Increasing compliance with low tidal volume ventilation in the ICU with two nudge-based interventions: evaluation through intervention time-series analyses

A multi-nudge-based behavioural insight into ward nurses' respiratory rate measurement: An observational study

AIM

This study observed changes in respiratory rate measurement (RRM) and identified barriers and challenges in clinical practice that influence healthcare worker behaviour, aiming to improve RRM in a hospital setting.

DESIGN

An observational study was conducted.

METHODS

We observed and analysed changes in the behaviour of healthcare workers at a hospital where multi-nudges were introduced to improve RRM.

RESULTS

We checked respiration rate using electronic data and discovered that the original measurement rates were low. Measurement rates rapidly increased after posters were added. Barriers such as time constraints and measurement equipment were also noted.

CONCLUSION

RRM was found to be effective in promoting behavioural economics in medical settings. The results show that incorporating behavioural science principles into medical interventions has the potential to positively change behaviour.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

By increasing nurses' awareness of respiratory rate measurement and addressing barriers to it, the measurement rate of respiratory rate can also increase, leading to more accurate patient evaluations and triage.

IMPACT

WHAT PROBLEM DID THE STUDY ADDRESS?: The proportion of respiratory rate measurements leading to rapid response system (RRS) calls was low. WHAT WERE THE MAIN FINDINGS?: The study observed that a multi-nudge approach effectively changes the behaviour of ward nurses, resulting in enhanced quality of medical care. WHERE AND ON WHOM WILL THE RESEARCH HAVE AN IMPACT?: This research can serve as a valuable reference for leaders promoting healthcare quality projects, by offering a method to encourage behavioural change.

REPORTING METHOD

This study complied with the EQUATOR guidelines and its reporting adheres to the STROBE checklist.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

Using a clinical decision support system to reduce excess driving pressure: the ALARM trial

BACKGROUND

Patients at need for ventilation often are at risk of acute respiratory distress syndrome (ARDS). Although lung-protective ventilation strategies, including low driving pressure settings, are well known to improve outcomes, clinical practice often diverges from these strategies. A clinical decision support (CDS) system can improve adherence to current guidelines; moreover, the potential of a CDS to enhance adherence can possibly be further increased by combination with a nudge type intervention.

METHODS

A prospective cohort trial was conducted in patients at risk of ARDS admitted to an intensive care unit (ICU). Patients were assigned to control or intervention by their date of admission: First, the control group was included without changing anything in clinical practice. Next, the CDS was activated showing an alert in the patient data management system if driving pressure exceeded recommended values; additionally, data on the performance of the wards were sent to the healthcare professionals as the nudge intervention. The main hypothesis was that this combined intervention would lead to a significant decrease in excess driving pressure.

RESULTS

The 472 included patients (230 in the control group and 242 in the intervention group) consisted of 33% females. The median age was 64 years; median Sequential Organ Failure Assessment score was 8. There was a significant reduction in excess driving pressure in the augmented ventilation modes (0.28 ± 0.67 mbar vs. 0.14 ± 0.45 mbar, p = 0.012) but not the controlled mode (0.37 ± 0.83 mbar vs. 0.32 ± 0.8 mbar, p = 0.53). However, there was no significant difference between groups in mechanical power, the number of ventilator-free days, or the percentage of patients showing progression to ARDS. Although there was no difference in progression to ARDS, 28-day mortality was higher in the intervention group. Notably, the mean overall driving pressure across both groups was low (12.02 mbar ± 2.77).

CONCLUSIONS

In a population at risk of ARDS, a combined intervention of a clinical decision support system and a nudge intervention was shown to reduce the excessive driving pressure above 15 mbar in augmented but not in controlled modes of ventilation.

Quality improvement project to improve adherence to lung protective ventilation guidelines

INTRODUCTION

Lung protective ventilation (LPV) is advocated for all patients requiring mechanical ventilation (MV), for any duration of time, to prevent worsening lung injury. Previous studies proved simple interventions can increase awareness of LPV and disease pathophysiology as well as improve adherence to LPV guidelines.

OBJECTIVE

To assess the impact of a multi-component LPV quality improvement project (QIP) on adherence to LPV guidelines.

METHODS

Tidal volume data for all patients requiring MV at a large, tertiary UK critical care unit were collected retrospectively over 3, 6 months, Plan-Do-Study-Act cycles between September 2019 and August 2022. These cycles included the sequential implementation of LPV reports, bedside whiteboards and targeted education led by a multispecialty working group.

MAIN OUTCOME MEASURE

Adherence against predetermined targets of <5% of MV hours spent at >10 mL/kg predicted body weight (PBW) and >75% of MV hours spent <8 mL/kg PBW for all patients requiring MV.

RESULTS

408 949 hours (17 040 days) of MV data were analysed. Improved LPV adherence was demonstrated throughout the QIP. During mandated MV, time spent >10 mL/kg PBW reduced from 7.65% of MV hours to 4.04% and time spent <8 mL/kg PBW improved from 68.86% of MV hours to 71.87% following the QIP. During spontaneous MV, adherence improved with a reduction in time spent >10 mL/kg PBW from baseline to completion (13.2% vs 6.75%) with increased time spent <8 mL/kg PBW (62.74% vs 72.25%). Despite demonstrating improvements in adherence, we were unable to achieve success in all our predetermined targets.

CONCLUSION

This multicomponent intervention including the use of LPV reports, bedside whiteboards and education improves adherence to LPV guidelines. More robust data analysis of reasons for non-adherence to our predetermined targets is required to guide future interventions that may allow further improvement in adherence to LPV guidelines.

Sharpening clinical decision support alert and reminder designs with MINDSPACE: A systematic review

BACKGROUND

Clinical decision support (CDS) alerts and reminders aim to influence clinical decisions, yet they are often designed without considering human decision-making behaviour. While this behaviour is comprehensively described by behavioural economics (BE), the sheer volume of BE literature poses a challenge to designers when identifying behavioural effects with utility to alert and reminder designs. This study tackles this challenge by focusing on the MINDSPACE framework for behaviour change, which collates nine behavioural effects that profoundly influence human decision-making behaviour: Messenger, Incentives, Norms, Defaults, Salience, Priming, Affect, Commitment, and Ego.

METHOD

A systematic review searching MEDLINE, Embase, PsycINFO, and CINAHL Plus to explore (i) the usage of MINDSPACE effects in alert and reminder designs and (ii) the efficacy of those alerts and reminders in influencing clinical decisions. The search queries comprised ten Boolean searches, with nine focusing on the MINDSPACE effects and one focusing on the term mindspace.

RESULTS

50 studies were selected from 1791 peer-reviewed journal articles in English from 1970 to 2022. Except for ego, eight of nine MINDSPACE effects were utilised to design alerts and reminders, with defaults and norms utilised the most in alerts and reminders, respectively. Overall, alerts and reminders informed by MINDSPACE effects showed an average 71% success rate in influencing clinical decisions (alerts 73%, reminders 69%). Most studies utilised a single effect in their design, with higher efficacy for alerts (64%) than reminders (41%). Others utilised multiple effects, showing higher efficacy for reminders (28%) than alerts (9%).

