Development and Evaluation of a Clinical Decision Support System to Improve Medication Safety

Abstract

Background Clinical decision support systems (CDSSs) are a good strategy for preventing medication errors and reducing the incidence and severity of adverse drug events (ADEs). However, these systems are not very effective and are subject to multiple limitations that prevent their implementation in clinical practice. Objectives The objective of this study was to evaluate the effectiveness of an advanced CDSS, HIGEA, which generates alerts based on predefined clinical rules to identify patients at risk of an ADE. Methods A multidisciplinary team defined the system and the clinical rules focusing on medication errors commonly encountered in clinical practice. Four intervention programs were defined: (1) dose adjustment in renal impairment; (2) adjustment of anticoagulation/antiplatelet therapy; (3) detection of biochemical/hematologic toxicities; and (4) therapeutic drug monitoring. We performed a 6-month observational prospective study to analyze the effectiveness of these clinical rules by calculating the positive predictive value (PPV). Results The team defined 211 clinical rules. During the study period, HIGEA generated 1,086 alerts (8.9 alerts per working day), which were reviewed by pharmacists. Fifty-one percent (554/1,086) of alerts generated an intervention to prevent a possible ADE; of these, 66% (368/554) required a documented modification to therapy owing to a real prescription error intercepted. The intervention program that induced the highest number of modifications to therapy was the dose adjustment in renal impairment program (PPV = 0.51), followed by the adjustment of anticoagulation/antiplatelet therapy program (PPV = 0.24). The percentage of accepted interventions was similar in surgical units (68%), medical units (67%), and critical care units (63%). Conclusion Our study offers evidence that HIGEA is highly effective in preventing potential ADEs at the prescription stage.

Clinical Decision Support System with Renal Dose Adjustment Did Not Improve Subsequent Renal and Hepatic Function among Inpatients: The Japan Adverse Drug Event Study

“…The patients' characteristics were similar between phases, and those with RD (< 60 mL/min/1.73 m 2 ) were one-third of all admitted patients (►Table 2). The median (interquartile range) length of hospital stay was 11 (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21) days.…”

Evaluation of Clinical Decision Support to Reduce Sedative-Hypnotic Prescribing in Older Adults

“…5 Two decades later, EHRs and computerized provider order entry (CPOE) systems have found their way into nearly every hospital and feature computerized clinical decision support (CDS) as a standard. 6,7 A systematic review of medication-related CPOE systems with CDS identified five studies where CDS led to a statistically significant decrease in ADEs, and five studies where there was no significant reduction of ADEs after CDS implementation. 8 In clinical practice, CDS alerts are often overridden or ignored, and potential issues with medication-related CDS are not well understood.…”

Drug Alert Experience and Salience during Medical Residency at Two Healthcare Institutions

“…6 CDS systems, now largely available across healthcare institutions, incorporate various features such as documentation templates, clinical guidelines, diagnostic support, drug alerts, and reminders. [7][8][9][10] The utilization of CDS has demonstrated different advantages for improving practitioner performance and clinical care, including prevention of harmful prescriptions 11 and reducing adverse drug events. 8,10 These advantages, however, do not come without associated risks of legal liability pointed out by physician making clinical diagnosis, 12 risks of alert fatigue, and negative impact on user skills by reliance on alert system, as well as limitation of identifying appropriate alerts.…”

“…[7][8][9][10] The utilization of CDS has demonstrated different advantages for improving practitioner performance and clinical care, including prevention of harmful prescriptions 11 and reducing adverse drug events. 8,10 These advantages, however, do not come without associated risks of legal liability pointed out by physician making clinical diagnosis, 12 risks of alert fatigue, and negative impact on user skills by reliance on alert system, as well as limitation of identifying appropriate alerts. 13,14 Drug alerts are triggered when a medical order is incompatible with a set of parameters which may include dose ranges, frequency of administration, associated allergies, and medical conditions, among others.…”