Medication-related problems
Conditions
Interventions
Group 1: Adult inpatients in German university hospitals who are (co-)cared for by ward pharmacists
Sponsors
Universität Leipzig
Eligibility
Sex/Gender
All
Age
18 Years to No maximum
Inclusion criteria
Inclusion criteria: Patients 18 years and older who are being cared for on wards with pharmaceutical services.
Exclusion criteria
Exclusion criteria: - pediatric wards - intensive care units - maternity wards
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| The primary objective of INTERPOLAR-1 is: 1.) To determine the average number of medication-related problems (MRPs) among hospitalized patients, as well as the resolution rate of MRPs detected in routine care. This is supported by the implementation of a standardized MRP documentation option for ward pharmacists. 2.) To show retrospectively in a multicenter setting that digital support for ward pharmacists can lead to an overall increase in the number of medication-related problems (MRPs) identified in hospitalized patients. The previous approach in usual care (number of manually documented MRPs) will be compared with a study phase subsequently expanded to include IT-based MRP detection (number of manually documented MRPs supplemented by algorithmically detected MRPs classified as relevant (absolute contraindications)). | — |
Secondary
| Measure | Time frame |
|---|---|
| Furthermore, the following secondary evaluation objectives are to be pursued. (1) Analysis of the profiles of MRPs that have occurred (contraindications, missing medications, dosing errors, application errors, adverse drug reactions that have occurred) (2) Analysis of the profiles of resolved MRPs (3) Analysis of relevant MRPs detected algorithmically but not documented manually (4) Analysis of MRPs detected algorithmically but not relevant (5) Predictability of MRPs (regression models) (6) Identification of adverse events (AEs) using algorithmic classifiers (7) Effort involved in recording and resolving MRPs in routine care. (8) Plausibility and validity of data processing Regarding (1) - (5): this implies ? Further analyses of ? The type of MRPs that occurred according to solubility ? The predictability of MRPs and their clinical relevance ? The creation of risk profiles for MRPs ? retrospective analysis of data on both types of MRPs (manually documented and algorithmically detected) with plausibility checks to estimate the sensitivity and specificity of the MRP algorithms using the IT-based algorithm ? the determination of prognostic factors for MRPs (risk profiles) Regarding (6): this implies a search for and analysis of adverse events (AEs) in the entire cohort ? Estimation of the cohort prevalence of approximately 10 important AEs, for which we have constructed algorithmic classifiers in INTERPOLAR using the TOP framework ? Plausibility check of these cases found according to TOP classifications by comparison with the EMR ? Association modeling/regression analyses for risk prediction of AEs ? Association modeling/regression analyses for risk prediction of AEs ? We will investigate whether we can establish a temporal relationship between identified MRP and the occurrence of AE Regarding (7): This implies a structured survey of pharmacists on the practice of medication analysis in general at the INTERPOLAR sites and on the s | — |
Countries
Germany
Contacts
Public ContactJenny Kaftan
Universität Leipzig
Outcome results
None listed