International Journal of Applied Information Systems |
Foundation of Computer Science (FCS), NY, USA |
Volume 12 - Number 13 |
Year of Publication: 2018 |
Authors: Jessica Chinezie Benson-Iyare, H. A. Soriyan |
10.5120/ijais2018451757 |
Jessica Chinezie Benson-Iyare, H. A. Soriyan . A Mathematical Model for Monitoring Laboratory Revenue Accrued from Tests. International Journal of Applied Information Systems. 12, 13 ( May 2018), 37-49. DOI=10.5120/ijais2018451757
One challenge in the laboratory is the discrepancies in the revenue reported to have been generated and the actual revenue generated from laboratory tests. In this paper, a mathematical model for tracking and monitoring revenue from hospital-based laboratory was formulated, simulated, and evaluated. The mathematical model was formulated using a multiple variable linear equation. The model was simulated using Matrix Laboratory (MATLAB) and evaluated for accuracy using the following performance metrics: Correlation coefficient, Mean absolute error, Root mean square error, Relative absolute error and Root relative squared error. Multivariate linear regression analysis method was used for the evaluation in Waikato Environment for Knowledge Analysis software (WEKA). Dataset for the simulation were retrieved from a government hospital-based laboratory in Idah, Nigeria. The result of the study showed that a multiple variable linear equation is sufficiently adequate in relating the revenue generated with the tests performed in hospital laboratory. Furthermore, the study revealed discrepancies in the revenue reported to have been generated from the laboratory tests. The regression analysis showed that the distribution of data for the classes of datasets have strong statistical relationship between tests and the revenue generated with a correlation coefficient of 0.9985 and 0.8113 respectively. In conclusion, the study established that the formulated multi-variate linear relationship between revenue and tests is appropriate in predicting revenue generated from hospital-based laboratory.