Usability, Benefits, and Barriers Associated With Patients’ Access to Electronic Health Record–Integrated Telehealth in Hospitals in Riyadh: Qualitative Study
Bibliographic record
Abstract
Background: The integration of electronic health records (EHRs) with telehealth platforms represents a transformative approach in health care, providing critical accessibility and engagement solutions, especially during the COVID-19 pandemic. In Riyadh's hospitals, the adoption of EHR-integrated telehealth has significantly increased and offers enhanced patient care options. However, there is a need to examine its continued relevance, effectiveness, and challenges in a postpandemic context. Objective: This research aimed to qualitatively investigate the usability, perceived benefits, and barriers to patients' access to EHR-integrated telehealth from both patients and health care providers (HCPs) in a major Riyadh hospital. Methods: A qualitative research design was used, featuring semistructured interviews with 20 patients and 10 HCPs, selected through purposive sampling for their direct experience with EHR-integrated telehealth services at Sulaiman Al Habib Hospital in Riyadh. Thematic analysis, supported by NVivo 14 software, was used to analyze the transcriptions and extract themes related to usability, perceived benefits, and barriers. Results: The findings indicate that patients generally regard EHR-integrated telehealth positively, appreciating its navigability, convenience, and facilitation of remote health care interactions. Reported benefits included reduced physical visits, time savings, and more accessible follow-ups, contributing to greater continuity of care. However, significant barriers were identified, including technical challenges, lack of integration across hospital branches, absence of insurance payment linkages, and limited patient choice among providers. HCPs also expressed concerns over digital literacy gaps, the platform's limitations for specialized and complex care, and technical disruptions impacting care delivery. Conclusions: EHR-integrated telehealth offers substantial potential to improve health care delivery in Riyadh's hospitals by enhancing access, convenience, and patient engagement. However, maximizing these benefits in Saudi Arabia's evolving health care landscape requires addressing identified barriers, particularly in platform stability, interbranch integration, insurance linkages, and patient support resources. Findings are grounded in a single-hospital sample and are intended to inform improvements in similar hospital settings in Saudi Arabia rather than national generalization.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".