Distinct components of alert fatigue in physicians' responses to a noninterruptive clinical decision support alert

Electronic Health Record Alert With Heart Failure Risk and Sodium Glucose Cotransporter 2 Inhibitor Prescriptions in Diabetes: A Randomized Clinical Trial

BACKGROUND

Sodium glucose cotransporter 2 inhibitors (SGLT2i) prevent heart failure (HF) in patients with type 2 diabetes mellitus (T2DM) but prescription rates are low. The effect of an electronic health record (EHR) alert notifying providers of patients' estimated risk of developing HF on SGTL2i prescriptions is unknown.

METHODS

This was a pragmatic, randomized clinical trial that compared an EHR alert and usual care among patients with T2DM and no history of HF or SGLT2i use at a single center. The EHR alert notified providers of their patient's HF risk and recommended HF prevention strategies. Randomization was performed at the provider level across general and subspecialty internal medicine as well as family medicine outpatient clinics. The primary outcome was proportion of SGLT2i prescriptions within 30 days. Proportion of natriuretic peptide (NP) tests within 90 days was also assessed.

RESULTS

A total of 1524 patients (median age 75 years, 45% women, 23% Black) were enrolled between September 28, 2021, and April 29, 2022 from 189 outpatient clinics. SGLT2i were prescribed to 1.2% (9/780) of patients in the EHR alert group and 0% (0/744) of those in the usual care group (P value = 0.009). Natriuretic peptide testing was performed within 90 days among 10.8% (84/780) of patients in the EHR alert group and 7.3% (54/744) of patients in the usual care group (P value = 0.02).

CONCLUSIONS

In a single-center trial with low overall SGLT2i use, an EHR alert incorporating HF risk information significantly increased SGLT2i prescriptions and NP testing although the absolute rates were low.

Stewardship Prompts to Improve Antibiotic Selection for Urinary Tract Infection: The INSPIRE Randomized Clinical Trial

Importance

Urinary tract infection (UTI) is the second most common infection leading to hospitalization and is often associated with gram-negative multidrug-resistant organisms (MDROs). Clinicians overuse extended-spectrum antibiotics although most patients are at low risk for MDRO infection. Safe strategies to limit overuse of empiric antibiotics are needed.

Objective

To evaluate whether computerized provider order entry (CPOE) prompts providing patient- and pathogen-specific MDRO risk estimates could reduce use of empiric extended-spectrum antibiotics for treatment of UTI.

Design, Setting, and Participants

Cluster-randomized trial in 59 US community hospitals comparing the effect of a CPOE stewardship bundle (education, feedback, and real-time and risk-based CPOE prompts; 29 hospitals) vs routine stewardship (n = 30 hospitals) on antibiotic selection during the first 3 hospital days (empiric period) in noncritically ill adults (≥18 years) hospitalized with UTI with an 18-month baseline (April 1, 2017-September 30, 2018) and 15-month intervention period (April 1, 2019-June 30, 2020).

Interventions

CPOE prompts recommending empiric standard-spectrum antibiotics in patients ordered to receive extended-spectrum antibiotics who have low estimated absolute risk (<10%) of MDRO UTI, coupled with feedback and education.

Main Outcomes and Measures

The primary outcome was empiric (first 3 days of hospitalization) extended-spectrum antibiotic days of therapy. Secondary outcomes included empiric vancomycin and antipseudomonal days of therapy. Safety outcomes included days to intensive care unit (ICU) transfer and hospital length of stay. Outcomes were assessed using generalized linear mixed-effect models to assess differences between the baseline and intervention periods.

Results

Among 127 403 adult patients (71 991 baseline and 55 412 intervention period) admitted with UTI in 59 hospitals, the mean (SD) age was 69.4 (17.9) years, 30.5% were male, and the median Elixhauser Comorbidity Index count was 4 (IQR, 2-5). Compared with routine stewardship, the group using CPOE prompts had a 17.4% (95% CI, 11.2%-23.2%) reduction in empiric extended-spectrum days of therapy (rate ratio, 0.83 [95% CI, 0.77-0.89]; P < .001). The safety outcomes of mean days to ICU transfer (6.6 vs 7.0 days) and hospital length of stay (6.3 vs 6.5 days) did not differ significantly between the routine and intervention groups, respectively.

Conclusions and Relevance

Compared with routine stewardship, CPOE prompts providing real-time recommendations for standard-spectrum antibiotics for patients with low MDRO risk coupled with feedback and education significantly reduced empiric extended-spectrum antibiotic use among noncritically ill adults admitted with UTI without changing hospital length of stay or days to ICU transfers.

Trial Registration

ClinicalTrials.gov Identifier: NCT03697096.

