Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients

Wit, Hugo A. J. M. de; Gonzalvo, Carlota Mestres; Cárdenas, Jenny Patricia Ortiz; Derijks, Hieronymus J.; Janknegt, R.; Kuy, Hugo van der; Winkens, Björn; Schols, Jos M. G. A.

doi:10.1016/j.ijmedinf.2015.02.004

Cited by 28 publications

(32 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Integration of a CDSS into a CPOE results in the presentation of alerts when a physician is prescribing medication. In this way the physician can adjust the prescription during the prescription process if necessary, instead of adjusting the prescription afterwards, such as when it is initiated by an alert from a stand-alone CDSS (de Wit et al 2015 ; Eppenga et al 2012 ; Tawadrous et al 2011 ). Patient outcome benefits of using advanced CDSSs remain limited, but several studies do report positive results related to prevention of adverse drug events (Rommers et al 2011 ; Tawadrous et al 2011 ; Bright et al 2012 ; Jaspers et al 2011 ).…”

Section: Introductionmentioning

confidence: 99%

“…The department of clinical pharmacy and toxicology of the Zuyderland medical centre has developed an advanced CDSS based on our experience with a simpler access based CDSS (de Wit et al 2015 ). The currently developed advanced CDSS consists of algorithms that alert for the inappropriate combination of medication and laboratory values, for lack of guideline implementation, and gives suggestions to prevent adverse drug events as a result of drug–disease interactions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The support of medication reviews in hospitalised patients using a clinical decision support system

Wit¹,

Hurkens²,

Gonzalvo³

et al. 2016

SpringerPlus

Self Cite

View full text Add to dashboard Cite

ObjectivesFirst, to estimate the added value of a clinical decision support system (CDSS) in the performance of medication reviews in hospitalised elderly. Second, to identify the limitations of the current CDSS by analysing generated drug-related problems (DRPs).MethodsMedication reviews were performed in patients admitted to the geriatric ward of the Zuyderland medical centre. Additionally, electronically available patient information was introduced into a CDSS. The DRP notifications generated by the CDSS were compared with those found in the medication review. The DRP notifications were analysed to learn how to improve the CDSS.ResultsA total of 223 DRP strategies were identified during the medication reviews. The CDSS generated 70 clinically relevant DRP notifications. Of these DRP notifications, 63 % (44) were also found during the medication reviews. The CDSS generated 10 % (26) new DRP notifications and conveyed 28 % (70) of all 249 clinically relevant DRPs that were found. Classification of the CDSS generated DRP notifications related to ‘medication error type’ revealed that ‘contraindications/interactions/side effects’ and ‘indication without medication’ were the main categories not identified during the manual medication review. The error types ‘medication without indication’, ‘double medication’, and ‘wrong medication’ were mostly not identified by the CDSS.ConclusionsThe CDSS used in this study is not yet sufficiently advanced to replace the manual medication review, though it does add value to the manual medication review. The strengths and weaknesses of the current CDSS can be determined according to the medication error types.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The support of medication reviews in hospitalised patients using a clinical decision support system

Wit¹,

Hurkens²,

Gonzalvo³

et al. 2016

SpringerPlus

Self Cite

View full text Add to dashboard Cite

show abstract

“…The CDSS has been described in detail previously [17,18]. In short, a clinical rule is an algorithm that analyses drugs based on the actual risk profile of a patient using current patient data such as laboratory data, age, sex and contraindications.…”

Section: The Clinical Decision Support Systemmentioning

confidence: 99%

“…We have developed a clinical decision support system that takes into account these implementation challenges [17,18]. The CDSS monitors all prescribed drugs continuously and independently from the prescribing software, while taking into account co-medication, patient characteristics and laboratory data.…”

Section: Introductionmentioning

confidence: 99%

Assessing the strengths and weaknesses of a computer assisted medication review in hospitalized patients

Hurkens¹,

Mestres-Gonzalvo²,

Wit³

et al. 2017

IJHP

Self Cite

View full text Add to dashboard Cite

“…Clinical Decision Support Systems (CDSS) can reduce the incidence of adverse events, optimize prescription safety and improve patient's care [1]. Most of the rules integrated in CDSS are explicit criteria based on validated tools, summary of product characteristics or based on recommendations from expert consensus [2]. Direct implementation of explicit criteria often lead to irrelevant alert rules [2].…”

Section: Introductionmentioning

confidence: 99%

Integration of Explicit Criteria in a Clinical Decision Support System Through Evaluation of Acute Kidney Injury Events

Robert¹,

Rousselière²,

Beuscart³

et al. 2021

Studies in Health Technology and Informatics

View full text Add to dashboard Cite

In Clinical Decision Support System (CDSS), relevance of alerts is essential to limit alert fatigue and risk of overriding relevant alerts by health professionals. Detection of acute kidney injury (AKI) situations is of great importance in clinical practice and could improve quality of care. Nevertheless, to our knowledge, no explicit rule has been created to detect AKI situations in CDSS. The objective of the study was to implement an AKI detection rule based on KDIGO criteria in a CDSS and to optimize this rule to increase its relevance in clinical pharmacy use. Two explicit rules were implemented in a CDSS (basic AKI rule and improved AKI rule), based on KDIGO criteria. Only the improved rule was optimized by a group of experts during the two-month study period. The CDSS provided 1,125 alerts on AKI situations (i.e. 643 were triggered for the basic AKI rule and 482 for the improved AKI rule). As the study proceeds, the pharmaceutically and medically relevance of alerts from the improved AKI rule increased. A ten-fold increase was shown for the improved AKI rule compared to the basic AKI rule. The study highlights the usefulness of a multidisciplinary review to enhance explicit rules integrated in CDSS. The improved AKI is able to detect AKI situations and can improve workflow of health professionals.

show abstract

Evaluation of clinical rules in a standalone pharmacy based clinical decision support system for hospitalized and nursing home patients

Cited by 28 publications

References 23 publications

The support of medication reviews in hospitalised patients using a clinical decision support system

The support of medication reviews in hospitalised patients using a clinical decision support system

Assessing the strengths and weaknesses of a computer assisted medication review in hospitalized patients

Integration of Explicit Criteria in a Clinical Decision Support System Through Evaluation of Acute Kidney Injury Events

Contact Info

Product

Resources

About