» Articles » PMID: 25765963

A Health Record Integrated Clinical Decision Support System to Support Prescriptions of Pharmaceutical Drugs in Patients with Reduced Renal Function: Design, Development and Proof of Concept

Overview
Date 2015 Mar 14
PMID 25765963
Citations 14
Authors
Affiliations
Soon will be listed here.
Abstract

Objectives: To develop and verify proof of concept for a clinical decision support system (CDSS) to support prescriptions of pharmaceutical drugs in patients with reduced renal function, integrated in an electronic health record system (EHR) used in both hospitals and primary care.

Methods: A pilot study in one geriatric clinic, one internal medicine admission ward and two outpatient healthcare centers was evaluated with a questionnaire focusing on the usefulness of the CDSS. The usage of the system was followed in a log.

Results: The CDSS is considered to increase the attention on patients with impaired renal function, provides a better understanding of dosing and is time saving. The calculated glomerular filtration rate (eGFR) and the dosing recommendation classification were perceived useful while the recommendation texts and background had been used to a lesser extent.

Discussion: Few previous systems are used in primary care and cover this number of drugs. The global assessment of the CDSS scored high but some elements were used to a limited extent possibly due to accessibility or that texts were considered difficult to absorb. Choosing a formula for the calculation of eGFR in a CDSS may be problematic.

Conclusions: A real-time CDSS to support kidney-related drug prescribing in both hospital and outpatient settings is valuable to the physicians. It has the potential to improve quality of drug prescribing by increasing the attention on patients with renal insufficiency and the knowledge of their drug dosing.

Citing Articles

Magnitude of multiple drug use and determinants of vulnerability among chronic kidney disease inpatients in Ethiopia: a multi-center study.

Zeleke T, Abebe R, Wondm S, Tegegne B BMC Nephrol. 2024; 25(1):332.

PMID: 39375593 PMC: 11460044. DOI: 10.1186/s12882-024-03773-x.


Prescription Precision: A Comprehensive Review of Intelligent Prescription Systems.

Tantray J, Patel A, Wani S, Kosey S, Prajapati B Curr Pharm Des. 2024; 30(34):2671-2684.

PMID: 39092640 DOI: 10.2174/0113816128321623240719104337.


Nephrotoxic drug burden and predictors of exposure among patients with renal impairment in Ethiopia: A multi-center study.

Zeleke T, Kemal L, Mehari E, Sema F, Seid A, Mekonnen G Heliyon. 2024; 10(2):e24618.

PMID: 38298684 PMC: 10828699. DOI: 10.1016/j.heliyon.2024.e24618.


The Role of Clinical Decision Support Systems in Preventing Stroke in Primary Care: A Systematic Review.

Fayea Alasiri S, Douiri A, Altukistani S, Porat T, Mousa O Perspect Health Inf Manag. 2023; 20(2):1d.

PMID: 37293480 PMC: 10245087.


Barriers and enablers to implementing and using clinical decision support systems for chronic diseases: a qualitative systematic review and meta-aggregation.

Chen W, OBryan C, Gorham G, Howard K, Balasubramanya B, Coffey P Implement Sci Commun. 2022; 3(1):81.

PMID: 35902894 PMC: 9330991. DOI: 10.1186/s43058-022-00326-x.