Factors influencing in-hospital prescribing errors: A systematic review.

AIM: In-hospital prescribing errors (PEs) may result in patient harm, prolonged hospitalization and hospital (re)admission. These events are associated with pressure on healthcare services and significant healthcare costs. To develop targeted interventions to prevent or reduce in-hospital PEs, identification and understanding of facilitating and protective factors influencing in-hospital PEs in current daily practice is necessary, adopting a Safety-II perspective. The aim of this systematic review was to create an overview of all factors reported in the literature, both protective and facilitating, as influencing in-hospital PEs. METHODS: PubMed, EMBASE.com and the Cochrane Library (via Wiley) were searched, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement, for studies that identified factors influencing in-hospital PEs. Both qualitative and quantitative study designs were included. RESULTS: Overall, 19 articles (6 qualitative and 13 quantitative studies) were included and 40 unique factors influencing in-hospital PEs were identified. These factors were categorized into five domains according to the Eindhoven classification ('organization-related', 'prescriber-related', 'prescription-related', 'technology-related' and 'unclassified') and visualized in an Ishikawa (Fishbone) diagram. Most of the identified factors (87.5%; n = 40) facilitated in-hospital PEs. The most frequently identified facilitating factor (39.6%; n = 19) was 'insufficient (drug) knowledge, prescribing skills and/or experience of prescribers'. CONCLUSION: The findings of this review could be used to identify points of engagement for future intervention studies and help hospitals determine how to optimize prescribing. A multifaceted intervention, targeting multiple factors might help to circumvent the complex challenge of in-hospital PEs.

The impact of a sepsis performance improvement program in the emergency department: a before-after intervention study.

PURPOSE: The latest Surviving Sepsis Campaign guidelines advocate that all hospitals use sepsis performance improvement programs. However, there is a limited evidence about how to structure such programs and what their potential impact is on sepsis management and outcomes in the emergency department (ED). In this study, we evaluated the implementation of a sepsis performance improvement program in the ED including a dedicated sepsis response team and analyzed the management and outcomes of sepsis patients before and after. METHODS: We conducted a before-after interventional study in the ED of the Amsterdam University Medical Centers, the Netherlands. The sepsis performance improvement program included regular educational meetings, daily audits and weekly feedback, a screening tool, and a dedicated multidisciplinary sepsis response team. We studied all adult patients who presented to the ED with a suspected infection and a Modified Early Warning Score (MEWS) ≥ 3 during their stay. In the postintervention phase, these patients were seen by the sepsis team. Process-related and patient-related outcomes were measured between November 2019 and February 2020 (preintervention) and December 2021-May 2022 (postintervention). RESULTS: A total of 265 patients were included in the primary study, 132 patients preintervention and 133 patients postintervention. The postintervention phase was associated with improvements in nearly all process-related outcomes, such as a shorter time to antibiotics (66 vs. 143 min; p < 0.001), increased number of lactate measurements (72.9 vs. 46.2%; p < 0.001), and improved completeness of documented MEWS scores (85.0 vs. 62.9%; p < 0.001). Except for an improvement in the number of immediate versus delayed ICU admissions (100% immediate vs. 64.3% immediate; p = 0.012), there was no improvement in the other patient-related outcomes such as 28 days mortality (14.3 vs. 9.1%; p = 0.261), during the postintervention phase. CONCLUSION: Our program stimulated physicians to make timely decisions regarding diagnostics and treatment of sepsis in the ED. Implementing the sepsis performance improvement program was associated with significant improvements in most process-related outcomes but with minimal improvements in patient-related outcomes in our cohort.

Host Response Biomarkers for Sepsis in the Emergency Room.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

Leaving the hospital on time: hospital bed utilization and reasons for discharge delay in the Netherlands.

