Telemedicine and Health System Strengthening: An ANOVA-Based Study on Access, Outcomes, and Satisfaction
NARWADIYA, S. C.; KASHYAP, D.; Rao, D. R.
Show abstract
Telemedicine has emerged as a transformative tool for enhancing healthcare accessibility, particularly in underserved and remote areas. This study assesses the effectiveness of telemedicine technologies in improving patient care, disease management, and overall health system performance from the perspective of medical professionals. A cross-sectional survey was conducted among 247 doctors using a structured and reliable questionnaire (Cronbachs alpha = 0.872). Paired samples t-tests and ANOVA were employed to evaluate perceptual changes before and after telemedicine awareness interventions. Results indicated significant improvements in doctors confidence regarding telemedicines role in diagnosing and managing conditions such as tuberculosis, chronic obstructive pulmonary disease (COPD), malaria, and COVID-19. ANOVA revealed statistically significant differences across three thematic domains: Patient Care Improvement (PCI), Disease Cure Improvement (DCI), and Health System Improvement (HSI). While telemedicine is widely supported for routine and chronic care, limitations remain in its application to complex treatment scenarios. The findings highlight telemedicines potential to enhance healthcare delivery and emphasize the need for targeted training and infrastructure development to facilitate its effective integration into health systems. ObjectiveTo assess the effectiveness of telemedicine technologies in enhancing healthcare delivery, with specific emphasis on accessibility, treatment outcomes, and systemic health improvements, as perceived by medical professionals.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Impact of electronic medical records on healthcare delivery in Nigeria: A Review 96%
- Views and experiences of young people on using mHealth platforms for sexual and reproductive health services in rural low- and middle-income countries: a qualitative systematic review 95%
- Benefits and Challenges of Using Virtual Primary Care During the COVID-19 Pandemic: From Key Lessons to a Framework for Implementation 95%
Similar papers in this journal
- Strengthening health service delivery and governance through institutionalizing ‘Urban Health Atlas’ - a geo-referenced Information Communication and Technology tool: lessons learned from an implementation research in three cities in Bangladesh 96%
- Strengthening government’s response to COVID-19 in Indonesia: a modified Delphi study of medical and health academics 96%
- Protocol: Waiting time and ways of accessing specialized health services in public hospitals in Ecuador 95%
Similar papers in this journal
- A Web-based, Mobile Responsive Application to Screen Healthcare Workers for COVID Symptoms: Descriptive Study 95%
- Knowledge, attitude and practice toward COVID-19 among healthcare workers in public health facilities, Eastern Ethiopia 94%
- Is virtual care the new normal? Evidence supporting Covid-19’s durable transformation on healthcare delivery 94%
Similar papers in this journal
- Conceptualizing centers of excellence: A global evidence 93%
- Women’s Awareness of Obstetric Fistula and its Associated Factors Among Reproductive-Age Women in Ethiopia: A Multilevel Analysis Based on National Survey Data 93%
- Family physicians supporting patients with palliative care needs within the Patient Medical Home in the community: An Appreciative Inquiry qualitative study 93%
Similar papers in this journal
- Caregivers’ Perspective: Satisfaction With Healthcare Services At The Paediatric Specialist Clinic Of The National Referral Centre In Malaysia 94%
- Learning from the resilience of hospitals and their staff to the COVID-19 pandemic: a scoping review 94%
- The role of IT ambidexterity, digital dynamic capability and knowledge processes as enablers of patient agility: an empirical study 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.