Secondary Logo

Journal Logo

Clinical Impact of an Electronic Dashboard and Alert System for Sedation Minimization and Ventilator Liberation: A Before-After Study

Anderson, Brian J. MD, MSCE1,2; Do, David MD3,4; Chivers, Corey PhD5; Choi, Katherine MD4; Gitelman, Yevgeniy MD2,4; Mehta, Shivan J. MD, MBA2,4; Panchandam, Venkat PhD7; Gudowski, Steve RRT8; Pierce, Margie MS, RRT8; Cereda, Maurizio MD6,9; Christie, Jason D. MD, MSCE1,2; Schweickert, William D. MD1,2; Gabrielli, Andrea MD9,10; Huffenberger, Ann DBA10; Draugelis, Mike BS5; Fuchs, Barry D. MD, MS1,2,8

doi: 10.1097/CCE.0000000000000057
Single-Center Quality Improvement Report
Open
SDC

Objectives: Sedation minimization and ventilator liberation protocols improve outcomes but are challenging to implement. We sought to demonstrate proof-of-concept and impact of an electronic application promoting sedation minimization and ventilator liberation.

Design: Multi-ICU proof-of-concept study and a single ICU before-after study.

Setting: University hospital ICUs.

Patients: Adult patients receiving mechanical ventilation.

Interventions: An automated application consisting of 1) a web-based dashboard with real-time data on spontaneous breathing trial readiness, sedation depth, sedative infusions, and nudges to wean sedation and ventilatory support and 2) text-message alerts once patients met criteria for a spontaneous breathing trial and spontaneous awakening trial. Pre-intervention, sedation minimization, and ventilator liberation were reviewed daily during a multidisciplinary huddle. Post-intervention, the dashboard was used during the multidisciplinary huddle, throughout the day by respiratory therapists, and text alerts were sent to bedside providers.

Measurements and Main Results: We enrolled 115 subjects in the proof-of-concept study. Spontaneous breathing trial alerts were accurate (98.3%), usually sent while patients were receiving mandatory ventilation (88.5%), and 61.9% of patients received concurrent spontaneous awakening trial alerts. We enrolled 457 subjects in the before-after study, 221 pre-intervention and 236 post-intervention. After implementation, patients were 28% more likely to be extubated (hazard ratio, 1.28; 95% CI, 1.01–1.63; p = 0.042) and 31% more likely to be discharged from the ICU (hazard ratio, 1.31; 95% CI, 1.03–1.67; p = 0.027) at any time point. After implementation, the median duration of mechanical ventilation was 2.20 days (95% CI, 0.09–4.31 d; p = 0.042) shorter and the median ICU length of stay was 2.65 days (95% CI, 0.13–5.16 d; p = 0.040) shorter, compared with the expected durations without the application.

Conclusions: Implementation of an electronic dashboard and alert system promoting sedation minimization and ventilator liberation was associated with reductions in the duration of mechanical ventilation and ICU length of stay.

1Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pennsylvania, Philadelphia, PA.

2Department of Medicine, University of Pennsylvania, Philadelphia, PA.

3Department of Neurology, University of Pennsylvania, Philadelphia, PA.

4Penn Medicine Center for Health Care Innovation, University of Pennsylvania, Philadelphia, PA.

5Department of Radiology, University of Pennsylvania, Philadelphia, PA.

6Penn Medicine Predictive Healthcare, University of Pennsylvania, Philadelphia, PA.

7Penn Medicine Penn Value Improvement, University of Pennsylvania, Philadelphia, PA.

8Respiratory Care Services, University of Pennsylvania, Philadelphia, PA.

9Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA.

10Penn Center for Connected Care, University of Pennsylvania, Philadelphia, PA.

Drs. Anderson and Do contributed equally to this article.

Drs. Do, Chivers, Choi, Gitelman, Draugelis, and Fuchs were involved in study concept and design. Drs. Anderson, Do, and Fuchs were involved in drafting of the article. All authors were involved in acquisition, analysis, and interpretation of the data, and critical revision of the article for important intellectual content

Supplemental digital content is available for this article. Direct URL citations appear in the HTML and PDF versions of this article on the journal’s website (http://journals.lww.com/ccejournal).

