Addressing Barriers in Data Collection, Transmission, and Security to Optimize Data Availability in Healthcare Systems for Improved Clinical Decision-Making and Analytics

Abstract

Data availability in healthcare faces numerous challenges that stem from various technical, environmental, and security issues. These include medical device malfunctions, unreliable data transmission protocols, and failures in authentication systems,that disrupt the timely and accurate collection and transmission of healthcare data. This study explores the core barriers to data availability in healthcare systems, categorizing them into three broad areas: (1) echnological Failures, such as device malfunctions and calibration errors that compromise data collection; (2) Authentication and Security Bottlenecks, which involve failures in access control systems that prevent authorized personnel from accessing critical data; and (3) Environmental and Infrastructural Constraints, such as network instability, electromagnetic interference, and power outages that interrupt data transmission. This paper also provides an in-depth evaluation of existing solutions aimed at addressing these challenges and proposes new methods to improve data availability. Specifically, it discusses data transmission protocols, real-time device diagnostics, decentralized security architectures like blockchain, and improved device calibration techniques using machine learning algorithms. The proposed solutions focus on increasing the resilience of healthcare data collection and transmission, integrating state-of-the-art technologies such as edge computing, predictive maintenance models, and biometric authentication systems. These technologies can improve data reliability, reduce latency, and ensure that healthcare data remains available in the correct format in order to supoport both real-time clinical decisions and long-term healthcare analytics.