Inappropriate bed occupancy due to delayed hospital discharge affects both physical and psychological well-being in patients and can disrupt patient flow. The Dutch healthcare system is facing ongoing pressure, especially during the current coronavirus disease pandemic, intensifying the need for optimal use of hospital beds. The aim of this study was to quantify inappropriate patient stays and describe the underlying reasons for the delays in discharge. The Day of Care Survey (DoCS) is a validated tool used to gain information about appropriate and inappropriate bed occupancy in hospitals. Between February 2019 and January 2021, the DoCS was performed five times in three different hospitals within the region of Amsterdam, the Netherlands. All inpatients were screened, using standardized criteria, for their need for in-hospital care at the time of survey and reasons for discharge delay. A total of 782 inpatients were surveyed. Of these patients, 94 (12%) were planned for definite discharge that day. Of all other patients, 145 (21%, ranging from 14% to 35%) were without the need for acute in-hospital care. In 74% (107/145) of patients, the reason for discharge delay was due to issues outside the hospital; most frequently due to a shortage of available places in care homes (26%, 37/145). The most frequent reason for discharge delay inside the hospital was patients awaiting a decision or review by the treating physician (14%, 20/145). Patients who did not meet the criteria for hospital stay were, in general, older [median 75, interquartile range (IQR) 65-84 years, and 67, IQR 55-75 years, respectively, P < .001] and had spent more days in hospital (7, IQR 5-14 days, and 3, IQR 1-8 days respectively, P < .001). Approximately one in five admitted patients occupying hospital beds did not meet the criteria for acute in-hospital stay or care at the time of the survey. Most delays were related to issues outside the immediate control of the hospital. Improvement programmes working with stakeholders focusing on the transfer from hospital to outside areas of care need to be further developed and may offer potential for the greatest gain. The DoCS can be a tool to periodically monitor changes and improvements in patient flow.

Antibody responses against SARS-CoV-2 variants induced by four different SARS-CoV-2 vaccines in health care workers in the Netherlands: A prospective cohort study.

BACKGROUND: Emerging and future SARS-CoV-2 variants may jeopardize the effectiveness of vaccination campaigns. Therefore, it is important to know how the different vaccines perform against diverse SARS-CoV-2 variants. METHODS AND FINDINGS: In a prospective cohort of 165 SARS-CoV-2 naive health care workers in the Netherlands, vaccinated with either one of four vaccines (BNT162b2, mRNA-1273, AZD1222 or Ad26.COV2.S), we performed a head-to-head comparison of the ability of sera to recognize and neutralize SARS-CoV-2 variants of concern (VOCs; Alpha, Beta, Gamma, Delta and Omicron). Repeated serum sampling was performed 5 times during a year (from January 2021 till January 2022), including before and after booster vaccination with BNT162b2. Four weeks after completing the initial vaccination series, SARS-CoV-2 wild-type neutralizing antibody titers were highest in recipients of mRNA-1273, followed by recipients of BNT162b2 (geometric mean titers (GMT) of 358 [95% CI 231-556] and 214 [95% CI 153-299], respectively; p<0.05), and substantially lower in those vaccinated with the adenovirus vector-based vaccines AZD1222 and Ad26.COV2.S (GMT of 18 [95% CI 11-30] and 14 [95% CI 8-25] IU/ml, respectively; p<0.001). VOCs neutralization was reduced in all vaccine groups, with the greatest reduction in neutralization GMT observed against the Omicron variant (fold change 0.03 [95% CI 0.02-0.04], p<0.001). The booster BNT162b2 vaccination increased neutralizing antibody titers for all groups with substantial improvement against the VOCs including the Omicron variant. We used linear regression and linear mixed model analysis. All results were adjusted for possible confounding of age and sex. Study limitations include the lack of cellular immunity data. CONCLUSIONS: Overall, this study shows that the mRNA vaccines appear superior to adenovirus vector-based vaccines in inducing neutralizing antibodies against VOCs four weeks after initial vaccination and after booster vaccination, which implies the use of mRNA vaccines for both initial and booster vaccination.

Sepsis Performance Improvement Programs: From Evidence Toward Clinical Implementation.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2022. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2022 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

Comparing complaint-based triage scales and early warning scores for emergency department triage.

BACKGROUND: Emergency triage systems are used globally to prioritise care based on patients' needs. These systems are commonly based on patient complaints, while the need for timely interventions on regular hospital wards is usually assessed with early warning scores (EWS). We aim to directly compare the ability of currently used triage scales and EWS scores to recognise patients in need of urgent care in the ED. METHODS: We performed a retrospective, single-centre study on all patients who presented to the ED of a Dutch Level 1 trauma centre, between 1 September 2018 and 24 June 2020 and for whom a Netherlands Triage System (NTS) score as well as a Modified Early Warning Score (MEWS) was recorded. The performance of these scores was assessed using surrogate markers for true urgency and presented using bar charts, cross tables and a paired area under the curve (AUC). RESULTS: We identified 12 317 unique patient visits where NTS and MEWS scores were documented during triage. A paired comparison of the AUC of these scores showed that the MEWS score had a significantly better AUC than the NTS for predicting the need for hospital admission (0.65 vs 0.60; p<0.001) or 30-day all-cause mortality (0.70 vs 0.60; p<0.001). Furthermore, when non-urgent MEWS scores co-occur with urgent NTS scores, the MEWS score seems to more accurately capture the urgency level that is warranted. CONCLUSIONS: The results of this study suggest that EWSs could potentially be used to replace the current emergency triage systems.