Dr. Anderson’s institution received grant support funding from National Institutes of Health (NIH) (HL140482)/National Heart, Lung, and Blood Institute and the American Thoracic Society Foundation, and he received funding from the NIH/National Institute of Neurological Disorders and Stroke (Loan Repayment Grant). Drs. Anderson and Christie (HL115354) received support for article research from the NIH. Dr. Christie’s institution received funding from GlaxoSmithKline and Bristol-Myers Squibb. Dr. Schweickert received funding from Arjo and the American College of Physicians. The remaining authors have disclosed that they do not have any potential conflicts of interest.

For information regarding this article, E-mail: brian.anderson@uphs.upenn.edu

This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Acute respiratory failure requiring mechanical ventilation accounts for a substantial portion of ICU admissions, and 12% of hospital costs, totaling nearly 27 billion dollars annually (12). Daily spontaneous awakening trials (SATs) and spontaneous breathing trials (SBTs), as well as sedation minimization protocols, reduce the duration of mechanical ventilation, tracheostomy rates, ICU and hospital length of stay (LOS), and mortality (3–7). Consequently, sedation minimization and ventilator liberation protocols are key components of the Society of Critical Care Medicine’s Assess, Prevent, and Manage Pain, Both SAT and SBT, Choice of analgesia and sedation, Delirium: Assess, Prevent, and Manage, Early mobility and Exercise, and Family engagement and empowerment (ABCDEF) bundle and ICU Liberation initiatives (8), and the American Thoracic Society/American College of Chest Physicians Clinical Practice Guidelines (910).

Despite their evidence base and inclusion in professional society guidelines, implementation is inconsistent, with some studies revealing only 40–44% compliance performing daily SATs (1112). Audits at our institution similarly revealed that SBT assessments were inconsistent across ICUs, knowledge of our institution’s SBT eligibility criteria was incomplete, extubation delays were frequently related to over-sedation despite sedation minimization strategies, and that manual review of these processes limited real-time feedback.

Because automated applications have been successful at detecting opportunities for improving care in sepsis, acute respiratory distress syndrome (ARDS) and acute kidney injury (13–16), we hypothesized that an automated application could improve adherence to sedation minimization and ventilator liberation protocols. We designed a novel software platform, the Awakening and Breathing Coordination (ABC) Application, which continuously screens patients for opportunities to minimize sedation and speed ventilator liberation, and is coupled with a dashboard and text-message alerts to inform bedside providers when an opportunity is identified.

In this study, we report the results of a proof-of-concept study and before-after implementation study assessing the impact of the ABC application.

Back to Top | Article Outline

MATERIALS AND METHODS

The ABC Application

The ABC application is a software platform that continuously screens charted data in the electronic health record (EHR), including nursing flowsheets, respiratory flowsheets, and medication administration records, and runs the data through locally developed algorithms to determine if patients meet criteria to undergo sedation minimization and ventilator liberation (Fig. S1 and Table S1, Supplemental Digital Content 1, http://links.lww.com/CCX/A107). The results are communicated through a web-based dashboard and text-message alerts to bedside providers (Fig. 1). The web-based dashboard displays real-time SBT eligibility (based on our institution’s ventilator liberation protocol [Table S1, Supplemental Digital Content 1, http://links.lww.com/CCX/A107]), sedation depth (Richmond Agitation-Sedation Scale [RASS]) (17), and sedative infusions for each patient. For patients not meeting SBT criteria, the dashboard displays the reason an SBT is not recommended and displays nudges to wean oxygen, positive end-expiratory pressure, and vasopressors as appropriate. The dashboard also displays a nudge to wean sedation in patients with a RASS less than or equal to –1 who are receiving sedative infusions (Fig. 1A). In addition to the dashboard, text-message alerts are sent to bedside providers when patients newly meet SBT and SAT eligibility (Fig. 1B).

Figure 1.

Figure 1.

