An Organizational Culture-Based Theory of Clinical Information Systems Implementation in Hospitals
Bibliographic record
Abstract
We propose an organizational culture-based explanation of the level of difficulty of clinical information system (CIS) implementation and of the practices that can contribute to reduce the level of difficulty of this process. Adopting an analytic induction approach, we developed initial theoretical propositions based on a three-perspective conceptualization of organizational culture: integration, differentiation, and fragmentation. Using data from three cases of CIS implementation, we first performed a deductive analysis to test our propositions on the relationships between culture, CIS characteristics, implementation practices, and the level of implementation difficulty. Then, applying an inductive analysis strategy, we re-analyzed the data and developed new propositions. Our analysis shows that four values play a central role in CIS implementation. Two values, quality of care and efficiency of clinical practices, are key from an integration perspective; two others, professional status/autonomy and medical dominance, are paramount from a differentiation perspective. A fragmentation perspective analysis reveals that hospital users sometimes have ambiguous interpretations of some CIS characteristics and/or implementation practices in terms of their consistency with these four values. Overall, the proposed theory provides a rich explanation of the relationships between CIS characteristics, implementation practices, user values, and the level of difficulty of the implementation process.
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 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 | 0.021 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".