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Record W3047525254 · doi:10.7759/cureus.9560

The Documentation of Goals of Care Discussions at a Canadian Academic Hospital

2020· article· en· W3047525254 on OpenAlexaffabout
Jaime-Lee Munroe, Stuart L. Douglas, Timothy Chaplin

Bibliographic record

VenueCureus · 2020
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineDocumentationHealth careMedical emergencyChartMedical recordQuality managementCardiopulmonary resuscitationFamily medicineEmergency medicineService (business)ResuscitationSurgery

Abstract

fetched live from OpenAlex

INTRODUCTION: Patient-centered care is a core principle of the Canadian healthcare system. In order to facilitate patient-centered care, the documentation of a patient's medical goals and expectations is important, especially in the event of acute decompensation when an informed conversation with the patient may not be possible. The 'Goals of Care Discussion Form (GCF)' at Kingston Health Sciences Centre (KHSC) documents goals of care discussions between patients and healthcare providers. All patients admitted to the Internal Medicine service are expected to have this form completed within 24 hours of admission. Formal measurement of form completion at our center has not previously been done, though anecdotally this form is often incomplete. The purpose of this study is to quantify the rate of completion and assess quality of documentation of the GCF at KHSC. METHODS: This prospective chart review took place between August 25, 2018, and March 25, 2019. Charts were reviewed for the presence of a completed GCF, and the quality of notation was assessed, as appropriate. Given there are no existing tools for assessing the quality of a document such as the GCF, authors TC and JM created one de novo for this study. Extracted data included the amount of time elapsed between admission and completion of the GCF, whether the 'yes/no cardiopulmonary resuscitation (CPR)' order in the patient's chart aligned with their wishes as outlined on the GCF, and whether or not a patient's GCF was uploaded to the hospital's electronic medical record (EMR). RESULTS: Two hundred sixteen charts were reviewed. Of these, 136 (63.0%) had a complete GCF. The mean GCF quality score was 3.4/7 (95% CI [3.2, 3.6]). The mean time elapsed from admission to the completion of the GCF was 1.5 days (95% CI [0.6, 2.4]). There were 130 charts with both a complete GCF and a 'yes/no CPR' order, and of these, 20 (15.4%) showed a discrepancy. Eighty-six (63.2%) of the completed GCFs were uploaded to the EMR. DISCUSSION AND CONCLUSIONS: The rate of GCF completion at KHSC is noticeably higher than expected based on the previous literature. However, our assessment of the quality of completion indicates that there is room for improvement. Most concerning, discrepancies were found between the 'yes/no CPR' order in a patient's chart and their stated wishes on the GCF. Furthermore, less than two-thirds of completed GCFs were found to have been uploaded to the hospital's EMR. Given the emphasis on patient-centered care in the Canadian healthcare system, our findings suggest that improvement initiatives are needed with respect to documenting goals of care discussions with patients.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.138
Threshold uncertainty score0.517

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.034
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.007
Science and technology studies0.0060.002
Scholarly communication0.0030.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.133
GPT teacher head0.428
Teacher spread0.295 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2020
Admission routes2
Has abstractyes

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