Early warning scores to assess the probability of critical illness in patients with COVID-19.

OBJECTIVE: Validated clinical risk scores are needed to identify patients with COVID-19 at risk of severe disease and to guide triage decision-making during the COVID-19 pandemic. The objective of the current study was to evaluate the performance of early warning scores (EWS) in the ED when identifying patients with COVID-19 who will require intensive care unit (ICU) admission for high-flow-oxygen usage or mechanical ventilation. METHODS: Patients with a proven SARS-CoV-2 infection with complete resuscitate orders treated in nine hospitals between 27 February and 30 July 2020 needing hospital admission were included. Primary outcome was the performance of EWS in identifying patients needing ICU admission within 24 hours after ED presentation. RESULTS: In total, 1501 patients were included. Median age was 71 (range 19-99) years and 60.3% were male. Of all patients, 86.9% were admitted to the general ward and 13.1% to the ICU within 24 hours after ED admission. ICU patients had lower peripheral oxygen saturation (86.7% vs 93.7, p≤0.001) and had a higher body mass index (29.2 vs 27.9 p=0.043) compared with non-ICU patients. National Early Warning Score 2 (NEWS2) ≥ 6 and q-COVID Score were superior to all other studied clinical risk scores in predicting ICU admission with a fair area under the receiver operating characteristics curve of 0.740 (95% CI 0.696 to 0.783) and 0.760 (95% CI 0.712 to 0.800), respectively. NEWS2 ≥6 and q-COVID Score ≥3 discriminated patients admitted to the ICU with a sensitivity of 78.1% and 75.9%, and specificity of 56.3% and 61.8%, respectively. CONCLUSION: In this multicentre study, the best performing models to predict ICU admittance were the NEWS2 and the Quick COVID-19 Severity Index Score, with fair diagnostic performance. However, due to the moderate performance, these models cannot be clinically used to adequately predict the need for ICU admission within 24 hours in patients with SARS-CoV-2 infection presenting at the ED.

Outcome of Immediate Versus Early Antibiotics in Severe Sepsis and Septic Shock: A Systematic Review and Meta-analysis.

STUDY OBJECTIVE: Debate exists about the mortality benefit of administering antibiotics within either 1 or 3 hours of sepsis onset. We performed this meta-analysis to analyze the effect of immediate (0 to 1 hour after onset) versus early (1 to 3 hours after onset) antibiotics on mortality in patients with severe sepsis or septic shock. METHODS: This review was consistent with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Searched databases included PubMed, EMBASE, Web of Science, and Cochrane Library, as well as gray literature. Included studies were conducted with consecutive adults with severe sepsis or septic shock who received antibiotics within each period and provided mortality data. Data were extracted by 2 independent reviewers and pooled with random effects. Two authors independently assessed quality of evidence across all studies with Cochrane's Grading of Recommendations Assessment, Development and Evaluation methodology and risk of bias within each study, using the Newcastle-Ottawa Scale. RESULTS: Thirteen studies were included: 5 prospective longitudinal and 8 retrospective cohort ones. Three studies (23%) had a high risk of bias (Newcastle-Ottawa Scale). Overall, quality of evidence across all studies (Grading of Recommendations Assessment, Development and Evaluation) was low. Pooling of data (33,863 subjects) showed no difference in mortality between patients receiving antibiotics in immediate versus early periods (odds ratio 1.09; 95% confidence interval 0.98 to 1.21). Analysis of severe sepsis studies (8,595 subjects) found higher mortality in immediate versus early periods (odds ratio 1.29; 95% confidence interval 1.09 to 1.53). CONCLUSION: We found no difference in mortality between immediate and early antibiotics across all patients. Although the quality of evidence across studies was low, these findings do not support a mortality benefit for immediate compared with early antibiotics across all patients with sepsis.

Impact of Blood Culture Contamination on Antibiotic Use, Resource Utilization, and Clinical Outcomes: A Retrospective Cohort Study in Dutch and US Hospitals.

