes can be used to explore different aspects of socioeconomic conditions by geographic areas. For each index, every geographic area in Australia is given a SEIFA score which shows how disadvantaged that area is compared with other areas in Australia. Each index summarises a different aspect of the socio-economic conditions of people living in an area. They each summarise a different set of social and economic information. The indexes take into account a range of factors in determining socio-economic conditions.
347
The four indexes in SEIFA 2006 are: • Index of Relative Socio-economic Disadvantage: focuses primarily on disadvantage, and is derived from Census variables like low income, low educational attainment, unemployment, and dwellings without motor vehicles. • Index of Relative Socio-economic Advantage and Disadvantage: is a continuum of advantage (high values) to disadvantage (low values), and is derived from Census variables related to both advantage and disadvantage. • Index of Economic Resources: focuses on financial aspects of advantage and disadvantage, using Census variables relating to residents' incomes, housing expenditure and assets. • Index of Education and Occupation: includes Census variables relating to the educational attainment, employment and vocational skills.
2.4. Variables measured All blood test results for fasting lipid profile, fasting glucose and HbA1c in patients with diabetes were verified by the coach from pathology reports. Information regarding blood pressure, body mass index (BMI), waist measurement, smoking status, alcohol intake and performance of regular moderate intensity physical activity was obtained by coaches over the telephone from patient self-report. Coronary risk factor targets were those recommended by the National Heart Foundation of Australia and the Cardiac Society of Australia and New Zealand (see Table 1).
2.5. Statistical analysis Analysis was performed on de-identified patient data. For categorical data, the tables of variables for public versus private are shown. Data are expressed as median (interquartile) range for continuous variables, and numbers (percentage) for categorical variables. Comparisons between groups were made with non-parametric methods (Mann–Whitney U test, Kruskal–Wallis test) and with Fisher's Exact Test or chi-squared analysis, respectively. Data were analysed with Stata version 12 (StataCorp, College Station, TX) and a P-value less than 0.05 set for statistical significance. Differences in coronary risk factor status were compared from entry to The COACH Program to the end of the coaching six months later. Comparison was made on the status of patients in public and private hospitals on admission to The COACH Program, discharge from The COACH Program and the net difference between the admission and discharge status of these patients in the two differing health care systems.
3. Results 3.1. Patient demographics Table 2 presents the patient demographics. There were 2266 public hospital patients and 3278 private hospital patients. The public hospital patients were 4 years younger than those derived from private hospitals (P b 0.0001). There were a higher proportion of women and indigenous Australians in the public hospital patients (P b 0.0001). Public hospital patients were, on average, less well educated than were the private hospital patients (P b 0.0001). More public hospital patients were employed and more private hospital patients were not in the workforce or looking for work (P b 0.0001). All of the postcode (SEIFA) derived information confirmed that the public hospital patients were, on average, of lower socio-economic status (P b 0.0001).
3.2. Coronary risk factor status on admission to The COACH Program On entry to The COACH Program, nearly all coronary risk factors of public hospital patients were worse than their privately insured counterparts (Table 3). The public hospital patients had higher total and LDL-cholesterol levels, higher triglyceride levels, higher fasting blood glucose levels, higher body weight, and lower levels of physical activity (P b 0.0001). A much higher proportion of public hospital patients were smokers on entry to The COACH Program than were privately insured patients (19.5% v 2.4%, P b 0.0001). A higher proportion of privately insured patients consumed alcohol above the recommended targets than did public hospital patients (P = 0.007). On admission to The COACH Program, the blood pressure of the public hospital patients was 4/4 mm Hg lower than that of the privately insured patients (P b 0.01).
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M.V. Jelinek et al. / International Journal of Cardiology 171 (2014) 346–350
Table 1 National Heart Foundation targets used in The COACH Program [29]. Coronary risk factors
Targets
Biomedical risk factors Total cholesterol LDL-cholesterol Triglycerides HDL-cholesterol Blood pressure Fasting glucose (without diabetes) HbA1c (diabetics only)
b4 mmol/L b2 mmol/L b1.5 mmol/L N1.0 mmol/L b130/80 mm Hg b5.5 mmol/L ≤7.0%
Lifestyle risk factors Smoking Waist measurement
Complete cessation of smoking and avoidance of second hand smoke ≤94 cm for men; ≤80 cm for women b25 kg/m2 At least 30 min of moderate intensity physical activity of most, preferably all days of the week No more than 2 standard drinks per day for men and women No more than 1 standard drink per day for women with high BP At least 2 alcohol free days per week for men and women with high BP
BMI Physical activity Alcohol intake
