Cognitive Aids for the Management of Deteriorating Surgical Patients
NCT ID: NCT03812861
Last Updated: 2019-01-23
Study Results
Results pending
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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Recruitment Status
COMPLETED
Clinical Phase
NA
Total Enrollment
50 participants
Study Classification
INTERVENTIONAL
Study Start Date
2017-02-07
Study Completion Date
2018-12-18
Brief Summary
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Background and Goal of Study: Adherence to best practice management of emergencies improves through the use of cognitive aids. Aim of this study was to develop and validate cognitive aids for management of deteriorating surgical ward patients (CAMDS) in order to improve adherence to best practice and hereby reduce the likelihood of failure to rescue.
Materials and Methods: Fifty surgical teams will be randomly assigned to manage 150 standardised high fidelity simulation cases of deteriorating patients using the CAMDS or not. There are 10 standardised patient scenarios; pneumonia, pneumothorax, bradycardia, cardiac arrest shockable and non-shockable rhythm, bleeding, myocardial infarction, anaphylaxis, sepsis and loss of consciousness. Two independent observers will score the team's performance in adhering to all the management steps. To assess perceived usability of the CAMDS participants will be asked about eight aspects of the CAMDS. These items will be scored on a Likert scale (0= strongly disagree to 4= strongly agree).
Materials and Methods: Fifty surgical teams will be randomly assigned to manage 150 standardised high fidelity simulation cases of deteriorating patients using the CAMDS or not. There are 10 standardised patient scenarios; pneumonia, pneumothorax, bradycardia, cardiac arrest shockable and non-shockable rhythm, bleeding, myocardial infarction, anaphylaxis, sepsis and loss of consciousness. Two independent observers will score the team's performance in adhering to all the management steps. To assess perceived usability of the CAMDS participants will be asked about eight aspects of the CAMDS. These items will be scored on a Likert scale (0= strongly disagree to 4= strongly agree).
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Detailed Description
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INTRODUCTION AND RATIONALE
The suboptimal management of deteriorating surgical patients is an important factor in preventable death and morbidity in hospitals. Several studies have shown that the mortality rate in different hospitals is not associated with different complication rates between these hospitals but with the ability to effectively rescue patients from these complications. This has been called failure to rescue. Misapplication of the early warning score, failure to recognize a deteriorating patient, delays in seeking senior advice and delays in adequate management or inadequate resuscitation are found to be important factors. Strategies focusing on the management of complications once they occur may be essential to improve outcomes.
Recent publications emphasized human factors as a cause that contributed towards failure to rescue. Medical staff often fails to recognize a deteriorating patient. Partly because there is lack of insight in the development of a critically illness. Ludikhuize showed that care-providers mostly rate their care, provided to patients in the hours preceding a life-threatening adverse event, as good. However, independent experts felt that patients often could have been identified as deteriorating, much earlier. It does not, however, seem wholly unexpected that the assessment of a deteriorating patient by an experienced ICU consultant is superior to the assessment made by a ward nurse or junior surgical doctor.
Another important cause of failure to rescue was the failure to react promptly tot a deterioration in care. It has been reported that the Rapid Response Team (RRT) was called in only 30% of cases when criteria for activating the RRT were fulfilled. Sometimes because of an unclear escalation policy, sometimes because of self-doubt and insecurity of the care provider or because of hierarchical barriers.
It is known that the management of intraoperative emergencies improves through the use of cognitive aids.These cognitive aids remind practitioners to best practice management of these emergencies and hereby increase adherence to these practices. Because the CAMDS will assist surgical staff at the bedside in the assessment of deteriorating surgical patients and prompt best practice management of specific complications it is likely that failure to rescue will also decrease. The CAMDS can furthermore prompt a nurse or junior doctor to liaise with seniors and/or critical care staff. Because they can communicate a differential diagnosis and management steps taken so far from the CAMDS this might decrease self-doubt and insecurity in liaising with seniors or critical care staff. A, clear escalation policy on the CAMDS, embraced by the hospital can further assist in the timely escalation of care and breakdown of hierarchical barriers. This will result in a decrease of the likelihood of failure to rescue.
OBJECTIVES
Primary Objective is to answer the following research questions:
Will the correct application of the CAMDS improve adherence (measured by the omission of critical steps) to best practice management of perioperative complications in surgical patients?
Secondary Objective is to validate the CAMDS in terms of user perceived usability.
STUDY DESIGN Randomized study comparing adherence rates to best practice management of patients with a perioperative complication in a high fidelity simulation session with and without the use of the CAMDS.
