Patients With Cardiovascular Disease Revisiting Specialist Physicians via Remote Treatment: Interview Study of Experiences
Bibliographic record
Abstract
BACKGROUND: Access to health care for an aging population with growing needs presents major challenges in northern Sweden's sparsely populated regions. Few people, the lack of professionals, and long distances make it difficult to provide health care on equitable terms according to the Swedish legislation. Remote treatment (RT) using information and communication technology has been suggested to overcome these difficulties, and person-centered care (PCC) is a desired philosophy to improve the quality of health care. However, there is scarce knowledge about how patients experience RT meetings. OBJECTIVE: This study aimed to describe the experiences of patients with cardiovascular disease revisiting specialist physicians via RT guided by a PCC perspective in northern Sweden's sparsely populated regions. METHODS: A qualitative study was conducted based on interviews with 8 patients with cardiovascular disease revisiting their physician through RT, from a digital health room to a health care center or from a health care center to a hospital. The interviews were recorded, transcribed verbatim, and analyzed using inductive content analysis. The results are discussed from a PCC perspective. RESULTS: The analysis resulted in 6 categories: good accessibility, safety with good relationships, proximity and distance with technology, habit and quality of the technology facilitating the meeting, cherishing personal integrity, and participation in own care. These categories were interpreted as the theme, participation and relationships are important for good and close care via RT. CONCLUSIONS: The study shows that participation and relationships are important for good and close care via RT. To improve the quality of an RT meeting, PCC can be applied but needs to be extended to the digital domain-electronic PCC, especially the communication component, as it is the most salient difference from a face-to-face meeting. Important factors that should be considered before, during, and after the RT meeting have been identified.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".