3.3. Coronary risk factor status on exit from The COACH Program The average duration of The COACH Program was 190 days (IQR 126, 217) for public hospital patients compared with 182 days for private patients (IQR 126, 218). Table 4 shows that at exit from The COACH Program, differences between the public hospital and privately insured patients had disappeared for LDL-cholesterol, diastolic BP, and fasting blood glucose. The differences between public hospital patients and privately insured patients had been reduced for total cholesterol, waist circumference and smoking status. Public hospital patients reported a 9.7% rate of smoking cigarettes at exit from The COACH Program (a 50% reduction from to entry to exit) compared with 2.1% smoking at exit in the privately insured patients. The worse coronary risk factor status of the public hospital patients remained for triglycerides, HDLcholesterol, smoking and body weight (P b 0.0001). The paradox of the better risk factor status for public hospital patients persisted for systolic BP and for excess alcohol intake (P b 0.0001). More public hospital patients reported that they were now physically active than the privately insured patients (P b 0.0001). 3.4. Changes from entry to exit for The COACH Program All the lifestyle and biomedical risk factors were better at exit from The COACH Program than at entry (P b 0.0001) [25]. However, greater
improvements in the risk factors occurred in the public patients than in the privately insured patients for fasting blood glucose, body weight, smoking, physical activity (all P b 0.0001), total and LDL-cholesterol and diastolic BP (P b 0.05). 4. Discussion The important result of this study is that The COACH Program had a more favourable impact on coronary risk factors in the lower socioeconomic public patients than in privately insured patients. All the coaches were formally trained in the delivery of The COACH Program. The coaches in public hospitals were employed by the state government health departments and the coaches in the private health care system were employed by the health insurance organisations. The coaches gave equal time to the patients in both health care systems. The greater improvements seen in the public hospital patients reflected their social disadvantage at entry into the program compared with the privately insured patients. The public hospital patients were four years younger at presentation to The COACH Program than their private hospital counterparts and the post-code (SEIFA) data confirm the hypothesis that these patients were of lower socio-economic status than the privately insured patients. The younger age of the public hospital patients explains why more of these patients were still working and actively seeking employment than the private patients. Furthermore, the coronary
Table 2 Demographic characteristics and socioeconomic status; continuous variables are median (interquartile range), categorical variables are %. Public
Private
Significance
Number of patients Age, years Gender, male n (%) Aboriginal & Torres Strait Islander, n (%) Prior CVD
2266 62.3 (53.5, 70.2) 1643 (72.5%) 73 (3.2%) 1055 (46.6%)
3278 66.4 (60.7, 72.2) 2521 (76.9%) 14 (0.4%) 2320 (47.5%)
b0.0001 b0.0001 b0.0001 NS
Employment status, n (%) Employed Not in labour force Unemployed (looking for work)
942 (44.0%) 1157 (54.0%) 43 (2.0%)
1286 (40.7%) 1851 (58.6%) 22 (0.7%)
b0.0001
Highest level of education completed, n (%) Primary schooling or less Secondary schooling Tertiary technical education University diploma/degree
63 (6.0%) 499 (47.4%) 277 (26.3%) 214 (20.3%)
51 (1.8%) 1281 (43.9%) 851 (29.1%) 737 (25.2%)
b0.0001
SEIFA measures of socioeconomic status Advantage/disadvantage Disadvantage Resource score Education/occupation
976 (937, 1021) 992 (956, 1031) 1005 (973, 1037) 951 (922, 987)
1001 (960, 1067) 1011 (978, 1062) 1009 (976, 1057) 977 (939, 1053)
b0.0001 b0.0001 b0.0001 b 0.0001
M.V. Jelinek et al. / International Journal of Cardiology 171 (2014) 346–350 Table 3 Entry into The COACH Program; continuous variables are median (interquartile range), categorical variables are %. Coronary risk factors
Public
Private
Significance
Total cholesterol (mmol/L) Triglycerides (mmol/L) LDL-cholesterol (mmol/L) HDL-cholesterol (mmol/L) Systolic BP (mm Hg) Diastolic BP (mm Hg) Fasting blood glucose (mmol/L) HbA1c% (diabetics only) Smoking status (current smokers) Waist circumference (cm) Weight (kg) Alcohol consumption (at target) Physical activity (at target)
4.4 (3.6, 5.3) 1.5 (1.1, 2.3) 2.5 (1.8, 3.3) 1.0 (0.9, 1.2) 121 (113, 130) 70 (67, 80) 5.5 (5.2, 6.1) 7.5 (6.6, 9.0) 428 (19.5%) 96.0 (89, 104) 84 (73, 96) 1580 (78.3%) 956 (45.4%)
4.2 (3.5, 5.1) 1.3 (1.0, 1.9) 2.3 (1.8, 3.1) 1.2 (1.0, 1.4) 125 (120, 135) 74 (70, 80) 5.3 (4.9, 5.7) 6.9 (6.3, 7.6) 79 (2.4%) 96.5 (90, 104) 82 (72, 92) 2306 (75.7%) 1765 (54.6%)
0.0007 b0.0001 b0.0001 b0.0001 b0.0001 0.0016 b0.0001 b0.0001 b0.0001 NS b0.0001 0.007 b0.0001
risk factor status of the public hospital patients was poorer than the private hospital patients for all coronary risk factors except the blood pressure. The finding of poorer coronary risk factor status in patients with poorer socio-economic circumstances is well recognised [21,22]. The lower blood pressure of the public hospital patients is most likely explained by their younger age at presentation. Unlike the prescription of pharmaceuticals, cardiac rehabilitation is not a standardised treatment. Variations in the practice of cardiac rehabilitation result from differences in the frequency and duration of cardiac rehabilitation programs, the intensity of the exercise prescribed in the programs, the presence or absence of psychological support, and the use and quality of education given in these programs. A recent randomised controlled trial of cardiac rehabilitation as usually practised in Britain showed that cardiac rehabilitation failed to impact on total mortality, cardiac morbidity, health related quality of life and behavioural risk factors. In fact, patients randomised to cardiac rehabilitation were performing less physical activity at follow-up than those in the control group [23]. Whilst this trial was met with widespread concern and disbelief one observer suggested that cardiac rehabilitation, as usually performed in Britain, might not be “fit for purpose” [24]. We have previously shown that The COACH Program reliably improves five lifestyle and eight biomedical coronary risk factors [25]. In this paper, we have shown that The COACH Program results in greater improvements in these coronary risk factors in the more socially disadvantaged public hospital patients who enter the programs younger and with worse risk factor profiles than more socially advantaged privately insured patients and exit the program almost on equal terms. In the long-term, improved risk factor status is likely to reduce CHD morbidity and mortality rates [26–28]. 4.1. Study limitations This is an observational cohort study based on the superiority of this secondary prevention program over usual care demonstrated in Table 4 Exit from The COACH Program; continuous variables are median (interquartile range), categorical variables are %. Coronary risk factors