The investigators will develop and validate cognitive aids for the assessment and management of deteriorating surgical patients (CAMDS). These CAMDS contain instructions for doctors and nursing staff to assess, manage and escalate care of deteriorating surgical patients. These management instructions will be derived from best practices that are linked with improved mortality and morbidity in surgical patients. The cognitive aids will be developed in an expert team of 2 surgical consultants, 2 surgical registrars (one junior and one senior), 3 nurses from a surgical ward, 1 critical care consultant, 2 anaesthetic consultants and an anaesthetic registrar. The content of the CAMDS and accompanying evidence will be determined within this team. The design of the CAMDS will be done by adaptation of the local emergency manual, which is a bundle of cognitive aids for intraoperative emergencies adapted from the Stanford Emergency Manual (with permission). The design for this bundle has been thoroughly tested. The simulation scenarios will be based upon the 10 different conditions that are in the CAMDS. Scenarios will be tested and validated through a pilot study.
STUDY POPULATION Population (base) Surgical doctors from the surgical departments of several Dutch hospitals will be included in the study. Doctors and nurses will be assigned to teams and randomised to a management scenario with the use of the CAMDS or without the use of the CAMDS. They will have to give individual consent to participate in the study and are only allowed to participate in the study once.
Sample size calculation Sample size calculation is based on a cluster-randomized design. No previous data on the effectiveness of CAMDS is available, thus no formal power analysis was possible. Available data on the use of cognitive aids in simulated crisis scenarios in the operating theatre shows a baseline omission of critical steps of about 75%.The investigators therefore estimate that the correct application of the CAMDS will reduce the omission of critical steps with 50%. Each team will run through three scenarios and will randomised to complete the scenario with or without the CAMDS. Across these three scenarios participants will be measured on a total of 45 (15 per scenario) process measures for adherence. Based on this effect size and an estimated intra-cluster correlation coefficient within teams of 0.1 and a mean cluster size of 45, with a two-sided alpha level of 0.05 and 80% power, 25 surgical teams per study arm are needed.
METHODS
Main study parameter/endpoint:
Failure to adhear to best practice (omission of critical management steps) for the given scenarios, as predefined by the team that developed the CAMDS.
Secondary study parameters/endpoints (if applicable):
Perceived utility, ease of use and user satisfaction of the CAMDS. Eight aspects of perceived usability; ease of use, logical order of described management steps, readability of the CAMDS, whether the CAMDS provided overview, interrupted treatment, improved treatment, recommendation to use and suitability for daily use, will be assessed through a survey. These items will be scored on a five-point Likert scale (strongly agree to strongly disagree). Completion of the questionnaires will be voluntary and no compensation of any kind will be provided.
Randomisation, blinding and treatment allocation This is a prospective randomised, non-blinded study. Surgical teams will be randomised through a computer generated code in sealed opaque envelopes to the CAMDS group or non CAMDS group. Randomisation will take place only after the teams have been made familiar with the cognitive aid bundle and the high fidelity simulation laboratory, so during the introduction study staff and participants will be unaware of allocation.
Study procedures Surgical teams will be asked to manage a simulated scenario of a deteriorating surgical patient. The simulated scenario will take place in the high fidelity simulator of the Academic Medical Centre Amsterdam and will be recorded on video. Two independent observers will score the key processes for managing the specific scenarios. Interrater reliability will be assessed with Cohen's Kappa. There are three independent EuSim trained simulation laboratory operators (CHSOS) who will run the simulated patient, the Laerdal SimMan 3G. Ten standardised patient cases- pneumonia, pneumothorax, bradycardia, cardiac arrest shockable and non-shockable rhythm, bleeding, myocardial infarction, anaphylaxis, sepsis and loss of consciousness- were preprogrammed for the study. So a correct action resulted in progression in the scenario.
Withdrawal of individual subjects Not applicable.
Premature termination of the study The study will be terminated after enclosure of the last participating surgical team (n=50)
STATISTICAL ANALYSIS Will be performed using SPSS statistics. All data will be checked for normal distribution using the Kolmogorov-Smirnov test and histograms. For normal distributed, continuous variables, an independent Student´s t-test will be used and the variables will be presented as mean ± standard deviation (SD). A p-value \<0.05 will be considered as statistically significant. For categorical variables, cross tabulation and the Pearson chi square test will be applied and variables will be allegorized as number and/or percentage of the total. Not normally distributed data will be compared using the Man-Whitney U-test where appropriate, and data will be presented by the median and the interquartile range. For the primary outcome measure univariate analysis to test failure rates (percentage omitted critical steps). Multivariate analysis will also be done to compare failure rates with and without the CAMDS. Descriptive statistics will be used to describe perceived usability.
