Differences, Opportunities, and Strategies in Drug Alert Optimization-Experiences of Two Different Integrated Health Care Systems

Optimising interruptive clinical decision support alerts for antithrombotic duplicate prescribing in hospital

INTRODUCTION

Duplicate prescribing clinical decision support alerts can prevent important prescribing errors but are frequently the cause of much alert fatigue. Stat dose prescriptions are a known reason for overriding these alerts. This study aimed to evaluate the effect of excluding stat dose prescriptions from duplicate prescribing alerts for antithrombotic medicines on alert burden, prescriber adherence, and prescribing.

MATERIALS AND METHODS

A before (January 1st, 2017 to August 31st, 2022) and after (October 5th, 2022 to September 30th, 2023) study was undertaken of antithrombotic duplicate prescribing alerts and prescribing following a change in alert settings. Alert and prescribing data for antithrombotic medicines were joined, processed, and analysed to compare alert rates, adherence, and prescribing. Alert burden was assessed as alerts per 100 prescriptions. Adherence was measured at the point of the alert as whether the prescriber accepted the alert and following the alert as whether a relevant prescription was ceased within an hour. Co-prescribing of antithrombotic stat dose prescriptions was assessed pre- and post-alert reconfiguration.

RESULTS

Reconfiguration of the alerts reduced the alert rate by 29 % (p < 0.001). The proportion of alerts associated with cessation of antithrombotic duplication significantly increased (32.8 % to 44.5 %, p < 0.001). Adherence at the point of the alert increased 1.2 % (4.8 % to 6.0 %, p = 0.012) and 11.5 % (29.4 % to 40.9 %, p < 0.001) within one hour of the alert. When ceased after the alert over 80 % of duplicate prescriptions were ceased within 2 min of overriding. Antithrombotic stat dose co-prescribing was unchanged for 4 out of 5 antithrombotic duplication alert rules.

CONCLUSION

By reconfiguring our antithrombotic duplicate prescribing alerts, we reduced alert burden and increased alert adherence. Many prescribers ceased duplicate prescribing within 2 min of alert override highlighting the importance of incorporating post-alert measures in accurately determining prescriber alert adherence.

Post-implementation optimization of medication alerts in hospital computerized provider order entry systems: a scoping review

OBJECTIVES

A scoping review identified interventions for optimizing hospital medication alerts post-implementation, and characterized the methods used, the populations studied, and any effects of optimization.

MATERIALS AND METHODS

A structured search was undertaken in the MEDLINE and Embase databases, from inception to August 2023. Articles providing sufficient information to determine whether an intervention was conducted to optimize alerts were included in the analysis. Snowball analysis was conducted to identify additional studies.

RESULTS

Sixteen studies were identified. Most were based in the United States and used a wide range of clinical software. Many studies used inpatient cohorts and conducted more than one intervention during the trial period. Alert types studied included drug-drug interactions, drug dosage alerts, and drug allergy alerts. Six types of interventions were identified: alert inactivation, alert severity reclassification, information provision, use of contextual information, threshold adjustment, and encounter suppression. The majority of interventions decreased alert quantity and enhanced alert acceptance. Alert quantity decreased with alert inactivation by 1%-25.3%, and with alert severity reclassification by 1%-16.5% in 6 of 7 studies. Alert severity reclassification increased alert acceptance by 4.2%-50.2% and was associated with a 100% acceptance rate for high-severity alerts when implemented. Clinical errors reported in 4 studies were seen to remain stable or decrease.

DISCUSSION

Post-implementation medication optimization interventions have positive effects for clinicians when applied in a variety of settings. Less well reported are the impacts of these interventions on the clinical care of patients, and how endpoints such as alert quantity contribute to changes in clinician and pharmacist perceptions of alert fatigue.

CONCLUSION

Well conducted alert optimization can reduce alert fatigue by reducing overall alert quantity, improving clinical acceptance, and enhancing clinical utility.