Public
Private
Significance
Total cholesterol (mmol/L) Triglycerides (mmol/L) LDL-cholesterol (mmol/L) HDL-cholesterol (mmol/L) Systolic BP (mm Hg) Diastolic BP (mm Hg) Fasting blood glucose (mmol/L) HbA1c% (diabetics only) Smoking status (current smokers) Waist circumference (cm) Weight (kg) Alcohol consumption (at target) Physical activity (at target)
3.7 (3.2, 4.1) 1.3 (0.9, 1.8) 1.8 (1.5, 2.1) 1.1 (0.9, 1.3) 120 (110, 128) 70 (70, 78) 5.3 (5.0, 5.6) 7.0 (6.4, 8.0) 219 (9.7%) 93 (86, 98) 82 (72, 94) 1963 (88.7%) 1909 (85.3%)
3.6 (3.2, 4.1) 1.1 (0.8, 1.5) 1.8 (1.5, 2.1) 1.2 (1.0, 1.4) 124 (120, 129) 70 (68, 77) 5.3 (4.9, 5.6) 6.8 (6.3, 7.5) 69 (2.1%) 94 (89, 100) 80 (71, 90) 2706 (83.9%) 2657 (81.1%)
0.0269 b0.0001 NS b0.0001 b0.0001 NS NS b0.0001 b0.0001 0.0003 b0.0001 b0.0001 b0.0001
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randomised controlled studies performed over 10 years ago [17,18]. The COACH Program Software is a minimum data set which provides patients with written information about their progress and monitors the skill of individual coaches in their pursuit of achieving guideline recommended risk factor targets. Some of the data was not collected in patients on their entry to The COACH Program and in others was not collected on their exit. Accordingly, this study has only reported data when this was available on entry and exit in the same patient. The data collected is at three levels. The most reliable data are from blood tests where the tests are confirmed by records received by the coaches from pathology laboratories. The next level of reliability is the quantitative measures reported by the patients but not verified by the coaches. These include blood pressure levels, body weight and waist measurements. We believe that these are likely to be correct. We also recognise a possibility of bias in the self-reported risk factor levels such as smoking status and the performance of physical activity. Being a minimum data set, The COACH Program Software recorded data which was essential in the provision of The COACH Program. It did not record other data which would have been descriptive of the patient group but not essential in the coaching of individual patients. Thus we did not record: the results of the interactions between the coaches and the patients on the nutritional status of the patients; the anxiety or depression status of the patients as we did not attempt to either assess the patient's mood or offer treatment for depression; marital status or rurality; and medical conditions, treatment or the severity of these conditions on entry to The COACH Program. We had no information on the prognosis of the patients during their 6 months coaching. The improvement in the patients' biomedical risk factors implies reasonable adherence to the prescribed medications. 5. Conclusion This study is important in demonstrating that a program of initiating contact with patients with CHD, identifying treatment gaps in their management and coaching to achieve guideline recommended risk factor targets can help reduce health inequalities in such patients and thus benefit all patients in the context of ongoing secondary prevention. References [1] World Health Organisation (WHO). Rehabilitation and comprehensive secondary prevention after acute myocardial infarction. Copenhagen: WHO Report, Vol 84; 1983. p. 1–99. [2] Leon AS, Franklin BA, Costa F, et al. American Heart Association scientific statement. Cardiac rehabilitation and secondary prevention of coronary heart disease. Circulation 2005;111:369–76. [3] Piepoli MF, Corra U, Benzer W, et al. A position paper from the European Association of Cardiovascular prevention and Rehabilitation. Secondary prevention through cardiac rehabilitation: from knowledge to implementation. Eur J Cardiovasc Prev Rehabil 2010;17:1–17. [4] Goble AJ, Worcester MUC. Best practice guidelines for cardiac rehabilitation and secondary prevention. Heart Research Centre on behalf of the Victorian Department of Human Services; 1999 1–236. [5] National Heart Foundation of Australia. Secondary prevention of cardiovascular disease; 2010 1–30. [6] Taylor RS, Brown A, Ebrahim S, et al. Exercise based rehabilitation for patients with coronary heart disease: systematic review and meta-analysis of randomized controlled trials. Am J Med 2004;116:682–92. [7] Heran BS, Chen JMH, Ebrahim S, et al. Exercise based cardiac rehabilitation for coronary heart disease. Cochrane Database Syst Rev 2011;7:CD001800. [8] Bunker S, McBurney H, Cox H, Jelinek M. Identifying participation rates at outpatient cardiac rehabilitation programs in Victoria, Australia. J Cardiopulm Rehabil 1999;19:334–8. [9] Scott IA, Lindsey KA, Harden HE. Utilisation of cardiac rehabilitation programs in Queensland. Med J Aust 2003;179:341–5. [10] Johnson N, Fisher J, Nagle A, Inder K, Wiggers J. Factors associated with referral to outpatient rehabilitation services. J Cardiopulm Rehabil 2004;24:165–70. [11] Kotseva K, Wood D, De Bacquer D, et al. Cardiac rehabilitation for coronary patients: lifestyle, risk factor, and therapeutic management. Results from EUROASPIRE II survey. Eur Heart J 2004;6:117–24. [12] Redfern J, Ellis ER, Briffa T, Freedman SB. High risk factor level and low risk factor knowledge in patients not accessing cardiac rehabilitation after acute coronary syndrome. Med J Aust 2007;186:21–5.
