ISPOR 5th Latin America Conference Minas Gerais - Brazil EQ-5D Research Kenya Noronha CEDEPLAR/UFMG W15: EQ-5D: EL MÉTODO BÁSICO PARA LA MEDICIÓN Y VALORACIÓN DE LA SALUD EN AMÉRICA LATINA Santiago, Chile September, 8th - 2014 ISPOR 5th Latin America Conference Andrade M, Noronha K, Kind P et al. Societal Preferences for EQ-5D Health States from a Brazilian Population Survey. Value in Health Regional Issues, Volume 2, Issue 3, Pages 405-412. Santiago, Chile September, 8th - 2014 1
RESEARCH INSTITUTIONS FEDERAL UNIVERSITY OF MINAS GERAIS (UFMG) GRADUATE PROGRAM OF ECONOMICS CENTER FOR REGIONAL DEVELOPMENT AND PLANNING (CEDEPLAR) WWW.CEDEPLAR.UFMG.BR HEALTH ECONOMICS AND CRIMINALITY GROUP Financial Support PROJECT SUPPORTED BY FUNDAÇÃO DE APOIO A PESQUISA DO ESTADO DE MINAS GERAIS FAPEMIG (MINAS GERAIS STATE RESEARCH FOUNDATION) Research approved by the Ethics Committee of Federal University of Minas Gerais 2
Research Team CEDEPLAR/UFMG: Mônica Viegas Andrade (PI) Kenya Noronha (PI) Ana Carolina Maia UNIVERSITY OF YORK: Paul Kind (Consultant) Research Assistants: Camila Lins Carla de Barros Reis Renata de Miranda Menezes Júlia Calazans Tamires Mascarenhas Diego Rezende Martins Michelle Nepomuceno Souza Lucas Gomes Costa de Paula Daniel Pinheiro Nichele Lucas Resende de Carvalho Ana Luisa Biet Field Research: Instituto Olhar MINAS GERAIS - Located at the southeast region - Population size: 20 million - 2 nd economy of Brazil - Great socioeconomic heterogeneity - Capital of the State: Belo Horizonte 3
YEAR BASE MINAS GERAIS X BRAZIL CHARACTERISTICS BRAZIL MG 2010 Population 190,732,694 19,595,309 2010 Urban Population 84% 85% 2010 Rural Population 16% 15% 2008 GDP per capita (US$) 8,690 7,635 2008 Average Schooling -individuals over 15 years old Source: Brazilian Institute of Geography and Statistics - IBGE 7.42 7.21 2008 Analphabets - individuals over 15 years old 9.96% 8.65% 2009 Gini's Index 0.543 0.513 2009 Poverty 21.42% 12.05% 2007 Infant mortality rate per 1000 live birth 20.0 17.4 Interview Protocol Revised version (Kind 2009) of the original MVH (Measurement and Valuation of Health) study It has already been applied in French and Korean valuation study 4
Original Protocol (Gudex 1994) Modification (Kind 2009) Importance Individuals classify health states using VAS after ranking exercise Health states cards are shuffled between Ranking and VAS exercise Allows to evaluate better the correlation between both methods Use unconscious card Remove unconscious from set of EQ-5D health states used in valuation studies The state unconscious lies outside the formal descriptive system defined by the 5 dimensions. It was incorporated within the EQ-5D classification from its inception. It is not clear that this state has any practical relevance within the general classification of health status although this question has yet to be resolved on the basis of empirical evidence. (Chevalier e Pouvourville 2011, Lee et al 2009, Zarate et al 2011). Original Protocol (Gudex 1994) Modification (Kind 2009) Importance Immediate Death Dead Immediate death has somewhat drastic implications. It implies that the respondent has to imagine dying instantly. Some people might find it difficult to imagine this being implemented other than through the use of external force, for example via euthanasia, thereby introducing a major uncontrolled source of potential distortion. 5
Original Protocol (Gudex 1994) Modification (Kind 2009) Importance 43 health states 102 health states To guarantee better estimation of all social parameters 13 health states evaluated by individual 06 health states evaluated + 33333 States were grouped into 26 blocks, with 6 health states in each comprising 2 mild, 2 moderate, and 2 severe states. This makes the evaluation exercise less demanding and individuals appear more likely to give responses that are not subject to fatigue or loss of attention. Fieldwork Commercial market research agency : Instituto Olhar Pre-test was conducted by the Institute team and CEDEPLAR research team 13 interviewers All interviewers received 3 days training conducted by University researchers Fieldwork was carried out between October and December 2011 20% of questionnaires were checked by phone call in order to detect possible fraud by interviewers. 6
