Evaluation of consulting and critiquing decision support systems: effect on adherence to a lower tidal volume mechanical ventilation strategy

Chinese experts' consensus on the application of intensive care big data

The development of intensive care medicine is inseparable from the diversified monitoring data. Intensive care medicine has been closely integrated with data since its birth. Critical care research requires an integrative approach that embraces the complexity of critical illness and the computational technology and algorithms that can make it possible. Considering the need of standardization of application of big data in intensive care, Intensive Care Medicine Branch of China Health Information and Health Care Big Data Society, Standard Committee has convened expert group, secretary group and the external audit expert group to formulate Chinese Experts' Consensus on the Application of Intensive Care Big Data (2022). This consensus makes 29 recommendations on the following five parts: Concept of intensive care big data, Important scientific issues, Standards and principles of database, Methodology in solving big data problems, Clinical application and safety consideration of intensive care big data. The consensus group believes this consensus is the starting step of application big data in the field of intensive care. More explorations and big data based retrospective research should be carried out in order to enhance safety and reliability of big data based models of critical care field.

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.

Intermediate tidal volume is an acceptable option for ventilated patients with acute respiratory distress syndrome

Objective

Evidence only proves low surpasses high tidal volume (V _T) for acute respiratory distress syndrome (ARDS). Intermediate V _T is a common setting for ARDS patients and has been demonstrated as effective as low V _T in non-ARDS patients. The effectiveness of intermediate V _T in ARDS has not been studied and is the objective of this study.

Design

A retrospective cohort study.

Setting

Five ICUs with their totally 130 beds in Taiwan.

Patients or participants

ARDS patients under invasive ventilation.

Interventions

No.

Main variables of interest

28-D mortality.

Result

Totally 382 patients, with 6958 ventilator settings eligible for lung protection, were classified into low (mean V _T = 6.7 ml/kg), intermediate (mean V _T = 8.9 ml/kg) and high (mean V _T = 11.2 ml/kg) V _T groups. With similar baseline ARDS and ICU severities, intermediate and low V _T groups did not differ in 28-D mortality (47% vs. 63%, P = 0.06) or other outcomes such as 90-D mortality, ventilator-free days, ventilator-dependence rate. Multivariate analysis revealed high V _T was independently associated with 28-D and 90-D mortality, but intermediate V _T was not significantly associated with 28-D mortality (HR 1.34, CI 0.92-1.97, P = 0.13) or 90-D mortality. When the intermediate and low V _T groups were matched in propensity scores (n = 66 for each group), their outcomes were also not significantly different.

Conclusion

Intermediate V _T, with its outcomes similar to small V _T, is an acceptable option for ventilated ARDS patients. This conclusion needs verification through clinical trials.

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.

The role of computer-based clinical decision support systems to deliver protective mechanical ventilation

PURPOSE OF REVIEW

Mechanical ventilation of adults and children with acute respiratory failure necessitates balancing lung and diaphragm protective ventilation. Computerized decision support (CDS) offers advantages in circumstances where complex decisions need to be made to weigh potentially competing risks, depending on the physiologic state of the patient.

RECENT FINDINGS

Significant variability in how ventilator protocols are applied still exists and clinical data show that there continues to be wide variability in ventilator management. We have developed a CDS, which we are currently testing in a Phase II randomized controlled trial. The CDS is called Real-time Effort Driven ventilator management (REDvent). We will describe the rationale and methods for development of CDS for lung and diaphragm protective ventilation, using the REDvent CDS as an exemplar.

SUMMARY

Goals for achieving compliance and physiologic objectives can be met when CDS instructions are simple and explicit, provide the clinician with the underlying rule set, permit acceptable reasons for declining and allow for iterative adjustments.

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.

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.

Effects of staff training and electronic event monitoring on long-term adherence to lung-protective ventilation recommendations

PURPOSE

To investigate long-term effects of staff training and electronic clinical decision support (CDS) on adherence to lung-protective ventilation recommendations.

MATERIALS AND METHODS

In 2012, group instructions and workshops at two surgical intensive care units (ICUs) started, focusing on standardized protocols for mechanical ventilation and volutrauma prevention. Subsequently implemented CDS functions continuously monitor ventilation parameters, and from 2015 triggered graphical notifications when tidal volume (V_T) violated individual thresholds. To estimate the effects of these educational and technical interventions, we retrospectively analyzed nine years of V_T records from routine care. As outcome measures, we calculated relative frequencies of settings that conform to recommendations, case-specific mean excess V_T, and total ICU survival.

RESULTS

Assessing 571,478 V_T records from 10,241 ICU cases indicated that adherence during pressure-controlled ventilation improved significantly after both interventions; the share of conforming V_T records increased from 61.6% to 83.0% and then 86.0%. Despite increasing case severity, ICU survival remained nearly constant over time.

CONCLUSIONS

Staff training effectively improves adherence to lung-protective ventilation strategies. The observed CDS effect seemed less pronounced, although it can easily be adapted to new recommendations. Both interventions, which futures studies could deploy in combination, promise to improve the precision of mechanical ventilation.