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[13] Martin B-J, Hauer T, Arena R, et al. Cardiac rehabilitation attendance and outcomes in coronary artery disease patients. Circulation 2012;126:667–87. [14] Jolly K, Taylor RS, Lip GY, Stevens A. Home-based cardiac rehabilitation compared with centre-based rehabilitation and usual care: systematic review and metaanalysis. Int J Cardiol 2006;111:343–51. [15] Taylor RS, Dalal H, Jolly K, et al. Home-based versus centre-based cardiac rehabilitation. Cochrane Database Syst Rev 2010;1:CD007130. [16] Wood DA, Kotseva K, Connolly S, et al. Nurse-coordinated multidisciplinary, family-based cardiovascular disease prevention program (EUROACTION) for patients with coronary heart disease and asymptomatic individuals at high risk of cardiovascular disease: a paired, cluster randomised controlled trial. Lancet 2008;371:1999–2012. [17] Vale MJ, Jelinek MV, Best JD, Santamaria JD. Coaching patients with coronary heart disease to achieve the target cholesterol: a method to bridge the gap between evidence-based medicine and the ‘real world’. Randomized controlled trial. J Clin Epidemiol 2002;55:245–52. [18] Vale MJ, Jelinek MV, Best JD, et al. Coaching patients on achieving cardiovascular health (COACH). A multicenter randomized trial in patients with coronary heart disease. Arch Intern Med 2003;163:2775–83. [19] Jelinek M, Vale MJ, Liew D, et al. The COACH Program produces sustained improvements in cardiovascular risk and adherence to recommended medications—2 year follow-up. Heart Lung Circ 2009;18:388–92. [20] Australian Bureau of Statistics. Updated September 5 2013.
[21] Beauchamp A, Peeters A, Wolfe R, et al. Inequalities in cardiovascular disease mortality: the role of behavioural, physiological, and social risk factors. J Epidemiol Community Health 2010;64:542–8. [22] Pearson-Stuttard J, Bajekal M, Scholes S, et al. Recent UK trends in the unequal burden of coronary heart disease. Heart 2012;98:1573–82. [23] West RR, Jones DA, Henderson AH. Rehabilitation after myocardial infarction trial (RAMIT): multi-centre randomised controlled trial of comprehensive cardiac rehabilitation in patients following acute myocardial infarction. Heart 2012;98:637–44. [24] Wood D. Is cardiac rehabilitation in the NHS fit for purpose: maybe not. Heart 2012;98:607–8. [25] Jelinek MV, Santamaria JD, Thompson DR, Vale MJ. ‘Fit for purpose’. The COACH Program improves lifestyle and biomedical risk factors. Heart 2012;98:1608. [26] Cholesterol Treatment Trialists' (CTT) Collaborators. Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90 056 participants in 14 randomised trials of statins. Lancet 2005;366:1267–78. [27] Cholesterol Treatment Trialists' (CTT) Collaboration. Efficacy and safety of more intensively lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet 2010;376:1670–81. [28] Blood Pressure Lowering Treatment Trialists Collaboration. Effect of different bloodpressure—lowering regimens on major cardiovascular events: results of prospectively designed overviews of randomised trials. Lancet 2003;362:1527–35. [29] National Heart Foundation of Australia and the Cardiac Society of Australia and New Zealand. Reducing risk in heart disease 2007 (updated 2008).
Contents lists available at ScienceDirect
International Journal of Cardiology journal homepage: www.elsevier.com/locate/ijcard
Reversing social disadvantage in secondary prevention of coronary heart disease Michael V. Jelinek a,b,c,⁎, John D. Santamaria a,b, James D. Best a,b, David R. Thompson c, Andrew M. Tonkin d, Margarite J. Vale b,1 a
St Vincent's Hospital, Melbourne, Australia The University of Melbourne, Department of Medicine, St Vincent's Hospital, Melbourne, Australia Cardiovascular Research Centre, Australian Catholic University, East Melbourne, Australia d Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia b c
a r t i c l e
i n f o
Article history: Received 2 August 2013 Received in revised form 4 November 2013 Accepted 12 December 2013 Available online 24 December 2013 Keywords: Secondary prevention Coronary disease Risk factors Telephone Rehabilitation
a b s t r a c t Background: To compare and contrast the coronary heart disease (CHD) risk factors of lower socio-economic status public hospital patients with those of privately insured CHD patients before and after six months of telephone delivered coaching using The COACH Program. Methods: A retrospective observational study which contrasts the lifestyle and biomedical coronary risk factor status of 2256 public hospital patients with the same risk factors of 3278 patients who had private health insurance. All patients received an average of 5 coach sessions over 6 months. Results: The public hospital patients were four years younger and had multiple measures confirming their lower socio-economic status than their private hospital counterparts. At entry to the program, the public hospital patients had worse risk factor levels than the privately insured patients for total and LDL-cholesterol, triglycerides, fasting glucose, smoking and physical activity levels (P b 0.0001) but better status for systolic and diastolic blood pressures and alcohol intake. At exit from the program, many of these differences had diminished or disappeared. The public hospital patients had greater improvements in their risk factor status for total and LDL-cholesterol, fasting glucose, body weight, smoking status and physical activity level than did the privately insured patients (P b 0.05). Conclusions: This paper demonstrates that a program of initiating contact with patients with CHD, identifying treatment gaps in their management and coaching to achieve guideline recommended risk factor targets can help reduce health inequalities in such patients and thus benefit all patients in the context of ongoing secondary prevention. © 2013 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Coronary heart disease (CHD) is a lifelong condition which results in a very large burden of death, disability, and health care costs. Whilst some patients die in the initial clinical episode, most will survive to leave hospital and a program of secondary prevention will be recommended. Exercise based cardiac rehabilitation has been the method recommended by authorities to educate the patient and reduce the risk of recurrence of CHD events and premature mortality [1–5]. Systematic review of best practice exercise based cardiac rehabilitation has shown that such programs reduce all-cause and cardiovascular mortality,