No interim analysis will be done
Handling and storage of data and documents Video data from the simulated scenarios will be stored on a password protected folder in a computer drive only available by the investigators. All questionnaires will be anonymously collected and electronic copies of the files will be stored in the same folder as the video data. Participants will be asked to fill in a training grade to allow stratification of the data. The study staff will ensure that the participants' anonymity is maintained. All documents will be stored securely and only accessible by study staff. The trial will comply with the Data Protection Act, which requires data to be anonymised as soon as it is practical to do so.
This study is funded by an Innovation Grant from the Academic Medical Centre, Amsterdam.
The suboptimal management of deteriorating surgical patients is an important factor in preventable death and morbidity in hospitals. Several studies have shown that the mortality rate in different hospitals is not associated with different complication rates between these hospitals but with the ability to effectively rescue patients from these complications. This has been called failure to rescue. Misapplication of the early warning score, failure to recognize a deteriorating patient, delays in seeking senior advice and delays in adequate management or inadequate resuscitation are found to be important factors. Strategies focusing on the management of complications once they occur may be essential to improve outcomes.
Recent publications emphasized human factors as a cause that contributed towards failure to rescue. Medical staff often fails to recognize a deteriorating patient. Partly because there is lack of insight in the development of a critically illness. Ludikhuize showed that care-providers mostly rate their care, provided to patients in the hours preceding a life-threatening adverse event, as good. However, independent experts felt that patients often could have been identified as deteriorating, much earlier. It does not, however, seem wholly unexpected that the assessment of a deteriorating patient by an experienced ICU consultant is superior to the assessment made by a ward nurse or junior surgical doctor.
Another important cause of failure to rescue was the failure to react promptly tot a deterioration in care. It has been reported that the Rapid Response Team (RRT) was called in only 30% of cases when criteria for activating the RRT were fulfilled. Sometimes because of an unclear escalation policy, sometimes because of self-doubt and insecurity of the care provider or because of hierarchical barriers.
It is known that the management of intraoperative emergencies improves through the use of cognitive aids.These cognitive aids remind practitioners to best practice management of these emergencies and hereby increase adherence to these practices. Because the CAMDS will assist surgical staff at the bedside in the assessment of deteriorating surgical patients and prompt best practice management of specific complications it is likely that failure to rescue will also decrease. The CAMDS can furthermore prompt a nurse or junior doctor to liaise with seniors and/or critical care staff. Because they can communicate a differential diagnosis and management steps taken so far from the CAMDS this might decrease self-doubt and insecurity in liaising with seniors or critical care staff. A, clear escalation policy on the CAMDS, embraced by the hospital can further assist in the timely escalation of care and breakdown of hierarchical barriers. This will result in a decrease of the likelihood of failure to rescue.
OBJECTIVES
Primary Objective is to answer the following research questions:
Will the correct application of the CAMDS improve adherence (measured by the omission of critical steps) to best practice management of perioperative complications in surgical patients?
Secondary Objective is to validate the CAMDS in terms of user perceived usability.
STUDY DESIGN Randomized study comparing adherence rates to best practice management of patients with a perioperative complication in a high fidelity simulation session with and without the use of the CAMDS.
The investigators will develop and validate cognitive aids for the assessment and management of deteriorating surgical patients (CAMDS). These CAMDS contain instructions for doctors and nursing staff to assess, manage and escalate care of deteriorating surgical patients. These management instructions will be derived from best practices that are linked with improved mortality and morbidity in surgical patients. The cognitive aids will be developed in an expert team of 2 surgical consultants, 2 surgical registrars (one junior and one senior), 3 nurses from a surgical ward, 1 critical care consultant, 2 anaesthetic consultants and an anaesthetic registrar. The content of the CAMDS and accompanying evidence will be determined within this team. The design of the CAMDS will be done by adaptation of the local emergency manual, which is a bundle of cognitive aids for intraoperative emergencies adapted from the Stanford Emergency Manual (with permission). The design for this bundle has been thoroughly tested. The simulation scenarios will be based upon the 10 different conditions that are in the CAMDS. Scenarios will be tested and validated through a pilot study.