Back to Top | Article Outline

Proof-of-Concept Study

We performed a proof-of-concept study in the ICUs of three university-affiliated hospitals, enrolling all mechanically ventilated patients who triggered an ABC application text-message alert from August 20, 2016, to September 10, 2016 (Table S2, Supplemental Digital Content 1, http://links.lww.com/CCX/A107). Alerts were deemed accurate if all the prespecified criteria were documented in the EHR at the time of the alert. SBT alerts were deemed valuable if they fired while the patient was receiving mandatory ventilation (i.e., Assist-Control). We evaluated perceived barriers to extubation to ensure the alerts were not solely identifying patients who remained ventilated for valid clinical reasons. SAT alert value was measured by how frequently it fired in the SBT alerted population, reflecting an opportunity for earlier sedative weaning, and by the sedation depth at the time of the SAT alert, as more deeply sedated SBT-eligible patients may fail an SBT due to over-sedation and may receive greater benefit from sedation interruption.

Back to Top | Article Outline

Before-After Study

We performed a before-after study of 457 mechanically ventilated patients admitted to the medical ICU at the Hospital of the University of Pennsylvania. We excluded patients with preexisting tracheostomies and overflow patients from nonstudy ICUs (Fig. S2, Supplemental Digital Content 1, http://links.lww.com/CCX/A107). This study was exempt on the basis of quality improvement by the University of Pennsylvania Institutional Review Board.

Pre-implementation (May 1, 2016, to September 25, 2016) the ABC application ran silently, and sedation minimization and ventilator liberation were performed according to existing protocols. Nurses titrated sedatives to the goal RASS defined by the medical team and respiratory therapists screened patients for SBT eligibility daily. A multidisciplinary huddle occurred each morning during which respiratory therapists reviewed each patient’s SBT eligibility and SBT results, and nurses reviewed each patient’s sedative infusions. The medical team made decisions on sedation minimization and ventilator liberation, which were then implemented independent of the team’s in-depth rounds.

Post-implementation (September 26, 2016, to February 1, 2017) the ABC application promoted compliance with existing protocols and provided continuous screening for sedation and ventilator weaning opportunities. The ABC dashboard was reviewed each morning at the multidisciplinary huddle and by respiratory therapists throughout the day. Respiratory therapists and nurses received the SBT and SAT text-message alerts and were instructed to act on the alert if clinically relevant or discuss it with the medical team. If a patient did not formally meet the application’s SBT criteria but was deemed SBT-ready based on clinical judgment, providers were instructed to use standard protocols.

In our primary analyses, we used Cox proportional hazards regression to test for differences in the primary outcomes of time to extubation, time to ICU discharge, and time to hospital discharge. We adjusted for illness severity (Acute Physiology and Chronic Health Evaluation [APACHE] IV score) (18) and receipt of vasopressors. Patients were censored at the time of death or transfer to a nonstudy ICU in all analyses and censored at the time of tracheostomy in the time to extubation analysis. In complementary analyses, we used interrupted time-series analysis (ITSA) with data aggregated by week to test for a difference in each outcome when comparing the postintervention period with the counterfactual scenario (1920). We used a level and slope change model, hypothesizing that implementation of the application would cause an immediate change in each outcome and change the slope of each outcome over time as implementation improved. For the ITSA, we excluded patients transferred to a nonstudy ICU while still receiving mechanical ventilation and excluded outliers that appeared to bias the pre-intervention trend away from the null. We performed sensitivity analyses without removing outliers and separately assuming the preintervention trend did not persist in the postintervention period.

Secondarily, we compared 48-hour reintubation rates to ensure the ABC application did not lead to unsafe extubations and compared the time to extubation among patients who never formally met SBT criteria to ensure the ABC application did not delay extubation based on clinical judgment alone. We explored the mechanisms through which the ABC application might have had an impact by comparing the time from initiation of invasive ventilation to meeting SBT criteria, time to cessation of continuous sedative infusions, and time from SBT alert to extubation.

Analyses were performed in Stata Version 15.1 (StataCorp, College Station, TX), and a two-sided p value of less than 0.05 was considered statistically significant. Detailed methods are provided in the supplementary online content (Supplemental Digital Content 1, http://links.lww.com/CCX/A107).