Background: Blood culture contamination (BCC) has been associated with prolonged antibiotic use (AU) and increased health care utilization; however, this has not been widely reevaluated in the era of increased attention to antibiotic stewardship. We evaluated the impact of BCC on AU, resource utilization, and length of stay in Dutch and US patients. Methods: This retrospective observational study examined adults admitted to 2 hospitals in the Netherlands and 5 hospitals in the United States undergoing ≥2 blood culture (BC) sets. Exclusion criteria included neutropenia, no hospital admission, or death within 48 hours of hospitalization. The impact of BCC on clinical outcomes-overall inpatient days of antibiotic therapy, test utilization, length of stay, and mortality-was determined via a multivariable regression model. Results: An overall 22 927 patient admissions were evaluated: 650 (4.1%) and 339 (4.8%) with BCC and 11 437 (71.8%) and 4648 (66.3%) with negative BC results from the Netherlands and the United States, respectively. Dutch and US patients with BCC had a mean ± SE 1.74 ± 0.27 (P < .001) and 1.58 ± 0.45 (P < .001) more days of antibiotic therapy than patients with negative BC results. They also had 0.6 ± 0.1 (P < .001) more BCs drawn. Dutch but not US patients with BCC had longer hospital stays (3.36 days; P < .001). There was no difference in mortality between groups in either cohort. AU remained higher in US but not Dutch patients with BCC in a subanalysis limited to BC obtained within the first 24 hours of admission. Conclusions: BCC remains associated with higher inpatient AU and health care utilization as compared with patients with negative BC results, although the impact on these outcomes differs by country.

Appropriate use of blood cultures in the emergency department through machine learning (ABC): study protocol for a randomised controlled non-inferiority trial.

INTRODUCTION: The liberal use of blood cultures in emergency departments (EDs) leads to low yields and high numbers of false-positive results. False-positive, contaminated cultures are associated with prolonged hospital stays, increased antibiotic usage and even higher hospital mortality rates. This trial aims to investigate whether a recently developed and validated machine learning model for predicting blood culture outcomes can safely and effectively guide clinicians in withholding unnecessary blood culture analysis. METHODS AND ANALYSIS: A randomised controlled, non-inferiority trial comparing current practice with a machine learning-guided approach. The primary objective is to determine whether the machine learning based approach is non-inferior to standard practice based on 30-day mortality. Secondary outcomes include hospital length-of stay and hospital admission rates. Other outcomes include model performance and antibiotic usage. Participants will be recruited in the EDs of multiple hospitals in the Netherlands. A total of 7584 participants will be included. ETHICS AND DISSEMINATION: Possible participants will receive verbal information and a paper information brochure regarding the trial. They will be given at least 1 hour consideration time before providing informed consent. Research results will be published in peer-reviewed journals. This study has been approved by the Amsterdam University Medical Centers' local medical ethics review committee (No 22.0567). The study will be conducted in concordance with the principles of the Declaration of Helsinki and in accordance with the Medical Research Involving Human Subjects Act, General Data Privacy Regulation and Medical Device Regulation. TRIAL REGISTRATION NUMBER: NCT06163781.

[Can artificial intelligence write a medical-scientific article of sufficient quality?] / Kan AI eenNTvG-artikel schrijven?

In this article, we describe the process - from the first draft, through peer revision to a final manuscript - of writing a scientific article only using AI. We discuss the problems and questions that arise and make recommendations for how text-generative AI may be used in the medical-scientific world.

Detecting changes in the performance of a clinical machine learning tool over time.

BACKGROUND: Excessive use of blood cultures (BCs) in Emergency Departments (EDs) results in low yields and high contamination rates, associated with increased antibiotic use and unnecessary diagnostics. Our team previously developed and validated a machine learning model to predict BC outcomes and enhance diagnostic stewardship. While the model showed promising initial results, concerns over performance drift due to evolving patient demographics, clinical practices, and outcome rates warrant continual monitoring and evaluation of such models. METHODS: A real-time evaluation of the model's performance was conducted between October 2021 and September 2022. The model was integrated into Amsterdam UMC's Electronic Health Record system, predicting BC outcomes for all adult patients with BC draws in real time. The model's performance was assessed monthly using metrics including the Area Under the Curve (AUC), Area Under the Precision-Recall Curve (AUPRC), and Brier scores. Statistical Process Control (SPC) charts were used to monitor variation over time. FINDINGS: Across 3.035 unique adult patient visits, the model achieved an average AUC of 0.78, AUPRC of 0.41, and a Brier score of 0.10 for predicting the outcome of BCs drawn in the ED. While specific population characteristics changed over time, no statistical points outside the statistical control range were detected in the AUC, AUPRC, and Brier scores, indicating stable model performance. The average BC positivity rate during the study period was 13.4%. INTERPRETATION: Despite significant changes in clinical practice, our BC stewardship tool exhibited stable performance, suggesting its robustness to changing environments. Using SPC charts for various metrics enables simple and effective monitoring of potential performance drift. The assessment of the variation of outcome rates and population changes may guide the specific interventions, such as intercept correction or recalibration, that may be needed to maintain a stable model performance over time. This study suggested no need to recalibrate or correct our BC stewardship tool. FUNDING: No funding to disclose.