Facilitators and Barriers to Interacting With Clinical Decision Support in the ICU: A Mixed-Methods Approach

OBJECTIVES

Clinical decision support systems (CDSSs) are used in various aspects of healthcare to improve clinical decision-making, including in the ICU. However, there is growing evidence that CDSS are not used to their full potential, often resulting in alert fatigue which has been associated with patient harm. Clinicians in the ICU may be more vulnerable to desensitization of alerts than clinicians in less urgent parts of the hospital. We evaluated facilitators and barriers to appropriate CDSS interaction and provide methods to improve currently available CDSS in the ICU.

DESIGN

Sequential explanatory mixed-methods study design, using the BEhavior and Acceptance fRamework.

SETTING

International survey study.

PATIENT/SUBJECTS

Clinicians (pharmacists, physicians) identified via survey, with recent experience with clinical decision support.

INTERVENTIONS

An initial survey was developed to evaluate clinician perspectives on their interactions with CDSS. A subsequent in-depth interview was developed to further evaluate clinician (pharmacist, physician) beliefs and behaviors about CDSS. These interviews were then qualitatively analyzed to determine themes of facilitators and barriers with CDSS interactions.

MEASUREMENTS AND MAIN RESULTS

A total of 48 respondents completed the initial survey (estimated response rate 15.5%). The majority believed that responding to CDSS alerts was part of their job (75%) but felt they experienced alert fatigue (56.5%). In the qualitative analysis, a total of five facilitators (patient safety, ease of response, specificity, prioritization, and feedback) and four barriers (excess quantity, work environment, difficulty in response, and irrelevance) were identified from the in-depth interviews.

CONCLUSIONS

In this mixed-methods survey, we identified areas that institutions should focus on to improve appropriate clinician interactions with CDSS, specific to the ICU. Tailoring of CDSS to the ICU may lead to improvement in CDSS and subsequent improved patient safety outcomes.

Barriers to Adoption of Tailored Drug-Drug Interaction Clinical Decision Support

OBJECTIVE

Despite the benefits of the tailored drug-drug interaction (DDI) alerts and the broad dissemination strategy, the uptake of our tailored DDI alert algorithms that are enhanced with patient-specific and context-specific factors has been limited. The goal of the study was to examine barriers and health care system dynamics related to implementing tailored DDI alerts and identify the factors that would drive optimization and improvement of DDI alerts.

METHODS

We employed a qualitative research approach, conducting interviews with a participant interview guide framed based on Proctor's taxonomy of implementation outcomes and informed by the Theoretical Domains Framework. Participants included pharmacists with informatics roles within hospitals, chief medical informatics officers, and associate medical informatics directors/officers. Our data analysis was informed by the technique used in grounded theory analysis, and the reporting of open coding results was based on a modified version of the Safety-Related Electronic Health Record Research Reporting Framework.

RESULTS

Our analysis generated 15 barriers, and we mapped the interconnections of these barriers, which clustered around three entities (i.e., users, organizations, and technical stakeholders). Our findings revealed that misaligned interests regarding DDI alert performance and misaligned expectations regarding DDI alert optimizations among these entities within health care organizations could result in system inertia in implementing tailored DDI alerts.

CONCLUSION

Health care organizations primarily determine the implementation and optimization of DDI alerts, and it is essential to identify and demonstrate value metrics that health care organizations prioritize to enable tailored DDI alert implementation. This could be achieved via a multifaceted approach, such as partnering with health care organizations that have the capacity to adopt tailored DDI alerts and identifying specialists who know users' needs, liaise with organizations and vendors, and facilitate technical stakeholders' work. In the future, researchers can adopt the systematic approach to study tailored DDI implementation problems from other system perspectives (e.g., the vendors' system).

