ABC | Volume 111, Nº1, July 2018

Original Article Stevens et al The Economic Burden of Heart Conditions in Brazil Arq Bras Cardiol. 2018; 111(1):29-36 a The ILO reports the unemployment rate for Brazil at 6.8% in 2014 (the most recent year it was reported) Cost of illness The analysis was based on estimating the prevalence, incidence, loss of wellbeing, health system and productivity losses attributed to the four heart conditions. Total cost estimates were adjusted based on the comorbidity between conditions. Underpinning the study was a literature search that used search terms associated with the country, region, epidemiology and economic impact of the four heart conditions. Sources included PubMed, government, healthcare and patient organization websites, and general internet search engines. Prevalence/incidence of conditions The sources used for estimating the prevalence or incidence are outlined in Table 1. Whenever possible, Brazil specific rates were used. All estimates were checked with stakeholders interviewed for the project. Identified rates were applied to projections from theUnitedNationsWorld Population Prospects. 2 Loss of wellbeing Disability weights were based on the WHO Global Burden of Disease studies 3,4 as shown in Table 2. These were then multiplied by the prevalence estimates to identify the years lost to disability for 2015. Years lost to life were based on reported mortality for each condition. Health system costs The discharges and average length of stay for each of the conditions 5 were combined with cost estimates for each of the four condition categories 5 to estimate each condition’s burden on the health system as a share of all conditions treated. This was then combined with an estimate of total relevant health expenditure for Brazil 6 to result in the cost of treating each of the four conditions. Health costs were estimated from the perspective of health care payers, i.e. both public and private payers. Cost breakdowns were based on those reported for Brazil. 7 This method allows us to reflect most appropriately the impacts based on the number, length of stay and cost intensity of each condition for Brazil specifically. However, data on condition-specific health expenditures are not available for other components of the health system (e.g. primary care). Accordingly, each condition’s share of total health system expenditure was assumed to be the same as its share of total hospital expenditure. Productivity losses Consistent with the ‘full or near-full employment’ criterion, a a human capital approach to the estimation of productivity losses was adopted. Calculations involving productivity losses were based on employment rates by age-gender groups. It was assumed that those with heart conditions were, in the absence of the condition, as likely to be employed as others in their corresponding age-gender group. Forgone wage income was based on wage data for Brazil. 7 Absenteeism was associated with all of the conditions. For HF it was estimated as 12.66 days for those with NYHA III/IV and 3.04 days per year for those with NYHA I/II. 8 Absenteeism was estimated as 3.03 days per year 8 for HTN, 75 days per year for those admitted to hospital 9 with MI, and 2.1 days per year 10 for AF. Reduced employment participation, where individuals are no longer able to be employed due to their condition, was identified for both HF and MI, but not for AF or HTN. For HF, there was 13% lower employment participation rate (based on those with coronary heart disease). 11 The study also showed increased withdrawal of unemployed people from the labor force, especially those aged below 60 years and those engaged in manual work. For MI, there was a 21% lower employment participation [based on those with acute coronary syndrome (ACS) five years after an event]. 12 As the lower employment participation rates in both the coronary heart disease and ACS studies were based on populations in developed countries, these rates were adjusted by the observed rates of reduced employment participation for those with disability in Europe and Latin America, as reported by the Organization for Economic Cooperation and Development (OECD). 13 Forgone income due to premature death was based on mortality statistics for each condition and the otherwise expected life expectancy according to WHO life tables. 14 The anticipated number of years of life left to live by the deceased individual was multiplied first by employment rates and then by the average weekly wage for men and women respectively. The productivity discount rate for future earnings was 5.25% based on the difference between wage growth and inflation (using the annualized average for both over the past five years). The present value of future wages was based on the five-year average real growth rate. 15 Informal care costs were identified for both HF and MI. For HF, each individual was provided an estimated 6.7 hours of informal care per week. 16 While there are a variety of sources Table 1 – Number of people with the four heart conditions in Brazil, 2015 Condition Number of people Percentage of the adult population * HF 2 845 722 2.0 MI 334 978 0.2 AF 1 202 151 0.8 HTN 44 526 201 31.2 Total conditions 48 909 052 34.3 Total persons with any condition (i.e. accounting for comorbidities) 45 658 048 32.0 * : Percentage reflects the evidence from studies among populations aged 20 years and over. HF: heart failure; MI: myocardial infarction;AF: atrial fibrillation; HTN: hypertension. 30