Appropriateness Of Alerts Research Articles

Assessing the efficacy of difficult airway alerts in electronic medical records: a quality improvement study

Study designRetrospective analysis of difficult airway alerts in a major tertiary centre.ObjectiveTo investigate the completeness, utility and efficacy of difficult airway alerts and their impact on future airway management episodes.Design, data sources and methodsPatients who had a “difficult airway” entry on electronic medical records (EMR) from 2011 to 2021 were included. Each alert was analyzed by a team of anesthetists with expertise in difficult airway management for its quality, appropriateness, and impact on future airway management episodes. Alert quality was defined as to whether the content of the alert contained pertinent information for emergent airway management. Alert appropriateness was defined as to whether the experts would be unhappy to perform a rapid sequence induction and intubation, if required, following review of all available documentation.Results141 patients were included for this study, with a mean age of 58.6 +/- 15.3 years. Ninety-three (66%) alerts were created by medical staff, of which 52 were recorded by consultant anesthetists. 117 alerts (83%) were deemed to be appropriate by the airway expert team, but only 40 alerts (28%) were found to have sufficient quality to be helpful in emergent airway management. Sixty-five patients (47%) had at least one subsequent airway management episode, of which 35 patients (56%) underwent a change of management following alert creation. We proceeded to modify 103 alerts (73%) to improve their quality to aid future encounters.ConclusionDifficult Airway encounters are an uncommon event in anesthesia, but clear, comprehensive and effectively communicated documentation is required to minimize the risk in future encounters. In our institution, while most difficult airway alerts were appropriate, we found significant heterogeneity in the quality of this documentation, which limits the clinical utility of the alert system. We have taken measures to improve local processes of difficult airway documentation and considered the implications of our project for the broader airway management community.Trial registrationNot applicable.

Evaluation of appropriateness of alerts overrides and physicians' responses of the medication-related clinical decision support system in China, a hospital-based study.

This study was designed to investigate the state quo of the appropriateness of alerts overrides of the medication-related clinical decision support system (MRCDSS) in China. The medication-related alerts in one hospital from Jan 2022 to Dec 2022 were acquired and sampled. Rates of alert overrides, appropriateness of alert generation and physicians' responses were observed. Total 14,612 medication-related alerts (≤ level 3) were recorded, of those, 12,659 (86.6%) alerts were overridden. The top 3 alert types were: drug and diagnosis contraindications (23.8%), drug and test value contraindications (23.3%), and compatibility issues (17.7%). Of all sampled 1,501 alerts, 80.2% of them were appropriately overridden by the physicians. The appropriate rate of alert generation was 57.9% and the inappropriate rate was 42.1%. The inappropriate rate of physicians' responses was 17.8%, and 2.0% physicians' responses were undetermined. A few medications accounted for over 10% of overrides, 88.3% of "overridden reasons" inputted by the physicians were meaningless characters or values, indicating an obvious "alert fatigue" in these physicians. Our results indicated that the overridden rate of MRCDSS in China was still high, and appropriateness of generation of alert was quite low. These data indicated that the MRCDSS currently using in China still needs constantly optimization and timely maintenance. Proper sensitivity to reduce triggering of useless alerts and generation of alert fatigue might play a vital role. We believed that these findings are helpful for better understanding the state quo of MRCDSS in China and providing useful insights for future developing and improving MRCDSS.

Appropriateness of Alerts and Physicians' Responses With a Medication-Related Clinical Decision Support System: Retrospective Observational Study.