STUDY POPULATION Population (base) Surgical doctors from the surgical departments of several Dutch hospitals will be included in the study. Doctors and nurses will be assigned to teams and randomised to a management scenario with the use of the CAMDS or without the use of the CAMDS. They will have to give individual consent to participate in the study and are only allowed to participate in the study once.
Sample size calculation Sample size calculation is based on a cluster-randomized design. No previous data on the effectiveness of CAMDS is available, thus no formal power analysis was possible. Available data on the use of cognitive aids in simulated crisis scenarios in the operating theatre shows a baseline omission of critical steps of about 75%.The investigators therefore estimate that the correct application of the CAMDS will reduce the omission of critical steps with 50%. Each team will run through three scenarios and will randomised to complete the scenario with or without the CAMDS. Across these three scenarios participants will be measured on a total of 45 (15 per scenario) process measures for adherence. Based on this effect size and an estimated intra-cluster correlation coefficient within teams of 0.1 and a mean cluster size of 45, with a two-sided alpha level of 0.05 and 80% power, 25 surgical teams per study arm are needed.
METHODS
Main study parameter/endpoint:
Failure to adhear to best practice (omission of critical management steps) for the given scenarios, as predefined by the team that developed the CAMDS.
Secondary study parameters/endpoints (if applicable):
Perceived utility, ease of use and user satisfaction of the CAMDS. Eight aspects of perceived usability; ease of use, logical order of described management steps, readability of the CAMDS, whether the CAMDS provided overview, interrupted treatment, improved treatment, recommendation to use and suitability for daily use, will be assessed through a survey. These items will be scored on a five-point Likert scale (strongly agree to strongly disagree). Completion of the questionnaires will be voluntary and no compensation of any kind will be provided.
Randomisation, blinding and treatment allocation This is a prospective randomised, non-blinded study. Surgical teams will be randomised through a computer generated code in sealed opaque envelopes to the CAMDS group or non CAMDS group. Randomisation will take place only after the teams have been made familiar with the cognitive aid bundle and the high fidelity simulation laboratory, so during the introduction study staff and participants will be unaware of allocation.
Study procedures Surgical teams will be asked to manage a simulated scenario of a deteriorating surgical patient. The simulated scenario will take place in the high fidelity simulator of the Academic Medical Centre Amsterdam and will be recorded on video. Two independent observers will score the key processes for managing the specific scenarios. Interrater reliability will be assessed with Cohen's Kappa. There are three independent EuSim trained simulation laboratory operators (CHSOS) who will run the simulated patient, the Laerdal SimMan 3G. Ten standardised patient cases- pneumonia, pneumothorax, bradycardia, cardiac arrest shockable and non-shockable rhythm, bleeding, myocardial infarction, anaphylaxis, sepsis and loss of consciousness- were preprogrammed for the study. So a correct action resulted in progression in the scenario.
Withdrawal of individual subjects Not applicable.
Premature termination of the study The study will be terminated after enclosure of the last participating surgical team (n=50)
STATISTICAL ANALYSIS Will be performed using SPSS statistics. All data will be checked for normal distribution using the Kolmogorov-Smirnov test and histograms. For normal distributed, continuous variables, an independent Student´s t-test will be used and the variables will be presented as mean ± standard deviation (SD). A p-value \<0.05 will be considered as statistically significant. For categorical variables, cross tabulation and the Pearson chi square test will be applied and variables will be allegorized as number and/or percentage of the total. Not normally distributed data will be compared using the Man-Whitney U-test where appropriate, and data will be presented by the median and the interquartile range. For the primary outcome measure univariate analysis to test failure rates (percentage omitted critical steps). Multivariate analysis will also be done to compare failure rates with and without the CAMDS. Descriptive statistics will be used to describe perceived usability.
No interim analysis will be done
Handling and storage of data and documents Video data from the simulated scenarios will be stored on a password protected folder in a computer drive only available by the investigators. All questionnaires will be anonymously collected and electronic copies of the files will be stored in the same folder as the video data. Participants will be asked to fill in a training grade to allow stratification of the data. The study staff will ensure that the participants' anonymity is maintained. All documents will be stored securely and only accessible by study staff. The trial will comply with the Data Protection Act, which requires data to be anonymised as soon as it is practical to do so.
This study is funded by an Innovation Grant from the Academic Medical Centre, Amsterdam.
