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A Mathematical Model for Monitoring Laboratory Revenue Accrued from Tests

by Jessica Chinezie Benson-Iyare, H. A. Soriyan
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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

@article{ 10.5120/ijais2018451757,
author = { Jessica Chinezie Benson-Iyare, H. A. Soriyan },
title = { A Mathematical Model for Monitoring Laboratory Revenue Accrued from Tests },
journal = { International Journal of Applied Information Systems },
issue_date = { May 2018 },
volume = { 12 },
number = { 13 },
month = { May },
year = { 2018 },
issn = { 2249-0868 },
pages = { 37-49 },
numpages = {9},
url = { https://www.ijais.org/archives/volume12/number13/1033-2018451757/ },
doi = { 10.5120/ijais2018451757 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T19:09:14.277531+05:30
%A Jessica Chinezie Benson-Iyare
%A H. A. Soriyan
%T A Mathematical Model for Monitoring Laboratory Revenue Accrued from Tests
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 12
%N 13
%P 37-49
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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.

References
  1. Mangels, J. I. (2008). Cost Effective Clinical Microbiology. California Association for Medical Laboratory Technology. DL-984. 1-25.
  2. Eze, J. C. (2013). Evaluation of Fraud and Internal Control Procedures: Evidence from Two South East Government Ministries in Nigeria. Research Journal of Finance and Accounting. 4(17): 63-70.
  3. Neumann, D. and Pueschel, T. (2009). Management of Cloud infrastructures: Policy-based Revenue of Optimization. Association of Information Systems Electronic Library (ICIS). Proceedings. 178.
  4. Vikica, B., Hrvoje, P., and Mladen, P. (2011). Clinical laboratory as an economic model for business performance analysis. Clinical Sciences doi: 10.3325/cmj.52.513.
  5. Michael, F. J. and Shatkin, L. (2004). Best jobs for the 21st century. JIST Works. 460. ISBN 1-56370-961-9.
  6. Wyman, O. (2006). Reducing Revenue Leakage. www.oliverwyman.com. Retrieved on March 25, 2014.
  7. Ramesh, V., Glass, R., and Vessey, I. (2004). Research in computer science: an empirical study. The Journal of Systems and Software, 70: 165-176.
  8. Di Caro, G. A. (2003). Analysis of simulation environments for mobile ad hoc networks. Technical Report No. IDSIA-24-03, Dalle Molle Institute for Artifcial Intelligence, Galleria 2, 6928 Manno, Switzerland.
  9. Fetter, K. (2017). Revenue Cycle Management Challenges in Laboratory Outreach. http://www.beckershospitalreview.com/finance/ revenue-cycle-management-challenges-in-laboratory- outreach.html. Retrieved on 11/05/2018.
  10. Adane, K., Abiyi, Z., and Desta, K. (2015). The Revenue Generated from Clinical Chemistry and Hematology Laboratory Services as Determined using Activity-Based Costing (ABC) Model. Cost Effectiveness and Resource Allocation 13(20): 1-7.
  11. Manickam, T. S. and Ankanagari, S. (2015). Evaluation of Quality Management Systems Implementation in Medical Diagnostic Laboratories Benchmarked for Accreditation. Journal of Medical Laboratory and Diagnosis. 6(5): 27-35.
Index Terms

Computer Science
Information Sciences

Keywords

Laboratory Hospital Model Revenue Monitoring Regression multiple variable linear equation simulation mathematical model evaluation multivariate linear regression analysis

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