Efficacy and unintended consequences of hard-stop alerts in electronic health record systems: a systematic review

Validity of Routinely Reported Rutherford Scores Reported by Clinicians as Part of Daily Clinical Practice

Routinely reported structured data from the electronic health record (EHR) are frequently used for secondary purposes. However, it is unknown how valid routinely reported data are for reuse. This study aimed to assess the validity of routinely reported Rutherford scores by clinicians as an indicator for the validity of structured data in the EHR. This observational study compared clinician-reported Rutherford scores with medical record review Rutherford scores for all visits at the vascular surgery department between April 1, 2016 and December 31, 2018. Free-text fields with clinical information for all visits were extracted for the assignment of the medical record review Rutherford score, after which the agreement with the clinician-reported Rutherford score was assessed using Fleiss' Kappa. A total of 6,633 visits were included for medical record review. Substantial agreement was shown between clinician-reported Rutherford scores and medical record review Rutherford scores for the left ( k  = 0.62, confidence interval [CI]: 0.60-0.63) and right leg ( k  = 0.62, CI: 0.60-0.64). This increased to the almost perfect agreement for left ( k  = 0.84, CI: 0.82-0.86) and right leg ( k  = 0.85, CI: 0.83-0.87), when excluding missing clinician-reported Rutherford scores. Expert's judgment was rarely required to be the deciding factor (11 out of 6,633). Substantial agreement between clinician-reported Rutherford scores and medical record review Rutherford scores was found, which could be an indicator for the validity of routinely reported data. Depending on its purpose, the secondary use of routinely collected Rutherford scores is a viable option.

Impact of an Electronic Health Record-Based Interruptive Alert Among Patients With Headaches Seen in Primary Care: Cluster Randomized Controlled Trial

Background

Headaches, including migraines, are one of the most common causes of disability and account for nearly 20%-30% of referrals from primary care to neurology. In primary care, electronic health record-based alerts offer a mechanism to influence health care provider behaviors, manage neurology referrals, and optimize headache care.

Objective

This project aimed to evaluate the impact of an electronic alert implemented in primary care on patients' overall headache management.

Methods

We conducted a stratified cluster-randomized study across 38 primary care clinic sites between December 2021 to December 2022 at a large integrated health care delivery system in the United States. Clinics were stratified into 6 blocks based on region and patient-to-health care provider ratios and then 1:1 randomized within each block into either the control or intervention. Health care providers practicing at intervention clinics received an interruptive alert in the electronic health record. The primary end point was a change in headache burden, measured using the Headache Impact Test 6 scale, from baseline to 6 months. Secondary outcomes included changes in headache frequency and intensity, access to care, and resource use. We analyzed the difference-in-differences between the arms at follow-up at the individual patient level.

Results

We enrolled 203 adult patients with a confirmed headache diagnosis. At baseline, the average Headache Impact Test 6 scores in each arm were not significantly different (intervention: mean 63, SD 6.9; control: mean 61.8, SD 6.6; P=.21). We observed a significant reduction in the headache burden only in the intervention arm at follow-up (3.5 points; P=.009). The reduction in the headache burden was not statistically different between groups (difference-in-differences estimate -1.89, 95% CI -5 to 1.31; P=.25). Similarly, secondary outcomes were not significantly different between groups. Only 11.32% (303/2677) of alerts were acted upon.

Conclusions

The use of an interruptive electronic alert did not significantly improve headache outcomes. Low use of alerts by health care providers prompts future alterations of the alert and exploration of alternative approaches.

Reducing Erythrocyte Sedimentation Rate Ordering: De-implementation and Diagnostic Stewardship

OBJECTIVES

The Choosing Wisely campaign recommends against the routine use of erythrocyte sedimentation rate (ESR) for the assessment of acute undiagnosed inflammation or infection. We examined ESR and C-reactive protein (CRP) ordering practices at a large, freestanding children's hospital. We found that 80% of ESR orders were placed concurrently with a CRP order. We aimed to reduce the ESR testing rate by 20% within 6 months in both inpatient and emergency department (ED) settings.

METHODS

Applying Lean process improvement principles, we interviewed stakeholders from multiple subspecialties and engaged the institutional laboratory stewardship committee to identify the root causes of ESR ordering and design interventions. We conducted provider education (November 2020) and employed clinical decision support through an order panel in the electronic health record (April 2021). The outcome measures were monthly ESR testing rate per 1000 patient days (inpatient) and per 1000 ED visits, analyzed using statistical process control charts. CRP testing rate was a balancing measure.

RESULTS

After intervention implementation, the ESR testing rate decreased from 11.4 to 8.9 tests per 1000 inpatient patient days (22% decrease) and from 49.4 to 29.5 tests per 1000 ED visits (40% decrease). This change has been sustained for >1 year postintervention. Interventions were effective even during the coronavirus disease 2019 pandemic when there was a rise in baseline ED ESR ordering rate. CRP testing rates did not increase after the interventions.

CONCLUSIONS

Education and clinical decision support were effective in reducing the ESR ordering rate in both inpatient and ED settings.

The PrescIT platform: An interoperable Clinical Decision Support System for ePrescription to Prevent Adverse Drug Reactions and Drug-Drug Interactions

INTRODUCTION

Preventable medication errors have been proven to cause significant public health burden, and ePrescription is a key part of the process where medication errors and adverse effects could be prevented. Information systems and "intelligent" computational approaches could provide a valuable tool to prevent such errors with profound impact in clinical practice.

OBJECTIVES

The PrescIT platform is a Clinical Decision Support System (CDSS) that aims to facilitate the prevention of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) in the phase of ePrescription in Greece. The proposed platform could be relatively easily localized for use in other contexts too.

METHODS

The PrescIT platform is based on the use of Knowledge Engineering (ΚΕ) approaches, i.e., the use of Ontologies and Knowledge Graphs (KGs) developed upon openly available data sources. Open standards (i.e., RDF, OWL, SPARQL) are used for the development of the platform enabling the integration with already existing IT systems or for standalone use. The main KG is based on the use of DrugBank, MedDRA, SemMedDB and OpenPVSignal. In addition, the Business Process Management Notation (BPMN) has been used to model long-term therapeutic protocols used during the ePrescription process. Finally, the produced software has been pilot tested in three hospitals by 18 clinical professionals via in-person think-aloud sessions.

RESULTS

The PrescIT platform has been successfully integrated in a transparent fashion in a proprietary Hospital Information System (HIS), and it has also been used as a standalone application. Furthermore, it has been successfully integrated with the Greek National ePrescription system. During the pilot phase, one psychiatric therapeutic protocol was used as a testbed to collect end-users' feedback. Summarizing the feedback from the end-users, they have generally acknowledged the usefulness of such a system while also identifying some challenges in terms of usability and the overall user experience.

CONCLUSIONS

The PrescIT platform has been successfully deployed and piloted in real-world environments to evaluate its ability to support safer medication prescriptions.

EMR-Documented Contraception for Patients Prescribed Medications With Adverse Perinatal Outcomes

This cross-sectional study examines the rates of method of contraception documentation in the electronic medical record (EMR) for patients receiving 1 of 3 drugs known to be associated with adverse perinatal outcomes.

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.

Comparison of Clinical Decision Support Tools to Improve Pediatric Lipid Screening

OBJECTIVE

To test whether different clinical decision support tools increase clinician orders and patient completions relative to standard practice and each other.

STUDY DESIGN

A pragmatic, patient-randomized clinical trial in the electronic health record was conducted between October 2019 and April 2020 at Geisinger Health System in Pennsylvania, with 4 arms: care gap-a passive listing recommending screening; alert-a panel promoting and enabling lipid screen orders; both; and a standard practice-no guideline-based notification-control arm. Data were analyzed for 13 346 9- to 11-year-old patients seen within Geisinger primary care, cardiology, urgent care, or nutrition clinics, or who had an endocrinology visit. Principal outcomes were lipid screening orders by clinicians and completions by patients within 1 week of orders.

RESULTS

Active (care gap and/or alert) vs control arm patients were significantly more likely (P < .05) to have lipid screening tests ordered and completed, with ORs ranging from 1.67 (95% CI 1.28-2.19) to 5.73 (95% CI 4.46-7.36) for orders and 1.54 (95% CI 1.04-2.27) to 2.90 (95% CI 2.02-4.15) for completions. Alerts, with or without care gaps listed, outperformed care gaps alone on orders, with odds ratios ranging from 2.92 (95% CI 2.32-3.66) to 3.43 (95% CI 2.73-4.29).

