The promise of Telemedicine in Pakistan: A Systematic Review (Preprint)
Bibliographic record
Abstract
BACKGROUND Telemedicine is a medical practice of assisting remote patients and it has great potential in developing countries like Pakistan. Telemedicine solves the logistical barriers, deliver good support to weak health systems and unite worldwide networks of healthcare personals. Because of high implementation costs, yet it is not possible to adopt telehealth systems for low and middle-income nations. OBJECTIVE In this systematic review, we aim to present an update revision of region-based telemedical services in Pakistan. METHODS Libraries such as PubMed (Medline), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Scopus (EMBASE) and Google Scholar were used for document search. Newcastle Ottawa Scale (NOS) is adopted to conduct study quality. Majority of the studies (n-8) included in the review were of high quality as assessed through the Newcastle Ottawa scale. Selected study characteristics further analyzed based on different parameters such as publication year, sample size, study design, methods, motivation and outcomes. RESULTS Search produced 955 articles and 11 items were ultimately selected to conduct the review. These studies further characterized as region-based telemedicine implementation. Out of 11, eight studies were conducted in the urban region and three studies were conducted in the rural areas of Pakistan. Majority of studies produced evidence on telehealth interventions by smartphone services like SMS, apps and web-based telemedicine. CONCLUSIONS Telehealth interventions like mHealth, eHealth, telemedicine, and telepharmacy are starting to evaluate for the last two decades but certainly needs to become an integral part of Pakistan's current health infrastructure.
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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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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 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".