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Innovation in clinical specialities: cardiovascular disease Table 1: Major risk factors a in coronary heart disease mortality Age groups (years) Risk factor 25–44 45–54 55–64 65–74 75–84 Systolic blood pressure 7 Men (log hazard ratio per 1 mmHg) -0.036 -0.035 -0.032 -0.027 -0.021 Women (log hazard ratio per 1 mmHg) -0.046 -0.046 -0.035 -0.032 -0.026 Total cholesterol 6 Men & women: mortality reduction per 1 mmol/l (38.6 mg/dl) change in total cholesterol 0.900 0.650 0.450 0.333 0.317 Log coefficient -1.2942 -0.8238 -0.5245 -0.3719 -0.3512 Body mass index (BMI) 8 Age-specific relative risks per 1 kg/m 2 1.04 1.03 1.02 1.01 1.01 c Men & women: log coefficients 0.0363 0.0297 0.0165 0.0132 0.0099 a Used as input for the IMPACT model for the United States of America Table 2: Relative risks a of smoking, diabetes and physical inactivity for coronary heart disease mortality Men Women 55 years >55 years ≤65 years > 65 years Smoking 3·33 (2·80–3·95) b 2·52 (2·15–2·96) 4·49 (3·11–6·47) 2·14 (1·35–3·39) Exercise 1·02 (0·83–1·25) b 0·79 (0·66–0·96) 0·74 (0·49–1·10) 0·75 (0·46–1·22) Diabetes 2·66 (2·04–3·46) b 1·93 (1·58–2·37) 3·53 (2·49–5·01) 2·59 (1·78–3·78) Source: INTERHEART study 27 a Used as input for the IMPACT model for the United States of America b Odds ratios for relative effect of ri sk factors with 99% confidence intervals A variety of CHD policy models have been developed to estimate the relative contributions and hence the population impact of medical and public-health interventions. Good models are able to integrate and simultaneously consider large amounts of data on patient numbers, treatments and population risk factor trends. 9–11 The CHD Policy Model developed in the USA was used successfully to examined trends in that country between 1980 and 1990 9 and later demonstrated the potential advantages of a population-based approach to prevention, 12 consistent with European studies. 13-15 Capewell et al. have subsequently developed, refined and applied the IMPACT model in a variety of populations. 10,16-19 Approximately 44% of the substantial CHD mortality decline in the USA between 1980 and 2000 was attributable to changes in major risk factors and 47% to specific cardiological treatments, 10 similar to findings in other industrialized countries. 16,17,19,20 Three earlier analyses suggested that further modest reductions in major risk factors could halve CHD deaths in the United Kingdom of Great Britain and Northern Ireland. 15,21–23 To determine whether similar gains may be possible for the population of the USA, or whether they would be negated by recent dramatic rises in obesity and diabetes, we used the previously calibrated IMPACT model 10 for the USA to estimate the number of CHD deaths that could potentially be prevented or postponed in 2010, compared with the number in 2000. The model was applied to three contrasting scenarios, the most optimistic of which assumed that the prevalence of risk factors in the entire population reaches the levels already reported in its “low-risk stratum”. 24,25 Methods The IMPACT model aims to explain changes in CHD mortality rates in a population. It quantifies the contribution from temporal trends in the major population risk factors (smoking, high systolic blood pressure, elevated total cholesterol, obesity, diabetes and physical inactivity) and from medical and surgical treatments given to CHD patients. 10,17,26 The model employs regression coefficients produced by large meta-analyses and cohort studies. 6-8 Each coefficient quantifies the independent (log linear) relationship between the absolute change in a specific cardiovascular risk factor, such as high systolic blood pressure or total cholesterol, and the consequent change in population mortality rates from CHD (Table 1). 6-8 For each risk factor, the subsequent reduction in deaths in 2010 from base year 2000 could then be estimated as the product of three variables: Number fewer deaths = number of CHD deaths observed in 2000 × the risk factor reduction × the specific regression coefficient exponentiated. 10,22,23 All the coefficients and relative risk values were obtained from multivariate logistic regression analyses and were assumed to be independent, having been adjusted for potential confounding from the other major risk factors. The total deaths prevented could therefore be summed. Independent regression coefficients were not available for smoking, diabetes and physical inactivity. An alternative methodology was therefore used, which involved population-attributable risk fractions 9,21,22 calculated for the INTERHEART study, a large, international multivariate analysis that included data from the USA27 (Table 2). The original 1980–2000 IMPACT model 10 was extended to 2010 using United States Census Bureau population projections and mortality data for men and women aged 25–84 years. The number of CHD deaths (ICD-10: I20-I25) expected in 2010 was then calculated under three contrasting risk factor scenarios. Risk factor scenarios The first scenario assumed that recent risk factor trends would continue to 2010. Using data from the Third National Health and Nutrition Examination Survey (NHANES) 1988–1994, NHANES 1999– 2002, and the Behavioral Risk Factor Surveillance System <strong>Hospital</strong> and Healthcare Innovation Book 2009/2010 69
