Thesis submitted in fulfillment of the requirements of the degree Master of Technology: Biomedical Technology in the Faculty of Health and Wellness Sciences at the Cape Peninsula University of Technology 2015 / Aim: The aim of the study was to compile pre-tested laboratory results stored in the laboratory database of the Namibia Institute of Pathology (NIP). The study also aimed to assess the usefulness and validity of using retrospective laboratory results of different patients in varying degrees of health and which were produced using various methods in different laboratories in Namibia. Methods: 254,271 test results (female: 134,261, male = 117,091, unknown gender= 2,919) consisting of Haemoglobin, serum Urea, serum Creatinine, plasma Glucose (fasting and random), serum Cholesterol, serum Triglycerides and serum Uric Acid was extracted from NIP Laboratory Information System over a period of four years and of the 13 different regions of Namibia were analyzed.. Each data set was sorted in ascending order and outliers were eliminated using SPSS Box plot function. Data available for analysis were Haemoglobin: 18,999 (male = 7,716, female = 11,283, serum Urea: 8,111 (male = 3,836, female=4.275), serum Creatinine: 8,794 (male=4,099, female= 4,506), plasma Glucose: 78,106 (fasting=32,591, random=45,515), serum Cholesterol: 48,354 (male=24,815, female=23,539), Serum Triglycerides: 22,138 (male=9,291, female=12,847) serum Uric Acid: 37,389 (male=18,972, female=18,427). Results of tests were also analysed according to the 13 regions in Namibia. Outliers were removed using the Box plot function of SPSS and statistics were calculated for each of the parameters. Tables and histogram as well as percentile ranges (2.5th -97.5th and 5th -95th) were determined for each parameter. Results: Non-parametric percentile ranges were as follows: Haemoglobin (2.5-97.5: M=6.64-16.9, F=7.81-15.2 and 5-95: M=7.39-16.3, F=8.48-14.7) g/L, Urea (2.5-97.5: 1.3- 9.1, 5-95:1.6-8.4) mmol/L, Creatinine (2.5-97.5: M=37-141, F=33-103 and 5-95: M=43- 133, F=39-117) μmol/L, Glucose (2.5-97.5: fasting=3.4-9.5, random=3.7-7.1 and 5-95: fasting=3.9-9.1, random 4-6.9) mmol/L, Cholesterol (2.5-97.5: M=2.6-6.9, F=2.8-7.0 and 5- 95: M=2.9-6.1, F=3.1-6.2) mmol/L, Triglyceride (2.5-97.5: 0.39-2.72 and 5-95: 0.46-2.5) mmol/L and Uric Acid (2.5-97.5: M=0.21-0.62, F=0.17-0.51 and 5-95: M=0.24-0.58, F=0.19-0.48) mmol/L. Conclusion: A statistically significant difference between the mean values of the study and the mean values of NIP reference range was detected and differences between these values and reference values in the region were observed. More work needs to be done to improve the data extraction process, data selection criteria and improvement of statistical analysis. If these can be addressed, it can be stated that using patient laboratory data values is a relatively easy and cost effective method of establishing laboratory and population specific reference values if skewness and kurtosis of the distribution are not too large.