⁎ Corresponding author at: St Vincent's Hospital, Melbourne, Australia. E-mail address: [email protected] (M.V. Jelinek). 1 Margarite J Vale is the director of The COACH Program. The data used in this study is not owned by The COACH Program. The data used in this study is owned by each health organisation using The COACH Program. The data was collected by each organisation as part of the usual care of delivering The COACH Program and not for study purposes. 0167-5273/$ – see front matter © 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijcard.2013.12.022
decrease hospital readmissions, and improve coronary risk factors [6,7]. However, despite widespread recommendations for the use of exercise based cardiac rehabilitation, only 10–30% of eligible patients attend these programs. This poor attendance has remained steady for at least 20 years despite major attempts to raise the profile and attendance at cardiac rehabilitation [8–11]. Most disturbing has been the finding that non-attenders at cardiac rehabilitation are typically older, are more likely to be female, have lower health literacy and worse coronary risk factors (particularly smoking), more complications of vascular disease and poorer left ventricular function. They are also more likely to be socio-economically disadvantaged [12,13]. There have been several responses to the problem of poor attendance of the neediest groups of patients. Some have recommended home based cardiac rehabilitation programs [14,15]. Others have recommended the use of practice nurses [16]. We have developed The COACH Program, a coaching program delivered by telephone and mail outs for patients with CHD in which a health professional coach trains patients to vigorously pursue the target levels for their particular coronary risk factors whilst working in partnership with the patient's own doctors.
M.V. Jelinek et al. / International Journal of Cardiology 171 (2014) 346–350
The benefits of The COACH Program have been demonstrated in two randomised controlled trials [17,18]. Furthermore, the improvements in coronary risk factor status achieved at six months are sustained for at least the next 18 months after cessation of coaching [19]. The program has been introduced to the public health system in all Australian states, financed by the state government health departments, and also most health insurance organisations which support patients discharged from private hospitals. All Australian citizens are entitled to hospital care funded in part by a taxation levy based on their annual income. Nearly one-half of Australians have additional health insurance which entitles them to the doctor and hospital of their choice, and the timing of an elective procedure. Private health insurance costs the average working Australian around 5% of their annual income. The lower an individual's personal income, the higher the proportion of that income which is spent on private medical care. Hence patients in private hospitals are usually of higher socio-economic status than those treated in the public hospital systems. On this background we aimed to compare the impact of The COACH Program on the coronary risk factor status in public and private health systems. In turn, this has allowed us to see whether this telephone assisted management could impact on the more disadvantaged patient who might not attend a typical exercise based cardiac rehabilitation program. 2. Methods 2.1. The COACH Program Coaching sessions are provided by a series of telephone calls and mail outs after the patient has been discharged from hospital, usually over a period of six months. A distinguishing feature of The COACH Program is that coaches identify and assist patients to close treatment gaps in the management of their lifestyle and biomedical risk factors. These ‘treatment gaps’ are gaps between the evidence based guideline recommended treatments patients should be receiving as against what they are actually receiving. Progress towards achieving risk factor targets is regularly monitored by the coach, who provides a structured written report that is a summary of each verbal coaching session. The written report is followed by a risk factor chart which lists the coronary risk factors, the actual risk factors levels for the patient, how they compare to the guideline recommended target levels and whether the targets have been achieved. The COACH Program is applicable to all patients with recent CHD hospitalisation, but in particular is appropriate for those patients with short stay admissions nowadays seen after percutaneous coronary interventions who may or may not have suffered myocardial infarction. The COACH Program is also especially useful for patients living in remote locations where access to cardiac rehabilitation or even primary medical care may be difficult. 2.2. The patients The patients reported in this study were either managed in public hospital systems run by two large Australian states or derived from any one of four private health funds throughout Australia. The coaches were dietitians or nurses who had been formally trained in The COACH Program methodology and in the use of the appropriate software. Patients were recruited either in-hospital or after discharge from hospital after an admission for CHD. The duration of involvement in The COACH Program for each patient was up to six months. We report here on all the patients enrolled by either public or private hospitals between March 21st 2007 and December 16th 2011. 2.3. Socio-economic status Objective support for our hypothesis that public hospital patients were, on average, more socially disadvantaged than private hospital patients was obtained by asking the patients for the highest level of education that they had achieved, and by using postcode derived measures of social advantage or disadvantage derived from data from the Australian Bureau of Statistics Socio-Economic Indexes for Areas (SEIFA) [20]. SEIFA is a suite of four summary measures that have been created from 2006 Census information. The indexes can be used to explore different aspects of socioeconomic conditions by geographic areas. For each index, every geographic area in Australia is given a SEIFA score which shows how disadvantaged that area is compared with other areas in Australia. Each index summarises a different aspect of the socio-economic conditions of people living in an area. They each summarise a different set of social and economic information. The indexes take into account a range of factors in determining socio-economic conditions.
