Opportunity for Innovation: Experiences in Implementing Telehealth Services to Enhance Access to Healthcare during COVID-19 Pandemic in Sri Lanka: A Case Study
Bibliographic record
Abstract
Telehealth is the delivery of health-related services and information using electronic information and communication technologies. Telehealth enables the health service providers to connect with a remote patient to provide care, advice, reminders, education, intervention, monitoring and facilitates remote admissions. Due to COVID-19 related travel restrictions, disruptions in access to healthcare were observed in Sri Lanka. Therefore, a telehealth solution to connect patients where specialist medical doctors were inaccessible or unavailable, was planned and implemented in the North Central province of Sri Lanka in 2020. The objective of this case study is to describe the experience during the planning and implementation of the telehealth intervention. Issues faced during planning and implementation were securing adequate funds, limited knowledge of information technology among the health staff, the reluctance of patients to explain and show the signs through video consultation, and difficulties faced during the allocation of responsibility at each step of the telehealth services and provision of network facilities to peripheral hospitals. These issues were overcome by creating awareness among the key stakeholders on telehealth and its advantages, addressing concerns of the patients and conducting awareness campaigns on telehealth, streamlining the maintenance of equipment and most importantly, addressing concerns of the administrators, including health officials, and obtaining their consensus for the implementation of telehealth services. If these key issues can be forecasted and addressed timely, telehealth services could be successfully implemented in a resource-limited country like Sri Lanka.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".