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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.

Completed

Finished. The study has ended and is not enrolling. Results may be posted on the official record.

Official record
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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

Other trials in Netherlands

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.

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 groups in NCT03812861
Study groupRoleWhat they receive
CAMDS bundleExperimental25 surgical teams will manage 10 standardised simulated deteriorating ward patients with the help of a cognitive aid bundle
Receives: Other: CAMDS bundle
No bundleNo intervention25 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.

  1. 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)
  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.

  1. First posted23 Jan 2019
  2. Study start7 Feb 2017
  3. Primary completion18 Dec 2018
  4. Study completion18 Dec 2018

Resources

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)
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 22002649
  • 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.

    PubMed 20800188
  • 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.

    PubMed 23044786
  • 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.

    PubMed 24443852
  • 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.

    PubMed 24768480
  • 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.

    PubMed 24786810
  • 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.

    PubMed 22890255
  • 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.

    PubMed 26317569
  • 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.

    PubMed 24887972
  • 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.

    PubMed 16542491
  • 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.

    PubMed 23323901
  • 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.

    PubMed 16931660
  • 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.

    PubMed 21658974

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.

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