Bibliographic record
Abstract
In the February issue of the Canadian Journal of Surgery (CJS), Dr. Waddell challenged CJS readers to consider the mismatch between physician numbers and patient demand and to reflect on ways to make access to surgery sustainable.1 A useful approach to this problem is to examine the association between the need for health care and the use of services provided by doctors. Nabalamba and Millar2 recently reviewed public access to doctors in Canada, as determined by the 2005 Canadian Community Health Survey.3 In this survey, the authors reported on Canadians' access to generalist and specialist physicians, based on the following 3 factors of need: state of health and illness acuity, predisposition to using services (e.g., age, sex, ethnicity) and enabling factors (e.g., education, income, and access to health providers and health facilities).4 Data for access to specialists merits attention, since they project the demand for services from our surgical colleagues. The data showed that 77% of Canadians aged 18 to 64 years and 88% of seniors reported consulting with a general practitioner (GP) in the previous year; corresponding numbers for specialists were 27% and 34%. It is reassuring that individual health need was a strong determinant for the use of services provided by doctors. When need was taken into account, physician consultations were independently associated with age, sex, household income, ethnicity, language, place of residence (rural v. urban) and having a regular GP. People over the age of 75, rural residents, visible minorities and Aboriginal people had low odds of obtaining specialist consultations. What does this portend for surgical specialists in the future? In concordance with health need as a strong determinant of access to surgeons, the article by Gaudet and others5 in this issue of the CJS shows that patients treated earlier with total hip replacement surgery had higher symptom scores.5 This demonstrates that prioritization of care for services with priority scoring tools and wait-time targets will play a role in resource allocation for surgical care in the future. Surgeons need to familiarize themselves with these tools to support quality and timely access. Interestingly, Gaudet and colleagues5 showed no association of age, sex and occupation with wait-time for arthroplasty care. The report by Nabalamba and Millar2 shows different data. Elderly people were shown to have access to family physicians, but their access to specialists was proportionately low. The aging baby boom population is not likely to tolerate this pattern. Specialists can expect this population to have high demands for such problems as fragility fractures and osteoarthritis. These have recently been addressed through wait-list funding to augment surgical services; however, targeted interventions impact on other surgical services that do not receive augment funds. This translates to surgeons operating from multiple sites (including private care facilities) instead of traditional hospital sites. These practice changes must be met by surgical teamwork and careful patient care handovers. In academic centres, the impact on surgical trainees must be taken up by innovative teaching, such as simulation. A chief enabling factor that facilitates access to specialists is ready access to a regular GP. However, it is estimated that 3.5 million Canadians do not have a regular GP. This issue has been addressed by increasing medical undergraduate and post-graduate enrolments and by the development of new models of medial education, for example, the distributed medical education programs at the Northern Ontario School of Medicine and at the University of British Columbia. Strategically aimed at improving access to family physicians in remote communities, distributed medial education programs will bring new pressures for surgical specialists. Developing education programs may conflict with the need for high service volumes, unless funding is also provided for quality education for new trainees and time is permitted to enable surgeons to teach their trainees in the operating room. Surgeons may be altruistic when offering to teach, but pressures to deliver service add new responsibilities. Can alternative providers such as nurse practitioners, advanced care physiotherapists and physician assistants help to ensure the best navigation throughout the system? These training programs also are meeting challenges in keeping up with demand. This will require sophisticated professional communication with surgeons, and issues over liability must be tackled. The dialogue will continue into the future to ensure that the Canada Health Act will maintain access to publicly funded, medically necessary health care that is free of financial or other barriers. Surgeons must accommodate novel models to deliver their services based on burgeoning health need as well as predisposing and enabling factors that determine Canadians' wishes for optimal health care. Hopefully, this can occur without “burnout”! Garth L. Warnock, MD Coeditor
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.299 | 0.133 |
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".