Conditions
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Surgery--Complications
Study Design
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Allocation Method
RANDOMIZED
Intervention Model
PARALLEL
50 surgical teams (1 doctor, 2 nurses) will be randomly allocated to intervention or control group
Primary Study Purpose
TREATMENT
Blinding Strategy
NONE
Study introduction and familiarisation of the simulation lab and cognitive aid bundle will be done blindly for both participant and study staff. Randomisation will be done after study introduction and familiarisation of the simulation lab and cognitive aid bundle by means of opening a opaque sealed envelope. The randomisation is done by a computer generated code for use of the CAMDS (intervention) or not (control) and 3 patient scenario's
Study Groups
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CAMDS bundle
25 surgical teams will manage 10 standardised simulated deteriorating ward patients with the help of a cognitive aid bundle
Group Type
EXPERIMENTAL
CAMDS bundle
Intervention Type
OTHER
Cognitive aids for the assessment and management of deteriorating surgical patients (CAMDS). This bundle contains instructions for doctors and nursing staff to assess, manage and escalate care of deteriorating surgical patients. These management instructions will be derived from best practices that are linked with improved mortality and morbidity in surgical patients.
No bundle
25 surgical teams will manage 10 standardised simulated deteriorating ward patients without the help of a cognitive aid bundle
Group Type
NO_INTERVENTION
No interventions assigned to this group
Interventions
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CAMDS bundle
Cognitive aids for the assessment and management of deteriorating surgical patients (CAMDS). This bundle contains instructions for doctors and nursing staff to assess, manage and escalate care of deteriorating surgical patients. These management instructions will be derived from best practices that are linked with improved mortality and morbidity in surgical patients.
Intervention Type
OTHER
Eligibility Criteria
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Inclusion Criteria
* All hospital surgical staff is eligible
Exclusion Criteria
* Surgical staff that is unwilling to give consent
* Staff that already has participated in the study
* Staff that already has participated in the study
Eligible Sex
ALL
Accepts Healthy Volunteers
Yes
Sponsors
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Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
OTHER
Sponsor Role
lead
Responsible Party
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B Preckel
Principle Investigator
Responsibility Role
PRINCIPAL_INVESTIGATOR
Principal Investigators
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Benedikt Preckel, M.D. P.h.D.
Role: PRINCIPAL_INVESTIGATOR
Amsterdam UMC, location AMC
Locations
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Amsterdam UMC, location: Academic Medical Centre
Amsterdam, North Holland, Netherlands
Site Status
Countries
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Netherlands
References
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NCEPOD. Knowing the risk. A review of the peri-operative care of surgical patients 2011 (via: https://www.ncepod.org.uk/2011poc.html )
Reference Type
BACKGROUND
Gaba DM, Howard SK, Fish KJ, Smith BE, Sowb YA. Simulation- based training in anesthesia crisis resource management (ACRM): a decade of experience. Simul Gaming 2001;32:175-93. ( via: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.454.6344&rep=rep1&type=pdf )
Reference Type
BACKGROUND
Ghaferi AA, Birkmeyer JD, Dimick JB. Hospital volume and failure to rescue with high-risk surgery. Med Care. 2011 Dec;49(12):1076-81. doi: 10.1097/MLR.0b013e3182329b97.
Reference Type
RESULT
Ghaferi AA, Osborne NH, Birkmeyer JD, Dimick JB. Hospital characteristics associated with failure to rescue from complications after pancreatectomy. J Am Coll Surg. 2010 Sep;211(3):325-30. doi: 10.1016/j.jamcollsurg.2010.04.025. Epub 2010 Jul 14.
Reference Type
RESULT
Symons NR, Almoudaris AM, Nagpal K, Vincent CA, Moorthy K. An observational study of the frequency, severity, and etiology of failures in postoperative care after major elective general surgery. Ann Surg. 2013 Jan;257(1):1-5. doi: 10.1097/SLA.0b013e31826d859b.
Reference Type
RESULT
Garry DA, McKechnie SR, Culliford DJ, Ezra M, Garry PS, Loveland RC, Sharma VV, Walden AP, Keating LM; PREVENT group. A prospective multicentre observational study of adverse iatrogenic events and substandard care preceding intensive care unit admission (PREVENT). Anaesthesia. 2014 Feb;69(2):137-42. doi: 10.1111/anae.12535.
Reference Type
RESULT
Johnston M, Arora S, King D, Stroman L, Darzi A. Escalation of care and failure to rescue: a multicenter, multiprofessional qualitative study. Surgery. 2014 Jun;155(6):989-94. doi: 10.1016/j.surg.2014.01.016. Epub 2014 Feb 7.
