2024, Volume 17, Issue 1, pp 50 – 56

Designing the future of prenatal care: an algorithm for a telemedicine-enhanced team-based care model

SCImago Journal & Country Rank

Issues

Special Issues

Authors and Affiliations

Corresponding author Luciana Alexandra Pavelescu Department of Cellular and Molecular Biology and Histology, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania E-mail: luciana.pavelescu@umfcd.ro

Abstract

This study provides a conceptual exploration of an innovative telemedicine-enhanced team-based care (TETC) model, tailored to prenatal care, integrating a multidisciplinary team approach with advanced telemedicine technologies. The algorithm developed for TETC aims to optimize communication and coordination among healthcare professionals, including obstetricians, midwives, nutritionists, and mental health experts. This cohesive team structure ensures a comprehensive care plan encompassing all facets of maternal and fetal health. Leveraging telemedicine tools like video conferencing and digital health records, the model supports remote consultations and coordinated care, proving particularly advantageous during pandemics or in regions with limited healthcare access. Central to the TETC model is patient-centered care, focusing on personalized care plans attuned to the individual needs, health status, and socioeconomic backgrounds of pregnant women. This approach not only enhances accessibility and convenience by diminishing the necessity for physical consultations but also ensures continuity of care throughout pregnancy. This continuity is crucial for consistent health parameter tracking and early risk identification. The paper discusses the model’s design, operational workflow, and ethical and legal considerations, providing implementation guidelines and potential applications. The TETC model, rooted in current technological capabilities and healthcare frameworks, underscores the need for close collaboration with healthcare professionals to adhere to medical standards and address real-world requirements effectively.

Keywords

About this article

PMC ID: 11080513
PubMed ID: 
DOI: 10.25122/jml-2024-0145

Article Publishing Date (print): 1 2024
Available Online: 

Journal information

ISSN Printing: 1844-122X
ISSN Online: 1844-3117
Journal Title: Journal of Medicine and Life

Copyright License: Open Access

This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited.


SCImago Journal & Country Rank

Issues

Special Issues