Back to Top | Article Outline

RESULTS

Proof-of-Concept Study

We evaluated 115 SBT alerts and 70 SAT alerts. All alerts fired accurately when evaluated against the EHR; only two SBT alerts (1.7%) were inaccurate and resulted from erroneous documentation of ongoing mechanical ventilation after extubation. Overall, the SBT alerts appeared valuable; 100 fired (88.5%) when the patient was still receiving mandatory ventilation and 13 fired when the patient was weaned but not yet extubated. Most patients, 60.2%, had no perceived barriers to extubation, suggesting the alert was not solely identifying patients who remained intubated for clinical reasons. Of the 45 patients with a barrier to extubation, 21 (46.7%) were due to over-sedation. The SAT alerts also appeared valuable; 70 of 113 SBT eligible patients (61.9%) received a concurrent SAT alert (indicating ongoing sedative infusion and RASS < 0), demonstrating an opportunity for earlier sedation minimization. Furthermore, 71.4% of SAT alerts were in moderately sedated patients (RASS ≤ –2), with 24.3% in deeply sedated patients (RASS ≤ –4).

Back to Top | Article Outline

Patient Characteristics in the Before-After Study

We enrolled 221 patients in the preintervention period and 236 in the postintervention period (Fig. S2, Supplemental Digital Content 1, http://links.lww.com/CCX/A107); clinical characteristics are shown in Table 1. Baseline severity of illness (APACHE IV) increased throughout the study (Fig. S3, Supplemental Digital Content 1, http://links.lww.com/CCX/A107) and was significantly higher post-intervention (93 [interquartile range (IQR), 74–116] vs 83 [IQR, 63.5–105]; p < 0.001). The proportions of patients who received an SBT alert were similar in both periods and averaged 1.2 alerts/day in the postintervention period.

TABLE 1.

TABLE 1.

Back to Top | Article Outline

Duration of Mechanical Ventilation

Extubation rates were similar in the two groups, 61.9% post-intervention and 57.5% pre-intervention (p = 0.82). However, the time to extubation was shorter after the ABC application was implemented. As shown in Figure 2A, patients were 28% more likely to be extubated at any time point after implementation, when adjusted for illness severity and receipt of vasopressors (hazard ratio [HR], 1.28; 95% CI, 1.01–1.63; p = 0.042). To ensure the reduced duration of mechanical ventilation was not due to a preexisting temporal trend, we performed an ITSA. We excluded five patients with prolonged duration of mechanical ventilation during the preintervention period (four > 50 d, one > 30 d) to prevent these outliers from increasing the preintervention duration of mechanical ventilation in a biased fashion. As shown in Figure 2B, the median duration of mechanical ventilation rose slightly during the preintervention period, followed by an immediate step-down and slight flattening of the trend post-intervention. Midway through the postintervention period (week 30), the median duration of mechanical ventilation was 2.20 days (95% CI, 0.09–4.31 d) shorter compared with the expected duration, ranging from 1.9 days shorter immediately after implementation to 2.5 days shorter near the end of the study (Table S3, Supplemental Digital Content 1, http://links.lww.com/CCX/A107). Results were similar in a sensitivity analysis including outliers (Fig. S4 and Table S3, Supplemental Digital Content 1, http://links.lww.com/CCX/A107) and remained significant (1.39 d [95% CI, 0.04–2.74 d] at week 30) when assuming the upward trend in the preintervention period did not persist post-intervention (Fig. S5 and Table S3, Supplemental Digital Content 1, http://links.lww.com/CCX/A107). We assessed for potential bias from variations in the time to death and time to tracheostomy pre- and post-intervention and found no significant difference in time to death (HR, 0.90; 95% CI, 0.64–1.27; p = 0.55) or time to tracheostomy (HR, 0.95; 95% CI, 0.43–2.07; p = 0.90).

Figure 2.

Figure 2.