CONCLUSIONS

Electronic alerts can increase lipid screening orders and completions, suggesting clinical decision support can improve guideline-concordant screening. The study also highlights electronic record-based patient randomization as a way to determine relative effectiveness of support tools.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04118348.

Covid-19 hotlines, helplines and call centers: a systematic review of characteristics, challenges and lessons learned

BACKGROUND

During the Covid-19 pandemic, a number of hotlines/helplines/call centers was implemented to provide remote services and support public health. The objective of this study was to investigate the characteristics, challenges and lessons learned of implementing Covid-19 hotlines/helplines/call centers during the pandemic.

METHODS

PubMed, Web of Science, Scopus, the Cochrane Library, IEEE Xplore, and ProQuest databases as well as Google Scholar were searched between 1st January 2020 and 31st December 2023 to retrieve relevant articles published in English. The quality and risk of bias of the studies were assessed using the Appraisal tool for Cross-Sectional Studies (AXIS), the Mixed Methods Appraisal Tool (MMAT), and Critical Appraisal Skills Programme (CASP) Checklist.

RESULTS

In total, 43 out of 1440 articles were included in this study. About half of the hotlines/helplines/call centers were launched in March 2020 (n = 19). Providing psychological support (n = 23), reliable information about Covid-19 (n = 10), healthcare advices about Covid-19 (n = 8), and triage (n = 7) were the most common purposes of implementing these services. The most common challenges included a lack of physical examination, unavailability of hotlines/helplines/call centers at the point of need, and delay in updating Covid-19 information. The most common lessons learned were employing qualified staff, providing proper training, and getting feedback from the callers and operators.

CONCLUSION

According to the results, most of the Covid-19 hotlines/helplines/call centers were launched in the early months of the pandemic, and about half of them were active seven days a week. Most of the operators were mental health providers and clinicians. The findings show the importance of continuous psychological support during crises, particularly when adequate information about the situation is not available. The challenges experienced by the callers and operators as well as the lessons learned by the service providers also need to be considered for future crises to increase the effectiveness of similar services.

Emergency department documentation of legal intervention injuries at a Washington, DC, hospital

BACKGROUND

The U.S. Centers for Disease Control and Prevention (CDC) defines legal intervention injuries as injuries caused by law enforcement agents in the course of official duties. Public health databases utilize International Classification of Diseases, 10th Revision (ICD-10), coding to collect these data through the "Y35" family ICD-10 code. Prior studies report deficiencies in public health recording of fatal legal intervention injuries. Few studies have characterized nonfatal injuries. This study investigates emergency department (ED) capture of legal intervention injury diagnostic coding.

METHODS

A retrospective chart review was performed on ED encounter data from January 1, 2017, to June 30, 2019, at an academic hospital in Washington, DC. Charts were identified using a keyword search program for "police." Chart abstracters reviewed the flagged charts and abstracted those that met injury definition. Primary outcomes included injury severity, patient demographics, and documented ICD-10 codes. One sample proportion testing was performed comparing sample census ED data.

RESULTS

A total of 340 encounters had sufficient descriptions of legal intervention injuries. A total of 259 had descriptions consistent with the patient specifier of "suspect." Hospital coders recorded 74 charts (28.6%) with the Y35 family legal intervention injury code. A total of 212 involved a Black patient. A total of 122 patients had Medicaid and 94 were uninsured. Black patients made up a higher proportion of individuals in the "suspect identified legal intervention injury" group than the total population (0.819 vs. 0.609, p < 0.01, 95% CI 0.772-0.866). Patients with Medicaid or who were uninsured made up substantial proportions as well (0.471 vs. 0.175, p < 0.01, 95% CI 0.410-0.532 for Medicaid patients and 0.363 vs. 0.155, p < 0.01, 95% CI 0.304-0.424 for the uninsured patients).

CONCLUSION

A large proportion of nonfatal legal intervention injuries remain unreported. Black and low-income patients are disproportionately affected. More research is needed but benefits from interprofessional data sharing, injury pattern awareness, and diagnostic coding guidance may improve reporting.

Working with the Electronic Health Record and Laboratory Information System to Maximize Ordering and Reporting of Molecular Microbiology Results

Molecular microbiology assays have a higher cost of testing compared to traditional methods and need to be utilized appropriately. Results from these assays may also require interpretation and appropriate follow-up. Electronic tools available in the electronic health record and laboratory information system can be deployed both preanalytically and postanalytically to influence ordering behaviors and positively impact diagnostic stewardship. Next generation technologies, such as machine learning and artificial intelligence, have the potential to expand upon the capabilities currently available and warrant additional study and development but also require regulation around their use in health care.

Use of Computerized Physician Order Entry with Clinical Decision Support to Prevent Dose Errors in Pediatric Medication Orders: A Systematic Review

BACKGROUND

Prescribing is a high-risk task within the pediatric medication-use process and requires defenses to prevent errors. Such system-centric defenses include electronic health record systems with computerized physician order entry (CPOE) and clinical decision support (CDS) tools that assist safe prescribing. The objective of this study was to examine the effects of CPOE systems with CDS functions in preventing dose errors in pediatric medication orders.

MATERIAL AND METHODS

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 criteria and Synthesis Without Meta-Analysis (SWiM) items. The study protocol was registered in PROSPERO (CRD42021277413). The final literature search on MEDLINE (Ovid), Scopus, Web of Science, and EMB Reviews was conducted on 10 September 2023. Only peer-reviewed studies considering both CPOE and CDS systems in pediatric inpatient or outpatient settings were included. Study selection, data extraction, and evidence quality assessment (JBI critical appraisal tool assessment and GRADE approach) were carried out by two individual reviewers. Vote counting method was used to evaluate the effects of CPOE-CDS systems on dose errors rates.

RESULTS

A total of 17 studies published in 2007-2021 met the inclusion criteria. The most used CDS tools were dose range check (n = 14), dose calculator (n = 8), and dosing frequency check (n = 8). Alerts were recorded in 15 studies. A statistically significant reduction in dose errors was found in eight studies, whereas an increase of dose errors was not reported.

CONCLUSIONS

The CPOE-CDS systems have the potential to reduce pediatric dose errors. Most beneficial interventions seem to be system customization, implementing CDS alerts, and the use of dose range check. While human factors are still present within the medication use process, further studies and development activities are needed to optimize the usability of CPOE-CDS systems.

The Unseen Hand: AI-Based Prescribing Decision Support Tools and the Evaluation of Drug Safety and Effectiveness

The use of artificial intelligence (AI)-based tools to guide prescribing decisions is full of promise and may enhance patient outcomes. These tools can perform actions such as choosing the 'safest' medication, choosing between competing medications, promoting de-prescribing or even predicting non-adherence. These tools can exist in a variety of formats; for example, they may be directly integrated into electronic medical records or they may exist in a stand-alone website accessible by a web browser. One potential impact of these tools is that they could manipulate our understanding of the benefit-risk of medicines in the real world. Currently, the benefit risk of approved medications is assessed according to carefully planned agreements covering spontaneous reporting systems and planned surveillance studies. But AI-based tools may limit or even block prescription to high-risk patients or prevent off-label use. The uptake and temporal availability of these tools may be uneven across healthcare systems and geographies, creating artefacts in data that are difficult to account for. It is also hard to estimate the 'true impact' that a tool had on a prescribing decision. International borders may also be highly porous to these tools, especially in cases where tools are available over the web. These tools already exist, and their use is likely to increase in the coming years. How they can be accounted for in benefit-risk decisions is yet to be seen.

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.

Using Clinical Decision Support Systems to Decrease Intravenous Acetaminophen Use: Implementation and Lessons Learned

BACKGROUND

Clinical decision support systems (CDSS) can enhance medical decision-making by providing targeted information to providers. While they have the potential to improve quality of care and reduce costs, they are not universally effective and can lead to unintended harm.

OBJECTIVES

To describe the implementation of an unsuccessful interruptive CDSS that aimed to promote appropriate use of intravenous (IV) acetaminophen at an academic pediatric hospital, with an emphasis on lessons learned.