The Need for Data Standards and Implementation Policies to Integrate CGM Data into the Electronic Health Record

The current lack of continuous glucose monitor (CGM) data integration into the electronic health record (EHR) is holding back the use of this wearable technology for patient-generated health data (PGHD). This failure to integrate with other healthcare data inside the EHR disrupts workflows, removes the data from critical patient context, and overall makes the CGM data less useful than it might otherwise be. Many healthcare organizations (HCOs) are either struggling with or delaying designing and implementing CGM data integrations. In this article, the current status of CGM integration is reviewed, goals for integration are proposed, and a consensus plan to engage key stakeholders to facilitate integration is presented.

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

OBJECTIVE

We sought to characterize the performance of inpatient and outpatient computerized clinical decision support (CDS) alerts aimed at reducing inappropriate benzodiazepine and nonbenzodiazepine sedative medication prescribing in older adults 18 months after implementation.

METHODS

We reviewed the performance of two CDS alerts in the outpatient and inpatient settings in 2019. To examine the alerts' effectiveness, we analyzed metrics including overall alert adherence, provider-level adherence, and reasons for alert trigger and override.

RESULTS

In 2019, we identified a total of 14,534 and 4,834 alerts triggered in the outpatient and inpatient settings, respectively. Providers followed only 1% of outpatient and 3% of inpatient alerts. Most alerts were ignored (68% outpatient and 60% inpatient), while providers selected to override the remaining alerts. In each setting, the top 2% of clinicians were responsible for approximately 25% of all ignored or overridden alerts. However, a small proportion of clinicians (2% outpatient and 4% inpatient) followed the alert at least half of the time and accounted for a disproportionally large fraction of the total followed alerts. Our analysis of the free-text comments revealed that many alerts were to continue outpatient prescriptions or for situational anxiety.

CONCLUSION

Our findings highlight the importance of evaluation of CDS performance after implementation. We found large variation in response to the inpatient and outpatient alerts, both with respect to follow and ignore rates. Reevaluating the alert design by providing decision support by indication may be more helpful and may reduce alert fatigue.

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

BACKGROUND

Drug alerts are clinical decision support tools intended to prevent medication misadministration. In teaching hospitals, residents encounter the majority of the drug alerts while learning under variable workloads and responsibilities that may have an impact on drug-alert response rates.

OBJECTIVES

This study was aimed to explore drug-alert experience and salience among postgraduate year 1 (PGY-1), postgraduate year 2 (PGY-2), and postgraduate year 3 (PGY-3) internal medicine resident physicians at two different institutions.

METHODS

Drug-alert information was queried from the electronic health record (EHR) for 47 internal medicine residents at the University of Pennsylvania Medical Center (UPMC) Pinnacle in Pennsylvania, and 79 internal medicine residents at the MetroHealth System (MHS) in Ohio from December 2018 through February 2019. Salience was defined as the percentage of drug alerts resulting in removal or modification of the triggering order. Comparisons were made across institutions, residency training year, and alert burden.

RESULTS

A total of 126 residents were exposed to 52,624 alerts over a 3-month period. UPMC Pinnacle had 15,574 alerts with 47 residents and MHS had 37,050 alerts with 79 residents. At MHS, salience was 8.6% which was lower than UPMC Pinnacle with 15%. The relatively lower salience (42% lower) at MHS corresponded to a greater number of alerts-per-resident (41% higher) compared with UPMC Pinnacle. Overall, salience was 11.6% for PGY-1, 10.5% for PGY-2, and 8.9% for PGY-3 residents.

CONCLUSION

Our results are suggestive of long-term drug-alert desensitization during progressive residency training. A higher number of alerts-per-resident correlating with a lower salience suggests alert fatigue; however, other factors should also be considered including differences in workload and culture.

A Narrative Review of Clinical Decision Support for Inpatient Clinical Pharmacists

OBJECTIVE

Increasingly, pharmacists provide team-based care that impacts patient care; however, the extent of recent clinical decision support (CDS), targeted to support the evolving roles of pharmacists, is unknown. Our objective was to evaluate the literature to understand the impact of clinical pharmacists using CDS.