CONCLUSION

This review presents sufficient evidence demonstrating the MINDSPACE framework's merits for designing CDS alerts and reminders with human decision-making considerations. The framework can adequately address challenges in identifying behavioural effects pertinent to the effective design of CDS alerts and reminders. The review also identified opportunities for future research into other relevant effects (e.g., framing).

Design and Evaluation of an Intensive Care Unit Dashboard Built in Response to the COVID-19 Pandemic: Semistructured Interview Study

BACKGROUND

Dashboards and interactive displays are becoming increasingly prevalent in most health care settings and have the potential to streamline access to information, consolidate disparate data sources and deliver new insights. Our research focuses on intensive care units (ICUs) which are heavily instrumented, critical care environments that generate vast amounts of data and frequently require individualized support for each patient. Consequently, clinicians experience a high cognitive load, which can translate to suboptimal performance. The global COVID-19 pandemic exacerbated this problem by generating a large number of additional hospitalizations, which necessitated a new tool that would help manage ICUs' census. In a previous study, we interviewed clinicians at the University Hospitals Bristol and Weston National Health Service Foundation Trust to capture the requirements for bespoke dashboards that would alleviate this problem.

OBJECTIVE

This study aims to design, implement, and evaluate an ICU dashboard to allow for monitoring of the high volume of patients in need of critical care, particularly tailored to high-demand situations, such as those seen during the COVID-19 pandemic.

METHODS

Building upon the previously gathered requirements, we developed a dashboard, integrated it within the ICU of a National Health Service trust, and allowed all staff to access our tool. For evaluation purposes, participants were recruited and interviewed following a 25-day period during which they were able to use the dashboard clinically. The semistructured interviews followed a topic guide aimed at capturing the usability of the dashboard, supplemented with additional questions asked post hoc to probe themes established during the interview. Interview transcripts were analyzed using a thematic analysis framework that combined inductive and deductive approaches and integrated the Technology Acceptance Model.

RESULTS

A total of 10 participants with 4 different roles in the ICU (6 consultants, 2 junior doctors, 1 nurse, and 1 advanced clinical practitioner) participated in the interviews. Our analysis generated 4 key topics that prevailed across the data: our dashboard met the usability requirements of the participants and was found useful and intuitive; participants perceived that it impacted their delivery of patient care by improving the access to the information and better equipping them to do their job; the tool was used in a variety of ways and for different reasons and tasks; and there were barriers to integration of our dashboard into practice, including familiarity with existing systems, which stifled the adoption of our tool.

CONCLUSIONS

Our findings show that the perceived utility of the dashboard had a positive impact on the clinicians' workflows in the ICU. Improving access to information translated into more efficient patient care and transformed some of the existing processes. The introduction of our tool was met with positive reception, but its integration during the COVID-19 pandemic limited its adoption into practice.

Leveraging Clinical Informatics and Data Science to Improve Care and Facilitate Research in Pediatric Acute Respiratory Distress Syndrome: From the Second Pediatric Acute Lung Injury Consensus Conference

OBJECTIVES

The use of electronic algorithms, clinical decision support systems, and other clinical informatics interventions is increasing in critical care. Pediatric acute respiratory distress syndrome (PARDS) is a complex, dynamic condition associated with large amounts of clinical data and frequent decisions at the bedside. Novel data-driven technologies that can help screen, prompt, and support clinician decision-making could have a significant impact on patient outcomes. We sought to identify and summarize relevant evidence related to clinical informatics interventions in both PARDS and adult respiratory distress syndrome (ARDS), for the second Pediatric Acute Lung Injury Consensus Conference.

DATA SOURCES

MEDLINE (Ovid), Embase (Elsevier), and CINAHL Complete (EBSCOhost).

STUDY SELECTION

We included studies of pediatric or adult critically ill patients with or at risk of ARDS that examined automated screening tools, electronic algorithms, or clinical decision support systems.

DATA EXTRACTION

Title/abstract review, full text review, and data extraction using a standardized data extraction form.

DATA SYNTHESIS

The Grading of Recommendations Assessment, Development and Evaluation approach was used to identify and summarize evidence and develop recommendations. Twenty-six studies were identified for full text extraction to address the Patient/Intervention/Comparator/Outcome questions, and 14 were used for the recommendations/statements. Two clinical recommendations were generated, related to the use of electronic screening tools and automated monitoring of compliance with best practice guidelines. Two research statements were generated, related to the development of multicenter data collaborations and the design of generalizable algorithms and electronic tools. One policy statement was generated, related to the provision of material and human resources by healthcare organizations to empower clinicians to develop clinical informatics interventions to improve the care of patients with PARDS.

CONCLUSIONS

We present two clinical recommendations and three statements (two research one policy) for the use of electronic algorithms and clinical informatics tools for patients with PARDS based on a systematic review of the literature and expert consensus.

Understanding clinical and biological heterogeneity to advance precision medicine in paediatric acute respiratory distress syndrome

Paediatric acute respiratory distress syndrome (PARDS) is a heterogeneous clinical syndrome that is associated with high rates of mortality and long-term morbidity. Factors that distinguish PARDS from adult acute respiratory distress syndrome (ARDS) include changes in developmental stage and lung maturation with age, precipitating factors, and comorbidities. No specific treatment is available for PARDS and management is largely supportive, but methods to identify patients who would benefit from specific ventilation strategies or ancillary treatments, such as prone positioning, are needed. Understanding of the clinical and biological heterogeneity of PARDS, and of differences in clinical features and clinical course, pathobiology, response to treatment, and outcomes between PARDS and adult ARDS, will be key to the development of novel preventive and therapeutic strategies and a precision medicine approach to care. Studies in which clinical, biomarker, and transcriptomic data, as well as informatics, are used to unpack the biological and phenotypic heterogeneity of PARDS, and implementation of methods to better identify patients with PARDS, including methods to rapidly identify subphenotypes and endotypes at the point of care, will drive progress on the path to precision medicine.

Using nudges to promote clinical decision making of healthcare professionals: A scoping review

Nudging has been discussed in the context of policy and public health, but not so much within healthcare. This scoping review aimed to assess the empirical evidence on how nudging techniques can be used to affect the behavior of healthcare professionals (HCPs) in clinical settings. A systematic database search was conducted for the period January 2010-December 2020 using the PRISMA extension for Scoping Review checklist. Two reviewers independently screened each article for inclusion. Included articles were reviewed to extract key information about each intervention, including purpose, target behavior, measured outcomes, key findings, nudging strategies, intervention objectives and their theoretical underpinnings. Two independent dimensions, building on Kahneman's System 1 and System 2, were used to describe nudging strategies according to user action and timing of their implementation. Of the included 51 articles, 40 reported statistically significant results, six were not significant and two reported mixed results. Thirteen different nudging strategies were identified aimed at modifying four types of HPCs' behavior: prescriptions and orders, procedure, hand hygiene, and vaccination. The most common nudging strategy employed were defaults or pre-orders, followed by alerts or reminders, and active choice. Many interventions did not require any deliberate action from users, here termed passive interventions, such as automatically changing prescriptions to their generic equivalent unless indicated by the user. Passive nudges may be successful in changing the target outcome but may go unnoticed by the user. Future work should consider the broader ethical implications of passive nudges.