Back to Top | Article Outline

ICU LOS

ICU mortality was similar in the two groups, 31.8% post-intervention and 35.3% pre-intervention (p = 0.70). However, ICU LOS was significantly shorter in the postintervention period. As shown in Figure 3A, patients were 31% more likely to be discharged from the ICU alive at any time point after implementation, when adjusted for illness severity and receipt of vasopressors (HR, 1.31; 95% CI, 1.03–1.67; p = 0.027). We found similar results using an ITSA. To ensure outliers did not increase the ICU LOS in the preintervention period in a biased fashion, we excluded two patients in the preintervention period with very long ICU stays (> 115 d and > 70 d). As shown in Figure 3B, the ICU LOS trended slightly upward throughout the preintervention period, followed by an immediate decrease and slight downtrend post-intervention. Midway through the postintervention period (week 30) the median ICU LOS was 2.65 days (95% CI, 0.13–5.16 d) shorter compared with the expected duration, ranging from 2.1 days shorter immediately after implementation to 3.2 days shorter near the end of the study (Table S4, Supplemental Digital Content 1, http://links.lww.com/CCX/A107). Results were similar in a sensitivity analysis including the outliers (Fig. S6 and Table S4, Supplemental Digital Content 1, http://links.lww.com/CCX/A107) and remained significant (1.85 d shorter [95% CI, 0.25–3.46 d] at week 30) when assuming the preexisting upward trend did not persist in the postintervention period (Fig. S7 and Table S4, Supplemental Digital Content 1, http://links.lww.com/CCX/A107). We assessed for potential bias from differences in the time to death, and time to ICU discharge among patients discharged to a long-term ventilator hospital in the preintervention and postintervention periods. There was no difference in time to death between the two groups (HR, 0.89; 95% CI, 0.65–1.23; p = 0.48). Seven patients (three pre-intervention, four post-intervention) underwent a tracheostomy and were discharged to a long-term ventilator hospital. These patients appeared to have a shorter ICU LOS in the postintervention period (median 22.3 vs 60.5 d); however, our results were similar when we excluded these patients in a sensitivity analysis (Fig. S8 and Table S4, Supplemental Digital Content 1, http://links.lww.com/CCX/A107).

Figure 3.

Figure 3.

Back to Top | Article Outline

Hospital LOS and Secondary Outcomes

Hospital mortality was similar in the postintervention (39.8%) and preintervention (42.1%) periods (p = 0.48), and hospital LOS was not significantly different post-intervention (Fig. S9, Supplemental Digital Content 1, http://links.lww.com/CCX/A107) (HR, 1.15; 95% CI, 0.90–1.47; p = 0.26). We found no difference in 48-hour reintubation rates (10.6% and 9.5%; p = 0.70). There was also no difference in the rate of successful extubation (35.0% compared with 29.3%; p = 0.79) or time to extubation (HR, 0.90; 95% CI, 0.51–1.61; p = 0.73) among patients who never formally met the ABC application’s SBT criteria.

In terms of the mechanisms through which the ABC application might improve outcomes, the time from meeting SBT criteria to extubation (HR, 1.27; 95% CI, 0.99–1.65; p = 0.065) and the time to cessation of sedative infusions (HR, 1.29; 95% CI, 0.98–1.70; p = 0.070) both appeared shorter after implementation, although neither was statistically significant (Fig. 4).

Figure 4.

Figure 4.

Back to Top | Article Outline

DISCUSSION

In this study, we demonstrate proof-of-concept that an EHR-based dashboard and text-alert system can identify opportunities to improve sedation minimization and ventilator liberation. Further, we have shown that implementation of such a system was associated with reductions in the duration of mechanical ventilation and ICU LOS in an ICU with existing sedation minimization and ventilator liberation protocols.

To date, numerous studies have reported improved outcomes with sedation minimization and ventilator liberation protocols, often in the context of clinical trials (3–6). However, outside of clinical trials, implementation of ABCDEF bundle components is often challenging and incomplete (1112). Our results add to a growing number of studies that have demonstrated improved patient outcomes by focusing on improving implementation of the ABCDEF bundle through quality improvement initiatives (21–24).

Our data suggest the ABC application improved outcomes through reductions in the time from being SBT ready to extubation and time to cessation of continuous sedative infusions. However, these analyses did not meet statistical significance and the mechanisms by which the ABC application improved outcomes are not entirely clear. A recent review codified the many barriers to ABCDEF bundle implementation (25), including several barriers we identified at our institution. This includes unclear protocol criteria, ineffective interprofessional care coordination, communication barriers, and strained workload and time. It may be that the ABC application helps providers overcome many of these barriers. The automated screening may decrease the workload for bedside providers. The dashboard displaying real-time sedation depth in relation to ventilator status might facilitate clinical decision-making, promote staff accountability, and improve knowledge of protocols. Finally, the text-message alerts may reduce communication barriers and promote interprofessional team coordination. Additional studies are needed to better understand the potential mechanisms through which the ABC application improved outcomes and assess any barriers to the ABC application’s implementation.