METHODS

Quality improvement methodology was used to study the effect of an interruptive CDSS, which set a mandatory expiry time of 24 hours for all IV acetaminophen orders. This CDSS was implemented on April 5, 2021. The primary outcome measure was number of IV acetaminophen administrations per 1,000 patient days, measured pre- and postimplementation. Process measures were the number of IV acetaminophen orders placed per 1,000 patient days. Balancing measures were collected via survey data and included provider and nursing acceptability and unintended consequences of the CDSS.

RESULTS

There was no special cause variation in hospital-wide IV acetaminophen administrations and orders after CDSS implementation, nor when the CDSS was removed. A total of 88 participants completed the survey. Nearly half (40/88) of respondents reported negative issues with the CDSS, with the majority stating that this affected patient care (39/40). Respondents cited delays in patient care and reduced efficiency as the most common negative effects.

CONCLUSION

This study underscores the significance of monitoring CDSS implementations and including end user acceptability as an outcome measure. Teams should be prepared to modify or remove CDSS that do not achieve their intended goal or are associated with low end user acceptability. CDSS holds promise for improving clinical practice, but careful implementation and ongoing evaluation are crucial for maximizing their benefits and minimizing potential harm.

Clinical impacts of an integrated electronic health record-based smoking cessation intervention during hospitalisation

OBJECTIVE

To assess the effects of an electronic health record (EHR) intervention that prompts the clinician to prescribe nicotine replacement therapy (NRT) at hospital admission and discharge in a large integrated health system.

DESIGN

Retrospective cohort study using interrupted time series (ITS) analysis leveraging EHR data generated before and after implementation of the 2015 EHR-based intervention.

SETTING

Kaiser Permanente Northern California, a large integrated health system with 4.2 million members.

PARTICIPANTS

Current smokers aged ≥18 hospitalised for any reason.

EXPOSURE

EHR-based clinical decision supports that prompted the clinician to order NRT on hospital admission (implemented February 2015) and discharge (implemented September 2015).

MAIN OUTCOMES AND MEASURES

Primary outcomes included the monthly percentage of admitted smokers with NRT orders during admission and at discharge. A secondary outcome assessed patient quit rates within 30 days of hospital discharge as reported during discharge follow-up outpatient visits.

RESULTS

The percentage of admissions with NRT orders increased from 29.9% in the year preceding the intervention to 78.1% in the year following (41.8% change, 95% CI 38.6% to 44.9%) after implementation of the admission hard-stop intervention compared with the baseline trend (ITS estimate). The percentage of discharges with NRT orders increased acutely at the time of both interventions (admission intervention ITS estimate 15.5%, 95% CI 11% to 20%; discharge intervention ITS estimate 13.4%, 95% CI 9.1% to 17.7%). Following the implementation of the discharge intervention, there was a small increase in patient-reported quit rates (ITS estimate 5.0%, 95% CI 2.2% to 7.8%).

CONCLUSIONS

An EHR-based clinical decision-making support embedded into admission and discharge documentation was associated with an increase in NRT prescriptions and improvement in quit rates. Similar systemic EHR interventions can help improve smoking cessation efforts after hospitalisation.

Early Insights into Implementation of Universal Screening, Brief Intervention, and Referral to Treatment for Perinatal Substance Use

OBJECTIVES

Perinatal substance use is a growing concern across the United States. Universal screening, brief intervention, and referral to treatment (SBIRT) is one systems-level approach to addressing perinatal substance use. The objective of this study is to assess early efforts to implement SBIRT in an outpatient obstetric clinic.

METHODS

The research team implemented universal screening with the 5 P's screening tool. Providers then engaged patients in a brief intervention and referred to a care manager who then worked with patients via tele-health to connect patients with needed services. Feasibility was measured through the collection of aggregate data describing frequency of universal screening and referral to treatment. The implementation team met bi-weekly to reflect on implementation barriers and facilitators.

RESULTS

In the first year of implementation, 48.5% of patients receiving care in the clinic completed the 5 P's screener at least once during the perinatal period. Screening occurred in a little over a quarter (26.5%) of eligible visits. Of the 463 patients that completed the 5 P's at least once during the perinatal period, 195 (42%) unique patients screened positive (answered yes to at least one question).

CONCLUSIONS FOR PRACTICE

Early implementation efforts suggest this approach is feasible in this obstetric setting. Similar implementation studies should consider implementing universal screening for substance use and perinatal mood and anxiety disorders simultaneously; guide efforts using an implementation framework; invest resources in more intensive training and ongoing coaching for providers; and adopt strategies to track frequency and fidelity of brief intervention.

Integration of Cirrhosis Best Practices Into Electronic Medical Record Documentation Associated With Reduction in 30-Day Mortality Following Hospitalization

BACKGROUND

Hospital admissions for patients with cirrhosis continue to increase. In New York City, 25% to 30% of hospitalized cirrhotics are readmitted within 30 days. Rehospitalization is associated with increased mortality, poor quality of life, and financial burden to patients, hospitals, and payers. Preventable readmissions are partially accounted for by a well-documented quality gap between evidence-based guidelines for cirrhosis management and real-world adherence to these recommendations.

METHODS

We performed a prospective cohort study that compared outcomes among cirrhotic patients admitted to 4 internal medicine teams over a 6-month period. An electronic medical record (EMR) note template that outlined best-practice measures for cirrhotics was developed. Inpatient providers on 2 teams were instructed to include it in daily progress notes and discharge summaries. The recommended practices included diagnostic paracentesis and diuretics for ascites, rifaximin, and lactulose for hepatic encephalopathy, beta blockers for esophageal varices, and antibiotic prophylaxis for spontaneous bacterial peritonitis. The remaining 2 teams continued the standard of care for cirrhotic patients. The primary outcome was 30-day readmissions. Secondary outcomes included in-hospital mortality, 30-day mortality, length of stay, and adherence to best-practice guidelines.

RESULTS

Over a 6-month period, 108 cirrhotic patients were admitted, 83 in the interventional group and 25 in the control group. MELD-Na scores on admission did not differ between the groups (20.1 vs. 21.1, P =0.56). Thirty-day readmissions were not significantly different between the interventional and control groups (19.3% vs. 24%, P =0.61). However, 30-day mortality was significantly lower in the interventional group (8.4% vs. 28%, P =0.01). There was no difference between the 2 groups in in-hospital mortality (4.8% vs. 0%, P =0.27), 90-day mortality (15.7% vs. 28.0%, P =0.17) or length of stay (10.2 vs. 12.6 d, P =0.34). Adherence to best-practice metrics was similar between the groups, except for rates of diagnostic paracentesis, which were higher in the interventional group (98% vs. 80%, P =0.01).

CONCLUSION

Implementation of an EMR note template with cirrhosis best practices was associated with lower 30-day mortality and higher rates of diagnostic paracentesis among admitted patients with cirrhosis. These findings suggest that the integration of best-practice measures into the EMR may improve outcomes in hospitalized cirrhotic patients. Larger studies are required to validate these findings.

Management of urologic prosthetic reservoirs at the time of inguinal or pelvic surgery

INTRODUCTION

The artificial urinary sphincter and 3-piece inflatable penile prosthesis each require a fluid storage component and thus have components in the inguinal and pelvic regions. Because of this, patients with urologic prosthetics sometimes present challenges during future nonprosthetic operations. Presently, there is no established guideline for device management with ensuing inguinal or pelvic surgery.

AIMS

This article outlines concerns during pelvic and inguinal surgery for patients with an artificial urinary sphincter and/or inflatable penile prosthesis and proposes an algorithm for preoperative surgical planning and decision making.

METHODS

We conducted a narrative review of the literature on operative management of these prosthetic devices. Publications were identified by searching electronic databases. Only peer-reviewed publications available in English were considered for this review.

RESULTS

We review the important considerations as well as available options for operative management of these prosthetic devices during subsequent nonprosthetic surgery and highlight the advantages and disadvantages of each. Finally, we suggest a framework for helping surgeons determine which management strategy is most appropriate for their individual patients.

CONCLUSION

The best management strategy will differ depending on patient values, the planned surgery, and patient-specific factors. Surgeons should understand and counsel patients on all available options and encourage informed, shared decision making to determine the best individualized approach.

Sepsis Prediction in Hospitalized Children: Clinical Decision Support Design and Deployment

BACKGROUND

Following development and validation of a sepsis prediction model described in a companion article, we aimed to use quality improvement and safety methodology to guide the design and deployment of clinical decision support (CDS) tools and clinician workflows to improve pediatric sepsis recognition in the inpatient setting.

