New diagnostic tools that can detect malaria parasites in conjunction with other diagnostic parameters are urgently required. In this study, Attenuated Total Reflection Fourier transform infrared (ATR-FTIR) spectroscopy in combination with Partial Least Square Discriminant Analysis (PLS-DA) and Partial Least Square Regression (PLS-R) have been applied as a point-of-care test for identifying malaria parasites, blood glucose, and urea levels in whole blood samples from thick blood films on glass slides. The specificity for the PLS-DA was found to be 98% for parasitemia levels >0.5%, but a rather low sensitivity of 70% was achieved because of the small number of negative samples in the model. In PLS-R the Root Mean Square Error of Cross Validation (RMSECV) for parasite concentration (0-5%) was 0.58%. Similarly, for glucose (0-400 mg/dL) and urea (0-250 mg/dL) spiked samples, relative RMSECVs were 16% and 17%, respectively. The method reported here is the first example of multianalyte/disease diagnosis using ATR-FTIR spectroscopy, which in this case, enabled the simultaneous quantification of glucose and urea analytes along with malaria parasitemia quantification using one spectrum obtained from a single drop of blood on a glass microscope slide.