Intelligent checklists improve checklist compliance in the intensive care unit: a prospective before-and-after mixed-method study

Assessing the impact of real-time random safety audits through full propensity score matching on reliable data from the clinical information system

BACKGROUND

Evidence-based care processes are not always applied at the bedside in critically ill patients. Numerous studies have assessed the impact of checklists and related strategies on the process of care and patient outcomes. We aimed to evaluate the effects of real-time random safety audits on process-of-care and outcome variables in critical care patients.

METHODS

This prospective study used data from the clinical information system to evaluate the impact of real-time random safety audits targeting 32 safety measures in two intensive care units during a 9-month period. We compared endpoints between patients attended with safety audits and those not attended with safety audits. The primary endpoint was mortality, measured by Cox hazard regression after full propensity-score matching. Secondary endpoints were the impact on adherence to process-of-care measures and on quality indicators.

RESULTS

We included 871 patients; 228 of these were attended in ≥ 1 real-time random safety audits. Safety audits were carried out on 390 patient-days; most improvements in the process of care were observed in safety measures related to mechanical ventilation, renal function and therapies, nutrition, and clinical information system. Although the group of patients attended in safety audits had more severe disease at ICU admission [APACHE II score 21 (16-27) vs. 20 (15-25), p = 0.023]; included a higher proportion of surgical patients [37.3 % vs. 26.4 %, p = 0.003] and a higher proportion of mechanically ventilated patients [72.8 % vs. 40.3 %, p < 0.001]; averaged more days on mechanical ventilation, central venous catheter, and urinary catheter; and had a longer ICU stay [12.5 (5.5-23.3) vs. 2.9 (1.7-5.9), p < 0.001], ICU mortality did not differ significantly between groups (19.3 % vs. 18.8 % in the group without safety rounds). After full propensity-score matching, Cox hazard regression analysis showed real-time random safety audits were associated with a lower risk of mortality throughout the ICU stay (HR 0.31; 95 %CI 0.20-0.47).

CONCLUSIONS

Real-time random safety audits are associated with a reduction in the risk of ICU mortality. Exploiting data from the clinical information system is useful in assessing the impact of them on the care process, quality indicators, and mortality.

Risk Management and Patient Safety in the Artificial Intelligence Era: A Systematic Review

BACKGROUND

Healthcare systems represent complex organizations within which multiple factors (physical environment, human factor, technological devices, quality of care) interconnect to form a dense network whose imbalance is potentially able to compromise patient safety. In this scenario, the need for hospitals to expand reactive and proactive clinical risk management programs is easily understood, and artificial intelligence fits well in this context. This systematic review aims to investigate the state of the art regarding the impact of AI on clinical risk management processes. To simplify the analysis of the review outcomes and to motivate future standardized comparisons with any subsequent studies, the findings of the present review will be grouped according to the possibility of applying AI in the prevention of the different incident type groups as defined by the ICPS.

MATERIALS AND METHODS

On 3 November 2023, a systematic review of the literature according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was carried out using the SCOPUS and Medline (via PubMed) databases. A total of 297 articles were identified. After the selection process, 36 articles were included in the present systematic review.

RESULTS AND DISCUSSION

The studies included in this review allowed for the identification of three main "incident type" domains: clinical process, healthcare-associated infection, and medication. Another relevant application of AI in clinical risk management concerns the topic of incident reporting.

CONCLUSIONS

This review highlighted that AI can be applied transversely in various clinical contexts to enhance patient safety and facilitate the identification of errors. It appears to be a promising tool to improve clinical risk management, although its use requires human supervision and cannot completely replace human skills. To facilitate the analysis of the present review outcome and to enable comparison with future systematic reviews, it was deemed useful to refer to a pre-existing taxonomy for the identification of adverse events. However, the results of the present study highlighted the usefulness of AI not only for risk prevention in clinical practice, but also in improving the use of an essential risk identification tool, which is incident reporting. For this reason, the taxonomy of the areas of application of AI to clinical risk processes should include an additional class relating to risk identification and analysis tools. For this purpose, it was considered convenient to use ICPS classification.

The use of checklists in the intensive care unit: a scoping review

BACKGROUND

Despite the extensive volume of research published on checklists in the intensive care unit (ICU), no review has been published on the broader role of checklists within the intensive care unit, their implementation and validation, and the recommended clinical context for their use. Accordingly, a scoping review was necessary to map the current literature and to guide future research on intensive care checklists. This review focuses on what checklists are currently used, how they are used, process of checklist development and implementation, and outcomes associated with checklist use.

