In the past decade, the use of microsampling in combination with the drying of the blood has gained vast popularity. Thereby, small volumes of capillary blood (typically 10–20 μL) are collected and allowed to dry on an absorbent sample support (e.g. cellulose filter paper or polymer-based tips). The collection of dried blood microsamples is easier, less invasive, and cheaper than conventional whole blood sampling, as samples can be handled, shipped, and stored more easily. In addition, it can be done by untrained persons, including the study subjects themselves and in remote settings. The patient's hematocrit (HCT) level can adversely affect the analysis results when dried blood spots (DBS) are used as a sample matrix. Volumetric DBS sampling has been proposed to nullify the impact of HCT area bias (spreading area) on DBS by normalizing it to a known sample volume. However, this strategy ignores DBS-related parameters such as analyte properties (red blood cell to plasma ratio) and HCT recovery bias. With the recent release of fully automated HCT measurement systems for DBS analysis, a broad range of end-users are now able to measure and correct a sample's HCT level in a non-destructive manner. These novel tools permit a correction for all known HCT-related impacts on DBS, such as analyte properties, HCT recovery bias, HCT area bias, and venous blood–to-DBS ratio, supporting and accelerating future quantitative DBS applications. However, with these novel tools, new questions arise concerning the normalization of analytical results, the choice of technique (single-wavelength reflectance VS near-infrared spectroscopy), and the DBS card-handling process post sampling. We address the necessary considerations for end-users and present real-life examples for the correction of the DBS's HCT based on the model compound Phosphatidylethanol 16:0/18:1 (PEth). PEth is remarkably HCT dependent due to its incorporation into red blood cells. For PEth a successful implementation of DBS HCT correction is presented based on the analysis of blood from four PEth positive individuals over a wide HCT range (HCT from 20%–70%) using fully automated DBS-Online-SPE-LC-MS/MS analysis. Such a correction can make the necessity of volumetric sampling for quantitative DBS analysis obsolete. Furthermore, combining automated HCT correction in combination with fully automated DBS LC-MS/MS analysis, the novel tools permits high-throughput analysis in combination with HCT independence. The obtained data demonstrate that as soon as the HCT dependence of an analyte is known, a correction factor can be applied for the normalization of HCT levels. In the context of PEth, a linear increase in PEth concentration was observed with increasing HCT concentrations (y = 1.9219x+0.0998, R2 = 0.9333), as PEth is primarily located within the cellular fraction. Thereby, for every 1% change in HCT, a PEth concentration change by 1.92% was observed (95% confidence interval of 1.695%–2.149%). The observed HCT dependency is in agreement with the earlier reported increase by Beck et al., which determined an approximate increase in PEth between 1.3–2.0% for every 1% increase in HCT. Based on the obtained results, the use of a common correction factor for PEth, when measuring with DBS is possible. Thereby, one could reference the obtained DBS analyte concentration to a common HCT level for all samples (e.g., 40%). Although this strategy appears attractive due to its simplicity, it does not consider genderspecific HCT differences. For example, the normal HCT range is 40.7%–50.3% for male subjects and 36.1%–44.3% for female subjects. Therefore, the novel tools to correct HCT not only offer many new possibilities but also create new challenges that need to be addressed.