BackgroundAlert fatigue is unavoidable when many irrelevant alerts are generated in response to a small number of useful alerts. It is necessary to increase the effectiveness of the clinical decision support system (CDSS) by understanding physicians’ responses.ObjectiveThis study aimed to understand the CDSS and physicians’ behavior by evaluating the clinical appropriateness of alerts and the corresponding physicians’ responses in a medication-related passive alert system.MethodsData on medication-related orders, alerts, and patients’ electronic medical records were analyzed. The analyzed data were generated between August 2019 and June 2020 while the patient was in the emergency department. We evaluated the appropriateness of alerts and physicians’ responses for a subset of 382 alert cases and classified them.ResultsOf the 382 alert cases, only 7.3% (n=28) of the alerts were clinically appropriate. Regarding the appropriateness of the physicians’ responses about the alerts, 92.4% (n=353) were deemed appropriate. In the classification of alerts, only 3.4% (n=13) of alerts were successfully triggered, and 2.1% (n=8) were inappropriate in both alert clinical relevance and physician’s response. In this study, the override rate was 92.9% (n=355).ConclusionsWe evaluated the appropriateness of alerts and physicians’ responses through a detailed medical record review of the medication-related passive alert system. An excessive number of unnecessary alerts are generated, because the algorithm operates as a rule base without reflecting the individual condition of the patient. It is important to maximize the value of the CDSS by comprehending physicians’ responses.

The appropriateness of clinical decision support systems alerts in supporting clinical workflows: A systematic review.

A CDSS generates a high number of inappropriate alerts that interrupt the clinical workflow. As a result, clinicians silence, disable, or ignore alerts, thereby undermining patient safety. Therefore, the effectiveness and appropriateness of CDSS alerts need to be evaluated. A systematic review was carried out to identify the factors that affect CDSS alert appropriateness in supporting clinical workflow. Seven electronic databases (PubMed, Scopus, ACM, Science Direct, IEEE, Ovid Medline, and Ebscohost) were searched for English language articles published between 1997 and 2018. Seventy six papers met the inclusion criteria, of which 26, 24, 15, and 11 papers are retrospective cohort, qualitative, quantitative, and mixed-method studies, respectively. The review highlights various factors influencing the appropriateness and efficiencies of CDSS alerts. These factors are categorized into technology, human, organization, and process aspects using a combination of approaches, including socio-technical framework, five rights of CDSS, and Lean. Most CDSS alerts were not properly designed based on human factor methods and principles, explaining high alert overrides in clinical practices. The identified factors and recommendations from the review may offer valuable insights into how CDSS alerts can be designed appropriately to support clinical workflow.

Evaluating the appropriateness of clinical decision support alerts: A case study.

Clinical decision support (CDS) generates excessive alerts that disrupt the workflow of clinicians. Therefore, inefficient clinical processes that contribute to the misfit between CDS alert and workflow must be evaluated. This study evaluates the appropriateness of CDS alerts in supporting clinical workflow from a socio-technical perspective. A qualitative case study evaluation was conducted at a 620-bed public teaching hospital in Malaysia using interview, observation, and document analysis to investigate the features and functions of alert appropriateness and workflow-related issues in cardiological and dermatological settings. The current state map for medication prescribing process was also modelled to identify problems pertinent to CDS alert appropriateness. The main findings showed that CDS was not well designed to fit into a clinician's workflow due to influencing factors such as technology (usability, alert content, and alert timing), human (training, perception, knowledge, and skills), organizational (rules and regulations, privacy, and security), and processes (documenting patient information, overriding default option, waste, and delay) impeding the use of CDS with its alert function. We illustrated how alert affect workflow in clinical processes using a Lean tool known as value stream mapping. This study also proposes how CDS alerts should be integrated into clinical workflows to optimize their potential to enhance patient safety. The design and implementation of CDS alerts should be aligned with and incorporate socio-technical factors. Process improvement methods such as Lean can be used to enhance the appropriateness of CDS alerts by identifying inefficient clinical processes that impede the fit of these alerts into clinical workflow.

A Systematic Review on CDSS Alert Appropriateness.

Clinical decision support systems (CDSSs) provides vital information for managing patients by advising clinicians through an alert or reminders about adverse events and medication errors. Clinicians receive a high number of alerts, resulting in alert override and workflow disruptions. A systematic review was carried out to identify factors affecting CDSS alert appropriateness in supporting clinical workflows using a recently introduced framework. The review findings identified several influencing factors of CDSS alert appropriateness including: technology (usability, alert presentation, workload and data entry), human (training, knowledge and skills, attitude and behavior), organization (rules and regulation, privacy and security) and process (waste, delay, tuning and optimization). The findings can be used to guide the design of CDSS alert and minimise potential safety hazards associated with CDSS use.