METHODS

A systematic search of MEDLINE (Ovid), Embase, Scopus, and Google Scholar databases was conducted, followed by a grey literature search. The abstracts of the identified studies were screened. Full texts of relevant articles were reviewed, and the references of included studies were subsequently screened for additional relevant articles. Details of the study characteristics, study design, checklist intervention, and outcomes were extracted.

RESULTS

Our search yielded 2046 studies, of which 167 were selected for further analysis. Checklists identified in these studies were categorised into the following types: rounding checklists; delirium screening checklists; transfer and handover checklists; central line-associated bloodstream infection (CLABSI) prevention checklists; airway management checklists; and other. Of 72 significant clinical outcomes reported, 65 were positive, five were negative, and two were mixed. Of 122 significant process of care outcomes reported, 114 were positive and eight were negative.

CONCLUSIONS

Checklists are commonly used in the intensive care unit and appear in many clinical guidelines. Delirium screening checklists and rounding checklists are well implemented and validated in the literature. Clinical and process of care outcomes associated with checklist use are predominantly positive. Future research on checklists in the intensive care unit should focus on establishing clinical guidelines for checklist types and processes for ongoing modification and improvements using post-intervention data.

Combining text mining with clinical decision support in clinical practice: a scoping review

OBJECTIVE

Combining text mining (TM) and clinical decision support (CDS) could improve diagnostic and therapeutic processes in clinical practice. This review summarizes current knowledge of the TM-CDS combination in clinical practice, including their intended purpose, implementation in clinical practice, and barriers to such implementation.

MATERIALS AND METHODS

A search was conducted in PubMed, EMBASE, and Cochrane Library databases to identify full-text English language studies published before January 2022 with TM-CDS combination in clinical practice.

RESULTS

Of 714 identified and screened unique publications, 39 were included. The majority of the included studies are related to diagnosis (n = 26) or prognosis (n = 11) and used a method that was developed for a specific clinical domain, document type, or application. Most of the studies selected text containing parts of the electronic health record (EHR), such as reports (41%, n = 16) and free-text narratives (36%, n = 14), and 23 studies utilized a tool that had software "developed for the study". In 15 studies, the software source was openly available. In 79% of studies, the tool was not implemented in clinical practice. Barriers to implement these tools included the complexity of natural language, EHR incompleteness, validation and performance of the tool, lack of input from an expert team, and the adoption rate among professionals.

DISCUSSION/CONCLUSIONS

The available evidence indicates that the TM-CDS combination may improve diagnostic and therapeutic processes, contributing to increased patient safety. However, further research is needed to identify barriers to implementation and the impact of such tools in clinical practice.

Quality Improvement in the Preoperative Evaluation: Accuracy of an Automated Clinical Decision Support System to Calculate CHA2DS2-VASc Scores

Background and Objectives: Clinical decision support systems are advocated to improve the quality and efficiency in healthcare. However, before implementation, validation of these systems needs to be performed. In this evaluation we tested our hypothesis that a computerized clinical decision support system can calculate the CHA₂DS₂-VASc score just as well compared to manual calculation, or even better and more efficiently than manual calculation in patients with atrial rhythm disturbances. Materials and Methods: In n = 224 patents, we calculated the total CHA₂DS₂-VASc score manually and by an automated clinical decision support system. We compared the automated clinical decision support system with manually calculation by physicians. Results: The interclass correlation between the automated clinical decision support system and manual calculation showed was 0.859 (0.611 and 0.931 95%-CI). Bland-Altman plot and linear regression analysis shows us a bias of −0.79 with limit of agreement (95%-CI) between 1.37 and −2.95 of the mean between our 2 measurements. The Cohen’s kappa was 0.42. Retrospective analysis showed more human errors than algorithmic errors. Time it took to calculate the CHA₂DS₂-VASc score was 11 s per patient in the automated clinical decision support system compared to 48 s per patient with the physician. Conclusions: Our automated clinical decision support system is at least as good as manual calculation, may be more accurate and is more time efficient.

Informing the standardising of care for prolonged stay patients in the ICU: A scoping review of quality improvement tools

OBJECTIVES

To inform design of quality improvement (QI) tools specific to patients with prolonged intensive care unit (ICU) stay, we determined characteristics (format/content), development, implementation, and outcomes of published multi-component QI tools used in ICU irrespective of length of stay.

