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Record W3135207877 · doi:10.2196/22974

Electronic Health Record Use in Swiss Nursing Homes and Its Association With Implicit Rationing of Nursing Care Documentation: Multicenter Cross-sectional Survey Study

2021· article· en· W3135207877 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Medical Informatics · 2021
Typearticle
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationNursingStaffingMedicineHealth careCross-sectional studyPatient safetyNursing careQuality (philosophy)Family medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Nursing homes (NHs) are increasingly implementing electronic health records (EHRs); however, little information is available on EHR use in NH settings. It remains unclear how care workers perceive its safety, quality, and efficiency, and whether EHR use might ease the burden of documentation, thereby reducing its implicit rationing. OBJECTIVE: This study aims to describe nurses' perceptions regarding the usefulness of the EHR system and whether sufficient numbers of computers are available in Swiss NHs, and to explore the system's association with implicit rationing of nursing care documentation. METHODS: This was a multicenter cross-sectional study using survey data from the Swiss Nursing Homes Human Resources Project 2018. It includes a convenience sample of 107 NHs, 302 care units, and 1975 care workers (ie, registered nurses and licensed practical nurses) from Switzerland's German- and French-speaking regions. Care workers completed questionnaires assessing the level of implicit rationing of nursing care documentation, their perceptions of the EHR system's usefulness and of how sufficient the number of available computers was, staffing and resource adequacy, leadership ability, and teamwork and safety climate. For analysis, we applied generalized linear mixed models, including individual-level nurse survey data and data on unit and facility characteristics. RESULTS: Overall, the care workers perceived the EHR systems as useful; ratings ranged from 69.42% (1362/1962; guarantees safe care and treatment) to 78.32% (1535/1960; allows quick access to relevant information on the residents). However, less than half (914/1961, 46.61%) of the care workers reported sufficient computers on their unit to allow timely documentation. Half of the care workers responded that they sometimes or often had to ration the documentation of care. After adjusting for work environment factors and safety and teamwork climate, both higher care worker ratings of the EHR system's usefulness (β=-.12; 95% CI -0.17 to -0.06) and sufficient numbers of computers (β=-.09; 95% CI -0.12 to -0.06) were consistently associated with lower implicit rationing of nursing care documentation. CONCLUSIONS: Both the usefulness of the EHR system and the number of computers available were important explanatory factors for care workers leaving care activities (eg, developing or updating nursing care plans) unfinished. NH managers should carefully select and implement their information technology infrastructure with greater involvement and attention to the needs of their care workers and residents. Further research is needed to develop and implement user-friendly information technology infrastructure in NHs and to evaluate their impact on care processes as well as resident and care worker outcomes.

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.

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)0.000
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 score0.021
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.026
GPT teacher head0.393
Teacher spread0.368 · 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