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Record W3184878148 · doi:10.29173/cjen129

Geriatric Recovery and Enhancement Alliance in Trauma (GREAT) multidisciplinary quality improvement initiative: improving rates of successful resuscitation, rehabilitation and reintegration of geriatric trauma patients across the trauma spectrum of care

2021· article· en· W3184878148 on OpenAlexaffvenueabout
Sandy Widder, Kristine Mørch, Nori Bradley, Lauren Ternan, N. Lam

Bibliographic record

VenueCanadian Journal of Emergency Nursing · 2021
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineGeriatric traumaRehabilitationMultidisciplinary approachPolypharmacyDeliriumGeriatricsTrauma centerMedical emergencyNursingIntensive care medicinePoison controlPsychiatryPhysical therapyInjury preventionInjury Severity ScoreSurgery

Abstract

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Geriatric Recovery and Enhancement Alliance in Trauma (GREAT) multidisciplinary quality improvement initiative: improving rates of successful resuscitation, rehabilitation and reintegration of geriatric trauma patients across the trauma spectrum of care. Sandy Widder, Kristin E. Morch, Nori L Bradley, Lauren Ternan, Ni Thuyen Lam Background: Traumatic injuries are a significant cause of morbidity and mortality in the elderly, with the risk of poor outcomes increasing with advanced age. Using a multidisciplinary geriatric trauma care approach, led by a dedicated nursing coordinator, standardized order sets were implemented to reduce in-hospital complications and screening tools applied early to identify patient specific care needs. Specifically, early trauma consult, identification of injuries, appropriate opioid ordering, polypharmacy avoidance, delirium prevention, mental health issues, and mobility needs were addressed The goal was to improve geriatric trauma awareness, decrease in-hospital complications and improve the likelihood of return to home and baseline function Implementation: Through stakeholder consultation process, it was recognized that the hospital needed a coordinated, geriatric trauma team process. The geriatric trauma navigator (GTN) role was created to lead these quality improvement initiatives. This included the development of educational strategies for frontline staff and physicians to highlight the unique challenges of trauma patient management and to introduce the GREAT study for optimized patient care. Patients 65 years of age or older with a traumatic mechanism were enrolled. GREAT patients then followed a protocol designed for tracking and implementing standardized processes, including early ED and in-patient order sets, engagement of trauma services, and the application of screening tools and specialty consultations. Screening tools (Identification of Seniors At Risk (ISAR), Confusion Assessment Method (CAM), Mini-Cog, Patient Health Questionnaire (PHQ-2), Geriatric Depression Scale (GDS-15), Alcohol Use Disorders Identification Test- Concise (AUDIT-C), Canadian Nutrition Screening Tool (CNST), Clinical Frailty Scale, ADL/IDLs) were administered to identify at-risk patients and to inform consultation with geriatrics and psychiatry, and allied health services (occupation therapy, physical therapy, nutrition services, pharmacy). The study team evaluated data on a monthly basis and met quarterly to evaluate and implement changes. Evaluation Methods: Data was prospectively collected and compared to control data from the Alberta Trauma Registry and Trauma Quality Improvement Program (American College of Surgeons). Data tabulation and statistical analysis was performed using Stat59 (STAT59 Services Ltd, Edmonton, AB, Canada). Outcome measures-provision of timely and comprehensive care: rates of trauma team activations, emergencydepartment and in-hospital length of stay-reduction of hospital complications: UTI, DVT/PE, pneumonia, pressure ulcers, ICUadmission, unexpected readmission to hospital-improvement of functionality upon discharge: in-hospital and 30 day mortality rates,return to function, disposition (home versus long term care) Process measures-time to diet and ambulation-tracking of number of days of urinary catheter in situ-compliance with GOC discussions-use of assessment screening tools-spinal clearance <24 hours Results: Enrollment of patients into GREAT based on study criteria lowered the threshold for triggering a trauma team consult, improving the recognition rate of geriatric trauma. This was reflected in the decreased average ISS scores and higher rate of trauma consults. Ground level falls, which previously did not typically activate a trauma consult, are now be recognized as major trauma. With the GTN, we determined that gaps exist in the current monitoring of key performance measures. Through the GREAT data collection process, we were able to establish baseline data and target PDSA changes to address these gaps. Advice and Lessons Learned: This quality initiative was designed as a proof of concept model for early identification of the geriatric trauma patient and a collaborative team approach to optimize care processes, and in turn minimize complications. The GTN role was vital to identify patients, implement screening tools, and coordinate care. With limited resources and increasing work loads for all programs, the additional GTN role required site leadership and stakeholder support. Ideally, a protocolized geriatric trauma team activation and admission process would ensure all patients receive screening tools as part of their in-patient orders for early assessments and interventions. Further educational campaigns will need to be developed to increase awareness of the importance of geriatric trauma. Additionally, processes need to be streamlined for data gathering and monitoring of performance measures. Access to screening tools and order sets need to be user friendly, built into currently existing workflows, and evaluated for optimization.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.334
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes3
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