RESEARCH METHODOLOGY

Scoping review searching electronic databases, trial registries and grey literature (January 2000 to January 2022).

RESULTS

We screened 58,378 citations, identifying 96 studies. All tools were designed for use commencing at ICU admission except 3 tools implemented at 3, 5 or 14 days. We identified 32 studies of locally developed checklists, 28 goal setting/structured communication templates, 23 care bundles, and 9 studies of mixed format tools. Most (43 %) tools were designed for use during rounds, fewer tools were designed for use throughout the ICU day (27 %) or stay (9 %). Most studies (55 %) reported process objectives i.e., improving communication, care standardisation, or rounding efficiency. Most common clinical processes QI tools were used to standardise were sedation (62, 65 %), ventilation and weaning (55, 57 %), and analgesia management (58, 60 %). 44 studies reported the effect of the tool on patient outcomes. Of these, only two identified a negative effect - increased ICU length of stay and increased ICU days with pain and delirium.

CONCLUSION

Although we identified numerous QI tools for use in ICU settings, few were designed to specifically address actionable processes of care relevant to the unique needs of prolonged ICU stay patients. Tools that address these needs are urgently required.

SYSTEMATIC REVIEW REGISTRATION

The review protocol is registered on the Open Science Framework, https://osf.io/, DOI 10.17605/OSF.IO/Z8MRE.

How to proceed after "negative" exome: A review on genetic diagnostics, limitations, challenges, and emerging new multiomics techniques

Exome sequencing (ES) in the clinical setting of inborn metabolic diseases (IMDs) has created tremendous improvement in achieving an accurate and timely molecular diagnosis for a greater number of patients, but it still leaves the majority of patients without a diagnosis. In parallel, (personalized) treatment strategies are increasingly available, but this requires the availability of a molecular diagnosis. IMDs comprise an expanding field with the ongoing identification of novel disease genes and the recognition of multiple inheritance patterns, mosaicism, variable penetrance, and expressivity for known disease genes. The analysis of trio ES is preferred over singleton ES as information on the allelic origin (paternal, maternal, "de novo") reduces the number of variants that require interpretation. All ES data and interpretation strategies should be exploited including CNV and mitochondrial DNA analysis. The constant advancements in available techniques and knowledge necessitate the close exchange of clinicians and molecular geneticists about genotypes and phenotypes, as well as knowledge of the challenges and pitfalls of ES to initiate proper further diagnostic steps. Functional analyses (transcriptomics, proteomics, and metabolomics) can be applied to characterize and validate the impact of identified variants, or to guide the genomic search for a diagnosis in unsolved cases. Future diagnostic techniques (genome sequencing [GS], optical genome mapping, long-read sequencing, and epigenetic profiling) will further enhance the diagnostic yield. We provide an overview of the challenges and limitations inherent to ES followed by an outline of solutions and a clinical checklist, focused on establishing a diagnosis to eventually achieve (personalized) treatment.

Impact of a Digital Cognitive Aid on the Performance of Military Healthcare Teams During Critical Care Management in a Warfront Injury Situation: A Simulation Randomized Controlled Study

INTRODUCTION

Initial healthcare delivery after warfront injury is unpredictably challenging for military forces. As preparatory training, healthcare providers use simulation to improve their performance in stressful critical situations. This study investigated whether a digital CA held by the team leader improved performance in simulated combat casualty care.

METHODS

This randomized controlled trial was performed during a combat casualty training course for military physicians and nurses in France. Each pair of care providers completed 2 scenarios randomized to be undertaken either with or without a digital CA. The primary end point was the technical performance evaluated from a video recording by 2 independent raters using a pre-established score grid (up to 100%) according to military protocols. The secondary end point was the nontechnical performance (TEAM scale, maximum: 54 points).

RESULTS

Thirty-six pairs of participants were included. Use of the digital CA improved both technical (74% vs 53%, P < 0.001) and nontechnical (42 vs 32, P < 0.001) performance.

CONCLUSIONS

The digital CA improved technical and nontechnical performance during training of medical care for military combat casualties. Use of a dedicated digital CA might improve care in a combat environment.

STUDY TYPE

This study is a randomized controlled trial.

Need for a new paradigm in the design of alarms for patient monitors and medical devices

Modern computerised medical devices emit large numbers of tone-based alerts and alarms. Notifications that comprise auditory icons or natural human speech substantially increase the psychological salience of alerts and alarms and may allow a larger set of notifications to be used, as they do not require memorisation of arbitrary sounds.