Prediction of pharmacist medication interventions using medication regimen complexity

Background Critically ill patients are managed with complex medication regimens that require medication management to optimize safety and efficacy. When performed by a critical care pharmacist (CCP), discrete medication management activities are termed medication interventions. The ability to define CCP workflow and intervention timeliness depends on the ability to predict the medication management needs of individual intensive care unit (ICU) patients. The purpose of this study was to develop prediction models for the number and intensity of medication interventions in critically ill patients.

This was a retrospective, observational cohort study of adult patients admitted to an ICU between June 1, 2020 and June 7, 2023. Models to predict number of pharmacist interventions using both patient and medication related predictor variables collected at either baseline or in the first 24 hours of ICU stay were created. Both regression and supervised machine learning models (Random Forest, Support Vector Machine, XGBoost) were developed. Root mean square derivation (RMSE), mean absolute error (MAE), and symmetric mean absolute percentage error (sMAPE) were calculated.

In a cohort of 13,373 patients, the average number of interventions was 4.7 (standard deviation (SD) 7.1) and intervention intensity was 24.0 (40.3). Among the ML models, the Random Forest model had the lowest RMSE (9.26) while Support Vector Machine had the lowest MAE (4.71). All machine learning models performed similarly to the stepwise logistic regression model, and these performed better than a base model combining severity of illness with medication regimen complexity scores.

Intervention quantity can be predicted using patient-specific factors. While inter-institutional variation in intervention documentation precludes external validation, our results provide a framework workload modeling at any institution. Competing Interest Statement The authors have declared no competing interest. Funding Statement Funding through Agency of Healthcare Research and Quality for Dr. Sikora was provided through R21HS028485 and for Drs. Sikora and Shen through R01HS029009. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This was a retrospective, observational study that was reviewed by the University of Georgia (UGA) Institutional Review Board (IRB) and determined to be exempt from IRB oversight (Project00001541). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Disclaimers: The authors have no conflicts of interest. Funding: Funding through Agency of Healthcare Research and Quality for Dr. Sikora was provided through R21HS028485 and for Drs. Sikora and Shen through R01HS029009. Dr. Shen’s work was also partially supported by R35GM146612 from the National Institute of General Medical Sciences. Data Availability All data produced in the present study are available upon reasonable request to the authors