A Narrative Review of the Laboratory Information System and Its Role in Antimicrobial Resistance Surveillance in South Africa ()
Peter S. Nyasulu,
Christine Paszko,
Nontombi Mbelle
Accelerated Technology Laboratories, Inc., West End, NC, USA.
Department of Medical Microbiology, University of the Pretoria, Pretoria, South Africa.
Department of Public Health, School of Health Sciences, Monash University, Johannesburg, South Africa.
DOI: 10.4236/aim.2014.410074
PDF HTML
5,846
Downloads
7,491
Views
Citations
Abstract
A
laboratory information system (LIS) established in a microbiology department
has the potential to play an important role in the quality of microbiology data such as culture of blood, urine, stool, pus swab
samples etc. Such data could be effectively utilised to measure the burden of antimicrobial
resistance among patients presented to various hospitals and clinics with an
episode of an infectious illness of bacterial origin. A variety of clinical and epidemiological
investigations are conducted using culture data and the presence of an electronic
system such as LIS enhances such investigations and improves the reliability of
measures of antimicrobial resistance owing to improved data quality as well as
completeness of data gathered as opposed to paper based system. Therefore to improve surveillance of antimicrobial
resistance in
South Africa, there is a need to reinforce the functionality of the LIS in both public and
private microbiology laboratories as this will help to improve internal quality
control methodologies.
Share and Cite:
Nyasulu, P. , Paszko, C. and Mbelle, N. (2014) A Narrative Review of the Laboratory Information System and Its Role in Antimicrobial Resistance Surveillance in South Africa.
Advances in Microbiology,
4, 692-696. doi:
10.4236/aim.2014.410074.
Conflicts of Interest
The authors declare no conflicts of interest.
References
|
[1]
|
Paszko, C. (2014) Computerised Laboratory Information Management System (LIMS).
www.samedanltd.com
|
|
[2]
|
NHLS (National Health Laboratory Services) (2013) http://www.nhls.ac.za
|
|
[3]
|
Skolbelev, D.O., Zaytseva, T.M., Kozlov, A.D., Perepelitsa, V.L. and Makarova, A.S. (2011) The Metrological Service: Labaratory Information Management Systems in the Work of the Analytic Laboratory. Measurement Techniques, 53, 1182-1189.
http://dx.doi.org/10.1007/s11018-011-9638-7
|
|
[4]
|
Zhu, J.Y. (2005) Automating Laboratory Operations by Intergrating Labortory Information Management Systems (LIMS) with Analytical Instruments and Scientific Data Mangement Systems (SDMS). Indiana University.
http://hdl.handle.net/1805/323
|
|
[5]
|
Health Systems Technologies. Laboratory Information System. http://www.healthsystems.co.za/?page_id=19
|
|
[6]
|
Patil, P.S., Rao, S. and Patil, S.B. (2011) Optimization of Data Warehousing System: Simplification in Reporting and Analysis. IJCA Proceedings on International Conference and Workshop on Emerging
Trends in Technology (ICWET), 9, 33-37. http://www.ijcaonline.org/proceedings/icwet/number9/213
1-db195
|
|
[7]
|
TrakCare Lab. Breakthroughs in Patient Outcomes, Lab Performance and Clinicians Communication.
http://www.intersystems.com/TrakCareLAB/TrakCareLAB.pdf
|
|
[8]
|
Hirsh, J. (1999) Open Database Connectivity Version 08.
www.erlang.org/documentation/doc-4.9.1/pdf/odbc-0.8.1.pdf
|
|
[9]
|
Haynes, R.B. and Wilczynski, N.L. (2010) Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes: Methods of a Decision-Maker-Researcher Partnership Systematic Review. Implementation Science, 5, 12.
http://www.implementationscience.com/content/5/1/12
http://dx.doi.org/10.1186/1748-5908-5-12
|