Objective Traditional conformance detection methods mostly consider the control flow and do not take into account the impact of data on the conformance checking process in process. To address this limitation a conformance checking method based on the directly following rule model DFRM was proposed extending the traditional directly following model. Methods Firstly the control flow and data flow of the real process model were respectively transformed into business process rules from their own perspectives. Then the control flow rules were combined with the data flow rules using association rules and the data rules were processed using satisfiability modulo theory SMT ultimately obtaining the representation based on the direct-following rule model. Then event logs were extracted from event data and control flow alignment was prioritized before data flow alignment to achieve multi-perspective business process conformance checking. Results The proposed method was evaluated using real medical event logs. Compared with other traditional methods the proposed method has better performance in terms of model fitness and F1 score and the model has less execution time due to its simplicity. Conclusion Combining the data perspective with the directly following model in the form of data association rules provides a new extension direction for the model representation of current business process software. Introducing the data perspective into the business process solves the problem that existing process models cannot express some decision requirements related to data and also takes into account the possible biases of other perspectives in the conformance checking process.