bThe ILO reports the unemployment rate for Mexico at 4.9% in 2014 (the most recent year it was reported).

cPercentage reflects the evidence from studies among populations aged 20 years and over.

Financing The study was supported by funding from the Novartis Group. The authors are solely responsible for its content.

Epidemiological data Whenever possible, Mexico specific rates were used and regional or other country estimates were only used only in the case where age group and population specific estimates were not available. Mortality was based on deaths by ICD-10 code from Instituto Nacional de Estadistica y Geografia to produce rates by age group. Identified rates were applied to population projections from the United Nations World Population Prospects.

Loss of wellbeing Lost wellbeing measured in DALYs from the four heart conditions, in comparison to being in full health, was estimated based on prevalence and mortality calculations from the epidemiological data, using ‘burden of disease’ methodology. This methodology was developed originally by the World Bank, World Health Organization (WHO), Harvard University and other stakeholders. Disability weights were based on the WHO Global Burden of Disease studies as Mexico specific weights were not identified. 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 Total health expenditure was based on health expenditure as a share of GDP for Mexico, less the ‘collective health care (prevention, health administration and health insurance)’ cost share provided by the OECD for Mexico. To estimate the cost associated with each condition, hospital data using total admissions and average length of stay data from Mexico was used for each condition to yield the total number of bed days for each condition (categories included ‘hypertensive diseases’, ‘myocardial infarction’, ‘conduction disorders and cardiac arrhythmias’ (with a proportion estimated to be AF based on data from Minsalud in Colombia, due to a lack of Mexico specific information) and ‘heart failure’ which is compared to the total bed days provided in the health system. These proportions were then combined with a cost loading per person per day to incorporate the cost of trea- ting each condition relative to non-cardiovascular conditions (based on Brazilian health system data, due to a lack of cost data in other health systems across Latin America). This method allowed condition specific loadings to be developed reflecting the differing costs associated --- and reflecting the complexity and type of care required. The combined result provided the cost of treating the condition as a share of total health expenditure, which is then multiplied by total health expenditure to estimate the total impact. This method allows us to most appropriately reflect the impacts based on the number, length of stay and cost intensity of each condition for Mexico 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 sys- tem expenditure was assumed to be the same as its share of total hospital expenditure.

Productivity losses For absenteeism losses, it was assumed that that 46% of time off work for people of working age across all conditions can be taken as sick leave, representing a cost to employers, and the remaining 54% was unpaid (based on the proportion in informal employment), representing a loss to individuals and government through the associated forgone tax revenue. Employment rates and the average weekly wage for men and women were based on data for Mexico from the International Labour Organization. For mortality costs, the anticipated number of years of life left to live (based on WHO life tables) 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, as 2015 data was not available when the study was conducted). The present value of future wages was based on the five-year average real growth rate. Informal care costs were identified for both HF and MI. For HF, each individual was provided an estimated 6.7 h of informal care per week. While there are a variety of sources for this parameter, the study chosen was the most robust methodologically and provided a similar estimate to what could be derived from a study in Latin America. For MI, based on a study of coronary heart disease patients, informal care hours were estimated to be 279 h per year per patient. The forgone informal care wage was constructed from data from a Mexican time use survey. The number of hours spent caring for individuals over 60 years old by men and women (65% women and 35% men) was used to weight average wages for men and women. The assumed fraction of individuals providing care who, in the absence of the heart condition, would be employed was based on a representative fraction from a Spanish based study, which was considered to be similar to the Latin American population in its demographic and cultural characteristics. Only the marginal increase in carer hours is attributed to the cost, rather than the total amount of care hours since, as individuals age, they frequently require care for a variety of reasons. Taxation revenue forgone was based on the average income tax rate for a single individual and the average indirect tax rate according to the OECD. The estimated income tax liability was applied to the estimated total value of forgone earnings to determine the value of taxation lost. An adjustment was also applied for the number working in the ‘informal economy’ which is likely to reduce the taxation revenue collected. Exchange rates between USD and the local currency were based on the average of the daily exchange rates from the International Monetary Fund from January 2015 to November 2015

Comorbidities As multiple conditions could affect one person simultaneously, the total cost of the four conditions was estimated by identifying literature that estimated the rates at which individuals had two or more of the conditions. The literature alone, however, does not present estimates for individuals with three or more conditions simultaneously so did not ensure completely consistent estimates. Where literature did not outline the concomitant rates between each of the four conditions, the sources were extrapolated until all combinations were derived.

Cost effectiveness analysis To undertake the analysis, a targeted literature review was carried out to identify either published cost effectiveness studies which could be adapted to the Mexican context, or literature which could inform the design of, and inputs to, a cost effectiveness model. The review identified a relatively recent network meta-analysis and cost effectiveness analysis of TM and STS programs after discharge in patients with HF, conducted by the National Institute for Health Research in 2013. This study was therefore used as the basis for a cost effectiveness analysis of STS and TM from the perspective of the Instituto Mexicano del Seguro Social. The model is based on monthly cycles with half cycle corrections. As HF is a life-long condition after onset, the model captured a life time horizon of 30 years with patients progressing through the model until they either died or reached the end of the 30-year time horizon. It was assumed that the interventions of STS, TM and standard care were provided for the full duration of the time horizon, outside of hospitalization. Both health system costs and QALYs were discounted at an annual rate of 5%. For the efficacy estimates, the monthly mortality probabilities were based on the ‘Candesartan in Heart failure: Assessment of Reduction in Mortality and Morbidity’ study. The mean number of HF related and other (all cause) hospitalizations were estimated from the published meta-analysis on the ‘Economic impact of remote patient monitoring: An integrated economic model derived from a meta-analysis of randomized controlled trials in heart failure’. Hazard ratios were estimated from the network meta-analysis on ‘Home telemonitoring or structured telephone support programmes after recent discharge in patients with heart failure’. Health state utilities for SC, STS and TM treatment approaches were based on the previous eco- nomic model of TM strategies of remote patient monitoring identified earlier. The units of resources making up the components of SC, STS and TM were based on the published literature, and unit costs were obtained from the Instituto Mexicano del Seguro Social.