The Effect of Patient-Specific Drug-Drug Interaction Alerting on the Frequency of Alerts: A Pilot Study.

Background: False-positive drug-drug interaction alerts are frequent and result in alert fatigue that can result in prescribers bypassing important alerts. Development of a method to present patient-appropriate alerts is needed to help restore alert relevance. Objective: The purpose of this study was to assess the potential for patient-specific drug-drug interaction (DDI) alerts to reduce alert burden. Methods: This project was conducted at a tertiary care medical center. Seven of the most frequently encountered DDI alerts were chosen for developing patient-specific, algorithm-based DDI alerts. For each of the DDI pairs, 2 algorithms featuring different values for modifying factors were made. DDI alerts from the 7 drug pairs were collected over 30 days. Outcome measures included the number of DDI alerts generated before and after patient-specific algorithm application to the same patients over the same time period. Results: A total of 14 algorithms were generated, and each was evaluated by comparing the number of alerts generated by our existing, customized clinical decision support (CDS) software and the patient-specific algorithms. The CDS DDI alerting software generated an average of 185.3 alerts per drug pair over the 30-day study period. Patient-specific algorithms reduced the number of alerts resulting from the algorithms by 11.3% to 93.5%. Conclusion and Relevance: Patient-specific DDI alerting is an innovative and effective approach to reduce the number of DDI alerts, may potentially increase the appropriateness of alerts, and may decrease the potential for alert fatigue.

Enhancing CDSS Alert Appropriateness in Clinical Workflow Using the Lean Method.

Despite the widespread use of clinical decision support systems with its alert function, there has been an increase in medical errors, adverse events as well as issues regarding patient safety, quality and efficiency. The appropriateness of CDSS must be properly evaluated by ensuring that CDSS provides clinicians with useful information at the point of care. Inefficient clinical workflow affects clinical processes; hence, it is necessary to identify processes in the healthcare system that affect provider's workflow. The Lean method was used to eliminate waste (non-value added) activities that affect the appropriate use of CDSS. Ohno's seven waste model was used to categorize waste in the context of healthcare and information technology.

Clinical Decision Support using a Terminology Server to improve Patient Safety.

Clinical Decision Support Systems (CDSS) are software applications that support clinicians in making healthcare decisions providing relevant information for individual patients about their specific conditions. The lack of integration between CDSS and Electronic Health Record (EHR) has been identified as a significant barrier to CDSS development and adoption. Andalusia Healthcare Public System (AHPS) provides an interoperable health information infrastructure based on a Service Oriented Architecture (SOA) that eases CDSS implementation. This paper details the deployment of a CDSS jointly with the deployment of a Terminology Server (TS) within the AHPS infrastructure. It also explains a case study about the application of decision support to thromboembolism patients and its potential impact on improving patient safety. We will apply the inSPECt tool proposal to evaluate the appropriateness of alerts in this scenario.

Capsule Commentary on Shelton et al., Reducing PSA-Based Prostate Cancer Screening in Men ≥ 75Years Old with Highly Specific Computerized Clinical Decision Support.

