Doctor Appointment Booking System Using MERN Stack: A Systematic Review and Analysis

• Author(s): Saloni Patil; Shruti Rohidas Ransing; Shilpa Sanjay Vantalkar; Purvii Sanjay Dhaybar
• Paper ID: 1712066
• Page: 1628-1632
• Published Date: 24-11-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 5 November-2025
• DOI: https://doi.org/10.64388/IREV9I5-1712066

Abstract

Scope: The healthcare sector is increasingly reliant on digital appointment-scheduling platforms to overcome inefficiencies of manual/phone-based booking (e.g., long waiting times, poor resource utilisation). This paper focuses on digital appointment systems specifically built using the MERN stack (MongoDB, Express.js, React.js, Node.js) architecture. Methodology: A systematic review of published works from 2020?2025 that implement or analyse MERN (or closely related full-stack JavaScript) solutions for doctor/health-provider appointment scheduling. Findings: The MERN stack offers benefits such as single-language full-stack development (JavaScript/TypeScript) and rapid front-end/back-end integration. However, critical challenges emerge: NoSQL databases like MongoDB may complicate relational modelling (doctor-patient-appointment links); authentication/authorization practices vary widely; and scalability/security issues (e.g., regulatory compliance, data integrity) are often under-analysed. Conclusion: This review identifies key gaps in existing MERN-based appointment-systems research?particularly around data integrity, security/compliance, and standard healthcare-data interoperability?and proposes future research avenues (e.g., integration with FHIR, microservices/serverless, stronger access control).

Citations

IRE Journals:
Saloni Patil, Shruti Rohidas Ransing, Shilpa Sanjay Vantalkar, Purvii Sanjay Dhaybar "Doctor Appointment Booking System Using MERN Stack: A Systematic Review and Analysis" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 1628-1632 https://doi.org/10.64388/IREV9I5-1712066

IEEE:
Saloni Patil, Shruti Rohidas Ransing, Shilpa Sanjay Vantalkar, Purvii Sanjay Dhaybar "Doctor Appointment Booking System Using MERN Stack: A Systematic Review and Analysis" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025, doi: https://doi.org/10.64388/IREV9I5-1712066

APA:
Saloni Patil, Shruti Rohidas Ransing, Shilpa Sanjay Vantalkar, Purvii Sanjay Dhaybar (2025). Doctor Appointment Booking System Using MERN Stack: A Systematic Review and Analysis. Iconic Research And Engineering Journals, 9(5). doi: https://doi.org/10.64388/IREV9I5-1712066

MLA:
Saloni Patil, Shruti Rohidas Ransing, Shilpa Sanjay Vantalkar, Purvii Sanjay Dhaybar "Doctor Appointment Booking System Using MERN Stack: A Systematic Review and Analysis" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1712066

BibTeX

@article{1712066,
author = {Saloni Patil, Shruti Rohidas Ransing, Shilpa Sanjay Vantalkar, Purvii Sanjay Dhaybar},
title = {Doctor Appointment Booking System Using MERN Stack: A Systematic Review and Analysis},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {5},
pages = {1628-1632},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712066.pdf},
abstract = {Scope: The healthcare sector is increasingly reliant on digital appointment-scheduling platforms to overcome inefficiencies of manual/phone-based booking (e.g., long waiting times, poor resource utilisation). This paper focuses on digital appointment systems specifically built using the MERN stack (MongoDB, Express.js, React.js, Node.js) architecture. Methodology: A systematic review of published works from 2020?2025 that implement or analyse MERN (or closely related full-stack JavaScript) solutions for doctor/health-provider appointment scheduling. Findings: The MERN stack offers benefits such as single-language full-stack development (JavaScript/TypeScript) and rapid front-end/back-end integration. However, critical challenges emerge: NoSQL databases like MongoDB may complicate relational modelling (doctor-patient-appointment links); authentication/authorization practices vary widely; and scalability/security issues (e.g., regulatory compliance, data integrity) are often under-analysed. Conclusion: This review identifies key gaps in existing MERN-based appointment-systems research?particularly around data integrity, security/compliance, and standard healthcare-data interoperability?and proposes future research avenues (e.g., integration with FHIR, microservices/serverless, stronger access control).},
month = {November}
}