Decision Support Software for Wounds and Injuries

Overseen By Iain Kehoe

Age: 18+

Sex: Any

Trial Phase: Phase 1

Sponsor: Andrew Tomas Reisner

Disqualifiers: Prisoners, Pregnant, EFIC Opt-Out, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

Duration: 30 minutes per session

20 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests new decision-support software designed to help doctors make quick, informed decisions when treating trauma patients. The study will assess the software's effectiveness during actual use and determine whether it aids or distracts doctors in emergency situations. Participants should be adults in the emergency department with a sudden injury serious enough to be in the "Acute" area, where critical cases are managed. The goal is to gather initial data to plan a larger study on the software's effectiveness.

As a Phase 1 trial, the research focuses on understanding how the software functions in real-life emergency situations, offering participants the chance to contribute to groundbreaking advancements in trauma care.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What prior data suggests that this decision-support software is safe for use in trauma cases?

In a previous study, researchers tested the APPRAISE Trauma Clinical Decision Support System to evaluate its effectiveness in assisting doctors and nurses with trauma patient care. Research has shown that the system effectively tracks patient conditions and medical actions. Although direct data on safety is unavailable due to the software nature of the tool, the pilot study will assess whether the system confuses or distracts healthcare providers. The primary concern is its impact on decision-making rather than physical safety.

This trial is in its early stages, so the safety of the software remains under evaluation. The current study will observe the system's performance in real-life situations to ensure it does not cause problems during patient care. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the APPRAISE Trauma Clinical Decision Support System because it leverages advanced software technology to assist in the management of wounds and injuries. Unlike traditional methods that rely heavily on clinician experience and standard protocols, this system uses data-driven algorithms to provide real-time, personalized recommendations for trauma care. This innovative approach aims to enhance decision-making speed and accuracy, potentially leading to better patient outcomes and more efficient use of medical resources.

What evidence suggests that the APPRAISE Trauma Decision Support System is effective for trauma cases?

Research shows that the APPRAISE Trauma Clinical Decision Support System, used by participants in this trial, could aid in treating trauma patients. This system employs artificial intelligence to analyze vital signs and predict severe bleeding risk, enabling doctors and nurses to make quicker decisions in emergencies. Early studies have found that similar systems enhance decision-making by helping medical staff adhere more closely to treatment guidelines. This real-time support aims to make patient care faster and more accurate. Although specific data on APPRAISE's effectiveness is still being collected, the technology has the potential to improve medical decision-making. ^{1 2 6 7 8}

Who Is on the Research Team?

Andrew Reisner, MD

Principal Investigator

Massachusetts General Hospital

Are You a Good Fit for This Trial?

This trial is for adults (18+) who arrive at the Emergency Department and are triaged to the 'Acute' area due to concerns of acute injury. This could be because they've reported an injury or the clinical team suspects one based on their symptoms.

Inclusion Criteria

I was directed to the critical care section of the emergency department.

I am being evaluated for a recent injury.

I am 18 years or older and currently in the emergency department.

Exclusion Criteria

Patients known to be pregnant

Prisoners

Patients wearing an 'EFIC Opt-Out' bracelet

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1 week

Treatment

Evaluation of the APPRAISE trauma decision-support software system during real-time clinical use

30 minutes per session

Follow-up

Participants are monitored for safety and effectiveness after treatment

1 week

What Are the Treatments Tested in This Trial?

Interventions

• APPRAISE Trauma Clinical Decision Support System

Trial Overview

The APPRAISE Trauma Clinical Decision Support System is being tested. It's a software designed to help clinicians make decisions in treating trauma patients, and this trial checks if it works as intended without distracting doctors.

How Is the Trial Designed?

Group I: APPRAISE cases Experimental Treatment 1 Intervention

Trauma patients for which APPRAISE system was used

Who Is Running the Clinical Trial?

Andrew Tomas Reisner

Lead Sponsor

Trials

2

Recruited

40+

Published Research Related to This Trial

The study introduces LogReg, a handheld decision-support system designed to enhance clinical decision-making at the point of care, addressing the challenge of needing computing power directly where patient interactions occur.

LogReg was successfully applied to predict clinical outcomes in crush injury cases, demonstrating its practical utility in real-world medical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Decisions at hand: a decision support system on handhelds. Zupan, B., Porenta, A., Vidmar, G., et al.[2008]

A clinical decision support system (CDSS) was developed to assist clinicians in managing post-cardiac surgery patients by modeling decision-making strategies based on key cardiovascular parameters like blood pressure and cardiac output.

