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Patient-directed Digital Health Technologies

2018· article· en· W4254992359 on OpenAlexaboutno aff
Thomas K. Houston, Lorilei Richardson, Shelia R. Cotten

Bibliographic record

VenueMedical Care · 2018
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsDigital healthMEDLINEMedicineComputer scienceHealth carePolitical science

Abstract

fetched live from OpenAlex

Background: Continuity of care (COC) measurements that reflect relational continuity have been used as quality indicators, yet their applicability near the end of life may be limited. Modified continuity indices—UPC-Team (Usual Provider of Care) and BB-Team (Bice-Boxerman)—were developed to reflect escalating care needs and capture associations with patient-centered outcomes. Objectives: To measure associations between the modified COC indices, UPC-Team, and BB-Team during the last year of life and end-of-life (EOL) health care outcomes. Methods: Retrospective cohort study of adults who died between January 1, 2018, and December 31, 2022, with advanced chronic obstructive pulmonary disease and/or heart failure prevalent ≥2 years before death, using health administrative data from Ontario, Canada. Multivariate regressions measured associations between the indices and days spent in community during the last 30 and 14 days of life, and place of death. Results: Among 175,323 included individuals (median age at death=80; 55.4% male), the median number of community days was 23 and 10 in the last 30 and 14 days of life; 56.5% died in a health care institution. Higher UPC-Team and BB-Team scores were associated with increased odds of institutional deaths and fewer community days. Conclusions: Higher continuity scores were associated with increased odds of institutional death and fewer days spent in the community, suggesting limited utility of these modified indices in predicting favorable EOL health care outcomes. Findings highlight the need for future research to incorporate all aspects of continuity (ie, relational, informational, and management) to better capture care coordination in this context.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.002

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 head0.022
GPT teacher head0.384
Teacher spread0.363 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2018
Admission routes1
Has abstractyes

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