How can the practice nurse be more involved in the care of the chronically ill? The perspectives of GPs, patients and practice nurses
Bibliographic record
Abstract
BACKGROUND: A well established "midlevel" of patient care, such as nurse practitioners and/or physician assistants, exits in many countries like the US, Canada, and Australia. In Germany, however there is only one kind of profession assisting the physician in practices, the practice nurse. Little is known about the present involvement of practice nurses in patients' care in Germany and about the attitudes of GPs, assistants and patients concerning an increased involvement. The aim of our study was to get qualitative information on the extent to which practice nurses are currently involved in the treatment of patients and about possibilities of increased involvement as well as on barriers of increased involvement. METHODS: We performed qualitative, semi-structured interviews with 20 GPs, 20 practice nurses and 20 patients in the Heidelberg area. The interviews were digitally recorded, transcribed and content-analysed with ATLAS.ti. RESULTS: Practice nurses are only marginally involved in the treatment of patients. GPs as well as patients were very sceptical about increased involvement in care. Patients were sceptical about nurses' professional background and feared a worsening of the patient doctor relationship. GPs also complained about the nurses' deficient education concerning medical knowledge. They feared a lack of time as well as a missing reimbursement for the efforts of an increased involvement. Practice nurses were mostly willing to be more involved, regarding it as an appreciation of their role. Important barriers were lack of time, overload with administrative work, and a lack of professional knowledge. CONCLUSION: Practice nurses were only little involved in patient care. GPs were more sceptical than patients regarding an increased involvement. One possible area, accepted by all interviewed groups, was patient education as for instance dietary counselling. New treatment approaches as the chronic care model will require a team approach which currently only marginally exists in the German health care system. Better medical education of practice nurses is indispensable, but GPs also have to accept that they cannot fulfil the requirement of future care alone.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".