Fieldwork All field research was supervised by University team to minimize any systematic errors by interviewers in applying the protocol rigorous quality control processes were enforced. A spreadsheet was used to support quality control and to examine interviewer s individual performance In the presence of systematic errors the interviewer was retrained 3 interviewers were excluded. Interviews lasted for an average of 44 minutes All respondent data were double-entered into a Microsoft Excel file. 7
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Study Design Target population literate individuals aged between 18 and 64 years old living in urban areas of Minas Gerais. Sample-size 2010 Brazilian Demographic Census with a margin of error equal to 3%. 3362 individuals were recruited 1115 lived in Belo Horizonte (capital) 626 in metropolitan area 1621 in the non-metropolitan area. Quota sampling by age and sex. Face to-face interviews One individual was selected by household. Study Design 102 health states selected from the complete set of 243 states covering 3 broad severity categories defined by their proximity to the best possible health state States were grouped into 26 blocks, with 6 health states in each comprising 2 mild, 2 moderate, and 2 severe states (Kind 2009): Mild states: no level 3 problem on any dimension and up to 3 level 2 problems (25 health states) Severe states: no level 1 problem on any dimension and at least 2 level 3 problems (25 health states) Moderate states: lie within these two boundaries (52 health states) All health states were evaluated by more than 100 individuals as recommended by Chuang and Kind (2010) 9
Estimation Methods Regression analysis was used to estimate social preference values for all 243 possible EQ-5D health states No inconsistent respondent data were excluded Aggregate and individual level models were estimated using Ordinary Least Square (OLS) method. Panel data regression models (FE and RE) were also used Estimation Methods Two tests were performed in order to assist the final choice of the estimation: Hausman test: FE x RE Breush-Pagan test: OLS x RE models MAE (Mean Absolute Error) and number of health states with absolute residuals over 0.05 were computed to as goodness-of-fit statistics. 10
Variables Definition Dependent Variable: 1 minus transformed TTO response (1-Vt) Independent Variables: a set of 10 dummy variables for each level of severity and health dimensions: Health Dimension MO SC UA PD AD Dummy Variables MO2 = 1 if mobility dimension is on level 2 MO3 = 1 if mobility dimension is on level 3 SC2 = 1 if self-care dimension is on level 2 SC3 = 1 if self-care dimension is on level 3 UA2 = 1 if usual activities dimension is on level 2 UA3 = 1 if usual activities dimension is on level 3 PD2 = 1 if pain/discomfort dimension is on level 2 PD3 = 1 if pain/discomfort dimension is on level 3 AD2 = 1 if anxiety/depression dimension is on level 2 AD3 = 1 if anxiety/depression dimension is on level 3 Sociodemographic and health characteristics of the achieved sample in the EQ-5D Valuation Study and other Household Surveys in Minas Gerais Sex Age Group Educational Level Characteristics EQ-5D FJP IBGE Men 51.58 52.43 52.08 Women 48.42 47.57 47.92 18-34 43.3 47.23 46.2 35-49 33.95 32.5 33.37 50-59 16.25 15.29 15.9 >60 6.5 4.98 5.13 <3 yrs 4.86-5.62 4-10 yrs 48.93-45.21 11 yrs 37.64-36.43 12+ 8.54-12.74 Source: Minas Gerais Valuation Study. 2011; Instituto Brasileiro de Geografia e Estatistica IBGE. 2008; Fundação João Pinheiro - FJP. 2009. 11
Sociodemographic and health characteristics of the achieved sample in the EQ-5D Valuation Study and other Household Surveys in Minas Gerais Marital Status Private Health Insurance Self-reported Health Characteristics EQ-5D FJP IBGE Married 45.85 56.12 - Widowed 2.95 2.83 - Divorced 6.71 7.92 - Single 44.41 33.13 - Yes 31.36 28.34 35.38 No 68.64 71.28 64.62 Very Good 25.35 29.17 31.18 Good 52.01 49.41 48.99 Fair 20.49 18.32 17.12 Bad 1.58 2.4 2.14 Very Bad 0.49 0.65 0.57 Source: Minas Gerais Valuation Study. 2011; Instituto Brasileiro de Geografia e Estatistica IBGE. 2008; Fundação João Pinheiro - FJP. 2009. Main Results Estimated coefficients: very similar irrespective of the estimation method used indicating very stable predictions. All dummy coefficients are positive and significant at the 1% level. Coefficients behave as expected: value decrement increases with increasing severity for all health dimensions The largest decrement is observed for severe mobility problems and the smallest for anxiety/ depression. 12
