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Record W2766778928 · doi:10.5430/jha.v6n6p8

Attributes of turnaround rural hospitals: Case study findings and research opportunities

2017· article· en· W2766778928 on OpenAlexvenueno aff
Asa B. Wilson

Bibliographic record

VenueJournal of Hospital Administration · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsStatus quoMindsetConceptualizationBusinessHealth careHealth administrationPublic relationsMedicineNursingMarketingPublic healthEconomic growthEconomicsPolitical science

Abstract

fetched live from OpenAlex

Background: Rural and Critical Access Hospitals (CAHs) have a history of operating challenges and closure-conversion threats. The history is reviewed including the supportive public policy provisions and administrative tactics designed to maintain a community’s hospital as the hub and access point for health services. Limited research indicates that rural facilities are not strategic in their responses to challenges. A question emerges regarding the enduring nature of operating difficulties for these facilities, i.e., no understanding with explanatory value.Objective: The author, as the CEO in six rural hospitals designated as turnaround facilities, used inductive participant-observer involvement to identify operating attributes characteristic of these organizations. An objective description of each facility is provided. While implementing a turnaround intervention, fifteen behaviors or outcomes were found to be consistent across all six entities. This information is used to posit factors associated with or accounting for identified performance weaknesses.Conclusions: It is conceptualization that observed organizational behaviors can be explained as remnants of an agrarian ideology. Such a mindset is focused on preserving the status quo despite challenges that would require strategic positioning of the organization. In addition, emerging studies on community types indicates that follow-up research is needed that assesses the impact of community attributes on rural hospital performance. Also, this study shows that a theory of the rural hospital firm based on neo-classical economics has no explanatory value. Thus, a theory of the firm can be developed that includes behavioral economic principles.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.103
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.252
GPT teacher head0.400
Teacher spread0.148 · 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
Published2017
Admission routes1
Has abstractyes

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