Collaborative care and professional boundaries: maternity care in Canada
Bibliographic record
Abstract
Introduction There is a growing interest in collaborative models of healthcare – or what has alternatively been referred to as ‘interprofessionalism’ – as a means to address a range of concerns within healthcare systems, not the least of which are shortages of healthcare professionals (DH, 2000; Institute of Medicine, 2003; Health Council of Canada, 2005). Collaborative models of practice are viewed as an important tool for increasing the flexibility of the health labour force. In a recently released report on health human resources in Canada it is argued that ‘bringing together physicians and other health professionals to work in teams can be an important part of the solution to challenges such as access to care, wait times for patients, shortages and burn out for professionals’ (Task Force Two, 2006, p iv). This reflects the broader view that increased interprofessional collaboration can address human resource shortages both by using existing resources more efficiently and by making the provision of care less demanding on practitioners, thereby improving retention. This has been particularly salient in rural areas where these problems are experienced most acutely (McNair, 2005). These trends raise a host of issues related to the management of professional boundaries and professional jurisdiction. In a previous article we examined the cases of primary and mental healthcare in Canada and the US in terms of how they revealed the structural embeddedness of medical dominance (Bourgeault and Mulvale, 2006). In this chapter, we seek to look beyond the structural features of the medical profession – or medical dominance – to examine how features of other health professions can also prove to be barriers to collaborative care. We focus on the case of maternity care in Canada, and the province of Ontario more specifically. This case is particularly interesting in light of the relative newness of the midwifery profession to the maternity care division of labour, the rapid changes occurring in maternity care human resources (particularly for intrapartum care) and extensive political and financial support that presently exists for collaborative initiatives in Canada. Interprofessionalism and professional boundaries The term ‘interprofessionalism’ has often been referred to in the literature as synonymous with teamwork or collaboration (Finch, 2000). Several authors have described the attributes of successful models of collaboration with much of this discussion focusing on micro-level factors pertaining to the relationships between the individuals involved (Stapleton, 1998; Rogers, 2003; Anderson, 2005a, 2005b).
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.021 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".