The impact of a hospitalist on role boundaries in an orthopedic environment
Bibliographic record
Abstract
PURPOSE: Hospitalists specialize in the management of hospitalized patients. They work with several health care professionals to provide patient care. There has been little research examining the perceived impact of the hospitalist's role on staff working in an orthopedic environment. This study examined the experiences of staff across several professional backgrounds in working with a hospitalist in an orthopedic environment. PARTICIPANTS AND METHODS: A qualitative descriptive approach was taken to investigate the experience of staff working with a hospitalist at a specialized orthopedic hospital. Purposive sampling was used to recruit interview participants including nurses, internists, pharmacists, physiotherapists, anesthetists, senior administration, and orthopedic surgeons to the point of theoretical saturation, which occurred after 12 interviews. Interviews were coded, and these codes were combined into categories and predominant themes were identified. FINDINGS: Overall, staff believed that the hospitalist role was a positive addition to the facility. The role benefitted patients and supported the clinical well-being and education of staff. Many staff felt the hospitalist had no impact on their workload, but others reported that their work had decreased or increased. Several described the potential for role overlap between the hospitalist and other physicians. CONCLUSION: The importance of interprofessional collaboration in the implementation of the hospitalist role was a recurring theme in our analysis. This study demonstrates the importance of educating staff about the hospitalist role boundaries prior to implementing hospitalist care.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| 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".