Comparison of Turnaround Time for Complete Blood Count Before and After LIS–HMIS Integration in a Clinical Laboratory

I Gede Widiaastawa, Putu Ayu Parwati, Ni Luh Gede Puspita Yanti

Abstract


Turnaround Time (TAT) is a key indicator of clinical laboratory performance as it affects diagnostic accuracy and clinical decision-making. This study aimed to compare complete blood count (CBC) TAT before and after the implementation of LIS–HMIS integration at Tabanan Regional General Hospital. This study used a quantitative comparative design with secondary data obtained from LIS and HMIS logs. A total of 316 records before integration (January–March 2025) and 316 records after integration (May–July 2025) were selected using simple random sampling. Data were analyzed using the Mann–Whitney test with a significance level of 0.05. The results showed that the proportion of TAT meeting the standard increased from 71.52% before integration to 75.95% after integration. However, statistical analysis indicated no significant difference (p=0.259). These findings suggest that LIS–HMIS integration improves operational efficiency, although the improvement is not statistically significant.

Keywords


Turnaround Time, Complete Blood Count, Hospital Management Information System, Laboratory Information System

Full Text:

PDF

References


WHO. Strengthening diagnostics capacity [Internet]. 2023 [cited 2026 Feb 3]. Available from: https://www.who.int/activities/strengthening-diagnostics-capacity

Marzinke MA, Clarke W, Dietzen DJ, Hoofnagle AN, McMillin GA, Willrich MA V. The VALIDity of Laboratory Developed Tests: Leave it to the experts? J mass Spectrom Adv Clin lab. 2023 Jan;27:1–6.

Singhal N, Vardhan H, Jain R, Gupta P, Pandey A, Wagri NK, et al. Role of artificial intelligence in automating diagnostic procedures in clinical microbiology laboratories. Curr Res Biotechnol [Internet]. 2025;10:100351. Available from: https://www.sciencedirect.com/science/article/pii/S2590262825000826

Lippi G, Ognibene A. Perspectives on emerging challenges and training needs for the Laboratory Medicine specialist of the future. Adv Lab Med. 2026 Mar;7(1):16–25.

K G N, Ahmad S, Kumar P, Mahto M, Bharti S. Turnaround Time of Laboratory Investigations and Factors Responsible for Delays in a Tertiary Care Teaching Hospital in Eastern India: A Cross-Sectional Study. Cureus. 2026 Jan;18(1):e100703.

Seo IH, Lee YJ. Usefulness of Complete Blood Count (CBC) to Assess Cardiovascular and Metabolic Diseases in Clinical Settings: A Comprehensive Literature Review. Biomedicines. 2022 Oct;10(11).

Cabalar I, Le TH, Silber A, O’Hara M, Abdallah B, Parikh M, et al. The role of blood testing in prevention, diagnosis, and management of chronic diseases: A review. Am J Med Sci [Internet]. 2024;368(4):274–86. Available from: https://www.sciencedirect.com/science/article/pii/S0002962924011698

Lukić V. Laboratory Information System - Where are we Today? J Med Biochem. 2017 Sep;36(3):220–4.

Hammoudeh S, Amireh A, Jaddoua S, Nazer L, Jazairy E, Al-Dewiri R. The Impact of Lean Management Implementation on Waiting Time and Satisfaction of Patients and Staff at an Outpatient Pharmacy of a Comprehensive Cancer Center in Jordan. Hosp Pharm. 2021 Dec;56(6):737–44.

Febrita H, Martunis M, Syahrizal D, Abdat M, Bakhtiar B. Analysis Of Hospital Information Management System Using Human Organization Fit Model. J Adm Kesehat Indones. 2021;9:23.

Zheng F, Wang K, Wang Q, Yu T, Wang L, Zhang X, et al. Factors Influencing Clinicians’ Use of Hospital Information Systems for Infection Prevention and Control: Cross-Sectional Study Based on the Extended DeLone and McLean Model. J Med Internet Res. 2023 Jun;25:e44900.

Tsai CH, Eghdam A, Davoody N, Wright G, Flowerday S, Koch S. Effects of Electronic Health Record Implementation and Barriers to Adoption and Use: A Scoping Review and Qualitative Analysis of the Content. Life (Basel, Switzerland). 2020 Dec;10(12).

Edayan JM, Gallemit AJ, Sacala N, Palmer XL, Potter L, Rarugal J, et al. Integration Technologies in Laboratory Information Systems: A Systematic Review. Informatics Med Unlocked. 2024;50:101566.

Alzghaibi H, Hutchings HA. Barriers to the implementation of large-scale electronic health record systems in primary healthcare centers: a mixed-methods study in Saudi Arabia. Front Med. 2025;12:1516714.

Faiz F, Le V, Masli EK. Determinants of digital technology adoption in innovative SMEs. J Innov Knowl [Internet]. 2024;9(4):100610. Available from: https://www.sciencedirect.com/science/article/pii/S2444569X24001495

Rahimi B, Nadri H, Lotfnezhad Afshar H, Timpka T. A Systematic Review of the Technology Acceptance Model in Health Informatics. Appl Clin Inform. 2018 Jul;9(3):604–34.




DOI: https://doi.org/10.30602/jlk.v9i2.2269

Refbacks

  • There are currently no refbacks.


Copyright (c) 2026 Jurnal Laboratorium Khatulistiwa

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.



JURNAL LABORATORIUM KHATULISTIWA (JLK)

Jurnal Laboratorium Khatulistiwa (JLK) (Print ISSN: 2597-9523 | e-ISSN: 2597-9531 ) is a peer-reviewed open-access scientific journal published by the Department of Medical Laboratory Technology, Poltekkes Kemenkes Pontianak. This journal focuses on the development of medical laboratory science and technology.



Jurnal Laboratorium Khatulistiwa is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License .
CONTACT
✉ jurnallaboratoriumkhatulistiwa@poltekkes-pontianak.ac.id
📍 Poltekkes Kemenkes Pontianak, Jl. 28 Oktober Siantan Hulu, Pontianak, Kalimantan Barat, Indonesia



COLLABORATION
© Poltekkes Kemenkes Pontianak - Jurnal Laboratorium Khatulistiwa (JLK)