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Record W2034576894 · doi:10.5430/jha.v4n3p9

Family attitudes towards an electronic personal health record in a long term care facility

2015· article· en· W2034576894 on OpenAlexaffvenueabout
Pria Nippak, Winston Isaac, Alice Geertsen, Candace J Ikeda-Douglas

Bibliographic record

VenueJournal of Hospital Administration · 2015
Typearticle
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsBaycrest HospitalToronto Metropolitan University
Fundersnot available
KeywordsConfidentialityFamily medicineHealth careElectronic health recordNursingTest (biology)MedicinePerceptionFamily memberPsychologyComputer science

Abstract

fetched live from OpenAlex

Objective: To explore the perceptions of family members regarding the importance of an electronic personal health record (EPHR) called MyChart as a healthcare information source to support the care of their loved ones within a long term care (LTC) facility in Toronto, Ontario.Methods: One hundred and fifty eight family members of the patients in six LTC units at the hospital were given a survey to determine their perceptions regarding the utility of the content items within an EPHR that was recently adopted by the LTC institution.Results: The response rate was 41% (n = 65). Many family members (n = 48) felt it was important to have access to their loved one’s EPHR. Respondents ranked test results (38%; n = 25), doctor’s clinical notes (26%; n = 17), medication lists (15%; n = 10) and upcoming appointments (11%; n = 7) as the number one most important content item that they would want to have access to. In addition to the standard content items found within an EPHR, family members requested electronic access to a variety of additional medical content items that are not currently offered within the EPHR, such as status alerts. Overall, they felt that an EPHR would enhance communication between the care team and the family, however 30% of family members identified concerns linked to security and confidentiality of the electronic health record information.Conclusions: Family members felt that an EPHR would be an important tool in the LTC facility to assist with information exchange between care providers and the family. It is important to consider that the additional information requested beyond what is traditionally found in an EPHR as well as the specific communication concerns raised, may be limited to a LTC setting.

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)0.003
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 score0.039
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.062
GPT teacher head0.436
Teacher spread0.374 · 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

Citations9
Published2015
Admission routes3
Has abstractyes

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