MétaCan
Menu
Back to cohort
Record W4387161549 · doi:10.1212/cpj.0000000000200205

Improving Documentation of Impulse Control Disorders at a Movement Disorder Program During the COVID-19 Pandemic

2023· article· en· W4387161549 on OpenAlexafffundabout
Brendan Putko, Janis M. Miyasaki

Bibliographic record

VenueNeurology Clinical Practice · 2023
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of Alberta
FundersParkinsonfondenUniversity of OxfordConsortium canadien en neurodégénérescence associée au vieillissementFondation Brain CanadaPatient-Centered Outcomes Research Institute
KeywordsMedicineNeurologyLewy bodyMedical recordPandemicDementia with Lewy bodiesDementiaDiseasePsychiatryCoronavirus disease 2019 (COVID-19)Internal medicine

Abstract

fetched live from OpenAlex

Background and Objectives: Impulse control disorders (ICD) are a group of behaviors in Parkinson disease (PD), (compulsive buying, gambling, binge eating, craving sweets, and hypersexuality) that occur in up to 20% of individuals with PD, sometimes with devastating results. We sought to determine the rate of ICD screening based on 2020 quality measures for PD care by the American Academy of Neurology. Methods: We conducted a quality improvement project to document and improve physician ICD screening in a tertiary movement disorder program. Serial medical records were reviewed for 5 weeks before and 13 weeks after an educational session and documentation tool deployments in 2020. Inclusion criteria included the following: idiopathic PD, PD dementia (PDD), or dementia with Lewy bodies (DLB). Individual encounters for 109 patients preintervention and 276 patients postintervention were reviewed. Results: = 0.444). Discussion: ICD queries immediately after ICD education and dissemination of documentation tools increased. Both preintervention and postintervention groups were similar in demographic and clinical characteristics. This program was instituted at the height of wave 2 of the COVID-19 pandemic in Alberta during staff redeployment and 100% shift to telemedicine ambulatory care. Our results demonstrate that amid a crisis, quality improvement can still be effective with education and provision of tools for clinicians.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.092
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.038
GPT teacher head0.414
Teacher spread0.376 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueNeurology Clinical PracticeSame topicParkinson's Disease Mechanisms and TreatmentsFrench-language works237,207