User-Centered Framework for Implementation of Technology (UFIT): Development of an Integrated Framework for Designing Clinical Decision Support Tools Packaged With Tailored Implementation Strategies

BACKGROUND

Electronic health record-based clinical decision support (CDS) tools can facilitate the adoption of evidence into practice. Yet, the impact of CDS beyond single-site implementation is often limited by dissemination and implementation barriers related to site- and user-specific variation in workflows and behaviors. The translation of evidence-based CDS from initial development to implementation in heterogeneous environments requires a framework that assures careful balancing of fidelity to core functional elements with adaptations to ensure compatibility with new contexts.

OBJECTIVE

This study aims to develop and apply a framework to guide tailoring and implementing CDS across diverse clinical settings.

METHODS

In preparation for a multisite trial implementing CDS for pediatric overweight or obesity in primary care, we developed the User-Centered Framework for Implementation of Technology (UFIT), a framework that integrates principles from user-centered design (UCD), human factors/ergonomics theories, and implementation science to guide both CDS adaptation and tailoring of related implementation strategies. Our transdisciplinary study team conducted semistructured interviews with pediatric primary care clinicians and a diverse group of stakeholders from 3 health systems in the northeastern, midwestern, and southeastern United States to inform and apply the framework for our formative evaluation.

RESULTS

We conducted 41 qualitative interviews with primary care clinicians (n=21) and other stakeholders (n=20). Our workflow analysis found 3 primary ways in which clinicians interact with the electronic health record during primary care well-child visits identifying opportunities for decision support. Additionally, we identified differences in practice patterns across contexts necessitating a multiprong design approach to support a variety of workflows, user needs, preferences, and implementation strategies.

CONCLUSIONS

UFIT integrates theories and guidance from UCD, human factors/ergonomics, and implementation science to promote fit with local contexts for optimal outcomes. The components of UFIT were used to guide the development of Improving Pediatric Obesity Practice Using Prompts, an integrated package comprising CDS for obesity or overweight treatment with tailored implementation strategies.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05627011; https://clinicaltrials.gov/study/NCT05627011.

Resident-Driven Clinical Decision Support Governance to Improve the Utility of Clinical Decision Support

OBJECTIVES

 This resident-driven quality improvement project aimed to better understand the known problem of a misaligned clinical decision support (CDS) strategy and improve CDS utilization.

METHODS

 An internal survey was sent to all internal medicine (IM) residents to identify the most bothersome CDS alerts. Survey results were supported by electronic health record (EHR) data of CDS firing rates and response rates which were collected for each of the three most bothersome CDS tools. Changes to firing criteria were created to increase utilization and to better align with the five rights of CDS. Findings and proposed changes were presented to our institution's CDS Governance Committee. Changes were approved and implemented. Postintervention firing rates were then collected for 1 week.

RESULTS

 Twenty nine residents participated in the CDS survey and identified sepsis alerts, lipid profile reminders, and telemetry renewals to be the most bothersome alerts. EHR data showed action rates for these CDS as low as 1%. We implemented changes to focus emergency department (ED)-based sepsis alerts to the right provider, better address the right information for lipid profile reminders, and select the right time in workflow for telemetry renewals to be most effective. With these changes we successfully eliminated ED-based sepsis CDS reminders for IM providers, saw a 97% reduction in firing rates for the lipid profile CDS, and noted a 55% reduction in firing rates for telemetry CDS.

CONCLUSION

 This project highlighted that alert improvements spearheaded by resident teams can be completed successfully using robust CDS governance strategies and can effectively optimize interruptive alerts.

Randomized Comparison of Electronic Health Record Alert Types in Eliciting Responses about Prognosis in Gynecologic Oncology Patients

OBJECTIVES

 To compare the ability of different electronic health record alert types to elicit responses from users caring for cancer patients benefiting from goals of care (GOC) conversations.

METHODS

 A validated question asking if the user would be surprised by the patient's 6-month mortality was built as an Epic BestPractice Advisory (BPA) alert in three versions-(1) Required on Open chart (pop-up BPA), (2) Required on Close chart (navigator BPA), and (3) Optional Persistent (Storyboard BPA)-randomized using patient medical record number. Meaningful responses were defined as "Yes" or "No," rather than deferral. Data were extracted over 6 months.

RESULTS

 Alerts appeared for 685 patients during 1,786 outpatient encounters. Measuring encounters where a meaningful response was elicited, rates were highest for Required on Open (94.8% of encounters), compared with Required on Close (90.1%) and Optional Persistent (19.7%) (p < 0.001). Measuring individual alerts to which responses were given, they were most likely meaningful with Optional Persistent (98.3% of responses) and least likely with Required on Open (68.0%) (p < 0.001). Responses of "No," suggesting poor prognosis and prompting GOC, were more likely with Optional Persistent (13.6%) and Required on Open (10.3%) than with Required on Close (7.0%) (p = 0.028).

CONCLUSION

 Required alerts had response rates almost five times higher than optional alerts. Timing of alerts affects rates of meaningful responses and possibly the response itself. The alert with the most meaningful responses was also associated with the most interruptions and deferral responses. Considering tradeoffs in these metrics is important in designing clinical decision support to maximize success.

