  Performance evaluation of nursing homes is usually accomplished by the
repeated administration of questionnaires aimed at measuring the health status
of the patients during their period of residence in the nursing home. We
illustrate how a latent Markov model with covariates may effectively be used
for the analysis of data collected in this way. This model relies on a not
directly observable Markov process, whose states represent different levels of
the health status. For the maximum likelihood estimation of the model we apply
an EM algorithm implemented by means of certain recursions taken from the
literature on hidden Markov chains. Of particular interest is the estimation of
the effect of each nursing home on the probability of transition between the
latent states. We show how the estimates of these effects may be used to
construct a set of scores which allows us to rank these facilities in terms of
their efficacy in taking care of the health conditions of their patients. The
method is used within an application based on data concerning a set of nursing
homes located in the Region of Umbria, Italy, which were followed for the
period 2003--2005.

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