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Record W4293105775 · doi:10.1186/s13643-022-02026-y

How does nursing-sensitive indicator feedback with nursing or interprofessional teams work and shape nursing performance improvement systems? A rapid realist review

2022· review· en· W4293105775 on OpenAlexafffund
Joachim Rapin, Joanie Pellet, Cédric Mabire, Sylvie Gendron, Carl‐Ardy Dubois

Bibliographic record

VenueSystematic Reviews · 2022
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversité de Montréal
FundersUniversité de Montréal
KeywordsMedicineAgency (philosophy)NursingWork (physics)Action (physics)Nursing researchGenerative grammarComputer scienceEpistemology

Abstract

fetched live from OpenAlex

BACKGROUND: Care quality varies between organizations and even units within an organization. Inadequate care can have harmful financial and social consequences, e.g. nosocomial infection, lengthened hospital stays or death. Experts recommend the implementation of nursing performance improvement systems to assess team performance and monitor patient outcomes as well as service efficiency. In practice, these systems provide nursing or interprofessional teams with nursing-sensitive indicator feedback. Feedback is essential since it commits teams to improve their practice, although it appears somewhat haphazard and, at times, overlooked. Research findings suggest that contextual dynamics, initial system performance and feedback modes interact in unknown ways. This rapid review aims to produce a theorization to explain what works in which contexts, and how feedback to nursing or interprofessional teams shape nursing performance improvement systems. METHODS: Based on theory-driven realist methodology, with reference to an innovative combination of Actor-Network Theory and Critical Realist philosophy principles, this realist rapid review entailed an iterative procedure: 8766 documents in French and English, published between 2010 and 2018, were identified via 5 databases, and 23 were selected and analysed. Two expert panels (scientific and clinical) were consulted to improve the synthesis and systemic modelling of an original feedback theorization. RESULTS: We identified three hypotheses, subdivided into twelve generative configurations to explain how feedback mobilizes nursing or interprofessional teams. Empirically founded and actionable, these propositions are supported by expert panels. Each configuration specifies contextualized mechanisms that explain feedback and team outcomes. Socially mediated mechanisms are particularly generative of action and agency. CONCLUSIONS: This rapid realist review provides an informative theoretical proposition to embrace the complexity of nursing-sensitive indicator feedback with nursing or interdisciplinary teams. Building on general explanations previously observed, this review provides insight into a deep explanation of feedback mechanisms. SYSTEMATIC REVIEW REGISTRATION: Prospero CRD42018110128 .

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)0.021
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.430
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.360
GPT teacher head0.572
Teacher spread0.212 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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

Citations11
Published2022
Admission routes2
Has abstractyes

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