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Abstract

This study looks at how Valenzuela Medical Center's (VMC) clinical workflow efficiency and patient outcomes are influenced by the installa-tion of a Laboratory Information System (LIS). Due to time constraints, convenience sampling was used to collect data from sixty-three (63) medical professionals in the clinical and diagnostic laboratory depart-ments using a descriptive study design and a mixed-methods technique. To measure participant responses, descriptive statistics such as means, standard deviations, and frequency distributions were used. Using paired sample t-tests, inferential analysis was carried out to compare metrics before and after LIS adoption, with an emphasis on factors like error rates, turnaround times, and specimen handling accuracy.
Key findings showed that LIS adoption improved data accessibility across departments, lowered transcription errors by about 28%, and cut specimen processing turnaround times by an average of 35%, all of which contributed to improved interdepartmental communication. Further-more, 90% of respondents expressed more confidence in the accuracy of laboratory results following LIS integration, and 85% of respondents re-ported higher satisfaction with data processing procedures. Significant improvements were also shown in patient outcomes, with quicker diag-nostic processing leading to earlier treatment commencement and, in some situations, shorter hospital stays overall. In addition to demon-strating the wider advantages of incorporating cutting-edge information systems in healthcare settings, this study emphasizes the critical role that LIS plays in improving laboratory operations, cutting down on diag-nostic delays, and improving the quality of patient care at VMC.

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How to Cite
Antonio, S. M., Dancel, M. B., Lim , C. N., Roberto, J. R. A., Malang, B. P., & Malang, J. D. (2024). Assessing the Impact of Laboratory Information System on Clinical Workflow and Patient Outcomes. International Journal of Multidisciplinary: Applied Business and Education Research, 5(11), 4629-4641. https://doi.org/10.11594/ijmaber.05.11.27

References

Ahmed, F., Jansen, M., & Roberts, L. (2023). Impact of rapid laboratory reporting on hospital stays. Journal of Clinical Patholo-gy, 76(4), 245-252.
Bates, D. W., & Gawande, A. A. (2003). "Im-proving Safety with Information Tech-nology." New England Journal of Medicine, 348(25), 2526-2534.
Hoyt, R. E., & Yoshihashi, A. K. (2014). Health Informatics: Practical Guide for Healthcare and Information Tech-nology Professionals. Lulu.com.
Kahn, S., Lee, T., & Patel, R. (2019). Reducing laboratory errors through information systems. Healthcare Informatics Re-search, 25(1), 12-20.
Kawamoto, K., Houlihan, C. A., Balas, E. A., & Lobach, D. F. (2005). "Improving Clinical Practice Using Clinical Decision Support Systems: A Systematic Review of Trials to Identify Features Critical to Success." BMJ, 330(7494), 765-773.
Marra, A., Zhang, Y., & O’Connell, M. (2020). The role of Laboratory Information Sys-tems in enhancing laboratory efficiency. Clinical Biochemistry, 80, 44-50.
Nair, S., Gupta, A., & Thomas, J. (2021). The effects of Laboratory Information Sys-tems on clinical workflow: A systematic review. International Journal of Medical Informatics, 150, 104449.
Smith, R., Kwan, T., & Kim, H. (2022). Interde-partmental communication and the role of Laboratory Information Systems. Jour-nal of Healthcare Management, 67(2), 114-122.
Singh, A., Kumar, R., & Patel, S. (2021). The impact of Laboratory Information Sys-tems on clinical workflow: A systematic review. Journal of Healthcare Manage-ment, 66(3), 145-158. https://doi.org/10.1016/j.jhm.2021.01.002
Singh H, Meyer AN, Thomas EJ. The frequency of diagnostic errors in outpatient care: estimations from three large observa-tional studies involving US adult popula-tions. BMJ Qual Saf. 2014;23(9):727–31.
Georgiou, A., Braithwaite, J., Westbrook, J. I., & Iedema, R. A. M. (2019). A systematic re-view of the effects of computerized pro-vider order entry systems on medical im-aging services. 251(3), Radiology, 629–636.
The National Academy of Medicine. (2015). enhancing diagnosis in medical treat-ment. The National Academies Press, Washington, DC. https://doi.org/10.17226/21794.
Balis, U. J., Tuthill, J. M., and Pantanowitz, L. (2013). Theory and Practice of Pathology Informatics. Springer Publishing, Chicago.
Authority for Philippine Statistics (PSA). (2021). National Health Accounts for the Philippines. Accessible at: https://psa.gov.ph Quezon City: PSA
Varshney, D., and Sharma, R. (2020). Obstacles to India's use of laboratory information systems. Health Informatics Journal, 6(1), 23–29.
Meyer, A. N. D., Singh, H., and Thomas, E. J. (2014). Three sizable observational stud-ies including adult US populations were used to estimate the prevalence of diag-nostic mistakes in outpatient care. 727–731 in BMJ Quality & Safety, 23(9). https://doi.org/10.1136/bmjqs-2013-002627
Park, H., and Williams, J. (2017). Opportunities and challenges in assessing laboratory in-formation systems in environments with limited resources. 1355626 in Global Health Action, 10(1). https://doi.org/10.1080/16549716.2017.1355626