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Record W3053542636 · doi:10.1093/pch/pxaa068.006

7 Understanding Regional Site Transfer: Perceptions of Health Care Professionals

2020· article· en· W3053542636 on OpenAlexaffabout
Sumedh Bele, J A Michelle Bailey, Alam Randhawa

Bibliographic record

VenuePaediatrics & Child Health · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsFocus groupHealth careMedicineTertiary careSpecialtyQualitative researchNursingRural areaFamily medicineBusinessPolitical scienceMarketing

Abstract

fetched live from OpenAlex

Abstract Background Alberta Health Services identified that tertiary sites are often in overcapacity (admitted patients exceeding inpatient beds) while regional sites have low occupancy in their pediatric inpatient units. Hospital overcapacity may have negative effects on the care received by patients, such as increased risk of infection, less time spent with each patient and increased stress on the hospital staff (Keegan, 2010). In addition, rural families face several barriers to access to health care including traveling long distances to access the sub-specialty care present in urban tertiary centers. Previous studies conducted by our team found that transfers back to regional sites are not common. Increasing transfers of pediatric patients from tertiary to regional sites with care supported by the tertiary site could aid in addressing tertiary overcapacity and enable patients and families to receive care closer to home. Objectives This qualitative study sought to understand tertiary site health care professionals’ perceptions of tertiary to regional inpatient transfer. Design/Methods Four semi-structured focus groups were held with health care professionals. Focus groups included a mixed group of staff physicians, residents, nurses and managers. Common themes of discussion included the current transfer process, understanding of regional site resources and ways to increase patient transfer. A qualitative data analysis software, NVivo 11, was used to code, organize, and manage the data to facilitate data interpretations and generate themes regarding the current patient transfer process. Results The main barriers of pediatric transfer to rural sites include a lack of standardized transfer guidelines, limited understanding of rural regional site resources and mistrust between medical teams that prohibit patient transfer. The most likely pediatric patients that could be transferred back to rural sites include clearly diagnosed, single body system patients. Participants who had previous experience working in regional sites were more comfortable with transfer to regional sites. Transfer to regional sites could be increased by improving communication between medical teams and correcting misinformation about regional inpatient pediatric sites. Conclusion There is a historical practice of concentrating resources at tertiary care sites. However, there are a lack of shared guidelines for transfer as well as well as limited knowledge of regional site capabilities. Health care professionals across the entire continuum of patient care recognize the need to find solutions that would aid in transfer.

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)0.009
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0050.003
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.000

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 head0.145
GPT teacher head0.316
Teacher spread0.170 · 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 designQualitative
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
Published2020
Admission routes2
Has abstractyes

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