METHODS

CDS tools and sepsis huddle workflows were created to implement an electronic health record-based sepsis prediction model. These were proactively analyzed and refined using simulation and safety science principles before implementation and were introduced across inpatient units during 2020-2021. Huddle compliance, alerts per non-ICU patient days, and days between sepsis-attributable emergent transfers were monitored. Rapid Plan-Do-Study-Act (PDSA) cycles based on user feedback and weekly metric data informed improvement throughout implementation.

RESULTS

There were 264 sepsis alerts on 173 patients with an 89% bedside huddle completion rate and 10 alerts per 1000 non-ICU patient days per month. There was no special cause variation in the metric days between sepsis-attributable emergent transfers.

CONCLUSIONS

An automated electronic health record-based sepsis prediction model, CDS tools, and sepsis huddle workflows were implemented on inpatient units with a relatively low rate of interruptive alerts and high compliance with bedside huddles. Use of CDS best practices, simulation, safety tools, and quality improvement principles led to high utilization of the sepsis screening process.

The impact of transition to a digital hospital on medication errors (TIME study)

Digital transformation in healthcare improves the safety of health systems. Within our health service, a new digital hospital has been established and two wards from a neighbouring paper-based hospital transitioned into the new digital hospital. This created an opportunity to evaluate the impact of complete digital transformation on medication safety. Here we discuss the impact of transition from a paper-based to digital hospital on voluntarily reported medication incidents and prescribing errors. This study utilises an interrupted time-series design and takes place across two wards as they transition from a paper to a digital hospital. Two data sources are used to assess impacts on medication incidents and prescribing errors: (1) voluntarily reported medication incidents and 2) a chart audit of medications prescribed on the study wards. The chart audit collects data on procedural, dosing and therapeutic prescribing errors. There are 588 errors extracted from incident reporting software during the study period. The average monthly number of errors reduces from 12.5 pre- to 7.5 post-transition (p < 0.001). In the chart audit, 5072 medication orders are reviewed pre-transition and 3699 reviewed post-transition. The rates of orders with one or more error reduces significantly after transition (52.8% pre- vs. 15.7% post-, p < 0.001). There are significant reductions in procedural (32.1% pre- vs. 1.3% post-, p < 0.001), and dosing errors (32.3% pre- vs. 14% post-, p < 0.001), but not therapeutic errors (0.6% pre- vs. 0.7% post-, p = 0.478). Transition to a digital hospital is associated with reductions in voluntarily reported medication incidents and prescribing errors.

Using AI-generated suggestions from ChatGPT to optimize clinical decision support

OBJECTIVE

To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions.

METHODS

We supplied summaries of CDS logic to ChatGPT, an artificial intelligence (AI) tool for question answering that uses a large language model, and asked it to generate suggestions. We asked human clinician reviewers to review the AI-generated suggestions as well as human-generated suggestions for improving the same CDS alerts, and rate the suggestions for their usefulness, acceptance, relevance, understanding, workflow, bias, inversion, and redundancy.

RESULTS

Five clinicians analyzed 36 AI-generated suggestions and 29 human-generated suggestions for 7 alerts. Of the 20 suggestions that scored highest in the survey, 9 were generated by ChatGPT. The suggestions generated by AI were found to offer unique perspectives and were evaluated as highly understandable and relevant, with moderate usefulness, low acceptance, bias, inversion, redundancy.

CONCLUSION

AI-generated suggestions could be an important complementary part of optimizing CDS alerts, can identify potential improvements to alert logic and support their implementation, and may even be able to assist experts in formulating their own suggestions for CDS improvement. ChatGPT shows great potential for using large language models and reinforcement learning from human feedback to improve CDS alert logic and potentially other medical areas involving complex, clinical logic, a key step in the development of an advanced learning health system.

Design and pilot implementation for the BETTER CARE-HF trial: A pragmatic cluster-randomized controlled trial comparing two targeted approaches to ambulatory clinical decision support for cardiologists

BACKGROUND

Beart failure with reduced ejection fraction (HFrEF) is a leading cause of morbidity and mortality. However, shortfalls in prescribing of proven therapies, particularly mineralocorticoid receptor antagonist (MRA) therapy, account for several thousand preventable deaths per year nationwide. Electronic clinical decision support (CDS) is a potential low-cost and scalable solution to improve prescribing of therapies. However, the optimal timing and format of CDS tools is unknown.

METHODS AND RESULTS

We developed two targeted CDS tools to inform cardiologists of gaps in MRA therapy for patients with HFrEF and without contraindication to MRA therapy: (1) an alert that notifies cardiologists at the time of patient visit, and (2) an automated electronic message that allows for review between visits. We designed these tools using an established CDS framework and findings from semistructured interviews with cardiologists. We then pilot tested both CDS tools (n = 596 patients) and further enhanced them based on additional semistructured interviews (n = 11 cardiologists). The message was modified to reduce the number of patients listed, include future visits, and list date of next visit. The alert was modified to improve noticeability, reduce extraneous information on guidelines, and include key information on contraindications.

CONCLUSIONS

The BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce CArdiovascular REcommendations for Heart Failure) trial aims to compare the effectiveness of the alert vs. the automated message vs. usual care on the primary outcome of MRA prescribing. To our knowledge, no study has directly compared the efficacy of these two different types of electronic CDS interventions. If effective, our findings can be rapidly disseminated to improve morbidity and mortality for patients with HFrEF, and can also inform the development of future CDS interventions for other disease states. (Trial registration: Clinicaltrials.gov NCT05275920).

From big data to better patient outcomes

Among medical specialties, laboratory medicine is the largest producer of structured data and must play a crucial role for the efficient and safe implementation of big data and artificial intelligence in healthcare. The area of personalized therapies and precision medicine has now arrived, with huge data sets not only used for experimental and research approaches, but also in the "real world". Analysis of real world data requires development of legal, procedural and technical infrastructure. The integration of all clinical data sets for any given patient is important and necessary in order to develop a patient-centered treatment approach. Data-driven research comes with its own challenges and solutions. The Findability, Accessibility, Interoperability, and Reusability (FAIR) Guiding Principles provide guidelines to make data findable, accessible, interoperable and reusable to the research community. Federated learning, standards and ontologies are useful to improve robustness of artificial intelligence algorithms working on big data and to increase trust in these algorithms. When dealing with big data, the univariate statistical approach changes to multivariate statistical methods significantly shifting the potential of big data. Combining multiple omics gives previously unsuspected information and provides understanding of scientific questions, an approach which is also called the systems biology approach. Big data and artificial intelligence also offer opportunities for laboratories and the In Vitro Diagnostic industry to optimize the productivity of the laboratory, the quality of laboratory results and ultimately patient outcomes, through tools such as predictive maintenance and "moving average" based on the aggregate of patient results.

Assessing the Value of ChatGPT for Clinical Decision Support Optimization

Objective

To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions.

Methods

We supplied summaries of CDS logic to ChatGPT, an artificial intelligence (AI) tool for question answering that uses a large language model, and asked it to generate suggestions. We asked human clinician reviewers to review the AI-generated suggestions as well as human-generated suggestions for improving the same CDS alerts, and rate the suggestions for their usefulness, acceptance, relevance, understanding, workflow, bias, inversion, and redundancy.

Results

Five clinicians analyzed 36 AI-generated suggestions and 29 human-generated suggestions for 7 alerts. Of the 20 suggestions that scored highest in the survey, 9 were generated by ChatGPT. The suggestions generated by AI were found to offer unique perspectives and were evaluated as highly understandable and relevant, with moderate usefulness, low acceptance, bias, inversion, redundancy.

Conclusion

AI-generated suggestions could be an important complementary part of optimizing CDS alerts, can identify potential improvements to alert logic and support their implementation, and may even be able to assist experts in formulating their own suggestions for CDS improvement. ChatGPT shows great potential for using large language models and reinforcement learning from human feedback to improve CDS alert logic and potentially other medical areas involving complex, clinical logic, a key step in the development of an advanced learning health system.

