The insurance model when the amount of claims depends on the state of the insured person (healthy, ill, or dead) and claims are connected in a Markov chain is investigated. The signed compound Poisson approximation is applied to the aggregate claims distribution after n∈N periods. The accuracy of order O(n−1) and O(n−1/2) is obtained for the local and uniform norms, respectively. In a particular case, the accuracy of estimates in total variation and non-uniform estimates are shown to be at least of order O(n−1). The characteristic function method is used. The results can be applied to estimate the probable loss of an insurer to optimize an insurance premium.