A nudge intervention to improve hand hygiene compliance in the hospital

Hand hygiene among professionals plays a crucial role in preventing healthcare-associated infections, yet poor compliance in hospital settings remains a lasting reason for concern. Nudge theory is an innovative approach to behavioral change first developed in economics and cognitive psychology, and recently spread and discussed in clinical medicine. To assess a combined nudge intervention (localized dispensers, visual reminders, and gain-framed posters) to promote hand hygiene compliance among hospital personnel. A quasi-experimental study including a pre-intervention phase and a post-intervention phase (9 + 9 consecutive months) with 117 professionals overall from three wards in a 350-bed general city hospital. Hand hygiene compliance was measured using direct observations by trained personnel and measurement of alcohol-based hand-rub consumption. Levels of hand hygiene compliance were low in the pre-intervention phase: 11.44% of hand hygiene opportunities prescribed were fulfilled overall. We observed a statistically significant effect of the nudge intervention with an increase to 18.71% (p < 0.001) in the post-intervention phase. Improvement was observed in all experimental settings (the three hospital wards). A statistical comparison across three subsequent periods of the post-intervention phase revealed no significant decay of the effect. An assessment of the collected data on alcohol-based hand-rub consumption indirectly confirms the main result in all experimental settings. Behavioral outcomes concerning hand hygiene in the hospital are indeed affected by contextual, nudging factors to a significant extent. If properly devised, nudging measures can provide a sustainable contribution to increase hand hygiene compliance in a hospital setting.

Use of a Portable Electronic Interface Improves Clinical Handoffs and Adherence to Lung Protective Ventilation

Background

Mechanical ventilation (MV) is used to support patients with respiratory impairment. Evidence supports the use of lung-protective ventilation (LPV) during MV to improve outcomes. However, studies have demonstrated poor adherence to LPV guidelines. We hypothesized that an electronic platform adapted to a hand-held tablet receiving real-time ventilatory parameters could increase clinician awareness of key LPV parameters. Furthermore, we speculated that an electronic shift-change tool could improve the quality of clinician handoffs.

Methods

Using a specially designed Wi-Fi dongle to transmit data from three ventilators and a respiratory monitor, we implemented a system that displays data from all ventilators under the care of a Respiratory Care Practitioner (RCP) on an electronic tablet. In addition, the tablet created a handoff checklist to improve shift-change communication. In a simulated ICU environment, we monitored the performance of eight RCPs at baseline and while using the system.

Results

Using the system, the time above guideline Pplat decreased by 74% from control, and the time outside the VT range decreased by 60% from control, p = 0.007 and 0.015, respectively. The handoff scores improved quality significantly from 2.8 to 1.6 on a scale of 1 to 5 (1 being best), p = 0.03.

Conclusion

In a simulated environment, an electronic RT tool can significantly improve shift-change communication and increase the RCP's level of LPV adherence.

We can't mitigate what we don't monitor: using informatics to measure and improve healthcare systems' climate impact and environmental footprint

Climate change, human health, and healthcare systems are inextricably linked. As the climate warms due to greenhouse gas (GHG) emissions, extreme weather events, such as floods, fires, and heatwaves, will drive up demand for healthcare. Delivering healthcare also contributes to climate change, accounting for ∼5% of the global carbon emissions. To rein in healthcare's carbon footprint, clinicians and health policy makers must be able to measure the GHG contributions of healthcare systems and clinical practices. Herein, we scope potential informatics solutions to monitor the carbon footprint of healthcare systems and to support climate-change decision-making for clinicians, and healthcare policy makers. We discuss the importance of methods and tools that can link environmental, economic, and healthcare data, and outline challenges to the sustainability of monitoring efforts. A greater understanding of these connections will only be possible through further development and usage of models and tools that integrate diverse data sources.

Process Mining the Performance of a Real-Time Healthcare 4.0 Systems Using Conditional Survival Models

As the world moves into the exciting age of Healthcare 4.0, it is essential that patients and clinicians have confidence and reassurance that the real-time clinical decision support systems being used throughout their care guarantee robustness and optimal quality of care. However, current systems involving autonomic behaviour and those with no prior clinical feedback, have generally to date had little focus on demonstrating robustness in the use of data and final output, thus generating a lack of confidence. This paper wishes to address this challenge by introducing a new process mining approach based on a statistically robust methodology that relies on the utilisation of conditional survival models for the purpose of evaluating the performance of Healthcare 4.0 systems and the quality of the care provided. Its effectiveness is demonstrated by analysing the performance of a clinical decision support system operating in an intensive care setting with the goal to monitor ventilated patients in real-time and to notify clinicians if the patient is predicted at risk of receiving injurious mechanical ventilation. Additionally, we will also demonstrate how the same metrics can be used for evaluating the patient quality of care. The proposed methodology can be used to analyse the performance of any Healthcare 4.0 system and the quality of care provided to the patient.

Requirements for a Bespoke Intensive Care Unit Dashboard in Response to the COVID-19 Pandemic: Semistructured Interview Study

BACKGROUND

Intensive care units (ICUs) around the world are in high demand due to patients with COVID-19 requiring hospitalization. As researchers at the University of Bristol, we were approached to develop a bespoke data visualization dashboard to assist two local ICUs during the pandemic that will centralize disparate data sources in the ICU to help reduce the cognitive load on busy ICU staff in the ever-evolving pandemic.

OBJECTIVE

The aim of this study was to conduct interviews with ICU staff in University Hospitals Bristol and Weston National Health Service Foundation Trust to elicit requirements for a bespoke dashboard to monitor the high volume of patients, particularly during the COVID-19 pandemic.

METHODS

We conducted six semistructured interviews with clinical staff to obtain an overview of their requirements for the dashboard and to ensure its ultimate suitability for end users. Interview questions aimed to understand the job roles undertaken in the ICU, potential uses of the dashboard, specific issues associated with managing COVID-19 patients, key data of interest, and any concerns about the introduction of a dashboard into the ICU.

RESULTS

From our interviews, we found the following design requirements: (1) a flexible dashboard, where the functionality can be updated quickly and effectively to respond to emerging information about the management of this new disease; (2) a mobile dashboard, which allows staff to move around on wards with a dashboard, thus potentially replacing paper forms to enable detailed and consistent data entry; (3) a customizable and intuitive dashboard, where individual users would be able to customize the appearance of the dashboard to suit their role; (4) real-time data and trend analysis via informative data visualizations that help busy ICU staff to understand a patient's clinical trajectory; and (5) the ability to manage tasks and staff, tracking both staff and patient movements, handovers, and task monitoring to ensure the highest quality of care.

