Comparisons of Physicians’, Nurses’, and Social Welfare Professionals’ Experiences With Participation in Information System Development: Cross-Sectional Survey Study
Bibliographic record
Abstract
Background: The integration of health care and social welfare services together with the consolidation of health care information systems (HISs) and client information systems (CISs) has become a timely topic. Despite this development, there is a scarcity of systematic research on physicians', registered nurses' (RNs) and social welfare professionals' (SWPs) experiences of participating in the development of HISs and CISs. Objective: This study aimed to examine how physicians, RNs and SWPs experience collaboration with HIS or CIS vendors, and what kinds of end users have participated in HIS or CIS development. Methods: National cross-sectional usability surveys were conducted in Finland among RNs and SWPs in 2020 and physicians in 2021. Questions concerning participation experiences were analyzed by professional group, working sector, managerial position, and age. Results: In total, 4683 physicians, 3610 RNs, and 990 SWPs responded to the surveys. In all 3 professional groups, those working in nonmanagerial positions and the youngest respondents participated least in HIS or CIS development, and 76% (n=3528) of physicians, 78% (n=2814) of RNs and 67% (n=664) of SWPs had not participated at all. When comparing the groups, physicians were least aware of feedback processes and least satisfied with vendors' interest in end-user feedback and the manner and speed of HIS development. Those who had dedicated working time for HIS or CIS development were less critical of vendors' interest and responsiveness to development ideas than those who had not participated at all. In all 3 professional groups, the youngest were most dissatisfied with HIS and CIS vendor collaboration. Conclusions: Experiences of participation in HIS and CIS development were relatively negative across all 3 professional groups, with physicians being the most critical. Dialogue and collaboration between developers and end users-also the youngest ones and frontline workers-need improvement; simply increasing allotted working time is unlikely to produce more positive participation experiences.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".