We evaluated potential modulators of alert acceptance by assessing content and human factors issues, and quantified the impact of a number of specific factors which influence alert acceptance. This information may help improve clinical decision support systems design.
BackgroundClinical decision support (CDS) for electronic prescribing systems (computerized physician order entry) should help prescribers in the safe and rational use of medicines. However, the best ways to alert users to unsafe or irrational prescribing are uncertain. Specifically, CDS systems may generate too many alerts, producing unwelcome distractions for prescribers, or too few alerts running the risk of overlooking possible harms. Obtaining the right balance of alerting to adequately improve patient safety should be a priority.MethodsA workshop funded through the European Regional Development Fund was convened by the University Hospitals Birmingham NHS Foundation Trust to assess current knowledge on alerts in CDS and to reach a consensus on a future research agenda on this topic. Leading European researchers in CDS and alerts in electronic prescribing systems were invited to the workshop.ResultsWe identified important knowledge gaps and suggest research priorities including (1) the need to determine the optimal sensitivity and specificity of alerts; (2) whether adaptation to the environment or characteristics of the user may improve alerts; and (3) whether modifying the timing and number of alerts will lead to improvements. We have also discussed the challenges and benefits of using naturalistic or experimental studies in the evaluation of alerts and suggested appropriate outcome measures.ConclusionsWe have identified critical problems in CDS, which should help to guide priorities in research to evaluate alerts. It is hoped that this will spark the next generation of novel research from which practical steps can be taken to implement changes to CDS systems that will ultimately reduce alert fatigue and improve the design of future systems.
Due to hugely varying tests for assessing outcomes, the methods are scarcely comparable. For a more valuable comparison, the anticholinergic load should be calculated with all scales and the equation and correlated with patient-related outcomes.
PurposeThe aim of this study was to 1) describe drug information desired by patients and 2) analyze how such information could be customized to be presented to patients according to their individual information needs.Materials and methodsWe performed a scoping literature search and identified relevant drug information topics by assessing and clustering 1) studies analyzing patients’ enquiries to drug information hotlines and services, and 2) qualitative studies evaluating patient drug information needs. For the two most frequently mentioned topics, we further analyzed which components (ie, information domains) the topics contained and examined patients’ and health care professionals’ (HCPs) views on these components.ResultsOf 27 identified drug information topics in the literature search, patients most frequently requested information on adverse drug reactions (ADRs) and drug–drug interactions (DDIs). Hypothetically, those topics are composed of seven distinct information domains each (eg, ADR and DDI classification by frequency, severity, or onset; information on management strategies, monitoring, and prevention strategies). Patients’ and HCPs’ appraisal concerning the information content of these domains varies greatly and is even lacking sometimes.ConclusionPatients particularly request information on ADRs and DDIs. Approaches to customize such information are sparse. The identified information domains of each topic could be used to structure corresponding drug information and to thus facilitate customization to individual information needs.
The authors developed and gathered preliminary evidence for the validity of an instrument that measures the appropriate use of human-factors principles in the design and display of DDI alerts. Designers of DDI alerts may use the instrument to improve usability and increase user acceptance of medication alerts, and organizations selecting an electronic medical record may find the instrument helpful in meeting their clinicians' usability needs.
Background While collaboration between community pharmacists (CPs) and general practitioners (GPs) is essential to provide comprehensive patient care, their communication often is scarce and hampered by multiple barriers. Objective We aimed to assess both professions' perceptions of interprofessional communication with regard to content and methods of communication as a basis to subsequently develop best-practice recommendations for information exchange. Setting Ambulatory care setting in Germany. Method CPs and GPs shared their experience in focus groups and in-depth interviews which were conducted using a semi-structured interview guideline. Transcribed recordings were assessed using qualitative content analysis according to Mayring. Main outcome measure Specification of existing barriers, CPs'/GPs' general perceptions of interprofessional communication and similarities and differences regarding prioritization of specific information items and how to best communicate with each other. Results Four focus groups and fourteen interviews were conducted. Seven internal (e.g. professions were not personally known to one another) and nine external barriers (e.g. mutual accessibility) were identified. Ten organizational, eight medication-related, and four patient-related information items were identified requiring interprofessional communication. Their relevance varied between the professions, e.g. CPs rated organizational issues higher than GPs. Both professions indicated communication via phone to be the most frequently used method of communication. Conclusion CPs and GPs opinions often differ. However, communication between CPs and GPs is perceived as crucial suggesting that a future concept has to offer standardized recommendations, while leaving CPs and GPs room to adjust it to their individual needs.
Objectives Prescription of excessive doses is the most common prescription error, provoking dose-dependent adverse drug reactions. Clinical decision support systems (CDSS) can prevent prescription errors especially when mainly clinically relevant warnings are issued. We have built and evaluated a CDSS providing upper dose limits personalised to individual patient characteristics thus guaranteeing for specific warnings. Methods For 170 compounds, detailed information on upper dose limits (according to the drug label) was compiled. A comprehensive software-algorithm extracted relevant patient information from the electronic chart (eg, age, renal function, comedication). The CDSS was integrated into the local prescribing platform for outpatients and patients at discharge, providing immediate dosage feedback. Its impact was evaluated in a 90-day intervention study (phase 1: baseline; phase 2: intervention). Outcome measures were frequency of excessive doses before and after intervention considering potential induction of new medication errors. Moreover, predictors for alert adherence were analysed. Results In phase 1, 552 of 12 197 (4.5%) prescriptions exceeded upper dose limits. In phase 2, initially 559 warnings were triggered (4.8%, p¼0.37). Physicians were responsive to one in four warnings mostly adjusting dosages. Thus, the final prescription rate of excessive doses was reduced to 3.6%, with 20% less excessive doses compared with baseline (p<0.001). No new manifest prescription errors were induced. Physicians' alert adherence correlated with patients' age, prescribed drug class, and reason for the alert. Conclusion During the 90-day study, implementation of a highly specific algorithm-based CDSS substantially improved prescribing quality with a high acceptance rate compared with previous studies.
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