CONCLUSIONS

The findings of this study confirm that digital solutions for ICU use would potentially reduce the cognitive load of ICU staff and reduce clinical errors at a time of notably high demand of intensive health care.

Improving delivery of low tidal volume ventilation in 10 ICUs

Low tidal volume ventilation (LTVV) is standard of care for mechanically ventilated patients with acute respiratory distress syndrome and has been shown to improve outcomes in the general mechanically ventilated population. Despite these improved outcomes, in clinical practice the LTVV standard of care is often not met. We aimed to increase compliance with LTVV in mechanically ventilated patients in 10 intensive care units at 3 hospitals within the University of Pittsburgh School of Medicine Department of Critical Care Medicine. Four Plan-Do-Study-Act (PDSA) cycles were implemented to improve compliance with LTVV. Initial compliance rates of 40.6%-60.1% improved to 91%-96% by the end of the fourth PDSA cycle. The most impactful step in the intervention was providing education and giving responsibility of selecting the tidal volume to the respiratory therapist. The overall intervention resulted in improved compliance with LTVV that has been sustained for multiple years after our active PDSA cycles.

Audit of low tidal volume ventilation in patients with hypoxic respiratory failure in a tertiary Australian intensive care unit

A low tidal volume ventilation (LTVV) strategy improves outcomes in patients with acute respiratory distress syndrome (ARDS). Subsequently, a LTVV strategy has become the standard of care for patients receiving mechanical ventilation. This strategy is poorly adhered to within intensive care units (ICUs). A retrospective analysis was conducted of prescribed tidal volumes in mechanically ventilated patients with hypoxic respiratory failure between April 2013 and March 2017. Data collection included the establishment of a new data-entry box for patient height in March 2016, aimed at assisting the calculation of LTVV. We reviewed 836 ICU admissions, comprising 19,884 hours of ventilation. A total of 92% of admissions lacked patient height recording. When height was recorded, 54% of hours of ventilation were LTVV adherent. Non-LTVV hours for both groups involved higher tidal volumes (38%) rather than lower tidal volumes (8%). Non-LTVV-adherent hours were significantly (P<0.001) more likely to be associated with patient mortality than LTVV-adherent hours were. For all hours of ventilation, mean tidal volume before March 2016 was significantly higher (496 (standard deviation (SD) 101) ml, compared to after March 2016 (451 (SD 107) ml, P<0.001, 95% confidence interval for true difference in means 42 to 48 ml). However, this trend gradually reversed over time. There was a clinician preference for multiples of 50 ml. There was poor adherence to LTVV strategy in patients with hypoxic respiratory failure, which was associated with an increase in patient mortality. An electronic medical record intervention was successful in producing change, but this was not sustainable over time. Clinician ventilation prescribing habits were based on numerical simplicity rather than evidence-based practice.

Nudging healthcare professionals in clinical settings: a scoping review of the literature

BACKGROUND

Healthcare organisations are in constant need of improvement and change. Nudging has been proposed as a strategy to affect people's choices and has been used to affect patients' behaviour in healthcare settings. However, little is known about how nudging is being interpreted and applied to change the behaviour of healthcare professionals (HCPs). The objective of this review is to identify interventions using nudge theory to affect the behaviour of HCPs in clinical settings.

METHODS

A scoping review. We searched PubMed and PsycINFO for articles published from 2010 to September 2019, including terms related to "nudging" in the title or abstract. Two reviewers screened articles for inclusion based on whether the articles described an intervention to change the behaviour of HCPs. Two reviewers extracted key information and categorized included articles. Descriptive analyses were performed on the data.

RESULTS

Search results yielded 997 unique articles, of which 25 articles satisfied the inclusion criteria. Five additional articles were selected from the reference lists of the included articles. We identified 11 nudging strategies: accountable justification, goal setting, suggested alternatives, feedback, information transparency, peer comparison, active choice, alerts and reminders, environmental cueing/priming, defaults/pre-orders, and education. These strategies were employed to affect the following 4 target behaviours: vaccination of staff, hand hygiene, clinical procedures, prescriptions and orders. To compare approaches across so many areas, we introduced two independent dimensions to describe nudging strategies: synchronous/asynchronous, and active/passive.

CONCLUSION

There are relatively few studies published referring to nudge theory aimed at changing HCP behaviour in clinical settings. These studies reflect a diverse set of objectives and implement nudging strategies in a variety of ways. We suggest distinguishing active from passive nudging strategies. Passive nudging strategies may achieve the desired outcome but go unnoticed by the clinician thereby not really changing a behaviour and raising ethical concerns. Our review indicates that there are successful active strategies that engage with clinicians in a more deliberate way. However, more research is needed on how different nudging strategies impact HCP behaviour in the short and long term to improve clinical decision making.

Implementation of lung protective ventilation order to improve adherence to low tidal volume ventilation: A RE-AIM evaluation

PURPOSE

Lung protective ventilation (LPV), defined as a tidal volume (Vt) ≤8 cc/kg of predicted body weight, reduces ventilator-induced lung injury but is applied inconsistently.

MATERIALS AND METHODS

We conducted a prospective, quasi-experimental, cohort study of adults mechanically ventilated admitted to intensive care units (ICU) in the year before, year after, and second year after implementation of an electronic medical record based LPV order, and a cross-sectional qualitative study of ICU providers regarding their perceptions of the order. We applied the Reach, Efficacy, Adoption, Implementation, and Maintenance (RE-AIM) framework to evaluate the implementation.

RESULTS

There were 1405, 1424, and 1342 in the control, adoption, and maintenance cohorts, representing 95% of mechanically ventilated adult ICU patients. The overall prevalence of LPV increased from 65% to 73% (p < 0.001, adjusted-OR for LPV adherence: 1.9, 95% CI 1.5-2.3), but LPV adherence in women was approximately 30% worse than in men (women: 44% to 56% [p < 0.001],men: 79% to 86% [p < 0.001]). ICU providers noted difficulty obtaining an accurate height measurement and mistrust of the Vt calculation as barriers to implementation. LPV adherence increased further in the second year post implementation.

CONCLUSION

We designed and implemented an LPV order that sustainably improved LPV adherence across diverse ICUs.

Nudging clinicians: A systematic scoping review of the literature

BACKGROUND

While the quality of medical care delivered by physicians can be very good, it can also be inconsistent and feature behaviours that are entrenched despite updated information and evidence. The "nudge" paradigm for behaviour change is being used to bring clinical practice in line with desired standards. The premise is that behaviour can be voluntarily shifted by making particular choices instinctively appealing. We reviewed studies that are explicit about their use of nudge theory in influencing clinician behaviour.