Main Results Goodness-of-fit statistics: satisfactory and quite similar among the five models MAE around 0.03 % states with an absolute error greater than 0.05 is 23% in the OLS individual model and 25% in the OLS aggregate model and RE model. OLS models excluding a constant term present higher % of health states with MAE greater than 0.05 (28% and 29%). As the results are quite similar across models, the model definition is not a significant issue. Main Results To take into account that each individual can have different patterns of responses, the RE model was chosen Hausman test was not significant: RE model can be safely accepted. Breush-Pagan test rejects the null hypothesis: presence of heteroscedasticity favours the use of RE models. Different forms of RE model were tested involving the introduction of interaction terms results were similar to the initial main effects specification with identical goodnessof-fit statistics Because the results were very similar among the RE models, the basic specification including only dummy variables for each health dimension and level of severity was selected. 13
-.2 0 Predicted TTO values.2.4.6.8 Minas Gerais Estimated and Observed TTO values for all EQ-5D health states (using RE model) -.2 0.2.4.6.8 Observed TTO values Source: MG EQ-5D Study 14
-.5 -.5 0 0.5.5 1 1 -.5 -.5 0 0.5.5 1 1 Societal preferences differences among selected EQ-5D health states EQ-5D states US HISPANIC by countries CHILE ARGENTINA MG (BRAZIL) 11111-11211 0.206 (3) 0.218 (1) 0.099 (1) 0.150 (1) 11111-11222 0.369 (6) 0.428 (5) 0.230 (3) 0.278 (2) 11121-22222 0.168 (2) 0.501 (6) 0.271 (4) 0.407 (6) 11122-22222 0.108 (1) 0.401 (4) 0.219 (2) 0.345 (5) 22222-33223 0.506 (7) 0.653 (7) 0.654 (7) 0.452 (7) 33222-33333 0.261 (5) 0.259 (2) 0.581 (6) 0.294 (3) 33311-33333 0.250 (4) 0.368 (3) 0.427 (5) 0.313 (4) Example: Assess cost-effectiveness of a health benefit from EQ-5D state 11211 to 11111 and assuming a marginal cost of US$10,000: - cost/qaly (Argentine values) US$100,000 - cost/qaly (Brazilian values) US$65,000. Estimated mean preferences weights for 243EQ-5D health states: MG x Other Selected Countries Predicted Values Brazil and Argentina Predicted Values Brazil and Chile 0 50 100 150 200 250 id 0 50 100 150 200 250 id Argent_tto BR_tto Chile_tto BR_tto Predicted Values Brazil and US Hispanic Predicted Values Brazil and USA 0 50 100 150 200 250 id 0 50 100 150 200 250 id Spain_tto BR_tto USA_tto BR_tto 15
Final Remarks Models used to estimate societal preferences weights for EQ-5D health states shows very stables results The use of non-domestic value sets, even from continental or regional neighbours may not be adequate for healthpolicy decision-makers in Brazil Comparison between values for MG study and those for other population showed meaningful differences even for Brazil Latin-American neighbors further highlighting the importance of specific-country value sets. Final Remarks The extent to which these results can be safely generalised to the Brazilian population as a whole is a matter of conjecture However, given the heterogeneity of the Minas Gerais population it may well be the case that these initial results are broadly indicative of what might be expected from a wider national survey that included data from a larger sample drawn from across Brazil. 16
In 2012, a study was conducted for 3 cities in Brazil: Porto Alegre (South), Rio de Janeiro City (Southeast) and Recife (Northeast) Sample Size: 5,785 Final Remarks 243 EQ-5D-3L health states directly evaluated Each individual evaluated 6 random and the worst health state possible (33333) do not guarantee that individuals evaluated at least one mild, one moderate and one severe health state (unbalanced blocks) PI: Marisa Santos (Paper under review) 17