oa Journal of Management & Administration - Inventory control systems for National Health Laboratory Services : the case of the KZN Health Department : research
|Article Title||Inventory control systems for National Health Laboratory Services : the case of the KZN Health Department : research|
|© Publisher:||Management College of Southern Africa (MANCOSA)|
|Journal||Journal of Management & Administration|
|Affiliations||1 MANCOSA and 2 Frere Hospital|
|Publication Date||Jan 2012|
|Pages||37 - 81|
The National Health Laboratory Services (NHLS) recently complained to Parliament that the KwaZulu-Natal (KZN) provincial health department is failing to pay R1.2 billion owed for laboratory tests. In dealing with non-payment and inventory management at the NHLS KZN the study conducted involved 65 participants drawn from 16 laboratories, 8 hospitals and 8 clinics in three KZN districts, namely, Sisonke Municipality, Ugu District Municipality and Umgungundlovu.
The study was based on post positivist research paradigm with both, a survey and qualitative document analysis as well as interviews conducted with key stakeholders. The key findings in the study highlight the critical need to manage inventory so as to lower holding costs, avoid stock outs and satisfy customers (Stevenson, 1999:561; McHugh, 2006, Lee, 1996; Chen and Simchi-Levi, 2004). In order to avoid stock outs and achieve satisfactory levels of customer service, inventory must be viewed periodically (Stevenson (1999:561, Cachon and Fischer, 2000, Fergruen and Heching, 1999). Over 77% of the respondents supported the view that the NHLS need to introduce electronic data interchange (EDI) that can assist in coordinating the flow of materials from laboratories to health departments so as to improve quantity and allocation decisions. For debt collection to improve at the NHLS, it is therefore important to introduce min-max system, build to order, build to stock, ABC analysis, vendor managed inventory (VMI), electronic data interchange (EDI), automatic pipeline inventory and order based production control system (APIOBPCS), stochastic inventory systems and genetic algorithm (Smaros, Lehtonnen, Appelqvist and Holstrom, 2003, Van der Laan and Salomon, 1997:264).
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