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The four indexes in SEIFA 2006 are: • Index of Relative Socio-economic Disadvantage: focuses primarily on disadvantage, and is derived from Census variables like low income, low educational attainment, unemployment, and dwellings without motor vehicles. • Index of Relative Socio-economic Advantage and Disadvantage: is a continuum of advantage (high values) to disadvantage (low values), and is derived from Census variables related to both advantage and disadvantage. • Index of Economic Resources: focuses on financial aspects of advantage and disadvantage, using Census variables relating to residents' incomes, housing expenditure and assets. • Index of Education and Occupation: includes Census variables relating to the educational attainment, employment and vocational skills.
2.4. Variables measured All blood test results for fasting lipid profile, fasting glucose and HbA1c in patients with diabetes were verified by the coach from pathology reports. Information regarding blood pressure, body mass index (BMI), waist measurement, smoking status, alcohol intake and performance of regular moderate intensity physical activity was obtained by coaches over the telephone from patient self-report. Coronary risk factor targets were those recommended by the National Heart Foundation of Australia and the Cardiac Society of Australia and New Zealand (see Table 1).
2.5. Statistical analysis Analysis was performed on de-identified patient data. For categorical data, the tables of variables for public versus private are shown. Data are expressed as median (interquartile) range for continuous variables, and numbers (percentage) for categorical variables. Comparisons between groups were made with non-parametric methods (Mann–Whitney U test, Kruskal–Wallis test) and with Fisher's Exact Test or chi-squared analysis, respectively. Data were analysed with Stata version 12 (StataCorp, College Station, TX) and a P-value less than 0.05 set for statistical significance. Differences in coronary risk factor status were compared from entry to The COACH Program to the end of the coaching six months later. Comparison was made on the status of patients in public and private hospitals on admission to The COACH Program, discharge from The COACH Program and the net difference between the admission and discharge status of these patients in the two differing health care systems.
3. Results 3.1. Patient demographics Table 2 presents the patient demographics. There were 2266 public hospital patients and 3278 private hospital patients. The public hospital patients were 4 years younger than those derived from private hospitals (P b 0.0001). There were a higher proportion of women and indigenous Australians in the public hospital patients (P b 0.0001). Public hospital patients were, on average, less well educated than were the private hospital patients (P b 0.0001). More public hospital patients were employed and more private hospital patients were not in the workforce or looking for work (P b 0.0001). All of the postcode (SEIFA) derived information confirmed that the public hospital patients were, on average, of lower socio-economic status (P b 0.0001).
3.2. Coronary risk factor status on admission to The COACH Program On entry to The COACH Program, nearly all coronary risk factors of public hospital patients were worse than their privately insured counterparts (Table 3). The public hospital patients had higher total and LDL-cholesterol levels, higher triglyceride levels, higher fasting blood glucose levels, higher body weight, and lower levels of physical activity (P b 0.0001). A much higher proportion of public hospital patients were smokers on entry to The COACH Program than were privately insured patients (19.5% v 2.4%, P b 0.0001). A higher proportion of privately insured patients consumed alcohol above the recommended targets than did public hospital patients (P = 0.007). On admission to The COACH Program, the blood pressure of the public hospital patients was 4/4 mm Hg lower than that of the privately insured patients (P b 0.01).
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Table 1 National Heart Foundation targets used in The COACH Program [29]. Coronary risk factors
Targets
Biomedical risk factors Total cholesterol LDL-cholesterol Triglycerides HDL-cholesterol Blood pressure Fasting glucose (without diabetes) HbA1c (diabetics only)
b4 mmol/L b2 mmol/L b1.5 mmol/L N1.0 mmol/L b130/80 mm Hg b5.5 mmol/L ≤7.0%
Lifestyle risk factors Smoking Waist measurement
Complete cessation of smoking and avoidance of second hand smoke ≤94 cm for men; ≤80 cm for women b25 kg/m2 At least 30 min of moderate intensity physical activity of most, preferably all days of the week No more than 2 standard drinks per day for men and women No more than 1 standard drink per day for women with high BP At least 2 alcohol free days per week for men and women with high BP
BMI Physical activity Alcohol intake
3.3. Coronary risk factor status on exit from The COACH Program The average duration of The COACH Program was 190 days (IQR 126, 217) for public hospital patients compared with 182 days for private patients (IQR 126, 218). Table 4 shows that at exit from The COACH Program, differences between the public hospital and privately insured patients had disappeared for LDL-cholesterol, diastolic BP, and fasting blood glucose. The differences between public hospital patients and privately insured patients had been reduced for total cholesterol, waist circumference and smoking status. Public hospital patients reported a 9.7% rate of smoking cigarettes at exit from The COACH Program (a 50% reduction from to entry to exit) compared with 2.1% smoking at exit in the privately insured patients. The worse coronary risk factor status of the public hospital patients remained for triglycerides, HDLcholesterol, smoking and body weight (P b 0.0001). The paradox of the better risk factor status for public hospital patients persisted for systolic BP and for excess alcohol intake (P b 0.0001). More public hospital patients reported that they were now physically active than the privately insured patients (P b 0.0001). 3.4. Changes from entry to exit for The COACH Program All the lifestyle and biomedical risk factors were better at exit from The COACH Program than at entry (P b 0.0001) [25]. However, greater