METHODS

Databases were searched from April 2008 (the publication date of the book that introduced nudge theory to a wider audience) to November 2018, inclusive. The search strategy and narrative review of results addressed the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews.

RESULTS

22 studies were identified. Randomized trials or pre-post comparisons were generally used in community-based settings; single-site pre-post studies were favoured in hospitals. The studies employed eight intervention types: active choice; patient chart redesign; default and default alerts; partitioning of prescription menus; audit and feedback; commitment messages; peer comparisons; and redirection of workflow. Three core cognitive factors underpinned the eight interventions: bias towards prominent choices (salience); predisposition to social norms; and bias towards time or cost savings.

CONCLUSIONS

Published studies that are explicit about their use of nudge theory are few in number and diverse in their settings, targets, and results. Default and chart re-design interventions reported the most substantial improvements in adherence to evidence and guideline-based practice. Studies that are explicit in their use of nudge theory address the widespread failure of clinical practice studies to identify theoretical frameworks for interventions. However, few studies identified in our review engaged in research to understand the contextual and site-specific barriers to a desired behaviour before designing a nudge intervention.

Impact of a computerized decision support tool deployed in two intensive care units on acute kidney injury progression and guideline compliance: a prospective observational study

BACKGROUND

Acute kidney injury (AKI) affects a large proportion of the critically ill and is associated with worse patient outcomes. Early identification of AKI can lead to earlier initiation of supportive therapy and better management. In this study, we evaluate the impact of computerized AKI decision support tool integrated with the critical care clinical information system (CCIS) on patient outcomes. Specifically, we hypothesize that integration of AKI guidelines into CCIS will decrease the proportion of patients with Stage 1 AKI deteriorating into higher stages of AKI.

METHODS

The study was conducted in two intensive care units (ICUs) at University Hospitals Bristol, UK, in a before (control) and after (intervention) format. The intervention consisted of the AKIN guidelines and AKI care bundle which included guidance for medication usage, AKI advisory and dashboard with AKI score. Clinical data and patient outcomes were collected from all patients admitted to the units. AKI stage was calculated using the Acute Kidney Injury Network (AKIN) guidelines. Maximum AKI stage per admission, change in AKI stage and other metrics were calculated for the cohort. Adherence to eGFR-based enoxaparin dosing guidelines was evaluated as a proxy for clinician awareness of AKI.

RESULTS

Each phase of the study lasted a year, and a total of 5044 admissions were included for analysis with equal numbers of patients for the control and intervention stages. The proportion of patients worsening from Stage 1 AKI decreased from 42% (control) to 33.5% (intervention), p = 0.002. The proportion of incorrect enoxaparin doses decreased from 1.72% (control) to 0.6% (intervention), p < 0.001. The prevalence of any AKI decreased from 43.1% (control) to 37.5% (intervention), p < 0.05.

CONCLUSIONS

This observational study demonstrated a significant reduction in AKI progression from Stage 1 and a reduction in overall development of AKI. In addition, a reduction in incorrect enoxaparin dosing was also observed, indicating increased clinical awareness. This study demonstrates that AKI guidelines coupled with a newly designed AKI care bundle integrated into CCIS can impact patient outcomes positively.

Automatic generation of minimum dataset and quality indicators from data collected routinely by the clinical information system in an intensive care unit

BACKGROUND

Quality indicators (QIs) are being increasingly used in medicine to compare and improve the quality of care delivered. The feasibility of data collection is an important prerequisite for QIs. Information technology can improve efforts to measure processes and outcomes. In intensive care units (ICU), QIs can be automatically measured by exploiting data from clinical information systems (CIS).

OBJECTIVE

To describe the development and application of a tool to automatically generate a minimum dataset (MDS) and a set of ICU quality metrics from CIS data.

METHODS

We used the definitions for MDS and QIs proposed by the Spanish Society of Critical Care Medicine and Coronary Units. Our tool uses an extraction, transform, and load process implemented with Python to extract data stored in various tables in the CIS database and create a new associative database. This new database is uploaded to Qlik Sense, which constructs the MDS and calculates the QIs by applying the required metrics. The tool was tested using data from patients attended in a 30-bed polyvalent ICU during a six-year period.

RESULTS

We describe the definitions and metrics, and we report the MDS and QI measurements obtained through the analysis of 4546 admissions. The results show that our ICU's performance on the QIs analyzed meets the standards proposed by our national scientific society.

CONCLUSIONS

This is the first step toward using a tool to automatically obtain a set of actionable QIs to monitor and improve the quality of care in ICUs, eliminating the need for professionals to enter data manually, thus saving time and ensuring data quality.

Comparing regression and neural network techniques for personalized predictive analytics to promote lung protective ventilation in Intensive Care Units

Mechanical ventilation is a lifesaving tool and provides organ support for patients with respiratory failure. However, injurious ventilation due to inappropriate delivery of high tidal volume can initiate or potentiate lung injury. This could lead to acute respiratory distress syndrome, longer duration of mechanical ventilation, ventilator associated conditions and finally increased mortality. In this study, we explore the viability and compare machine learning methods to generate personalized predictive alerts indicating violation of the safe tidal volume per ideal body weight (IBW) threshold that is accepted as the upper limit for lung protective ventilation (LPV), prior to application to patients. We process streams of patient respiratory data recorded per minute from ventilators in an intensive care unit and apply several state-of-the-art time series prediction methods to forecast the behavior of the tidal volume metric per patient, 1 hour ahead. Our results show that boosted regression delivers better predictive accuracy than other methods that we investigated and requires relatively short execution times. Long short-term memory neural networks can deliver similar levels of accuracy but only after much longer periods of data acquisition, further extended by several hours computing time to train the algorithm. Utilizing Artificial Intelligence, we have developed a personalized clinical decision support tool that can predict tidal volume behavior within 10% accuracy and compare alerts recorded from a real world system to highlight that our models would have predicted violations 1 hour ahead and can therefore conclude that the algorithms can provide clinical decision support.