Innovation in clinical specialities: cardiovascular disease Table 3: 3. Risk factor levels in in 2000 base year and and projections to 2010 under three scenarios of cardiovascular risk factor change, United States of America Scenario Smoking prevalence (%) Total cholesterol (mg/dl) (mmol/l) a Systolic blood pressure (mmHg) Body mass index (kg/m 2 ) Diabetes prevalence (%) Prevalence of physical activity b (%) Men Women Men Women Men Women Men Women Men Women Men Women NHANES III (1988–1994) 31.6 24.7 206 (5.32) 210 (5.42) 123.5 119.6 26.87 26.73 9.0 8.9 70.4 68.0 207 (5.35) 124.4 123.9 27.86 28.51 11.7 9.5 75.1 70.5 In 2010, assuming recent trends continue 22.6 18.7 204 (5.28) 204 (5.28) 125.3 128.5 29.18 30.16 15.2 10.1 80.8 74.1 In 2010, assuming Healthy People targets are achieved In 2010, assuming all in “low-risk stratum” 12.0 12.0 199 (5.15) 199 (5.15) 119.4 c 118.9 c 25.00 d 26.00 d 6.0 e 6.0 e 80 80 0 0 176 (4.54) 179 (4.64) 115.7 114.7 25.50 23.60 0.0 0.0 100 100 NHANES, National Health and Nutrition Examination Survey a Cholesterol conversion factor mg/dl to mmol/l = 38.67 b Any leisure time activity c Assuming a 5 mmHg decrease from 2000 d Assuming that obesity prevalence falls to 15% e Total diabetes (diagnosed and undiagnosed), equivalent to HP2010 target of 25 per 1000 population diagnosed cases Table 4: Observed a and projected coronary heart disease mortality rates and deaths in the United States of America in 2000 and 2010 Men 25–34 years 35–44 years 45–54 years 55–64 years 65–74 years 75–84 years Total men Population in 2010 (thousands) CHD mortality rates per 100 000 observed in 2000 Annual change in CHD mortality rates 1997–2002 (%) CHD mortality rates per 100 000 expected in 2010 if trends continue Number of CHD deaths in 2010 if recent trends continue Number of CHD deaths in 2010 if 2000 rates unchanged Expected decrease in number of CHD deaths in 2010 compared with 2000 Decrease in CHD deaths in 2010 compared with 2000 (%) 21 105 3.50 - 0.52% 3.32 700 739 -39 -5.2% 20 552 25.78 - 0.52% 24.43 5 022 5 298 - 277 -5.2% 22 064 103.52 - 2.70% 75.59 16 679 22 841 - 6 163 -27.0% 17 438 290.20 - 4.14% 170.10 29 663 50 607 - 20 944 -41.4% 9 797 705.19 - 4.03% 420.76 41 222 69 088 - 27 866 -40.3% 5 272 1736.85 3.20% 1180.98 62 265 91 573 - 29 307 -32.0% 96 229 236.00 -1.97% 161.65 155 550 240 145 -84 595 -35.2% Women 25–34 20 541 1.17 +2.16% 1.42 292 240 +52 +21.6% years 35–44 20 568 7.63 +2.16% 9.28 1 909 1 569 +339 +21.6% years 45–54 22 763 29.93 - 1.56% 25.25 5 749 6 813 - 1 065 -15.6% years - 4.15% - 8 591 -41.5% 55–64 years 18 747 110.39 64.57 12 104 20 696 65–74 11 473 340.32 - 3.69% 214.61 24 621 39 044 - 14 423 -36.9% years 75–84 7 578 1055.16 - 3.14% 723.60 54 838 79 964 - 25 127 -31.4% years Total women 10 1670 146.90 -1.12% 97.88 99 515 148 325 -48 815 -32.9% Total men & 19 7900 190.00 -1.5% 142.15 25 5060 388 470 -133 410 -34.3% women a Source: American Heart Association 1 70 <strong>Hospital</strong> and Healthcare Innovation Book 2009/2010
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International Hospital Federation I
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Introduction Sterile Barrier System
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Contents Healthcare transformation
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International Hospital Federation H
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Introduction Introduction ERIC DE R
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Innovation and strategy 14 Creativi
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Innovation and strategy: creativity
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Innovation and strategy: risk manag
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Innovations in patient care: infect
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Innovation in patient care: patient
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Innovation in patient care: patient
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IHF reference The International Hos
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C M Y CM MY CY CMY K with support f
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IHF reference IHF Governing Council
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IHF reference IHF Consultants Audit
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IHF reference JAPAN JAPAN HOSPITAL
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IHF reference KENYA THE NAIROBI HOS
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IHF Corporate Member Profiles GE He
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How Can Health Organizations Get th
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