EFEKTIFITAS LAYANAN KESEHATAN TELEHEALTH DALAM MENUNJANG KUALITAS PELAYANAN KESEHATAN : META ANALISIS
Bibliographic record
Abstract
Era digitalisasi mempengaruhi adanya perubahan dalam bidang kesehatan, terutama dalam pelayanan kesehatan. Telehealth merupakan salah satu bentuk layanan kesehatan yang ada pada era digitalisasi saat ini. Adanya layanan telehealth diharapkan dapat membantu penyediaan layanan kesehatan dalam pemberian layanan ke masyarakat secara optimal sehingga masyarakat dapat dengan mudah mendapatkan layanan kesehatan yang ada. Tujuan penelitian ini adalah untuk mengetahui efektifitas layanan kesehatan telehealth dalam menunjang kualitas pelayanan kesehatan. Metode dalam penelitian ini merupakan penelitian meta analisis dan systematic review dengan PICO (Population = pengguna layanan kesehatan telehealth, Intervention = telehealth, Comparison = tidak menggunakan telehealth, Outcome = pelayanan kesehatan). Artikel yang digunakan dalam penelitian ini diperoleh dari beberapa database diantaranya yaitu PubMed,, ScienceDirect, dan Google Scholar. Artikel yang digunakan adalah artikel full-text dari tahun 2020 hingga 2025. Artikel dipilih menggunakan diagram PRISMA flow. Artikel dianalisis menggunakan aplikasi RevMan 5.3. Hasil pada penelitian ini menunjukkan dari 6 artikel yang dianalisis dalam studi meta analisis ini berasal dari Amerika dan Kuwait. Studi menunjukkan bahwa layanan kesehatan telehealth efektif dalam menunjang pelayanan kesehatan (OR 1.79; CI 95% = 0.95 hingga 3.34; p = 0.07). Kesimpulan dalam penelitian ini adalah adanya layanan kesehatan telehealth efektif dalam menunjang pelayanan kesehatan. Kata kunci : digitalisasi kesehatan, kualitas pelayanan kesehatan, telehealth The digitalization era has brought changes in the healthcare sector, particularly in healthcare services. Telehealth is one form of healthcare service that has emerged in this digital age. The presence of telehealth services is expected to support the provision of healthcare services to the public more optimally, making it easier for people to access healthcare.The aim of this study is to determine the effectiveness of telehealth services in supporting healthcare delivery. This study uses a meta-analysis and systematic review method based on the PICO framework (Population = telehealth service users, Intervention = telehealth, Comparison = non-telehealth users, Outcome = healthcare services). The articles used in this study were obtained from several databases, including PubMed, ScienceDirect, and Google Scholar. The selected articles were full-text publications from 2020 to 2025. The selection of articles was carried out using the PRISMA flow diagram. The analysis was conducted using the RevMan 5.3 software. The results of this study show that six articles included in the meta-analysis originated from the United States, Ethiopia, Iran, and Canada. The studies indicate that telehealth services are effective in supporting healthcare delivery (OR 1.79; 95% CI = 0.95 to 3.34; p = 0.07). In conclusion, telehealth services are effective in supporting healthcare delivery. Keywords: digitalization of health, health service, telehealth
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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 | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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; both teacher heads agree on what is shown here.
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".