Clinical decision support (CDS) systems can improve patient safety by providing physicians with important information and guidance at the point of care. This guidance should be evidence-based, and the alert message clear and concise, to allow physicians to directly act on the information received. Shelton et al. develop a highly specific and targeted CDS alert to remind providers of the current guidelines and policy at the point of ordering a screening PSA.1 This relatively simple intervention has been shown to significantly reduce inappropriate PSA screening for prostate cancer. Alerts which lack clinical relevance (low alert specificity) are often overridden by the physician, thus contributing to alert fatigue.2,3 The authors of this study reflected on how they used a wide range of structured clinical data (including laboratory, pharmacy, and problem list data) to help increase the specificity of their alert, and believe that this may have contributed to its success. Alert specificity and sensitivity is recognized as being important.4 Patient specific parameters, e.g., age, should be incorporated into decision-making algorithms to improve the accuracy and appropriateness of alerts. One study found that only 10 % of drug–drug interaction alerts would be applicable in all circumstances; however, by incorporating laboratory results and other clinical parameters, this percentage could rise to 25 % or possibly higher.5 The effectiveness of alerts should always be monitored; this includes how often they fire and whether clinicians choose to accept or override the alerts. Interestingly, Shelton et al. reported sharp increases in screening rates during periods when the alerts were switched off. This finding underscores the importance of CDS as a tool to guide physician decision-making and improve the quality and efficiency of health care. Furthermore, it shows how they can address inappropriate overuse of preventive care and, in turn, reduce health care costs.

Appropriateness of commercially available and partially customized medication dosing alerts among pediatric patients

To evaluate dosing alert appropriateness, categorize orders with alerts, and compare the appropriateness of alerts due to customized and non-customized dose ranges at a pediatric hospital. This was a retrospective analysis of medication orders causing dosing alerts. Orders for outpatient prescriptions, patients ≥18 years of age, and research protocols were excluded. Patient medical records were reviewed and ordered doses compared with a widely used pediatric reference (Lexi-Comp) and institutional recommendations. The alerted orders were categorized and the occurrence of appropriate alerts was compared. There were 47 181 inpatient orders during the studied period; 1935 orders caused 3774 dosing alerts for 369 medications in 573 patients (median age 6.1 years). All alerted orders had an alert overridden by the prescriber. The majority (86.2%) of alerted orders inappropriately caused alerts; 58.0% were justifiable doses and 28.2% were within Lexi-Comp. However, 13.8% of alerted orders appropriately caused alerts; 8.0% were incorrect doses and 5.8% had no dosing recommendations available. Appropriately alerted orders occurred in 19.7% of alerted orders due to customized ranges compared to 12.8% due to non-customized ranges (p=0.002). Preterm and term neonates, infants, and children (2-5 years) had higher proportions of inappropriate alerts compared to appropriate alerts (all p<0.01). The vast majority of dosing alerts were presented to practitioners inappropriately, potentially contributing to alert fatigue. Appropriate alerts occurred more often when alerts were due to customized ranges. Advances in dosing alerts should aim to provide accurate and clinically relevant alerts that minimize excessive inappropriate alerting. Medications requiring dosing adjustments based on clinical parameters must be taken into account when designing and evaluating dosing alerts.

A framework for evaluating the appropriateness of clinical decision support alerts and responses

Alerting systems, a type of clinical decision support, are increasingly prevalent in healthcare, yet few studies have concurrently measured the appropriateness of alerts with provider responses to alerts. Recent reports of suboptimal alert system design and implementation highlight the need for better evaluation to inform future designs. The authors present a comprehensive framework for evaluating the clinical appropriateness of synchronous, interruptive medication safety alerts. Through literature review and iterative testing, metrics were developed that describe successes, justifiable overrides, provider non-adherence, and unintended adverse consequences of clinical decision support alerts. The framework was validated by applying it to a medication alerting system for patients with acute kidney injury (AKI). Through expert review, the framework assesses each alert episode for appropriateness of the alert display and the necessity and urgency of a clinical response. Primary outcomes of the framework include the false positive alert rate, alert override rate, provider non-adherence rate, and rate of provider response appropriateness. Application of the framework to evaluate an existing AKI medication alerting system provided a more complete understanding of the process outcomes measured in the AKI medication alerting system. The authors confirmed that previous alerts and provider responses were most often appropriate. The new evaluation model offers a potentially effective method for assessing the clinical appropriateness of synchronous interruptive medication alerts prior to evaluating patient outcomes in a comparative trial. More work can determine the generalizability of the framework for use in other settings and other alert types.