Real-World Observational Evaluation of Common Interventions to Reduce Emergency Department Prescribing of Opioid Medications

BACKGROUND

Prior work on opioid prescribing has examined dosing defaults, interruptive alerts, or "harder" stops such as electronic prescribing of controlled substances (EPCS), which has become increasingly required by state policy. Given that real-world opioid stewardship policies are concurrent and overlapping, the authors examined the effect of such policies on emergency department (ED) opioid prescriptions.

METHODS

The researchers performed observational analysis of all ED visits discharged between December 17, 2016, and December 31, 2019, across seven EDs of a hospital system. Four interventions were examined in chronological order, with each successive intervention added on top of all previous interventions: 12-pill prescription default, EPCS, electronic health record (EHR) pop-up alert, and 8-pill prescription default. The primary outcome was opioid prescribing, which was described as number of opioid prescriptions per 100 discharged ED visits and modeled as a binary outcome for each visit. Secondary outcomes included prescription morphine milligram equivalents (MME) and non-opioid analgesia prescriptions.

RESULTS

A total of 775,692 ED visits were included in the study. Compared to the preintervention period, cumulative reductions in opioid prescribing were seen with incremental interventions, including after adding a 12-pill default (odds ratio [OR] 0.88, 95% confidence interval [CI] 0.82-0.94), after adding EPCS (OR 0.7, 95% CI 0.63-0.77), after adding pop-up alerts (OR 0.67, 95% CI 0.63-0.71), and after adding an 8-pill default (OR 0.61, 95% CI 0.58-0.65).

CONCLUSION

EHR-implemented solutions such as EPCS, pop-up alerts, and pill defaults had varying but significant effects on reducing ED opioid prescribing. Policy makers and quality improvement leaders might achieve sustainable improvements in opioid stewardship while balancing clinician alert fatigue through policy efforts promoting implementation of EPCS and default dispense quantities.

Changes in Substance Use Treatment Providers' Delivery of the 5A's for Non-Cigarette Tobacco Use in the Context of a Comprehensive Tobacco-Free Workplace Program Implementation

Tobacco use treatment is not prioritized in substance use treatment centers (SUTCs), leading to tobacco-related health inequities for patients with substance use disorders (SUDs) and necessitating efforts to enhance providers' care provision. Training providers on how to treat tobacco use increases their intervention on patients' smoking, but limited work addresses its effects on their non-cigarette tobacco use intervention provision. This study redressed this gap using data from 15 unaffiliated SUTCs in Texas (serving 82,927 patients/year) participating in a tobacco-free workplace program (TFWP) that included provider education on treating tobacco use, including non-cigarette tobacco use. SUTC providers completed surveys before (n = 259) and after (n = 194) TFWP implementation. Past-month screening/intervention provision for non-cigarette tobacco use (the 5A's; ask, advise, assess, assist, arrange) and provider factors theoretically and practically presumed to underlie change [i.e., beliefs about concurrently treating tobacco use disorder (TUD) and other SUDs, self-efficacy for tobacco use assessment (TUA) delivery, barriers to treating tobacco dependence, receipt of tobacco intervention training] were assessed. Generalized linear or linear mixed models assessed changes over time from before to after TFWP implementation; low vs. high SUTC-level changes in provider factors were examined as moderators of changes in 5A's delivery. Results indicated significant improvement in each provider factor and increases in providers' asking, assisting, and arranging for non-cigarette tobacco use over time (ps < 0.04). Relative to their counterparts, SUTCs with high changes in providers' beliefs in favor of treating patients' tobacco use had greater odds of advising, assessing, assisting, and arranging patients, and SUTCs with greater barrier reductions had greater odds of advising and assisting patients. Results suggest that TFWPs can address training deficits and alter providers' beliefs about treating non-tobacco TUD during SUD care, improve their TUA delivery self-efficacy, and reduce intervention barriers, ultimately increasing intervention provision for patients' non-cigarette tobacco use. SUTCs with the greatest room for improvement in provider beliefs and barriers to care provision seem excellent candidates for TFWP implementation aimed at increasing non-cigarette tobacco use care delivery.

Workload and workflow implications associated with the use of electronic clinical decision support tools used by health professionals in general practice: a scoping review

BACKGROUND

Electronic clinical decision support tools (eCDS) are increasingly available to assist General Practitioners (GP) with the diagnosis and management of a range of health conditions. It is unclear whether the use of eCDS tools has an impact on GP workload. This scoping review aimed to identify the available evidence on the use of eCDS tools by health professionals in general practice in relation to their impact on workload and workflow.

METHODS

A scoping review was carried out using the Arksey and O'Malley methodological framework. The search strategy was developed iteratively, with three main aspects: general practice/primary care contexts, risk assessment/decision support tools, and workload-related factors. Three databases were searched in 2019, and updated in 2021, covering articles published since 2009: Medline (Ovid), HMIC (Ovid) and Web of Science (TR). Double screening was completed by two reviewers, and data extracted from included articles were analysed.

RESULTS

The search resulted in 5,594 references, leading to 95 full articles, referring to 87 studies, after screening. Of these, 36 studies were based in the USA, 21 in the UK and 11 in Australia. A further 18 originated from Canada or Europe, with the remaining studies conducted in New Zealand, South Africa and Malaysia. Studies examined the use of eCDS tools and reported some findings related to their impact on workload, including on consultation duration. Most studies were qualitative and exploratory in nature, reporting health professionals' subjective perceptions of consultation duration as opposed to objectively-measured time spent using tools or consultation durations. Other workload-related findings included impacts on cognitive workload, "workflow" and dialogue with patients, and clinicians' experience of "alert fatigue".

CONCLUSIONS

The published literature on the impact of eCDS tools in general practice showed that limited efforts have focused on investigating the impact of such tools on workload and workflow. To gain an understanding of this area, further research, including quantitative measurement of consultation durations, would be useful to inform the future design and implementation of eCDS tools.

Interruptive Electronic Alerts for Choosing Wisely Recommendations: A Cluster Randomized Controlled Trial

OBJECTIVE

To assess the efficacy of interruptive electronic alerts in improving adherence to the American Board of Internal Medicine's Choosing Wisely recommendations to reduce unnecessary laboratory testing.

MATERIALS AND METHODS

We administered 5 cluster randomized controlled trials simultaneously, using electronic medical record alerts regarding prostate-specific antigen (PSA) testing, acute sinusitis treatment, vitamin D testing, carotid artery ultrasound screening, and human papillomavirus testing. For each alert, we assigned 5 outpatient clinics to an interruptive alert and 5 were observed as a control. Primary and secondary outcomes were the number of postalert orders per 100 patients at each clinic and number of triggered alerts divided by orders, respectively. Post hoc analysis evaluated whether physicians experiencing interruptive alerts reduced their alert-triggering behaviors.

RESULTS

Median postalert orders per 100 patients did not differ significantly between treatment and control groups; absolute median differences ranging from 0.04 to 0.40 for PSA testing. Median alerts per 100 orders did not differ significantly between treatment and control groups; absolute median differences ranged from 0.004 to 0.03. In post hoc analysis, providers receiving alerts regarding PSA testing in men were significantly less likely to trigger additional PSA alerts than those in the control sites (Incidence Rate Ratio 0.12, 95% CI [0.03-0.52]).

DISCUSSION

Interruptive point-of-care alerts did not yield detectable changes in the overall rate of undesired orders or the order-to-alert ratio between active and silent sites. Complementary behavioral or educational interventions are likely needed to improve efforts to curb medical overuse.

CONCLUSION

Implementation of interruptive alerts at the time of ordering was not associated with improved adherence to 5 Choosing Wisely guidelines.

TRIAL REGISTRATION

NCT02709772.

Addressing Therapeutic Inertia: Development and Implementation of an Electronic Health Record-Based Diabetes Intensification Tool

Objective

To assess whether an electronic health record (EHR)-based diabetes intensification tool can improve the rate of A1C goal attainment among patients with type 2 diabetes and an A1C ≥8%.

Methods

An EHR-based tool was developed and sequentially implemented in a large, integrated health system using a four-phase, stepped-wedge design (single pilot site [phase 1] and then three practice site clusters [phases 2-4]; 3 months/phase), with full implementation during phase 4. A1C outcomes, tool usage, and treatment intensification metrics were compared retrospectively at implementation (IMP) sites versus nonimplementation (non-IMP) sites with sites matched on patient population characteristics using overlap propensity score weighting.