Computerized Decision Support Systems for Mechanical Ventilation in Children

Mechanical ventilation is an effective treatment in the ICU but can have significant adverse effects. Approaches from adult research have been adopted in pediatric critical care despite known differences in respiratory physiology and ICU processes. There continues to be considerable variation in how ventilators are managed. Computerized decision support systems implement explicit protocols, and are designed to make mechanical ventilation management safer, more consistent, and more lung protective. Variable results and low or unknown compliance with protocols and CDSS tools have been reported. To date, there has been limited research regarding CDSS for mechanical ventilation in children.

User centered clinical decision support tools: adoption across clinician training level

BACKGROUND

Dissemination and adoption of clinical decision support (CDS) tools is a major initiative of the Affordable Care Act's Meaningful Use program. Adoption of CDS tools is multipronged with personal, organizational, and clinical settings factoring into the successful utilization rates. Specifically, the diffusion of innovation theory implies that 'early adopters' are more inclined to use CDS tools and younger physicians tend to be ranked in this category.

OBJECTIVE

This study examined the differences in adoption of CDS tools across providers' training level.

PARTICIPANTS

From November 2010 to 2011, 168 residents and attendings from an academic medical institution were enrolled into a randomized controlled trial.

INTERVENTION

The intervention arm had access to the CDS tool through the electronic health record (EHR) system during strep and pneumonia patient visits.

MAIN MEASURES

The EHR system recorded details on how intervention arm interacted with the CDS tool including acceptance of the initial CDS alert, completion of risk-score calculators and the signing of medication order sets. Using the EHR data, the study performed bivariate tests and general estimating equation (GEE) modeling to examine the differences in adoption of the CDS tool across residents and attendings.

KEY RESULTS

The completion rates of the CDS calculator and medication order sets were higher amongst first year residents compared to all other training levels. Attendings were the less likely to accept the initial step of the CDS tool (29.3%) or complete the medication order sets (22.4%) that guided their prescription decisions, resulting in attendings ordering more antibiotics (37.1%) during an CDS encounter compared to residents.

CONCLUSION

There is variation in adoption of CDS tools across training levels. Attendings tended to accept the tool less but ordered more medications. CDS tools should be tailored to clinicians' training levels.

From assessment to improvement of elderly care in general practice using decision support to increase adherence to ACOVE quality indicators: study protocol for randomized control trial

Background

Previous efforts such as Assessing Care of Vulnerable Elders (ACOVE) provide quality indicators for assessing the care of elderly patients, but thus far little has been done to leverage this knowledge to improve care for these patients. We describe a clinical decision support system to improve general practitioner (GP) adherence to ACOVE quality indicators and a protocol for investigating impact on GPs’ adherence to the rules.

Design

We propose two randomized controlled trials among a group of Dutch GP teams on adherence to ACOVE quality indicators. In both trials a clinical decision support system provides un-intrusive feedback appearing as a color-coded, dynamically updated, list of items needing attention. The first trial pertains to real-time automatically verifiable rules. The second trial concerns non-automatically verifiable rules (adherence cannot be established by the clinical decision support system itself, but the GPs report whether they will adhere to the rules). In both trials we will randomize teams of GPs caring for the same patients into two groups, A and B. For the automatically verifiable rules, group A GPs receive support only for a specific inter-related subset of rules, and group B GPs receive support only for the remainder of the rules. For non-automatically verifiable rules, group A GPs receive feedback framed as actions with positive consequences, and group B GPs receive feedback framed as inaction with negative consequences. GPs indicate whether they adhere to non-automatically verifiable rules. In both trials, the main outcome measure is mean adherence, automatically derived or self-reported, to the rules.

Discussion

We relied on active end-user involvement in selecting the rules to support, and on a model for providing feedback displayed as color-coded real-time messages concerning the patient visiting the GP at that time, without interrupting the GP’s workflow with pop-ups. While these aspects are believed to increase clinical decision support system acceptance and its impact on adherence to the selected clinical rules, systems with these properties have not yet been evaluated.

Trial registration

Controlled Trials NTR3566

Computerized decision support in adult and pediatric critical care

Computerized decision support (CDS) is the most advanced form of clinical decision support available and has evolved with innovative technologies to provide meaningful assistance to medical professionals. Critical care clinicians are in unique environments where vast amounts of data are collected on individual patients, and where expedient and accurate decisions are paramount to the delivery of quality healthcare. Many CDS tools are in use today among adult and pediatric intensive care units as diagnostic aides, safety alerts, computerized protocols, and automated recommendations for management. Some CDS use have significantly decreased adverse events and improved costs when carefully implemented and properly operated. CDS tools integrated into electronic health records are also valuable to researchers providing rapid identification of eligible patients, streamlining data-gathering and analysis, and providing cohorts for study of rare and chronic diseases through data-warehousing. Although the need for human judgment in the daily care of critically ill patients has limited the study and realization of meaningful improvements in overall patient outcomes, CDS tools continue to evolve and integrate into the daily workflow of clinicians, and will likely provide advancements over time. Through novel technologies, CDS tools have vast potential for progression and will significantly impact the field of critical care and clinical research in the future.