Reclaiming Humanity in Healthcare—The First and Most Important Role for Physicians Is to Relieve Suffering Associated with Illness
Bibliographic record
Abstract
In this perspective, we argue that healthcare systems around the world are in a state of crisis, partly due to the loss of humanity. We trace this in part to the new public management systems that were implemented to increase efficiency and have had a counterproductive effect. We argue that these processes have contributed to the rising trend of burnout and moral injury that threaten healthcare workforces across the world. A multifaceted approach is required to address this complex issue. We believe that one of the key solutions is the transformation of the practice of medicine to facilitate a meaningful, valuable, person, and relationship-centered approach, caring for "this patient" instead of "patients like this." Establishing trusting relationships is important not only for care and decision-making but also for mutual fulfilment in a doctor-patient relationship. The sense of meaning and fulfilment builds resilience and may prevent moral injury that often leads to burnout. This cannot be accomplished without the practice of compassion in care. Therefore, creation of a compassionate physician workforce should be a top priority to address this issue. We advocate to include compassion as a required competence and as the "first physician role" in the medical education framework. We discuss the evidence to support these ideas and provide examples of such teaching aids. The transformation of medical education and care will require tectonic shifts in thinking, attitudes, and acceptance at both the personal and organizational levels. Through this perspective, we hope to share our vision, seek valuable feedback, and possibly inspire action on an issue that affects us all.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.058 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".