Results

Overall, tool utilization was low among patient encounters at IMP sites (1,122 of 11,549 [9.7%]). During phases 1-3, the proportions of patients achieving the A1C goal (<8%) were not significantly improved between IMP and non-IMP sites at 6 months (range 42.9-46.5%) or 12 months (range 46.5-53.1%). In phase 3, fewer patients at IMP sites versus non-IMP sites achieved the goal at 12 months (46.7 vs. 52.3%, P = 0.02). In phases 1-3, mean changes in A1C from baseline to 6 and 12 months (range -0.88 to -1.08%) were not significantly different between IMP and non-IMP sites. Times to intensification were similar between IMP and non-IMP sites.

Conclusion

Utilization of a diabetes intensification tool was low and did not influence rates of A1C goal attainment or time to treatment intensification. The low level of tool adoption is itself an important finding highlighting the problem of therapeutic inertia in clinical practice. Testing additional strategies to better incorporate, increase acceptance of, and improve proficiency with EHR-based intensification tools is warranted.

Current Venous Thromboembolism Chemoprophylaxis Practices After Surgery for Inflammatory Bowel Diseases

Recent events shed light on the high risk of venous thromboembolism (VTE) in patients with inflammatory bowel disease and the importance of prophylaxis in such patients. Protocols within the electronic medical record help improve compliance with VTE prophylaxis.

User centered clinical decision support to implement initiation of buprenorphine for opioid use disorder in the emergency department: EMBED pragmatic cluster randomized controlled trial

OBJECTIVE

To determine the effect of a user centered clinical decision support tool versus usual care on rates of initiation of buprenorphine in the routine emergency care of individuals with opioid use disorder.

DESIGN

Pragmatic cluster randomized controlled trial (EMBED).

SETTING

18 emergency department clusters across five healthcare systems in five states representing the north east, south east, and western regions of the US, ranging from community hospitals to tertiary care centers, using either the Epic or Cerner electronic health record platform.

PARTICIPANTS

599 attending emergency physicians caring for 5047 adult patients presenting with opioid use disorder.

INTERVENTION

A user centered, physician facing clinical decision support system seamlessly integrated into user workflows in the electronic health record to support initiating buprenorphine in the emergency department by helping clinicians to diagnose opioid use disorder, assess the severity of withdrawal, motivate patients to accept treatment, and complete electronic health record tasks by automating clinical and after visit documentation, order entry, prescribing, and referral.

MAIN OUTCOME MEASURES

Rate of initiation of buprenorphine (administration or prescription of buprenorphine) in the emergency department among patients with opioid use disorder. Secondary implementation outcomes were measured with the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework.

RESULTS

1 413 693 visits to the emergency department (775 873 in the intervention arm and 637 820 in the usual care arm) from November 2019 to May 2021 were assessed for eligibility, resulting in 5047 patients with opioid use disorder (2787 intervention arm, 2260 usual care arm) under the care of 599 attending physicians (340 intervention arm, 259 usual care arm) for analysis. Buprenorphine was initiated in 347 (12.5%) patients in the intervention arm and in 271 (12.0%) patients in the usual care arm (adjusted generalized estimating equations odds ratio 1.22, 95% confidence interval 0.61 to 2.43, P=0.58). Buprenorphine was initiated at least once by 151 (44.4%) physicians in the intervention arm and by 88 (34.0%) in the usual care arm (1.83, 1.16 to 2.89, P=0.01).

CONCLUSIONS

User centered clinical decision support did not increase patient level rates of initiating buprenorphine in the emergency department. Although streamlining and automating electronic health record workflows can potentially increase adoption of complex, unfamiliar evidence based practices, more interventions are needed to look at other barriers to the treatment of addiction and increase the rate of initiating buprenorphine in the emergency department in patients with opioid use disorder.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03658642.

Implementation effort: Reducing the ordering of inappropriate echocardiograms through a point-of-care decision support tool

Study objective

Reduce inappropriate transthoracic echocardiograms (TTEs) using a series of Plan-Do-Study-Act (PDSA) quality improvement cycles.

Design

Three PDSA cycles were designed with the first integrating a previously published decision support tool (DST) into the electronic TTE order, the second tailoring the DST to reflect the most common inappropriately ordered TTEs at our institution, and the third integrating direct clinician education.

Setting

Malcom Randall Veterans Administration Medical Center, Gainesville, Florida, USA.

Participants

Consecutive patients were studied using the database of all TTEs performed at our institution without regard for specific patient characteristics.

Interventions

Three PDSA Cycles as described above.

Main outcome measure

Reduction in inappropriate TTEs at our institution.

Results

After implementing our DST during the first cycle, no difference in inappropriate TTEs was observed (relative risk [RR] 0.71, p = 0.12, 95 % confidence interval [CI] 0.46-1.09). After the second cycle, we observed a reduction in the proportion of inappropriate TTEs (RR = 0.69, p = 0.014, 95 % CI 0.5-0.94), however two of the four inappropriate TTEs targeted by the DST increased. Feedback gathered from clinicians in the third cycle showed significant knowledge gaps regarding appropriate use criteria for TTE.

Conclusions

At our facility, implementation of a DST failed to substantially reduce inappropriate TTEs, even when adapted to facility-specific ordering patterns. Gaps in clinician knowledge about TTEs may have contributed to the inefficacy of our DST.

Assessing Suicide Risk in a Pediatric Outpatient Behavioral Health System: A Quality Improvement Report

Introduction

Standardized suicide risk assessment improves the detection of individuals at risk of suicide. We conducted a quality improvement initiative in a system of outpatient behavioral health practices affiliated with a free-standing children's hospital to implement standardized suicide risk assessment for new patients.

Methods

Clinicians received education in suicide risk assessment and were trained to use an evidence-based suicide risk assessment tool, the Columbia Suicide Severity Rating Scale (C-SSRS). We standardized workflow processes and integrated the C-SSRS in the electronic health record with a feature to communicate instances of elevated risk across care teams through a problem list. We analyzed C-SSRS responses and adherence to standardized processes and compared the percentage of patients with a suicide-related item on the problem list before and after implementation. We assessed clinician knowledge through a survey. All patients with identified suicide risk received treatment to reduce their risk of suicide in the context of usual care.

Results

For 3,972 new patient visits occurring postimplementation (November 2016-December 2018), the average monthly adherence to the standardized process was 97.7%. The mean monthly incidence of nonspecific active suicidal thoughts was 16%, aborted suicide attempts were 2%, and actual suicide attempts were 3%. The mean monthly incidence of a suicide-related item documented on the problem list was 5.66% in the postimplementation period compared with 1.47% in the 1-year preimplementation. Clinicians demonstrated statistically significant increases in knowledge about suicide risk factors and assessment.

Conclusions

Standardization of suicide risk assessment processes improved detection and documentation of suicide risk in a pediatric outpatient behavioral health setting.

A mixed-methods needs assessment to identify pharmacology education objectives for emergency medicine residents

Objectives

Medication errors represent a significant threat to patient safety. Pharmacotherapy is one of the 23 Accreditation Council of Graduate Medical Education milestones for emergency medicine, yet there is minimal understanding of what content should be prioritized during training. The study aim was to develop objectives for a patient-safety focused pharmacology curriculum for emergency medicine residents.

Methods

We incorporated data from a de-identified safety event database and survey responses of 30 faculty and clinical pharmacists at a single-site suburban university hospital with 24-hour emergency medicine pharmacists and an annual volume of approximately 70,000. We reviewed the database to quantify types and severity of medication errors over a 5-year period for a total of 370 errors. Anonymous surveys included categorical items that we analyzed with descriptive statistics and short answer questions that underwent thematic analysis by 2 coders. We summarized all data sources to identify curriculum gaps.

Results

Common medication errors reported in our database were wrong dose (43%) and computer order entry errors (14%). Knowledge gaps were medication cost (63%), pregnancy risk information (60%), antibiotic stewardship (53%), interactions (47%), and side effects (47%). Qualitative analysis revealed the need to optimize computer order entry, understand the scope of critical medications, use references, and consult pharmacists. Integration of data suggested specific medications should be covered in curricular efforts, including antibiotics, analgesics, sedatives, and insulin.

Conclusion

We developed objectives of pharmacology topics to prioritize during emergency medicine training to enhance prescribing safety. This study is limited due to its small sample and single institution source of data. Future studies should investigate the impact of pharmacology curriculum on minimizing clinical errors.

