Identical Telemedicine-Enabled Clinics in Three Different Geographies: Our Learnings
Keywords:telemedicine, rural health, underserved communities, social issues, primary healthcare, last mile care delivery
Background: Scarcity of primary care is felt most in underserved communities. Telemedicine (TM)-enabled clinics bridge the gap in such scenarios. There was a need to understand how the same TM model would work in different settings.
Aim: The aim was to study outcomes in three identical TM-enabled clinics in different geographies so as to understand how to scale up clinics in future.
Setting: Three totally different sites were chosen: a rural village with low socioeconomic status, a rurban (rural-urban) prosperous village, and an urban slum. The clinics planned was identical. The process of establishment, training, recruitment and treatment guidelines were the same. Any deviation was noted.
Methodology: Data were gathered through public health survey, interactions with villagers and local leaders, medical examination of individuals, feedback from patients, and household survey to understand the socioeconomic status of the community.
Main outcome measures: The article attempted to study how different social, cultural, and economic settings affected the outcome of identical TM clinics.
Results: TM, though accepted in different settings, was not sufficient to meet the healthcare needs of the community. These needs were related to the social and economic characteristics. Public health initiatives along with TM were most beneficial. In the underserved areas, infrastructure posed challenges to implementing TM, and ‘Last Mile Care Delivery’ was essential to create the full impact of TM.
Conclusion: TM-enabled clinics along with last mile care delivery are the key to improve healthcare in underserved communities. Further research into customized TM models for different geographies would help in providing the best care.
Limitations of the study: The study period was 4 months. The study was in one state of India, so the applicability of the findings to other states/countries may vary.
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Copyright (c) 2021 Suchitra Mankar, Nikhilesh Paradkar
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TMT is published under a Creative Commons Attribution-NonCommercial 4.0 International License.