The sustainability of healthcare innovations: a concept analysis
Bibliographic record
Abstract
AIM: To report on an analysis of the concept of the sustainability of healthcare innovations. BACKGROUND: While there have been significant empirical, theoretical and practical contributions made towards the development and implementation of healthcare innovations, there has been less attention paid to their sustainability. Yet many desired healthcare innovations are not sustained over the long term. There is a need to increase clarity around the concept of innovation sustainability to guide the advancement of knowledge on this topic. DESIGN: Concept analysis. DATA SOURCES: We included literature reviews, theoretical and empirical articles, books and grey literature obtained through database searching (ABI/INFORM, Academic Search Complete, Business Source Complete, CINAHL, Embase, MEDLINE and Web of Science) from 1996-May 2014, reference harvesting and citation searching. METHODS: We examined sources according to terms and definitions, characteristics, preconditions, outcomes and boundaries to evaluate the maturity of the concept. RESULTS: This concept is partially mature. Healthcare innovation sustainability remains a multi-dimensional, multi-factorial notion that is used inconsistently or ambiguously and takes on different meanings at different times in different contexts. We propose a broad conceptualization that consists of three characteristics: benefits, routinization or institutionalization, and development. We also suggest that sustained innovations are influenced by a variety of preconditions or factors, which are innovation-, context-, leadership- and process-related. CONCLUSION: Further conceptual development is essential to continue advancing our understanding of the sustainability of healthcare innovations, especially in nursing where this topic remains largely unexplored.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".