The researchers developed a new model called zero-inflated Poisson quasi-Lindley regression to analyze data on the number of doctor visits. This model is used when there are more zeros in the data than expected, which can cause issues with traditional methods. By comparing this new model to existing ones using real medical expenditure data, they found it to be effective in handling over-dispersed count data with excessive zeros.