Based on its success in our single ICU before-after study, the ABC application has been employed across our health system and validation of our findings in a larger study is underway. Future studies will also seek to expand the application’s technology to improve other aspects of ABCDEF bundle implementation, such as delirium management and early mobilization, and improve implementation of other evidence-based practices, such as lung-protective ventilation in ARDS.

Our study has several strengths. First, our institution had preexisting sedation minimization and ventilator liberation protocols in place prior to implementation of the ABC application. Second, no other quality improvement projects related to sedation minimization or ventilator liberation were undertaken during this study. Last, the ABC application is portable to other EHRs, straightforward and requires minimal training for bedside users, suggesting it could easily be expanded and implemented at other sites.

Our study has several limitations that are worth noting. The before-after study design could be prone to bias, specifically temporal trends. However, we performed interrupted time-series analyses to evaluate temporal trends and found a slight uptrend in the duration of mechanical ventilation and ICU LOS before our intervention. The reasons for this increase over time are not clear but may be related to the increasing severity of illness throughout the study period, and our findings overall suggest the improvements in the postintervention period were not due to preexisting downward trends. As mentioned, we found that the baseline severity of illness increased throughout the study, and although we adjusted for severity of illness, other unmeasured confounders could have influenced our results given our nonrandomized study design. Our study was performed in a single quaternary-care ICU, and therefore, our findings require validation in a larger study. In addition, our study was designed to assess the short-term impact of the intervention and future studies are needed to evaluate whether the intervention’s impact is sustained. In the proof-of-concept study, we focused on ensuring the alerts were accurate, and we did not formally assess the sensitivity of the alert; therefore, it is possible that additional opportunities for earlier sedation weaning and ventilator liberation were missed. Although we demonstrated reductions in the duration of mechanical ventilation and ICU LOS, our study was not powered to detect differences in mortality or rates of tracheostomy as shown in prior studies (57). In addition, our study was not designed to measure other ventilator-associated events such as delirium or ventilator-associated pneumonia.

Back to Top | Article Outline

CONCLUSIONS

In conclusion, we describe an electronic dashboard and text-alert system designed to promote sedation minimization and ventilator liberation and demonstrate its clinical impact through reductions in the duration of mechanical ventilation and ICU LOS. Future studies should seek to leverage similar technology to improve implementation of other evidence-based practices.

Back to Top | Article Outline

ACKNOWLEDGMENTS

We would like to acknowledge contributions from Penn Medicine’s Department of Data Science, Center for Healthcare Innovation, Information Services, and PENN Elert in the development of the Awakening and Breathing Coordination (ABC) application. We also thank the nurses, pharmacists, respiratory therapists, and physicians in the Medical ICU of the Hospital of the University of Pennsylvania for their invaluable support with implementing the ABC application.

