Comparison of a basic and an advanced pharmacotherapy-related clinical decision support system in a hospital care setting in the Netherlands

Abstract

The advanced CDSS produced a higher proportion of clinically relevant medication alerts, but the number of irrelevant alerts remained high. To improve the PPV of the advanced CDSS, the algorithms should be optimized by identifying additional risk modifiers and more data should be made electronically available to improve the performance of the algorithms. Our study illustrates and corroborates the need for cyclic testing of technical improvements in information technology in circumstances representative of daily clinical practice.

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

“…To reduce alert fatigue a structural assessment of the algorithms in the G-standard is made by taking into account four parameters: (i) evidence relating to the interaction; (ii) clinical relevance of the potential adverse reaction resulting from the interaction; (iii) risk factors identifying patient, medication or disease characteristics for which the interaction is of particular importance; and (iv) the incidence of the adverse reaction [17]. Despite the structural assessment of clinical relevance the G-standard still has a low percentage of relevant drug safety alerts (5.8%), however this has been shown to increase to 17% when used in combination with a standalone CDSS [18]. In relation to alert fatigue, more complex clinical rules can in some cases replace simple G-standard algorithms thereby reducing the number of alerts.…”

Reducing PSA-Based Prostate Cancer Screening in Men Aged 75 Years and Older with the Use of Highly Specific Computerized Clinical Decision Support

“…26,27 Studies of CCDS tools that allow for more complex data input have shown better performance of alerts. 28,29 One human factors analysis of medication alerts identified 15 ways to improve alerts, with the reduction of redundant alerts and the inclusion of adequate information to facilitate physician decision-making as two of the most important. 30 The CCDS instrument that we developed used complex trigger criteria to favor specificity over sensitivity in an attempt to limit false triggers and to avoid contributing to alert fatigue.…”

“…We believe that the combination of a highly specifiable pop-up architecture such as ours and the electronic availability of a wide range of structured clinical data (including inpatient and outpatient diagnosis and procedure codes, laboratory, pharmacy, demographics, and problem list data) allowed our alert to be more targeted than most previously reported CCDS tools, which may have contributed to its success. 28,29,[31][32][33] Formal development of the alert language through focus groups and solicited feedback may have further improved its performance.…”

Evaluation of the Pharmacy Support System in the Detection of Drug-Related Problems

“…Based on the few existing studies, GPSS development is still open to be conducted to determine the proper dose. Eppenga et al (2012) conducted CDSS development including the determination of the drug dose that requires laboratory data and guidelines for the dose adjusted to kidney functions. The warning in this system includes interactions of drug-drug, drug-age, drug duplication, drug-disease, and dosage guidelines [17].…”