Clinicians' Perceptions of Behavioral Economic Strategies to Increase the Use of Lung-Protective Ventilation

Rationale: Lung-protective ventilation (LPV) improves outcomes in patients with acute respiratory distress syndrome (ARDS) and has also shown benefits in patients without ARDS. Despite this evidence, LPV use remains low.Objectives: To understand clinicians' perceptions of using behavioral economic strategies to improve rates of LPV use.Methods: We conducted semistructured interviews of clinicians across seven intensive care units within a university health system. We purposefully sampled clinicians of different professional backgrounds and experience levels. Each interview included descriptions of three of five strategies grounded in behavioral economic theory designed to facilitate clinicians' use of LPV: 1) an order set autopopulated with LPV settings ("default"), 2) an order set providing a choice between autopopulated LPV settings and open-ended order entry for alternative settings ("active choice"), 3) requirement of written justification if settings other than LPV were ordered or documented ("accountable justification"), 4) automated ARDS identification and clinician prompting ("alert"), and 5) provision of clinicians' and their peers' individual rates of LPV use ("peer comparison"). Descriptions were followed by open-ended questions to elicit perceptions about advantages, disadvantages, and acceptability. Initial interview transcripts were reviewed by two investigators to develop a thematic codebook, which was refined iteratively with the use of constant comparative methods.Results: We completed 17 interviews of physicians, nurse practitioners, and respiratory therapists. Strategies that prepopulated settings (default, active choice, and accountable justification) were perceived as providing benefit by reducing workloads and serving as cognitive prompts. The default and active choice strategies were more acceptable than accountable justification, which was perceived as potentially frustrating due to workflow impedance. The alert strategy was met with concerns about alert accuracy and alarm fatigue. The peer comparison strategy led to concerns about timing and fear of punitive measures. Participants believed that the default and active choice strategies would be highly acceptable, whereas few interviewees thought the alert would be acceptable. The active choice strategy was most consistently identified as potentially highly effective.Conclusions: Behavioral economic strategies have great potential as acceptable and potentially effective strategies to increase the use of LPV.

How Should Clinicians' Performance Be Assessed When Health Care Organizations Implement Behavioral Architecture That Generates Negative Consequences?

Behavioral interventions have been shown to have powerful effects on human behavior both outside of and within the context of health care. As organizations increasingly adopt behavioral architecture, care must be taken to consider its potential negative consequences. An evidenced-based approach is best, whereby interventions that might have a significant deleterious effect on patients' health outcomes are first tested and rigorously evaluated before being systematically rolled out. In the case of clinical decision support, brief and thorough instructions should be provided for use. Physician performance when using these systems is best measured relatively, in the context of peers with similar training. Responsibility for errors must be shared with clinical team members and system designers.

Novel approaches to facilitate the implementation of guidelines in the ICU

The effective implementation of evidence-based recommendations in routine intensive care unit (ICU) practice is challenging. Barriers related to the proposed recommendations, local contexts and processes can make the adoption of evidence-based practices difficult, contributing to healthcare inefficiency and worse patient and family outcomes. This review discusses the common barriers to guideline implementation in critical care settings, explores how implementation science provides an important framework for guiding implementation interventions, and discusses some specific and proven implementation strategies to improve adherence to evidence-based practices in the ICU.

Novel displays of patient information in critical care settings: a systematic review

OBJECTIVE

Clinician information overload is prevalent in critical care settings. Improved visualization of patient information may help clinicians cope with information overload, increase efficiency, and improve quality. We compared the effect of information display interventions with usual care on patient care outcomes.

MATERIALS AND METHODS

We conducted a systematic review including experimental and quasi-experimental studies of information display interventions conducted in critical care and anesthesiology settings. Citations from January 1990 to June 2018 were searched in PubMed and IEEE Xplore. Reviewers worked independently to screen articles, evaluate quality, and abstract primary outcomes and display features.

RESULTS

Of 6742 studies identified, 22 studies evaluating 17 information displays met the study inclusion criteria. Information display categories included comprehensive integrated displays (3 displays), multipatient dashboards (7 displays), physiologic and laboratory monitoring (5 displays), and expert systems (2 displays). Significant improvement on primary outcomes over usual care was reported in 12 studies for 9 unique displays. Improvement was found mostly with comprehensive integrated displays (4 of 6 studies) and multipatient dashboards (5 of 7 studies). Only 1 of 5 randomized controlled trials had a positive effect in the primary outcome.

CONCLUSION

We found weak evidence suggesting comprehensive integrated displays improve provider efficiency and process outcomes, and multipatient dashboards improve compliance with care protocols and patient outcomes. Randomized controlled trials of physiologic and laboratory monitoring displays did not show improvement in primary outcomes, despite positive results in simulated settings. Important research translation gaps from laboratory to actual critical care settings exist.

Community Experience With Acute Respiratory Distress Syndrome in the Prone Position

Mechanical ventilation in the prone position has been shown to improve outcomes in randomized trials of patients with moderate to severe acute respiratory distress syndrome and is recommended in clinical practice guidelines. However, data is lacking on the results of attempts to implement this practice in the community outside of clinical trials. To describe our early outcomes implementing mechanical ventilation in the prone position.

DESIGN

Retrospective cohort study.

SETTING

Medical intensive care unit of a large community-based teaching hospital.

PARTICIPANTS

All patients ventilated in the prone position between June 2013 and October 2016.

MEASUREMENTS AND MAIN RESULTS

We describe patient characteristics, mortality, and frequency of complications (such as skin breakdown and accidental extubation) at our center. Eighty-one patients with a mean age of 55 years underwent mechanical ventilation in the prone position during the study period. Most patients also received vasopressors, neuromuscular blockade, and steroids. Overall mortality was 43%. The duration of the first proning session ranged from 1.5 to 40.5 hours. Mortality was lower (34%) in those ventilated in the prone position for more than 16 hours during the first session. In the 50 patients without treatment limitations, only 14% expired. There were no accidental extubations during prone positioning. Most of those who died had limitations placed on treatment prior to death.

CONCLUSIONS

Overall mortality was higher in our cohort than in the randomized trial. However, differences such as lack of stabilization period, different cultures impacting end-of-life decisions, and timing of enrollment in the course of illness limit interpretation of this comparison. This exercise allows identification of areas for future quality improvement efforts such as increasing the duration of some proning sessions. Complications of prone positioning were uncommon.

Case Study: More Patient Safety by Design - System-based Approaches for Hospitals

Since the publication of the report "To Err Is Human: Building a Safer Health System" by the US Institute of Medicine in 2000, much has changed with regard to patient safety. Many of the more recent initiatives to improve patient safety target the behavior of health care staff (e.g., training, double-checking procedures, and standard operating procedures). System-based interventions have so far received less attention, even though they produce more substantial improvements, being less dependent on individuals' behavior. One type of system-based intervention that can benefit patient safety involves improvements to hospital design. Given that people's working environments affect their behavior, good design at a systemic level not only enables staff to work more efficiently; it can also prevent errors and mishaps, which can have serious consequences for patients. While an increasing number of studies have demonstrated the effect of hospital design on patient safety, this knowledge is not easily accessible to clinicians, practitioners, risk managers, and other decision-makers, such as designers and architects of health care facilities. This is why the Swiss Patient Safety Foundation launched its project, "More Patient Safety by Design: Systemic Approaches for Hospitals," which is presented in this chapter.

Evaluating Delivery of Low Tidal Volume Ventilation in Six ICUs Using Electronic Health Record Data

OBJECTIVES

Mechanical ventilation with low tidal volumes is recommended for all patients with acute respiratory distress syndrome and may be beneficial to other intubated patients, yet consistent implementation remains difficult to obtain. Using detailed electronic health record data, we examined patterns of tidal volume administration, the effect on clinical outcomes, and alternate metrics for evaluating low tidal volume compliance in clinical practice.