The CDSS successfully replicated expert anesthetists' therapeutic interventions in simulated patient scenarios, effectively controlling hemodynamic parameters to target values, demonstrating its potential efficacy in clinical settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A hybrid hierarchical decision support system for cardiac surgical intensive care patients. Part I: Physiological modelling and decision support system design. Denaï, MA., Mahfouf, M., Ross, JJ.[2015]

Computer-assisted decision-making systems have the potential to improve outcomes for trauma patients by providing real-time predictions and management suggestions based on continuously acquired patient data.

Despite their promise, widespread implementation of these systems faces challenges, including technological barriers, data protection regulations, and the need for large multicenter studies to validate their effectiveness.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[Computer-assisted decision-making for trauma patients]. Osterhoff, G., Pförringer, D., Scherer, J., et al.[2020]

Computerized clinical decision support (CCDS) can effectively implement and refine evidence-based guidelines (EBGs) in healthcare, helping to ensure that patients receive appropriate care based on proven therapies.

By utilizing CCDS, clinicians can decrease variability in patient care, test new interventions, and validate improvements in the quality of care, particularly in complex environments like intensive care units.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Computerized clinical decision support: a technology to implement and validate evidence based guidelines. Sucher, JF., Moore, FA., Todd, SR., et al.[2022]

A dual-method usability evaluation combining user-driven and expert-driven approaches identified 79 usability issues in a rib fracture clinical decision support system, with experts uncovering 63% of the issues, including 58% of the severe ones, highlighting the importance of both perspectives in usability testing.

Five guiding themes for designing effective clinical decision support systems were identified: transparency, functionality and integration into workflow, automated and noninterruptive features, flexibility, and layout and appearance, which can enhance usability and adherence to evidence-based practices.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Combined Expert and User-Driven Usability Assessment of Trauma Decision Support Systems Improves User-Centered Design. Jones, EK., Hultman, G., Schmoke, K., et al.[2022]

A computerized decision support system was developed to assist ATLS-trained surgeons in managing patients with penetrating abdominal injuries, showing promise in providing accurate advice on diagnoses and treatments.

In a comparison with 13 medical trainees, the expert system's management suggestions were ranked higher than those of individual trainees, indicating its potential to enhance decision-making in trauma care.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Artificial intelligence: a computerized decision aid for trauma. Clarke, JR., Cebula, DP., Webber, BL.[2019]

Clinical decision support systems, like Project IMPACT and APACHE III, are essential for managing patient outcomes in critical care by enabling data analysis and predictive modeling.

These tools help clinicians compare actual patient outcomes with predicted outcomes, which can improve quality control and process improvement in healthcare settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical decision support systems for outcome measurement and management. Sakallaris, BR., Jastremski, CA., Von Rueden, KT.[2019]

Citations

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clinicaltrials.gov

clinicaltrials.gov/study/NCT06121661

Live Trial of the APPRAISE Trauma Decision Support System

Individual Patients: Allows a single patient, with a serious disease or condition who cannot participate in a clinical trial, access to a drug or biological ...

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mgh-cdtl.org

mgh-cdtl.org/appraise.html

Clinical Decision Technology Laboratory

APPRAISE is a research study. In this research study, we will evaluate a software system intended to help doctors and nurses manage patients after major trauma.

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APPRAISE-HRI: AN ARTIFICIAL INTELLIGENCE ...

This study aims to assess the ability of an artificial intelligence triage algorithm to automatically analyze vital-sign data and stratify hemorrhage risk in ...

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link.springer.com

link.springer.com/article/10.1007/s11548-024-03191-2

TraumaFlow—development of a workflow-based clinical ...

TraumaFlow enables real-time decision support for the treatment of polytrauma patients. It improves guideline-based decision-making in complex and critical ...

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researchgate.net

researchgate.net/publication/375557634_Trauma_THOMPSON_Clinical_Decision_Support_for_the_Frontline_Medic

Trauma THOMPSON: Clinical Decision Support for the ...

Conclusions We expect the Trauma Triage, Treatment, and Training Decision Support system will augment a medic's ability to make informed decisions based on ...

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mgriblog.org

mgriblog.org/2023/02/15/appraise-study-team-seeks-feedback-on-new-clinical-trial-for-trauma-patients/

APPRAISE Study Team Seeks Feedback on New Clinical Trial ...

The APPRAISE software system was developed to help the trauma team track patient states and clinical interventions.

7.

animatorsworkshop.com

animatorsworkshop.com/portfolio-view/appraise-trauma-support/

APPRAISE Trauma Support - Jackie Watson

Brief: APPRAISE is a research initiative evaluating a software system designed to support doctors and nurses in managing patients after major trauma.

8.

pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC9589228/

Decision support by machine learning systems for acute ...

This systematic review aimed to summarize the existing literature on the value of ML for the initial management of severely injured patients.