METHODS

We searched MEDLINE, EMBASE, and Cochrane Central for randomized controlled trials, nonrandomized trials, and quasi-experimental studies which evaluated CDS tools that were developed for inpatient pharmacists as a target user. The primary outcome of our analysis was the impact of CDS on patient safety, quality use of medication, and quality of care. Outcomes were scored as positive, negative, or neutral. The secondary outcome was the proportion of CDS developed for tasks other than medication order verification. Study quality was assessed using the Newcastle-Ottawa Scale.

RESULTS

Of 4,365 potentially relevant articles, 15 were included. Five studies were randomized controlled trials. All included studies were rated as good quality. Of the studies evaluating inpatient pharmacists using a CDS tool, four showed significantly improved quality use of medications, four showed significantly improved patient safety, and three showed significantly improved quality of care. Six studies (40%) supported expanded roles of clinical pharmacists.

CONCLUSION

These results suggest that CDS can support clinical inpatient pharmacists in preventing medication errors and optimizing pharmacotherapy. Moreover, an increasing number of CDS tools have been developed for pharmacists' roles outside of order verification, whereby further supporting and establishing pharmacists as leaders in safe and effective pharmacotherapy.

Reducing Inappropriate Outpatient Medication Prescribing in Older Adults across Electronic Health Record Systems

BACKGROUND

The American Geriatrics Society recommends against the use of certain potentially inappropriate medications (PIMs) in older adults. Prescribing of these medications correlates with higher rates of hospital readmissions, morbidity, and mortality. Vanderbilt University Medical Center previously deployed clinical decision support (CDS) to decrease PIM prescribing rates, but recently transitioned to a new electronic health record (EHR).

OBJECTIVE

The goal of this study was to evaluate PIM prescribing rates for older adults before and after migration to the new EHR system.

METHODS

We reviewed prescribing rates of PIMs in adults 65 years and older, normalized per 100 total prescriptions from the legacy and new EHR systems between July 1, 2014 and December 31, 2019. The PIM prescribing rates before and after EHR migration during November 2017 were compared using a U-chart and Poisson regression model. Secondary analysis descriptively evaluated the frequency of prescriber acceptance rates in the new EHR.

RESULTS

Prescribing rates of PIMs decreased 5.2% (13.5 per 100 prescriptions to 12.8 per 100 prescriptions; p < 0.0001) corresponding to the implementation of alternatives CDS in the legacy EHR. After migration of the alternative CDS from the legacy to the new EHR system, PIM prescribing rates dropped an additional 18.8% (10.4 per 100 prescriptions; p < 0.0001). Acceptance rates of the alternative recommendations for PIMs was low overall at 11.1%.

CONCLUSION

The prescribing rate of PIMs in adults aged 65 years and older was successfully decreased with the implementation of prescribing CDS. This decrease was not only maintained but strengthened by the transition to a new EHR system.

Clinical Decision Support and Implications for the Clinician Burnout Crisis

OBJECTIVES

This survey aimed to review aspects of clinical decision support (CDS) that contribute to burnout and identify key themes for improving the acceptability of CDS to clinicians, with the goal of decreasing said burnout.

METHODS

We performed a survey of relevant articles from 2018-2019 addressing CDS and aspects of clinician burnout from PubMed and Web of Science™. Themes were manually extracted from publications that met inclusion criteria.

RESULTS

Eighty-nine articles met inclusion criteria, including 12 review articles. Review articles were either prescriptive, describing how CDS should work, or analytic, describing how current CDS tools are deployed. The non-review articles largely demonstrated poor relevance and acceptability of current tools, and few studies showed benefits in terms of efficiency or patient outcomes from implemented CDS. Encouragingly, multiple studies highlighted steps that succeeded in improving both acceptability and relevance of CDS.

CONCLUSIONS

CDS can contribute to clinician frustration and burnout. Using the techniques of improving relevance, soliciting feedback, customization, measurement of outcomes and metrics, and iteration, the effects of CDS on burnout can be ameliorated.