DESIGN

Observational cohort study.

SETTING

Six ICUs in a single hospital system.

PATIENTS

Adult patients who received invasive mechanical ventilation more than 12 hours.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Tidal volumes were analyzed across 1,905 hospitalizations. Although mean tidal volume was 6.8 mL/kg predicted body weight, 40% of patients were exposed to tidal volumes greater than 8 mL/kg predicted body weight, with 11% for more than 24 hours. At a patient level, exposure to 24 total hours of tidal volumes greater than 8 mL/kg predicted body weight was associated with increased mortality (odds ratio, 1.82; 95% CI, 1.20-2.78), whereas mean tidal volume exposure was not (odds ratio, 0.87/1 mL/kg increase; 95% CI, 0.74-1.02). Initial tidal volume settings strongly predicted exposure to volumes greater than 8 mL/kg for 24 hours; the adjusted rate was 21.5% when initial volumes were greater than 8 mL/kg predicted body weight and 7.1% when initial volumes were less than 8 mL/kg predicted body weight. Across ICUs, correlation of mean tidal volume with alternative measures of low tidal volume delivery ranged from 0.38 to 0.66.

CONCLUSIONS

Despite low mean tidal volume in the cohort, a significant percentage of patients were exposed to a prolonged duration of high tidal volumes which was correlated with higher mortality. Detailed ventilator records in the electronic health record provide a unique window for evaluating low tidal volume delivery and targets for improvement.

Curation of an intensive care research dataset from routinely collected patient data in an NHS trust

In this data note we provide the details of a research database of 4831 adult intensive care patients who were treated in the Bristol Royal Infirmary, UK between 2015 and 2019. The purposes of this publication are to describe the dataset for external researchers who may be interested in making use of it, and to detail the methods used to curate the dataset in order to help other intensive care units make secondary use of their routinely collected data. The curation involves linkage between two critical care datasets within our hospital and the accompanying code is available online. For reasons of data privacy the data cannot be shared without researchers obtaining appropriate ethical consents. In the future we hope to obtain a data sharing agreement in order to publicly share the de-identified data, and to link our data with other intensive care units who use a Philips clinical information system.

The effect of emergency department crowding on lung-protective ventilation utilization for critically ill patients

OBJECTIVE

To measure effects of ED crowding on lung-protective ventilation (LPV) utilization in critically ill ED patients.

METHODS

This is a retrospective cohort study of adult mechanically ventilated ED patients admitted to the medical intensive care unit (MICU), over a 3.5-year period at a single academic tertiary care hospital. Clinical data, including reason for intubation, severity of illness (MPM₀-III), acute respiratory distress syndrome (ARDS) risk score (EDLIPS), and ventilator settings were extracted via electronic query of electronic health record and standardized chart abstraction. Crowding metrics were obtained at 5-min intervals and averaged over the ED stay, stratified by acuity and disposition. Multivariate logistic regression was used to predict likelihood of LPV prior to ED departure.

RESULTS

Mechanical ventilation was used in 446 patients for a median ED duration of 3.7 h (interquartile ratio, IQR, 2.3, 5.6). Mean MPM₀-III score was 32.5 ± 22.7, with high risk for ARDS (EDLIPS ≥5) seen in 373 (82%) patients. Initial and final ED ventilator settings differed in 134 (30.0%) patients, of which only 47 (35.1%) involved tidal volume changes. Higher percentages of active ED patients (workup in-progress) and those requiring eventual admission were associated with lower odds of LPV utilization by ED departure (OR 0.97, 95%CI 0.94-1.00; OR 0.97, 95%CI 0.94-1.00, respectively). In periods of high volume, ventilator adjustments to settings other than the tidal volume were associated with higher odds of LPV utilization. Reason for intubation, MPM₀-III, and EDLIPS were not associated with LPV utilization, with no interactions detected in times of crowding.

CONCLUSIONS

ED patients remain on suboptimal tidal volume settings with infrequent ventilator adjustments during the ED stay. Hospitals should focus on both systemic factors and bedside physician and/or respiratory therapist interventions to increase LPV utilization in times of ED boarding and crowding for all patients.

Towards a decision support tool for intensive care discharge: machine learning algorithm development using electronic healthcare data from MIMIC-III and Bristol, UK

OBJECTIVE

The primary objective is to develop an automated method for detecting patients that are ready for discharge from intensive care.

DESIGN

We used two datasets of routinely collected patient data to test and improve on a set of previously proposed discharge criteria.

SETTING

Bristol Royal Infirmary general intensive care unit (GICU).

PATIENTS

Two cohorts derived from historical datasets: 1870 intensive care patients from GICU in Bristol, and 7592 from Medical Information Mart for Intensive Care (MIMIC)-III.

RESULTS

In both cohorts few successfully discharged patients met all of the discharge criteria. Both a random forest and a logistic classifier, trained using multiple-source cross-validation, demonstrated improved performance over the original criteria and generalised well between the cohorts. The classifiers showed good agreement on which features were most predictive of readiness-for-discharge, and these were generally consistent with clinical experience. By weighting the discharge criteria according to feature importance from the logistic model we showed improved performance over the original criteria, while retaining good interpretability.

CONCLUSIONS

Our findings indicate the feasibility of the proposed approach to ready-for-discharge classification, which could complement other risk models of specific adverse outcomes in a future decision support system. Avenues for improvement to produce a clinically useful tool are identified.

Behavioral Economics Interventions in Clinical Decision Support Systems

Background:  Clinical decision support (CDS) systems can improve safety and facilitate evidence-based practice. However, clinical decisions are often affected by the cognitive biases and heuristics of clinicians, which is increasing the interest in behavioral and cognitive science approaches in the medical field.

Objectives:  This review aimed to identify decision biases that lead clinicians to exhibit irrational behaviors or responses, and to show how behavioral economics can be applied to interventions in order to promote and reveal the contributions of CDS to improving health care quality.

Methods:  We performed a systematic review of studies published in 2016 and 2017 and applied a snowball citationsearch method to identify topical publications related to studies forming part of the BEARI (Application of Behavioral Economics to Improve the Treatment of Acute Respiratory Infections) multisite, cluster-randomized controlled trial performed in the United States.

Results:  We found that 10 behavioral economics concepts with nine cognitive biases were addressed and investigated for clinician decision-making, and that the following five concepts, which were actively explored, had an impact in CDS applications: social norms, framing effect, status-quo bias, heuristics, and overconfidence bias.

Conclusions:  Our review revealed that the use of behavioral economics techniques is increasing in areas such as antibiotics prescribing and preventive care, and that additional tests of the concepts and heuristics described would be useful in other areas of CDS. An improved understanding of the benefits and limitations of behavioral economics techniques is also still needed. Future studies should focus on successful design strategies and how to combine them with CDS functions for motivating clinicians.