Impact of a Clinical Decision Support Alert on Informed Consent Documentation in the Neonatal Intensive Care Unit

Background

Informed consent is necessary to preserve patient autonomy and shared decision-making, yet compliant consent documentation is suboptimal in the intensive care unit (ICU). We aimed to increase compliance with bundled consent documentation, which provides consent for a predefined set of common procedures in the neonatal ICU from 0% to 50% over 1 year.

Methods

We used the Plan-Do-Study-Act model for quality improvement. Interventions included education and performance awareness, delineation of the preferred consenting process, consent form revision, overlay tool creation, and clinical decision support (CDS) alert use within the electronic health record. Monthly audits categorized consent forms as missing, present but noncompliant, or compliant. We analyzed consent compliance on a run chart using standard run chart interpretation rules and obtained feedback on the CDS as a countermeasure.

Results

We conducted 564 audits over 37 months. Overall, median consent compliance increased from 0% to 86.6%. Upon initiating the CDS alert, we observed the highest monthly compliance of 93.3%, followed by a decrease to 33.3% with an inadvertent discontinuation of the CDS. Compliance subsequently increased to 73.3% after the restoration of the alert. We created a consultant opt-out selection to address negative feedback associated with CDS. There were no missing consent forms within the last 7 months of monitoring.

Conclusions

A multi-faceted approach led to sustained improvement in bundled consent documentation compliance in our neonatal intensive care unit, with the direct contribution of the CDS observed. A CDS intervention directed at the informed consenting process may similarly benefit other ICUs.

Cognitive task analysis of clinicians' drug-drug interaction management during patient care and implications for alert design

BACKGROUND

Drug-drug interactions (DDIs) are common and can result in patient harm. Electronic health records warn clinicians about DDIs via alerts, but the clinical decision support they provide is inadequate. Little is known about clinicians' real-world DDI decision-making process to inform more effective alerts.

OBJECTIVE

Apply cognitive task analysis techniques to determine informational cues used by clinicians to manage DDIs and identify opportunities to improve alerts.

DESIGN

Clinicians submitted incident forms involving DDIs, which were eligible for inclusion if there was potential for serious patient harm. For selected incidents, we met with the clinician for a 60 min interview. Each interview transcript was analysed to identify decision requirements and delineate clinicians' decision-making process. We then performed an inductive, qualitative analysis across incidents.

SETTING

Inpatient and outpatient care at a major, tertiary Veterans Affairs medical centre.

PARTICIPANTS

Physicians, pharmacists and nurse practitioners.

OUTCOMES

Themes to identify informational cues that clinicians used to manage DDIs.

RESULTS

We conducted qualitative analyses of 20 incidents. Data informed a descriptive model of clinicians' decision-making process, consisting of four main steps: (1) detect a potential DDI; (2) DDI problem-solving, sensemaking and planning; (3) prescribing decision and (4) resolving actions. Within steps (1) and (2), we identified 19 information cues that clinicians used to manage DDIs for patients. These cues informed their subsequent decisions in steps (3) and (4). Our findings inform DDI alert recommendations to improve clinicians' decision-making efficiency, confidence and effectiveness.

CONCLUSIONS

Our study provides three key contributions. Our study is the first to present an illustrative model of clinicians' real-world decision making for managing DDIs. Second, our findings add to scientific knowledge by identifying 19 cognitive cues that clinicians rely on for DDI management in clinical practice. Third, our results provide essential, foundational knowledge to inform more robust DDI clinical decision support in the future.

Advances in Clinical Decision Support Systems: Contributions from the 2022 Literature

OBJECTIVE

To summarize significant research contributions published in 2022 in the field of clinical decision support (CDS) systems and select the best papers for the Decision Support section of the International Medical Informatics Association (IMIA) Yearbook 2023.

METHODS

A renewed search query for identifying CDS scholarship was developed using Medical Subject Headings (MeSH) terms and related keywords. The query was executed in PubMed in January 2023. The search results were reviewed in three stages by two reviewers: title-based triaging, followed by abstract screening, and then full text review. The resulting articles were sent for external review to identity best paper candidates.

RESULTS

A total of 1,939 articles related to CDS were retrieved. Of these, 11 articles were selected as candidates for best papers. The general themes of the final three best papers are (1) reducing documentation burden through in-line guidance for clinical notes, (2) clinician engagement for continuous improvement of CDS, and (3) mitigating healthcare-related carbon emissions using scalable and accessible CDS, respectively.

CONCLUSION

The field of clinical decision support remains highly active and dynamic, with innovative contributions to a range of clinical domains from primary to acute care. Interoperability issues, documentation burden, clinician acceptance, and the need for effective integration into existing healthcare workflows are among the prominent challenges and areas of interest faced by CDS implementation efforts.