Accessing patient satisfaction for palliative care outpatient telemedicine services at a tertiary care hospital in Karachi, Pakistan.
Bibliographic record
Abstract
Abstract Background: Telemedicine has been projected as one way to improve access to palliative care services for patients with serious illness, delivering health care services remotely given a shortage of trained physicians and available specialty services. This technology is being used extensively to improve quality of life of patients needing palliation during unprecedented times of COVID-19 pandemic. However, its efficacy has not been evaluated, specifically in palliative care specialty, where it is instrumental for healthcare access. We aimed to evaluate satisfaction and factors related to satisfaction with telemedicine appointment system and palliative care team during virtual outpatient palliative care telemedicine consultations. Methods This cross-sectional study was conducted on patients seen in adult palliative care telemedicine clinics between February 2020 to March 2022 at a tertiary care hospital in Pakistan. Results A total of 130 participants participated, with a mean age of 63.2 years, n = 61 (47%) males and n = 69 (53%) females. There were n = 76 (58.4%) initial visits and n = 54 (41.5%) follow-ups. 94% of the participants agreed with healthcare access, 92% with the quality of care, 92% with patient-physician interaction, 77% with convenience, 91% wanted to continue teleconsultation and 88% found it cost-effective. Besides this, 46% of participants expressed that they were worried about privacy breach. Conclusion Telemedicine is an innovative approach. Participants find it accessible, cost-effective, convenient and of good quality. In future, it can be implemented and should be promoted in the post pandemic landscape as an effective patient care modality to address enormous unmet needs of patients with functional frailty or living in remote area.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".