Back to Top | Article Outline

REFERENCES

1. Wunsch H, Linde-Zwirble WT, Angus DC, et al. The epidemiology of mechanical ventilation use in the United States.Crit Care Med2010381947–1953
2. Barrett ML, Smith MW, Elixhauser A, et al. Utilization of Intensive Care Services, 20112014Rockville, MDAgency for Healthcare Research and QualityHCUP Statistical Brief #185
3. Girard TD, Kress JP, Fuchs BD, et al. Efficacy and safety of a paired sedation and ventilator weaning protocol for mechanically ventilated patients in intensive care (awakening and breathing controlled trial): A randomised controlled trial.Lancet2008371126–134
4. Kress JP, Pohlman AS, O’Connor MF, et al. Daily interruption of sedative infusions in critically ill patients undergoing mechanical ventilation.N Engl J Med20003421471–1477
5. Minhas MA, Velasquez AG, Kaul A, et al. Effect of protocolized sedation on clinical outcomes in mechanically ventilated intensive care unit patients: A systematic review and meta-analysis of randomized controlled trials.Mayo Clin Proc201590613–623
6. Strøm T, Martinussen T, Toft P. A protocol of no sedation for critically ill patients receiving mechanical ventilation: A randomised trial.Lancet2010375475–480
7. Pun BT, Balas MC, Barnes-Daly MA, et al. Caring for critically ill patients with the ABCDEF bundle: Results of the ICU liberation collaborative in over 15,000 adults.Crit Care Med2019473–14
8. Ely EW. The ABCDEF bundle: Science and philosophy of how ICU liberation serves patients and families.Crit Care Med201745321–330
9. Girard TD, Alhazzani W, Kress JP, et al.; ATS/CHEST Ad Hoc Committee on Liberation from Mechanical Ventilation in AdultsAn official American Thoracic Society/American College of Chest Physicians clinical practice guideline: Liberation from mechanical ventilation in critically ill adults. Rehabilitation protocols, ventilator liberation protocols, and cuff leak tests.Am J Respir Crit Care Med2017195120–133
10. Ouellette DR, Patel S, Girard TD, et al. Liberation from mechanical ventilation in critically ill adults: An official American College of Chest Physicians/American Thoracic Society clinical practice guideline: Inspiratory pressure augmentation during spontaneous breathing trials, protocols minimizing sedation, and noninvasive ventilation immediately after extubation.Chest2017151166–180
11. Patel RP, Gambrell M, Speroff T, et al. Delirium and sedation in the intensive care unit: Survey of behaviors and attitudes of 1384 healthcare professionals.Crit Care Med200937825–832
12. Tanios MA, de Wit M, Epstein SK, et al. Perceived barriers to the use of sedation protocols and daily sedation interruption: A multidisciplinary survey.J Crit Care20092466–73
13. Henry KE, Hager DN, Pronovost PJ, et al. A targeted real-time early warning score (TREWScore) for septic shock.Sci Transl Med20157299ra122
14. Sawyer AM, Deal EN, Labelle AJ, et al. Implementation of a real-time computerized sepsis alert in nonintensive care unit patients.Crit Care Med201139469–473
15. Umscheid CA, Betesh J, VanZandbergen C, et al. Development, implementation, and impact of an automated early warning and response system for sepsis.J Hosp Med20151026–31
16. Wilson FP, Shashaty M, Testani J, et al. Automated, electronic alerts for acute kidney injury: A single-blind, parallel-group, randomised controlled trial.Lancet20153851966–1974
17. Ely EW, Truman B, Shintani A, et al. Monitoring sedation status over time in ICU patients: Reliability and validity of the Richmond Agitation-Sedation Scale (RASS).JAMA20032892983–2991
18. Zimmerman JE, Kramer AA, McNair DS, et al. Acute Physiology and Chronic Health Evaluation (APACHE) IV: Hospital mortality assessment for today’s critically ill patients.Crit Care Med2006341297–1310
19. Bernal JL, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: A tutorial.Int J Epidemiol201746348–355
20. Linden A. A comprehensive set of post-estimation measures to enrich interrupted time series analysisStata J20171773–88
21. Barnes-Daly MA, Phillips G, Ely EW. Improving hospital survival and reducing brain dysfunction at seven california community hospitals: Implementing PAD guidelines via the ABCDEF bundle in 6,064 patients.Crit Care Med201745171–178
22. Kram SL, DiBartolo MC, Hinderer K, et al. Implementation of the ABCDE bundle to improve patient outcomes in the intensive care unit in a rural community hospital.Dimens Crit Care Nurs201534250–258
23. Balas MC, Vasilevskis EE, Olsen KM, et al. Effectiveness and safety of the awakening and breathing coordination, delirium monitoring/management, and early exercise/mobility bundle.Crit Care Med2014421024–1036
24. Hsieh SJ, Otusanya O, Gershengorn HB, et al. Staged implementation of awakening and breathing, coordination, delirium monitoring and management, and early mobilization bundle improves patient outcomes and reduces hospital costs.Crit Care Med201947885–893
25. Costa DK, White MR, Ginier E, et al. Identifying barriers to delivering the awakening and breathing coordination, delirium, and early exercise/mobility bundle to minimize adverse outcomes for mechanically ventilated patients: A systematic review.Chest2017152304–311
Keywords:

ABCDEF bundle; electronic dashboard; sedation minimization; spontaneous awakening trial; spontaneous breathing trial

Supplemental Digital Content

Back to Top | Article Outline
Copyright © 2019 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.