Surgery--ComplicationsCAMDSNCT03812861
Cognitive Aids for the Management of Deteriorating Surgical Patients
A study testing CAMDS bundle in people with Surgery--Complications, run by Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA) at 1 site in Netherlands.
Trial summary
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… Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Surgery--Complications
- What is being tested?
- CAMDS bundle
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 50 participants
- Where
- 1 siteNetherlands
- Study dates
- 7 Feb 2017to 18 Dec 2018
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Who may be able to join
- All hospital surgical staff is eligible
Who cannot join
- Surgical staff that is unwilling to give consent
- Staff that already has participated in the study
Trial locations and contacts
1 site in 1 country.
Netherlands1 site
Amsterdam UMC, location: Academic Medical Centre
Amsterdam, North Holland, 1105 AZ
About this study
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).
Read the detailed description
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.
- Conditions
- Surgery--Complications
- Being tested
- CAMDS bundle
- Keywords
- failure to rescue, postoperative complications, adherence to best practice
- Medical subject headings
- Postoperative Complications
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
CAMDS bundleOther
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.
| Study group | Role | What they receive |
|---|---|---|
| CAMDS bundle | Experimental | 25 surgical teams will manage 10 standardised simulated deteriorating ward patients with the help of a cognitive aid bundle Receives: Other: CAMDS bundle |
| No bundle | No intervention | 25 surgical teams will manage 10 standardised simulated deteriorating ward patients without the help of a cognitive aid bundle |
What is being measured
The primary outcome is the main question the study is designed to answer.
Failure to adhear to best practice (percentage of omitted critical management steps) for the given scenario
Every scenario consisted of 15 predefined critical management steps (for examle cardiac arrest with a shockable rhythm critical steps would be; start basic life support, open the airway, identify shockable rhythm, defibrillate with appropriate amount of Joules etc.) Primary outcome is the failure to adhear to best practice expressed as percentage of omitted predefined critical management steps.
Measured: start to end of high fidelity simulation session (aprox. 10 min)
Secondary outcomes (1)
Perceived usability 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).
Measured: During debrief of high fidelity simulation session (aprox. 30 min)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted23 Jan 2019
- Study start7 Feb 2017
- Primary completion18 Dec 2018
- Study completion18 Dec 2018
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (19)Papers the sponsor has linked to this study.
- Other trials for Surgery--ComplicationsStudies of the same condition, open and under way.
- More trials run by Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)The sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Model description
- 50 surgical teams (1 doctor, 2 nurses) will be randomly allocated to intervention or control group
- Masking
- None (open label)
- Enrolment
- 50 participants (actual)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, B Preckel, Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
- Investigators
- Benedikt Preckel, M.D. P.h.D., Principal investigator, Amsterdam UMC, location AMC
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03812861
- Sponsor's protocol ID
- W16_209
- Acronym
- CAMDS
- Status last verified
- Jan 2019
- First submitted
- 14 Jan 2019
- Last updated
- 23 Jan 2019
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
NCEPOD. Knowing the risk. A review of the peri-operative care of surgical patients 2011 (via: https://www.ncepod.org.uk/2011poc.html )
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 )
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.
PubMed 22002649Ghaferi 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.
PubMed 20800188Symons 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.
PubMed 23044786Garry 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.
PubMed 24443852Johnston 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.
PubMed 24768480Roberts 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.
PubMed 24786810Ludikhuize 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.
PubMed 22890255Ludikhuize 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.
PubMed 26317569Johnston 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.
PubMed 24887972Chrysochoou 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.
PubMed 16542491Arriaga 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.
PubMed 23323901Harrison 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.
PubMed 16931660Ziewacz 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.
PubMed 21658974
Study at a glance
From the registry record, last updated by the sponsor on 23 Jan 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Cognitive Aids for the Management of Deteriorating Surgical Patients
- ClinicalTrials.gov ID
- NCT03812861
- Acronym / sponsor ID
- CAMDS / W16_209
- Conditions
- Surgery--Complications
- Keywords
- failure to rescue, postoperative complications, adherence to best practice
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 50 participants (actual)
- Lead sponsor
- Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)University, hospital or other
- Study start
- 7 Feb 2017 (actual)
- Primary completion
- 18 Dec 2018 (actual)
- Study completion
- 18 Dec 2018 (actual)
- First posted
- 23 Jan 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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).
Detailed description
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.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- 50 surgical teams (1 doctor, 2 nurses) will be randomly allocated to intervention or control group
| Arm | Type | Receives |
|---|---|---|
| CAMDS bundle | Experimental | Other: CAMDS bundle25 surgical teams will manage 10 standardised simulated deteriorating ward patients with the help of a cognitive aid bundle |
| No bundle | No intervention | –25 surgical teams will manage 10 standardised simulated deteriorating ward patients without the help of a cognitive aid bundle |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (1 listed)
- All hospital surgical staff is eligible
Key exclusion criteria (2 listed)
- Surgical staff that is unwilling to give consent
- Staff that already has participated in the study
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| CAMDS bundleCognitive 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. | Other | CAMDS bundle |
Primary outcome
Failure to adhear to best practice (percentage of omitted critical management steps) for the given scenario
Time frame: start to end of high fidelity simulation session (aprox. 10 min)
Every scenario consisted of 15 predefined critical management steps (for examle cardiac arrest with a shockable rhythm critical steps would be; start basic life support, open the airway, identify shockable rhythm, defibrillate with appropriate amount of Joules etc.) Primary outcome is the failure to adhear to best practice expressed as percentage of omitted predefined critical management steps.
1 secondary outcome
Perceived usability of the CAMDS
Time frame: During debrief of high fidelity simulation session (aprox. 30 min)
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Jan 2019.
- BackgroundNCEPOD. Knowing the risk. A review of the peri-operative care of surgical patients 2011 (via: https://www.ncepod.org.uk/2011poc.html )
- BackgroundGaba 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 )
- Results publication: PubMed 22002649Ghaferi 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.
- Results publication: PubMed 20800188Ghaferi 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.
- Results publication: PubMed 23044786Symons 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.
- Results publication: PubMed 24443852Garry 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.
- Results publication: PubMed 24768480Johnston 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.
- Results publication: PubMed 24786810Roberts 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.
- Results publication: PubMed 22890255Ludikhuize 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.
- Results publication: PubMed 26317569Ludikhuize 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.
- Results publication: PubMed 24887972Johnston 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.
- Results publication: PubMed 16542491Chrysochoou 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.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Benedikt Preckel, M.D. P.h.D. principal investigator
Amsterdam UMC, location AMC
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing CAMDS bundle in people with Surgery--Complications, run by Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA) at 1 site in Netherlands.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 23 Jan 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Netherlands. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Failure to adhear to best practice (percentage of omitted critical management steps) for the given scenario (time frame: start to end of high fidelity simulation session (aprox. 10 min)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03812861, which also lists 19 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Jan 2019.