Abstract
Abnormal laboratory test results can indicate illness, but can also be a direct result of drug use. These drug laboratory test interactions (DLTIs) often concern a physiological effect of the drug in vivo and sometimes an analytical reaction in vitro. The analytic interaction is misleading, because the measured analyte concentration in a sample does not reflect the actual concentration in blood or urine in the patient. A clear example is an elevated level of chromogranin A, which is indicative of the activity of a neuroendocrine tumour, but may also be the result of the frequently prescribed proton pump inhibitors. Physiological interactions are in vivo processes, in which drugs affect patients’ laboratory test results and may also cause diagnostic confusion. Both the analytical and physiological interactions are not all known by specialists in laboratory medicine and clinicians. Unrecognized DLTIs can cause diagnostic error.
Electronic signaling systems or so-called clinical decision support systems (CDSS) may offer a solution to the problem of unrecognized DLTIs. CDSS send automatic alerts about DLTIs based on algorithms, which use data from pharmacy and laboratory data systems.
The work described in this thesis reflects a first initiative to create more awareness of Drug Laboratory Test Interactions (DLTIs) in laboratory test interpretation. DLTI algorithms were designed in a clinical decision support system and implemented in three hospitals for real-time monitoring of DLTIs. DLTI alert frequencies were substantial. Specialists in laboratory medicine and clinicians were positive about receiving the alerts.
A retrospective medical record study showed unnecessary diagnostics when a possible DLTI was not immediately recognized. Further research must reveal the value and impact of DLTI monitoring in patient care.
Electronic signaling systems or so-called clinical decision support systems (CDSS) may offer a solution to the problem of unrecognized DLTIs. CDSS send automatic alerts about DLTIs based on algorithms, which use data from pharmacy and laboratory data systems.
The work described in this thesis reflects a first initiative to create more awareness of Drug Laboratory Test Interactions (DLTIs) in laboratory test interpretation. DLTI algorithms were designed in a clinical decision support system and implemented in three hospitals for real-time monitoring of DLTIs. DLTI alert frequencies were substantial. Specialists in laboratory medicine and clinicians were positive about receiving the alerts.
A retrospective medical record study showed unnecessary diagnostics when a possible DLTI was not immediately recognized. Further research must reveal the value and impact of DLTI monitoring in patient care.
Original language | English |
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Qualification | Doctor of Philosophy |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 13 May 2022 |
Place of Publication | Enschede |
Publisher | |
Print ISBNs | 978-94-6419-488-3 |
DOIs | |
Publication status | Published - 13 May 2022 |