improvements in the risk factors occurred in the public patients than in the privately insured patients for fasting blood glucose, body weight, smoking, physical activity (all P b 0.0001), total and LDL-cholesterol and diastolic BP (P b 0.05). 4. Discussion The important result of this study is that The COACH Program had a more favourable impact on coronary risk factors in the lower socioeconomic public patients than in privately insured patients. All the coaches were formally trained in the delivery of The COACH Program. The coaches in public hospitals were employed by the state government health departments and the coaches in the private health care system were employed by the health insurance organisations. The coaches gave equal time to the patients in both health care systems. The greater improvements seen in the public hospital patients reflected their social disadvantage at entry into the program compared with the privately insured patients. The public hospital patients were four years younger at presentation to The COACH Program than their private hospital counterparts and the post-code (SEIFA) data confirm the hypothesis that these patients were of lower socio-economic status than the privately insured patients. The younger age of the public hospital patients explains why more of these patients were still working and actively seeking employment than the private patients. Furthermore, the coronary
Table 2 Demographic characteristics and socioeconomic status; continuous variables are median (interquartile range), categorical variables are %. Public
Private
Significance
Number of patients Age, years Gender, male n (%) Aboriginal & Torres Strait Islander, n (%) Prior CVD
2266 62.3 (53.5, 70.2) 1643 (72.5%) 73 (3.2%) 1055 (46.6%)
3278 66.4 (60.7, 72.2) 2521 (76.9%) 14 (0.4%) 2320 (47.5%)
b0.0001 b0.0001 b0.0001 NS
Employment status, n (%) Employed Not in labour force Unemployed (looking for work)
942 (44.0%) 1157 (54.0%) 43 (2.0%)
1286 (40.7%) 1851 (58.6%) 22 (0.7%)
b0.0001
Highest level of education completed, n (%) Primary schooling or less Secondary schooling Tertiary technical education University diploma/degree
63 (6.0%) 499 (47.4%) 277 (26.3%) 214 (20.3%)
51 (1.8%) 1281 (43.9%) 851 (29.1%) 737 (25.2%)
b0.0001
SEIFA measures of socioeconomic status Advantage/disadvantage Disadvantage Resource score Education/occupation
976 (937, 1021) 992 (956, 1031) 1005 (973, 1037) 951 (922, 987)
1001 (960, 1067) 1011 (978, 1062) 1009 (976, 1057) 977 (939, 1053)
b0.0001 b0.0001 b0.0001 b 0.0001
M.V. Jelinek et al. / International Journal of Cardiology 171 (2014) 346–350 Table 3 Entry into The COACH Program; continuous variables are median (interquartile range), categorical variables are %. Coronary risk factors
Public
Private
Significance
Total cholesterol (mmol/L) Triglycerides (mmol/L) LDL-cholesterol (mmol/L) HDL-cholesterol (mmol/L) Systolic BP (mm Hg) Diastolic BP (mm Hg) Fasting blood glucose (mmol/L) HbA1c% (diabetics only) Smoking status (current smokers) Waist circumference (cm) Weight (kg) Alcohol consumption (at target) Physical activity (at target)
4.4 (3.6, 5.3) 1.5 (1.1, 2.3) 2.5 (1.8, 3.3) 1.0 (0.9, 1.2) 121 (113, 130) 70 (67, 80) 5.5 (5.2, 6.1) 7.5 (6.6, 9.0) 428 (19.5%) 96.0 (89, 104) 84 (73, 96) 1580 (78.3%) 956 (45.4%)
4.2 (3.5, 5.1) 1.3 (1.0, 1.9) 2.3 (1.8, 3.1) 1.2 (1.0, 1.4) 125 (120, 135) 74 (70, 80) 5.3 (4.9, 5.7) 6.9 (6.3, 7.6) 79 (2.4%) 96.5 (90, 104) 82 (72, 92) 2306 (75.7%) 1765 (54.6%)
0.0007 b0.0001 b0.0001 b0.0001 b0.0001 0.0016 b0.0001 b0.0001 b0.0001 NS b0.0001 0.007 b0.0001
risk factor status of the public hospital patients was poorer than the private hospital patients for all coronary risk factors except the blood pressure. The finding of poorer coronary risk factor status in patients with poorer socio-economic circumstances is well recognised [21,22]. The lower blood pressure of the public hospital patients is most likely explained by their younger age at presentation. Unlike the prescription of pharmaceuticals, cardiac rehabilitation is not a standardised treatment. Variations in the practice of cardiac rehabilitation result from differences in the frequency and duration of cardiac rehabilitation programs, the intensity of the exercise prescribed in the programs, the presence or absence of psychological support, and the use and quality of education given in these programs. A recent randomised controlled trial of cardiac rehabilitation as usually practised in Britain showed that cardiac rehabilitation failed to impact on total mortality, cardiac morbidity, health related quality of life and behavioural risk factors. In fact, patients randomised to cardiac rehabilitation were performing less physical activity at follow-up than those in the control group [23]. Whilst this trial was met with widespread concern and disbelief one observer suggested that cardiac rehabilitation, as usually performed in Britain, might not be “fit for purpose” [24]. We have previously shown that The COACH Program reliably improves five lifestyle and eight biomedical coronary risk factors [25]. In this paper, we have shown that The COACH Program results in greater improvements in these coronary risk factors in the more socially disadvantaged public hospital patients who enter the programs younger and with worse risk factor profiles than more socially advantaged privately insured patients and exit the program almost on equal terms. In the long-term, improved risk factor status is likely to reduce CHD morbidity and mortality rates [26–28]. 4.1. Study limitations This is an observational cohort study based on the superiority of this secondary prevention program over usual care demonstrated in Table 4 Exit from The COACH Program; continuous variables are median (interquartile range), categorical variables are %. Coronary risk factors
