Predictive Modelling of Covid-19 Stimulus Funds Paid for Nursing Home Quality Incentive Program


Omar Al-Azzam and Paul Court, St. Cloud State University, USA


Painstaking measures should be taken to determine how federal dollars are spent. Proper justification for allocation of funds rooted in logic and fairness leads to trust and transparency. The COVID-19 pandemic has warranted rapid response by government agencies to provide vital aide to those in need. Decisions made should be evaluated in hindsight to see if they indeed achieve their objectives. In this paper, the data collected in the final four months of 2020 to determine funding for nursing home facilities via the Quality Incentive Program will be analysed using data mining techniques. The objective is to determine the relationships among numeric variables and formulae given. The dataset was assembled by the Health Resources and Services Administration. Results are given for the reader’s insight and interpretation. With the data collection and analytical process, new questions come to light. These questions should be pondered for further analysis.


Predictive modelling, Cross validation, Linear Regression.

Full Text  Volume 11, Number 22