Med Decis Making - Use of multiparameter evidence synthesis to assess the appropriateness of data and structure in decision models.

Tópicos

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Resumo

JECTIVES: Decision models for health technology appraisal are defined by their structure and data. Often there are alternatives for how the model might be specified and what data to include, and criteria are required to guide these choices. This study uses multiparameter evidence synthesis (MPES) to synthesize data from diverse sources and test alternative model structures. The methods are illustrated by a comparison of blood ketone testing versus urine ketone testing for young people with Type 1 diabetes.METHODS: Two approaches were compared. A simple statistical model (Model 1) was used to estimate the difference in the rates of adverse events from the outcome data of a randomized controlled trial (RCT). MPES (Model 2) was constructed to synthesize data on outcome and process variables from the RCT with data from nonrandomized studies on specificity and sensitivity. Sensitivity analyses were carried out using alternative model specifications for the MPES, and the consistency of the data was evaluated.RESULTS: Model 1 estimated that the mean difference in the rate of adverse events per day was 0.0011 (95% confidence interval 0.0005-0.00229) lower with blood ketone testing. Model 2 estimated a similar outcome but also estimated parameters for which there were no direct data, including the prevalence of high ketone levels and the sensitivity and specificity of the tests as used in the home.CONCLUSIONS: Model 1, which used only outcome data from an RCT, showed that blood ketone testing is more effective but did not explain why this is so. Model 2, estimated by MPES, suggested that the blood test is more accurate and that patients are more likely to comply with the protocol.

Resumo Limpo

jectiv decis model health technolog apprais defin structur data often altern model might specifi data includ criteria requir guid choic studi use multiparamet evid synthesi mpes synthes data divers sourc test altern model structur method illustr comparison blood keton test versus urin keton test young peopl type diabetesmethod two approach compar simpl statist model model use estim differ rate advers event outcom data random control trial rct mpes model construct synthes data outcom process variabl rct data nonrandom studi specif sensit sensit analys carri use altern model specif mpes consist data evaluatedresult model estim mean differ rate advers event per day confid interv lower blood keton test model estim similar outcom also estim paramet direct data includ preval high keton level sensit specif test use homeconclus model use outcom data rct show blood keton test effect explain model estim mpes suggest blood test accur patient like compli protocol

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