Evidence map›Paper›PMID 41855417›Full record

ArticleJournal of medical Internet research2026

Telemedicine Adoption for Managing Chronic and Rare Diseases in Indonesia During and Beyond the COVID-19 Era: Qualitative Study.

Christine Gracia Pratama, Rima Nurlianti, Cornelius Herstatt, Moritz Goeldner

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Christine Gracia PratamaTechnology and Innovation Management, Hamburg University of Technology (TUHH), Am Schwarzenberg-Campus 4, Hamburg, 21073, Germany, 49 40 30601 4777.ORCID http://orcid.org/0009-0003-5348-7748
Rima NurliantiTechnology and Innovation Management, Hamburg University of Technology (TUHH), Am Schwarzenberg-Campus 4, Hamburg, 21073, Germany, 49 40 30601 4777.ORCID http://orcid.org/0009-0004-1820-7859
Cornelius HerstattLeuphana University of Lüneburg, Lüneburg, Germany.ORCID http://orcid.org/0000-0001-5585-1169
Moritz GoeldnerTechnology and Innovation Management, Hamburg University of Technology (TUHH), Am Schwarzenberg-Campus 4, Hamburg, 21073, Germany, 49 40 30601 4777.ORCID http://orcid.org/0000-0002-8584-8080

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Telemedicine has emerged as a valuable tool for improving health care delivery, especially in low-resource and geographically isolated regions. In Indonesia, the COVID-19 pandemic highlighted the need for digital health solutions to manage chronic diseases and improve access to specialists. Objective: This study aimed to examine the rapid adoption of telemedicine in Indonesia, focusing on its role in managing chronic and rare diseases and highlighting both its benefits and challenges to long-term viability during and post pandemic. Methods: A qualitative study was used, following the Consolidated Criteria for Reporting Qualitative Research 32-item checklist and guided by established theories and frameworks. Recruitment followed a systematic multistage procedure suited to the context of Indonesia, an upper-middle-income country and Group of Twenty member characterized by wide regional and socioeconomic disparities. Data were collected through 15 semistructured interviews conducted between October and December 2024. The interviews were divided into 2 phases: first with physicians from various medical specialties and 6 out of 7 regions within Indonesia, and then with patients diagnosed with autoimmune diseases. All interviews were audio-recorded, transcribed verbatim, and analyzed inductively to identify recurrent themes and subthemes. Results: Before the COVID-19 pandemic, telemedicine adoption in Indonesia was limited, with many physicians recalling its nonexistence before 2015. The pandemic accelerated the adoption of virtual platforms, which became essential for patient consultation, follow-ups, and medication management. Though its use decreased after the pandemic, telemedicine remains valuable, particularly for chronic and rare disease management in remote areas with limited access to specialists. At least three overarching themes were identified: (1) acceleration and normalization of telemedicine (the pandemic catalyzed the integration of virtual consultations into routine care, transforming initial skepticism into broad acceptance); (2) accessibility and cost efficiency (telemedicine reduced financial and travel burdens, especially for patients in remote areas, with several reporting cost savings from hybrid consultation models); and (3) limitations of virtual care (physicians highlighted constraints related to the absence of physical examination). Conclusions: The findings reveal that telemedicine has become a valuable tool in Indonesia for managing chronic and rare diseases, particularly for follow-up care and medical specialist access across diverse geographical areas. While telemedicine has improved health care accessibility and demonstrated significant cost benefits by reducing transportation and consultation costs, challenges such as limited infrastructure and physician burnout remain. Long-term success will depend on the development of sustainable regulatory frameworks, continued investment in digital infrastructure, and a focus on optimizing cost-effectiveness in health care delivery.

Indexed as

COVID-19Rare DiseasesTelemedicineChronic DiseaseDigital HealthHumansIndonesiaPandemicsQualitative ResearchSARS-CoV-2chronic diseaseCOVID-19digital healthIndonesiarare diseasetelemedicine

Identifiers

PMID41855417
PMCPMC13002011

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.