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Record W3211526259 · doi:10.35680/2372-0247.1561

Perceptions of the healthcare system among stakeholders

2021· article· en· W3211526259 on OpenAlexaff
Michael D. Markee, Christine Ascencio, Laura Brugger, Renee Jonas, Hisako Matsuo

Bibliographic record

VenuePatient Experience Journal · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsCollège Boréal
Fundersnot available
KeywordsHealth careInefficiencyEquity (law)Public relationsBlameBusinessNursingPsychologyMarketingMedicinePolitical scienceSocial psychologyEconomicsEconomic growth

Abstract

fetched live from OpenAlex

The U.S. healthcare system is rife with complexities and is consistently a source of political debate. One’s interaction with the system may directly impact the understanding of the system. The objective of this research is to examine the perceptions of the United States healthcare system from the viewpoint of healthcare providers, insurers, and consumers. Using a grounded theory approach, theoretical sampling was used to explore similarities and differences between the three groups of actors in the healthcare system. Data were collected through interviews with thirty-one participants using a semi-structured interview schedule. Themes of cost, access, and inefficiency emerged from the data. The theme of cost included the ability to pay, innovative care delivery, and relation to access. Access included the need for guidance, geographical proximity to healthcare, and socioeconomic status. The theme of inefficiency included how insurance dictates care, and the unwieldy system. Similarities among groups were the high cost of care, ability to pay, and complexity. Differences discovered were the insurers’ dual role as professional and consumer, providers’ informal access to care, and differing views on who is to blame for the high cost of healthcare. This research unveils perspectives of three stakeholders of actors in the healthcare system, providing a foundation for further research to better understand these perspectives in improving equity and access in healthcare. Experience Framework This article is associated with the Staff & Provider Engagement lens of The Beryl Institute Experience Framework (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.286

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)0.0000.000

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 head0.104
GPT teacher head0.277
Teacher spread0.174 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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