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Background  Risk adjustment models were used to estimate health care consumption after adjusting for individual characteristics or other factors. The results of this technique were not satisfying. One reason could be that the length of time to document consumption might be associated with the mean and variance of observed health care consumption. This study aims to use a simplified mathematical model and real-world data to explore the relationship of observation time (one or two years) and predictability.    Methods  This study used cross-sectional (one-year) and 2-year panel data sets of the Medical Expenditure Panel Survey (MEPS) from 1996 to 2008. Comparisons of the health care consumption (total health expenditure, emergency room (ER) and office-based visits) included ratios of means and standard errors (SEs). Risk adjustment models for one- and two-year data used generalized linear model.    Results  The ratios of mean health care consumption (two-year to one-year total expenditure, ER and office-based visits) seemed to be two in most age groups and the ratios of SEs varied around or above two. The R-squared of two-year models seemed to be slightly better than that of one-year models.    Conclusions  We find health expenditure and ER or office-based visits observed in two consecutive years were about twice those observed in a single year for most age, similar to the ratios predicted in mathematical examples. The ratios of mean spending and visits varied across age groups. The other finding is that the predictability of two-year consumption seems better than that of one-year slightly. The reason is not clear and we will continue studying this phenomenon.    Electronic supplementary material  The online version of this article (doi:10.1186/2047-2501-2-5) contains supplementary material, which is available to authorized users.

Risk adjustment and observation time: comparison between cross-sectional and 2-year panel data from the Medical Expenditure Panel Survey (MEPS)