Alerts in Clinical Decision Support Systems (CDSS): A Bibliometric Review and Content Analysis

A clinical decision support system (CDSS) informs or generates medical recommendations for healthcare practitioners. An alert is the most common way for a CDSS to interact with practitioners. Research about alerts in CDSS has proliferated over the past ten years. The research trend is ongoing with new emerging terms and focus. Bibliometric analysis is ideal for researchers to understand the research trend and future directions. Influential articles, institutes, countries, authors, and commonly used keywords were analyzed to grasp a comprehensive view on our topic, alerts in CDSS. Articles published between 2011 and 2021 were extracted from the Web of Science database. There were 728 articles included for bibliometric analysis, among which 24 papers were selected for content analysis. Our analysis shows that the research direction has shifted from patient safety to system utility, implying the importance of alert usability to be clinically impactful. Finally, we conclude with future research directions such as the optimization of alert mechanisms and comprehensiveness to enhance alert appropriateness and to reduce alert fatigue.

Evaluation of an Electronic Medical Record Module for Nursing Documentation in Paediatric Palliative Care: Involvement of Nurses with a Think-Aloud Approach

BACKGROUND

Paediatric palliative care (PPC) is a noncurative approach to the care of children and adolescents with life-limiting and life-threatening illnesses. Electronic medical records (EMRs) play an important role in documenting such complex processes. Despite their benefits, they can introduce unintended consequences if future users are not involved in their development.

AIM

The aim of this study was to evaluate the acceptance of a novel module for nursing documentation by nurses working in the context of PPC.

METHODS

An observational study employing concurrent think-aloud and semi-structured qualitative interviews were conducted with 11 nurses working in PPC. Based on the main determinants of the unified theory of acceptance and use of technology (UTAUT), data were analysed using qualitative content analysis.

RESULTS

The main determinants of UTAUT were found to potentially influence acceptance of the novel module. Participants perceived the module to be self-explanatory and intuitive. Some adaptations, such as the reduction of fragmentation in the display, the optimization of confusing mouseover fields, and the use of familiar nursing terminology, are reasonable ways of increasing software adoption.

CONCLUSIONS

After adaptation of the modules based on the results, further evaluation with the participation of future users is required.

Non-Interruptive Clinical Decision Support to Improve Perioperative Electronic Positive Patient Identification

Positive patient identification (PPID) is an integral step to ensure the correct patient identity prior to a healthcare delivery event. Following implementation of a new EHR in November 2017, Vanderbilt University Medical Center (VUMC) experienced frequent and inconsistent failure of barcode scanners which impacted the electronic PPID (ePPID) and blood verification processes. Following multiple iterations of troubleshooting, vendor engagement, and device upgrades, we developed a clinical decision support (CDS) tool as a visual reminder to perform ePPID. If ePPID was initially bypassed, the clinician received a passive alert which remained visible throughout the procedure or until ePPID was completed successfully. We conducted a retrospective observational study using an interrupted time series analysis and analysis of variance pre- and post- CDS intervention. Following CDS intervention, we observed an immediate 20.8% increase in successful ePPID (p < 0.001). The mean success rate of ePPID attempts increased from 62.0% pre-intervention to 94.4% post-intervention (p < 0.001). There were 108 providers who had less than 80.0% success in the six-months prior to CDS intervention, of whom all improved to an average of 95.9% success. Our CDS approach highlights the utility of non-interruptive but continually visible alerts to improve patient safety workflows. By making errors clearly visible to users and their peers, performance improved to only 5.6% of alerts bypassed.

Participatory Design of a Medication Module in an Electronic Medical Record for Paediatric Palliative Care: A Think-Aloud Approach with Nurses and Physicians

BACKGROUND

Electronic medical records (EMRs) play a key role in improving documentation and quality of care in paediatric palliative care (PPC). Inadequate EMR design can cause incorrect prescription and administration of medications. Due to the fact of complex diseases and the resulting high level of medical complexity, patients in PPC are vulnerable to medication errors. Consequently, involving users in the development process is important. Therefore, the aim of this study was to evaluate the acceptance of a medication module from the perspective of potential users in PPC and to involve them in the development process.

METHODS

A qualitative observational study was conducted with 10 nurses and four physicians using a concurrent think-aloud protocol and semi-structured qualitative interviews. A qualitative content analysis was applied based on a unified theory of acceptance and use of technology.

RESULTS

Requirements from the user's perspective could be identified as possible influences on acceptance and actual use. Requirements were grouped into the categories "performance expectancies" and "effort expectancies".

CONCLUSIONS

The results serve as a basis for further development. Attention should be given to the reduction of display fragmentation, as it decreases cognitive load. Further approaches to evaluation should be taken.

Headache neuroimaging: A survey of current practice, barriers, and facilitators to optimal use

OBJECTIVE

The objective of this study was to understand current practice, clinician understanding, attitudes, barriers, and facilitators to optimal headache neuroimaging practices.

BACKGROUND

Headaches are common in adults, and neuroimaging for these patients is common, costly, and increasing. Although guidelines recommend against routine headache neuroimaging in low-risk scenarios, guideline-discordant neuroimaging is still frequently performed.

METHODS

We administered a 60-item survey to headache clinicians at the Veterans Affairs health system to assess clinician understanding and attitudes on headache neuroimaging and to determine neuroimaging practice patterns for three scenarios describing hypothetical patients with headaches. Descriptive statistics were used to summarize responses, stratified by clinician type (physicians or advanced practice clinicians [APCs]) and specialty (neurology or primary care).

RESULTS

The survey was successfully completed by 431 of 1426 clinicians (30.2% response rate). Overall, 317 of 429 (73.9%) believed neuroimaging was overused for patients with headaches. However, clinicians would utilize neuroimaging a mean (SD) 30.9% (31.7) of the time in a low-risk scenario without red flags, and a mean 67.1% (31.9) of the time in the presence of minor red flags. Clinicians had stronger beliefs in the potential benefits (268/429, 62.5%) of neuroimaging compared to harms (181/429, 42.2%) and more clinicians were bothered by harms stemming from the omission of neuroimaging (377/426, 88.5%) compared to commission (329/424, 77.6%). Additionally, APCs utilized neuroimaging more frequently than physicians and were more receptive to potential interventions to improve neuroimaging utilization.

CONCLUSIONS

Although a majority of clinicians believed neuroimaging was overused for patients with headaches, many would utilize neuroimaging in low-risk scenarios with a small probability of changing management. Future studies are needed to define the role of currently used red flags given their importance in neuroimaging decisions. Importantly, APCs may be an ideal target for future optimization efforts.

Translating Violence Prevention Programs from Research to Practice: SafERteens Implementation in an Urban Emergency Department

BACKGROUND

Youth violence is a leading cause of adolescent mortality, underscoring the need to integrate evidence-based violence prevention programs into routine emergency department (ED) care.

OBJECTIVES

To examine the translation of the SafERteens program into clinical care.

METHODS

Hospital staff provided input on implementation facilitators/barriers to inform toolkit development. Implementation was piloted in a four-arm effectiveness-implementation trial, with youth (ages 14-18 years) screening positive for past 3-month aggression randomized to either SafERteens (delivered remotely or in-person) or enhanced usual care (EUC; remote or in-person), with follow-up at post-test and 3 months. During maintenance, ED staff continued in-person SafERteens delivery and external facilitation was provided. Outcomes were measured using the RE-AIM implementation framework.

RESULTS

SafERteens completion rates were 77.6% (52/67) for remote and 49.1% (27/55) for in-person delivery. In addition to high acceptability ratings (e.g., helpfulness), post-test data demonstrated increased self-efficacy to avoid fighting among patients receiving remote (incidence rate ratio [IRR] 1.22, 95% confidence interval [CI] 1.09-1.36) and in-person (IRR 1.23, 95% CI 1.12-1.36) SafERteens, as well as decreased pro-violence attitudes among patients receiving remote (IRR 0.83, 95% CI 0.75-0.91) and in-person (IRR 0.87, 95% CI 0.77-0.99) SafERteens when compared with their respective EUC groups. At 3 months, youth receiving remote SafERteens reported less non-partner aggression (IRR 0.52, 95% CI 0.31-0.87, Cohen's d -0.39) and violence consequences (IRR 0.47, 95% CI 0.22-1.00, Cohen's d -0.49) compared with remote EUC; no differences were noted for in-person SafERteens delivery. Barriers to implementation maintenance included limited staff availability and a lack of reimbursement codes.