Reference Type
RESULT
Roberts KE, Bonafide CP, Paine CW, Paciotti B, Tibbetts KM, Keren R, Barg FK, Holmes JH. Barriers to calling for urgent assistance despite a comprehensive pediatric rapid response system. Am J Crit Care. 2014 May;23(3):223-9. doi: 10.4037/ajcc2014594.
Reference Type
RESULT
Ludikhuize J, Dongelmans DA, Smorenburg SM, Gans-Langelaar M, de Jonge E, de Rooij SE. How nurses and physicians judge their own quality of care for deteriorating patients on medical wards: self-assessment of quality of care is suboptimal*. Crit Care Med. 2012 Nov;40(11):2982-6. doi: 10.1097/CCM.0b013e31825fe2cb.
Reference Type
RESULT
Ludikhuize J, Brunsveld-Reinders AH, Dijkgraaf MG, Smorenburg SM, de Rooij SE, Adams R, de Maaijer PF, Fikkers BG, Tangkau P, de Jonge E; Cost and Outcomes of Medical Emergency Teams Study Group. Outcomes Associated With the Nationwide Introduction of Rapid Response Systems in The Netherlands. Crit Care Med. 2015 Dec;43(12):2544-51. doi: 10.1097/CCM.0000000000001272.
Reference Type
RESULT
Johnston M, Arora S, Anderson O, King D, Behar N, Darzi A. Escalation of care in surgery: a systematic risk assessment to prevent avoidable harm in hospitalized patients. Ann Surg. 2015 May;261(5):831-8. doi: 10.1097/SLA.0000000000000762.
Reference Type
RESULT
Chrysochoou G, Gunn SR. Demonstrating the benefit of medical emergency teams (MET) proves more difficult than anticipated. Crit Care. 2006;10(2):306. doi: 10.1186/cc4865. No abstract available.
Reference Type
RESULT
Arriaga AF, Bader AM, Wong JM, Lipsitz SR, Berry WR, Ziewacz JE, Hepner DL, Boorman DJ, Pozner CN, Smink DS, Gawande AA. Simulation-based trial of surgical-crisis checklists. N Engl J Med. 2013 Jan 17;368(3):246-53. doi: 10.1056/NEJMsa1204720.
Reference Type
RESULT
Harrison TK, Manser T, Howard SK, Gaba DM. Use of cognitive aids in a simulated anesthetic crisis. Anesth Analg. 2006 Sep;103(3):551-6. doi: 10.1213/01.ane.0000229718.02478.c4.
Reference Type
RESULT
Ziewacz JE, Arriaga AF, Bader AM, Berry WR, Edmondson L, Wong JM, Lipsitz SR, Hepner DL, Peyre S, Nelson S, Boorman DJ, Smink DS, Ashley SW, Gawande AA. Crisis checklists for the operating room: development and pilot testing. J Am Coll Surg. 2011 Aug;213(2):212-217.e10. doi: 10.1016/j.jamcollsurg.2011.04.031. Epub 2011 Jun 11.
Reference Type
RESULT
Neal JM, Hsiung RL, Mulroy MF, Halpern BB, Dragnich AD, Slee AE. ASRA checklist improves trainee performance during a simulated episode of local anesthetic systemic toxicity. Reg Anesth Pain Med. 2012 Jan-Feb;37(1):8-15. doi: 10.1097/AAP.0b013e31823d825a.
Reference Type
RESULT
Burden AR, Carr ZJ, Staman GW, Littman JJ, Torjman MC. Does every code need a "reader?" improvement of rare event management with a cognitive aid "reader" during a simulated emergency: a pilot study. Simul Healthc. 2012 Feb;7(1):1-9. doi: 10.1097/SIH.0b013e31822c0f20.
Reference Type
RESULT
Koers L, Eveleens FM, Schlack WS, Preckel B. [Cognitive aid for emergencies in the OR--AMC bundle helps ensure that no steps are left out]. Ned Tijdschr Geneeskd. 2015;159:A8325. Dutch.
Reference Type
RESULT
Koers L, van Haperen M, Meijer CGF, van Wandelen SBE, Waller E, Dongelmans D, Boermeester MA, Hermanides J, Preckel B. Effect of Cognitive Aids on Adherence to Best Practice in the Treatment of Deteriorating Surgical Patients: A Randomized Clinical Trial in a Simulation Setting. JAMA Surg. 2020 Jan 1;155(1):e194704. doi: 10.1001/jamasurg.2019.4704. Epub 2020 Jan 15.
Reference Type
DERIVED
Other Identifiers
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W16_209
Identifier Type: -
Identifier Source: org_study_id
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