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Record W2785715348 · doi:10.1155/2018/1875967

Chronic Pain in the Emergency Department: A Pilot Interdisciplinary Program Demonstrates Improvements in Disability, Psychosocial Function, and Healthcare Utilization

2018· article· en· W2785715348 on OpenAlexafffund
Joshua A. Rash, Patricia A. Poulin, Yaadwinder Shergill, Heather Romanow, Jeffrey Freeman, Monica Taljaard, Guy Hebert, Ian G. Stiell, Catherine Smyth

Bibliographic record

VenuePain Research and Management · 2018
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsUniversity of OttawaUniversity of British ColumbiaOttawa HospitalMemorial University of Newfoundland
FundersOttawa Hospital
KeywordsMedicineEmergency departmentPsychosocialChronic painPhysical therapyHealth carePatient satisfactionDepression (economics)PsychiatryNursing

Abstract

fetched live from OpenAlex

Objective: To evaluate the feasibility of an individualized interdisciplinary chronic pain care plan as an intervention to reduce emergency department (ED) visits and improve clinical outcomes among patients who frequented the ED with concerns related to chronic pain. Methods: A prospective cohort design was used in an urban tertiary care hospital. As a pilot program, fourteen patients with chronic pain who frequented the ED (i.e., >12 ED visits within the last year, of which ≥50% were for chronic pain) received a rapid interdisciplinary assessment and individualized care plan that was uploaded to an electronic medical record system (EMR) accessible to the ED and patient's primary care provider. Patients were assessed at baseline and every three months over a 12-month period. Primary outcomes were self-reported pain and function assessed using psychometrically valid scales. Results: Nine patients completed 12-month follow-up. Missing data and attrition were handled using multiple imputation. Patients who received the intervention reported clinically significant improvements in pain, function, ED visits, symptoms of depression, pain catastrophizing, sleep, health-related quality of life, and risk of future aberrant opioid use. Discussion: Individualized care plans uploaded to an EMR may be worth implementing in hospital EDs for high frequency visitors with chronic pain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.009
metaresearch head score (Gemma)0.000
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 score0.473
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
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 head0.084
GPT teacher head0.429
Teacher spread0.345 · 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".

Quick stats

Citations25
Published2018
Admission routes2
Has abstractyes

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