Exploring Health Information Technology Innovativeness and its Antecedents in Canadian Hospitals
Bibliographic record
Abstract
OBJECTIVES: The primary aim of this study was to assess the antecedents of health information technology (HIT) innovativeness in public hospitals. To do so, we built upon our own previous work to relate the level of HIT innovativeness to organizational capacity characteristics. METHODS: We conducted a survey of chief information officers (CIOs) in public hospitals in the two largest Canadian provinces to identify the level of HIT innovativeness in these settings and test nine research hypotheses derived from the proposed research model. RESULTS: A total of 106 completed questionnaires were received, which represents a response rate of 52%. Our findings indicate strong support for the research model. Seven out of nine hypotheses were supported indicating a significant relationship between HIT innovativeness and structural, financial, leadership, and knowledge sharing capacity characteristics. Results also reveal a moderate level of HIT innovativeness in the surveyed hospitals, with more emphasis on administrative systems and their integration than on clinical systems and emerging technologies. CONCLUSIONS: This study demonstrates that organizational characteristics are related to HIT innovativeness; this relationship holds irrespective of the public or private nature of hospitals.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".