Developing Electronic Cooperation Tools: A Case From Norwegian Health Care
Bibliographic record
Abstract
BACKGROUND: Many countries aim to create electronic cooperational tools in health care, but the progress is rather slow. OBJECTIVE: The study aimed to uncover how the authoritys' financing policies influence the development of electronic cooperational tools within public health care. METHODS: An interpretative approach was used in this study. We performed 30 semistructured interviews with vendors, policy makers, and public authorities. Additionally, we conducted an extensive documentation study and participated in 18 workshops concerning information and communication technology (ICT) in Norwegian health care. RESULTS: We found that the interorganizational communication in sectors like health care, that have undergone an independent development of their internal information infrastructure would find it difficult to create electronic services that interconnect the organizations because such connections would affect all interconnected organizations within the heterogenic structure. The organizations would, to a large extent, depend on new functionality in existing information systems. Electronic patient records play a central role in all parts of the health care sector and therefore dependence is established to the information systems and theirs vendors. The Norwegian government authorities, which run more than 80% of the Norwegian health care, have not taken extraordinary steps to compensate for this dependency-the government's political philosophy is that each health care institution should pay for further electronic patient record development. However, cooperational tools are complex due to the number of players involved and the way they are intertwined with the overall workflow. The customers are not able to buy new functionalities on the drawing table, while the electronic patient record vendors are not willing to take the economic risk in developing cooperational tools. Thus, the market mechanisms in the domain are challenged. We also found that public projects that were only financed for the first steps of project management could partially explain why many initiatives did not get past the initial planning and specification stages, but were stopped before further development could be made. Vendors were often unwilling to provide further own contribution without guaranteed return. CONCLUSIONS: We propose that the authorities take a coordinating role and provide financial help for development of electronic cooperational tools for health because the regular market mechanisms are insufficient to push these developments to the market. It is, however, critical that the role of users be considered, and for users to decide which developments should go forward.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".