A Critical Care Clinician Survey Comparing Attitudes and Perceived Barriers to Low Tidal Volume Ventilation with Actual Practice

RATIONALE

Low-Vt ventilation lowers mortality in patients with acute respiratory distress syndrome (ARDS) but is underused. Little is known about clinician attitudes toward and perceived barriers to low-Vt ventilation use and their association with actual low-Vt ventilation use.

OBJECTIVES

The objectives of this study were to assess clinicians' attitudes toward and perceived barriers to low-Vt ventilation (Vt <6.5 ml/kg predicted body weight) in patients with ARDS, to identify differences in attitudes and perceived barriers among clinician types, and to compare attitudes toward and perceived barriers to actual low-Vt ventilation use in patients with ARDS.

METHODS

We conducted a survey of critical care physicians, nurses, and respiratory therapists at four non-ARDS Network hospitals in the Chicago region. We compared survey responses with performance in a cohort of 362 patients with ARDS.

RESULTS

Survey responses included clinician attitudes toward and perceived barriers to low-Vt ventilation use. We also measured low-Vt ventilation initiation by these clinicians in 347 patients with ARDS initiated after ARDS onset as well as correlation with clinician attitudes and perceived barriers. Of 674 clinicians surveyed, 467 (69.3%) responded. Clinicians had positive attitudes toward and perceived few process barriers to ARDS diagnosis or initiation of low-Vt ventilation. Physicians had more positive attitudes and perceived fewer barriers than nurses or respiratory therapists. However, use of low-Vt ventilation by all three clinician groups was low. For example, whereas physicians believed that 92.5% of their patients with ARDS warranted treatment with low-Vt ventilation, they initiated low-Vt ventilation for a median (interquartile range) of 7.4% (0 to 14.3%) of their eligible patients with ARDS. Clinician attitudes and perceived barriers were not correlated with low-Vt ventilation initiation.

CONCLUSIONS

Clinicians had positive attitudes toward low-Vt ventilation and perceived few barriers to using it, but attitudes and perceived process barriers were not correlated with actual low-Vt ventilation use, which was low. Implementation strategies should be focused on examining other issues, such as ARDS recognition and process solutions, to improve low-Vt ventilation use.

Translating evidence into practice in acute respiratory distress syndrome: teamwork, clinical decision support, and behavioral economic interventions

PURPOSE OF REVIEW

Although the treatment of the acute respiratory distress syndrome (ARDS) with low tidal volume (LTV) mechanical ventilation improves mortality, it is not consistently administered in clinical practice. This review examines strategies to improve LTV and other evidence-based therapies for patients with ARDS.

RECENT FINDINGS

Despite the well established role of LTV in the treatment of ARDS, a recent multinational study suggests it is under-utilized in clinical practice. Strategies to improve LTV include audit and feedback, provider education, protocol development, interventions to improve ICU teamwork, computer decision support, and behavioral economic interventions such as making LTV the default-ventilator setting. These strategies typically target all patients receiving invasive mechanical ventilation, effectively avoiding the problem of poor ARDS recognition in clinical practice. To more effectively administer advanced ARDS therapies, such as prone positioning, better approaches for ARDS recognition will also be required.

SUMMARY

Multiple strategies can be utilized to improve adherence to LTV ventilation in ARDS patients.

Variable effectiveness of stepwise implementation of nudge-type interventions to improve provider compliance with intraoperative low tidal volume ventilation

BACKGROUND

Identifying mechanisms to improve provider compliance with quality metrics is a common goal across medical disciplines. Nudge interventions are minimally invasive strategies that can influence behavioural changes and are increasingly used within healthcare settings. We hypothesised that nudge interventions may improve provider compliance with lung-protective ventilation (LPV) strategies during general anaesthesia.

METHODS

We developed an audit and feedback dashboard that included information on both provider-level and department-level compliance with LPV strategies in two academic hospitals, two non-academic hospitals and two academic surgery centres affiliated with a single healthcare system. Dashboards were emailed to providers four times over the course of the 9-month study. Additionally, the default setting on anaesthesia machines for tidal volume was decreased from 700 mL to 400 mL. Data on surgical cases performed between 1 September 2016 and 31 May 2017 were examined for compliance with LPV. The impact of the interventions was assessed via pairwise logistic regression analysis corrected for multiple comparisons.

RESULTS

A total of 14 793 anaesthesia records were analysed. Absolute compliance rates increased from 59.3% to 87.8%preintervention to postintervention. Introduction of attending physician dashboards resulted in a 41% increase in the odds of compliance (OR 1.41, 95% CI 1.17 to 1.69, p=0.002). Subsequently, the addition of advanced practice provider and resident dashboards lead to an additional 93% increase in the odds of compliance (OR 1.93, 95% CI 1.52 to 2.46, p<0.001). Lastly, modifying ventilator defaults led to a 376% increase in the odds of compliance (OR 3.76, 95% CI 3.1 to 4.57, p<0.001).

CONCLUSION

Audit and feedback tools in conjunction with default changes improve provider compliance.

Translational research needs us to go back to basics and collaborate: interview with Lars Sundstrom

Lars Sundstrom is Director of Enterprise and Translation at the West of England Academic Health Sciences Network [1] (UK), a Professor of Practice in Translational Medicine and Co-Director of the Elizabeth Blackwell Institute for Health Research at Bristol University [2] (UK), and an honorary Professor of Medicine at Cardiff University (UK). He has extensive experience in translational medicine and clinical neurosciences, holding positions at several eminent universities. He has also held executive and board-level positions at several SMEs, developing new therapeutics for neurological conditions and tools for drug discovery. He has also been an advisor to several UK and local government task forces and to the European Commission and the European Federation of Pharmaceutical Industry Associations. He was a founding member of the European Brain Council in Brussels, and set up the Severnside Alliance for Translational Research, developing a regional network partnership to link clinical and basic scientists. He was also involved in the creation of Health Research Wales.

Protective mechanical ventilation in United Kingdom critical care units: A multicentre audit

Lung protective ventilation is becoming increasingly used for all critically ill patients being mechanically ventilated on a mandatory ventilator mode. Compliance with the universal application of this ventilation strategy in intensive care units in the United Kingdom is unknown. This 24-h audit of ventilation practice took place in 16 intensive care units in two regions of the United Kingdom. The mean tidal volume for all patients being ventilated on a mandatory ventilator mode was 7.2(±1.4) ml kg^-1 predicted body weight and overall compliance with low tidal volume ventilation (≤6.5 ml kg^-1 predicted body weight) was 34%. The mean tidal volume for patients ventilated with volume-controlled ventilation was 7.0(±1.2) ml kg^-1 predicted body weight and 7.9(±1.8) ml kg^-1 predicted body weight for pressure-controlled ventilation (P < 0.0001). Overall compliance with recommended levels of positive end-expiratory pressure was 72%. Significant variation in practice existed both at a regional and individual unit level.