Support for healthcare workers and patients after medical error through mutual healing: another step towards patient safety
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Medical errors, especially those resulting in patient harm, have a negative psychological impact on patients and healthcare workers (HCWs). Healing may be promoted if both parties are able to work together and explore the effect and outcome of the event from each of their perspectives. There is little existing research in this area, even though this has the potential to improve patient safety and wellness for both HCWs and patients. METHODS: Using a patient-oriented research approach with constructive grounded theory methodology, we examined the potential for patients and HCWs to heal together after harm from a medical error. Individual interviews were conducted and transcribed verbatim. We conducted concurrent data collection and analysis according to grounded theory principles. With our findings, we created a framework and visual breakdown of the communication process between patients and HCWs. RESULTS: Our findings suggest that, after a medical error causing harm, both patients and HCWs have feelings of empathy and respect towards each other that often goes unrecognised. Barriers to communication for patients were related to their perception that HCWs did not care about them, showed no remorse or did not admit to the error. For HCWs, communication barriers were related to feelings of blame or shame, and fear of professional and legal consequences. Patients reported needing open and transparent communications to help them heal, and HCWs required leadership and peer support, including training and space to talk about the event(s). DISCUSSION: Our resulting framework suggests that if there was an opportunity for an open and purposeful conversation early or before increased emotional suffering, there might be an opportunity to bridge the barriers, and help patients and HCWs heal together. This, in turn, contributes to improved health quality and patient safety.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it