CONCLUSIONS

Implementing behavioral interventions such as SafERteens into routine ED care is feasible using remote delivery. Policymakers should consider reimbursement for violence prevention services to sustain long-term implementation.

Improving the Diagnosis of Menstrual Dysfunction through Quality Improvement

Introduction:

Prevalence of menstrual dysfunction (MD) in high school athletes ranges from 7% to 54%. Early recognition and intervention are crucial to prevent future consequences. The purpose of this Quality Improvement project was to optimize the institution’s Epic Best Practice Advisory (BPA) screening tool and synthesize new patient questionnaires to diagnose MD in athletes greater than 12 years of age presenting to a pediatric sports medicine clinic.

Methods:

Using Quality Improvement methodology, we evaluated clinic flow, the Epic BPA tool, and actions by the physician following the appropriate triggering of the BPA. Diagnoses targeted were primary amenorrhea, oligomenorrhea, or irregular menstruation unspecified. Areas for intervention were global staff education, patient education, and provider alert fatigue. Our team implemented interventions using monthly Plan-Do-Study-Act cycles to address our key drivers. Proper implementation of questionnaire data and restructuring of the Epic BPA promoted identification and diagnosis of MD. The clinician discussed the diagnosis with the patient and family and provided an educational handout on MD.

Results:

The rate of appropriate diagnosis of MD in athletes greater than 12 years of age seen at a pediatric sports medicine clinic increased from a baseline of 2.1% to 30% over ten months. Identification of three key drivers ultimately drove the success and achievement of our aim.

Conclusions:

Using Quality Improvement methodology, we optimized the EPIC BPA and subsequently increased the rate of appropriate diagnosis of MD. Identification of the proper diagnosis improves our patient education. Ultimately, this project provided the framework for applicable discussion, interventions, and work-up for at-risk athletes.

Clinical Decision Support for Laboratory Testing

BACKGROUND

As technology enables new and increasingly complex laboratory tests, test utilization presents a growing challenge for healthcare systems. Clinical decision support (CDS) refers to digital tools that present providers with clinically relevant information and recommendations, which have been shown to improve test utilization. Nevertheless, individual CDS applications often fail, and implementation remains challenging.

CONTENT

We review common classes of CDS tools grounded in examples from the literature as well as our own institutional experience. In addition, we present a practical framework and specific recommendations for effective CDS implementation.

SUMMARY

CDS encompasses a rich set of tools that have the potential to drive significant improvements in laboratory testing, especially with respect to test utilization. Deploying CDS effectively requires thoughtful design and careful maintenance, and structured processes focused on quality improvement and change management play an important role in achieving these goals.

Low Efficacy of Medication Shortage Clinical Decision Support Alerts

OBJECTIVE

 We examined clinical decision support (CDS) alerts designed specifically for medication shortages to characterize and assess provider behavior in response to these short-term clinical situations.

MATERIALS AND METHODS

 We conducted a retrospective analysis of the usage of medication shortage alerts (MSAs) that included at least one alternative medication suggestion and were active for 60 or more days during the 2-year study period, January 1, 2018 to December 31, 2019, in a large health care system. We characterized ordering provider behavior in response to inpatient MSAs. We then developed a linear regression model to predict provider response to alerts using the characteristics of the ordering provider and alert frequency groupings.

RESULTS

 During the study period, there were 67 MSAs in use that focused on 42 distinct medications in shortage. The MSAs suggested an average of 3.9 alternative medications. Adjusting for the different alerts, fellows (p = 0.004), residents (p = 0.03), and physician assistants (p = 0.02) were less likely to accept alerts on average compared with attending physicians. Further, female ordering clinicians (p < 0.001) were more likely to accept alerts on average compared with male ordering clinicians.

CONCLUSION

 Our findings demonstrate that providers tended to reject MSAs, even those who were sometimes flexible about their responses. The low overall acceptance rate supports the theory that alerts appearing at the time of order entry may have limited value, as they may be presented too late in the decision-making process. Though MSAs are designed to be attention-grabbing and higher impact than traditional CDS, our findings suggest that providers rarely change their clinical decisions when presented with these alerts.

Implementation of mandatory opioid prescribing limits in North Carolina: healthcare administrator and prescriber perspectives

BACKGROUND

Recent increases in state laws to reduce opioid prescribing have demonstrated a need to understand how they are interpreted and implemented in healthcare systems. The purpose of this study was to explore the systems, strategies, and resources that hospital administrators and prescribers used to implement the 2017 North Carolina Strengthen Opioid Prevention (STOP) Act opioid prescribing limits, which limited initial prescriptions to a five (for acute) or seven (for post-surgical) days' supply.

METHODS

We interviewed 14 hospital administrators and 38 prescribers with degrees in medicine, nursing, pharmacy, business administration and public health working across North Carolina. Interview guides, informed by the Consolidated Framework for Implementation Research, explored barriers and facilitators to implementation. Interview topics included communication, resources, and hospital system support. Interviews were recorded and transcribed, then analyzed using flexible coding, integrating inductive and deductive coding, to inform analytic code development and identify themes.

RESULTS

We identified three main themes around implementation of STOP act mandated prescribing limits: organizational communication, prescriber education, and changes in the electronic medical record (EMR) systems. Administrators reflected on implementation in the context of raising awareness and providing reminders to facilitate changes in prescriber behavior, operationalized through email and in-person communications as well as dedicated resources to EMR changes. Prescribers noted administrative communications about prescribing limits often focused on legality, suggesting a directive of the organization's policy rather than a passive reminder. Prescribers expressed a desire for more spaces to have their questions answered and resources for patient communications. While hospital administrators viewed compliance with the law as a priority, prescribers reflected on concerns for adequately managing their patients' pain and limited time for clinical care.

CONCLUSIONS

Hospital administrators and prescribers approached implementation of the STOP act prescribing limits with different mindsets. While administrators were focused on policy compliance, prescribers were focused on their patients' needs. Strategies to implement the mandate then had to balance patient needs with policy compliance. As states continue to legislate to prevent opioid overdose deaths, understanding how laws are implemented by healthcare systems and prescribers will improve their effectiveness through tailoring and maximizing available resources.

Utilizing health information technology in the treatment and management of patients during the COVID-19 pandemic: Lessons from international case study sites

Objective

To develop an in-depth understanding of how hospitals with a long history of health information technology (HIT) use have responded to the COVID-19 pandemic from a HIT perspective.

Materials and methods

We undertook interviews with 44 healthcare professionals with a background in informatics from six hospitals internationally. Interviews were informed by a topic guide and were conducted via videoconferencing software. Thematic analysis was employed to develop a coding framework and identify emerging themes.

Results

Three themes and six sub-themes were identified. HITs were employed to manage time and resources during a surge in patient numbers through fast-tracked governance procedures, and the creation of real-time bed capacity tracking within electronic health records. Improving the integration of different hospital systems was identified as important across sites. The use of hard-stop alerts and order sets were perceived as being effective at helping to respond to potential medication shortages and selecting available drug treatments. Utilizing information from multiple data sources to develop alerts facilitated treatment. Finally, the upscaling/optimization of telehealth and remote working capabilities was used to reduce the risk of nosocomial infection within hospitals.

Discussion

A number of the HIT-related changes implemented at these sites were perceived to have facilitated more effective patient treatment and management of resources. Informaticians generally felt more valued by hospital management as a result.

Conclusions

Improving integration between data systems, utilizing specialized alerts, and expanding telehealth represent strategies that hospitals should consider when using HIT for delivering hospital care in the context of the COVID-19 pandemic.

Aligning Patient Safety and Stewardship: A Harm Reduction Strategy for Children

Purpose of review

Review important patient safety and stewardship concepts and use clinical examples to describe how they align to improve patient outcomes and reduce harm for children.

Recent findings

Current evidence indicates that healthcare overuse is substantial. Unnecessary care leads to avoidable adverse events, anxiety and distress, and financial toxicity. Increases in antimicrobial resistance, venous thromboembolism, radiation exposure, and healthcare costs are examples of patient harm associated with a lack of stewardship. Studies indicate that many tools can increase standardization of care, improve resource utilization, and enhance safety culture to better align safety and stewardship.

Summary

The principles of stewardship and parsimonious care can improve patient safety for children.