Public
Private
Significance
Total cholesterol (mmol/L) Triglycerides (mmol/L) LDL-cholesterol (mmol/L) HDL-cholesterol (mmol/L) Systolic BP (mm Hg) Diastolic BP (mm Hg) Fasting blood glucose (mmol/L) HbA1c% (diabetics only) Smoking status (current smokers) Waist circumference (cm) Weight (kg) Alcohol consumption (at target) Physical activity (at target)
3.7 (3.2, 4.1) 1.3 (0.9, 1.8) 1.8 (1.5, 2.1) 1.1 (0.9, 1.3) 120 (110, 128) 70 (70, 78) 5.3 (5.0, 5.6) 7.0 (6.4, 8.0) 219 (9.7%) 93 (86, 98) 82 (72, 94) 1963 (88.7%) 1909 (85.3%)
3.6 (3.2, 4.1) 1.1 (0.8, 1.5) 1.8 (1.5, 2.1) 1.2 (1.0, 1.4) 124 (120, 129) 70 (68, 77) 5.3 (4.9, 5.6) 6.8 (6.3, 7.5) 69 (2.1%) 94 (89, 100) 80 (71, 90) 2706 (83.9%) 2657 (81.1%)
0.0269 b0.0001 NS b0.0001 b0.0001 NS NS b0.0001 b0.0001 0.0003 b0.0001 b0.0001 b0.0001
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randomised controlled studies performed over 10 years ago [17,18]. The COACH Program Software is a minimum data set which provides patients with written information about their progress and monitors the skill of individual coaches in their pursuit of achieving guideline recommended risk factor targets. Some of the data was not collected in patients on their entry to The COACH Program and in others was not collected on their exit. Accordingly, this study has only reported data when this was available on entry and exit in the same patient. The data collected is at three levels. The most reliable data are from blood tests where the tests are confirmed by records received by the coaches from pathology laboratories. The next level of reliability is the quantitative measures reported by the patients but not verified by the coaches. These include blood pressure levels, body weight and waist measurements. We believe that these are likely to be correct. We also recognise a possibility of bias in the self-reported risk factor levels such as smoking status and the performance of physical activity. Being a minimum data set, The COACH Program Software recorded data which was essential in the provision of The COACH Program. It did not record other data which would have been descriptive of the patient group but not essential in the coaching of individual patients. Thus we did not record: the results of the interactions between the coaches and the patients on the nutritional status of the patients; the anxiety or depression status of the patients as we did not attempt to either assess the patient's mood or offer treatment for depression; marital status or rurality; and medical conditions, treatment or the severity of these conditions on entry to The COACH Program. We had no information on the prognosis of the patients during their 6 months coaching. The improvement in the patients' biomedical risk factors implies reasonable adherence to the prescribed medications. 5. Conclusion This study is important in demonstrating that a program of initiating contact with patients with CHD, identifying treatment gaps in their management and coaching to achieve guideline recommended risk factor targets can help reduce health inequalities in such patients and thus benefit all patients in the context of ongoing secondary prevention. References [1] World Health Organisation (WHO). Rehabilitation and comprehensive secondary prevention after acute myocardial infarction. Copenhagen: WHO Report, Vol 84; 1983. p. 1–99. [2] Leon AS, Franklin BA, Costa F, et al. American Heart Association scientific statement. Cardiac rehabilitation and secondary prevention of coronary heart disease. Circulation 2005;111:369–76. [3] Piepoli MF, Corra U, Benzer W, et al. A position paper from the European Association of Cardiovascular prevention and Rehabilitation. Secondary prevention through cardiac rehabilitation: from knowledge to implementation. Eur J Cardiovasc Prev Rehabil 2010;17:1–17. [4] Goble AJ, Worcester MUC. Best practice guidelines for cardiac rehabilitation and secondary prevention. Heart Research Centre on behalf of the Victorian Department of Human Services; 1999 1–236. [5] National Heart Foundation of Australia. Secondary prevention of cardiovascular disease; 2010 1–30. [6] Taylor RS, Brown A, Ebrahim S, et al. Exercise based rehabilitation for patients with coronary heart disease: systematic review and meta-analysis of randomized controlled trials. Am J Med 2004;116:682–92. [7] Heran BS, Chen JMH, Ebrahim S, et al. Exercise based cardiac rehabilitation for coronary heart disease. Cochrane Database Syst Rev 2011;7:CD001800. [8] Bunker S, McBurney H, Cox H, Jelinek M. Identifying participation rates at outpatient cardiac rehabilitation programs in Victoria, Australia. J Cardiopulm Rehabil 1999;19:334–8. [9] Scott IA, Lindsey KA, Harden HE. Utilisation of cardiac rehabilitation programs in Queensland. Med J Aust 2003;179:341–5. [10] Johnson N, Fisher J, Nagle A, Inder K, Wiggers J. Factors associated with referral to outpatient rehabilitation services. J Cardiopulm Rehabil 2004;24:165–70. [11] Kotseva K, Wood D, De Bacquer D, et al. Cardiac rehabilitation for coronary patients: lifestyle, risk factor, and therapeutic management. Results from EUROASPIRE II survey. Eur Heart J 2004;6:117–24. [12] Redfern J, Ellis ER, Briffa T, Freedman SB. High risk factor level and low risk factor knowledge in patients not accessing cardiac rehabilitation after acute coronary syndrome. Med J Aust 2007;186:21–5.
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