Health information technology success and the art of being mindful
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Information technologies (ITs) represent an important lever for improving performance in health care systems. In recent years, most industrialized countries have made substantial investments in this area. Nevertheless, the sad truth is that far too many of these IT projects have failed. PURPOSE: The primary goals of this study were to explore the notion of mindfulness proposed by E. B. Swanson and N. C. Ramiller (2004) and to assess the extent to which, and how, innovating mindfully influences health IT project success. METHODOLOGY: Two in-depth case studies were conducted in comparable health care organizations that adopted the same clinical information system. Observation, semistructured interviews, informal discussions, and documentation were the primary data collection methods. Data analyses were performed following recognized guidelines. RESULTS: Throughout the unfolding of the two projects, the actions and decisions of key stakeholders reflected different levels of mindfulness. The cross-case comparison was particularly relevant given that project circumstances led to contrasting outcomes. PRACTICE IMPLICATIONS: Taking action and making decisions in light of the particular context of each particular health IT project, that is, innovating mindfully, favor innovation acceptance and positive outcomes, whereas acting and deciding following fads, fashion, or best practices without paying attention to the specifics of the project context, that is, innovating mindlessly, increase the risk of human resistance and limited added value.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it