Integrating Centralized Barcode Techniques for Effective and Secure Transfer of Patients’ Data among Different Healthcare Sectors

Introduction

Currently, the main challenge of the hospitals in the United States derived from the fragmented structure of the healthcare system. There is no one integrated system that supports a unified communication and management of patient records in one centralized cloud. It is possible that such fragmented systems lead to patient burden and medical input error because patients need to register as long as hospitals share patient health records. That consumes patients’ time and effort to fill the medical or personal health data when they visit a new hospital or laboratories. Especially, patients who lack knowledge of medical terms have a difficulty in filling history of disease or diagnoses that might cause medical input errors. To fill in the gap, we propose a novel prototype concept that has benefits for low health literacy groups. Therefore, having patients’ health records including their past medical history, lab results, and any other related data shared among healthcare sectors can be useful for effectively managing patient data with the help of a unified way of centralized patients’ data. Such system helps stakeholders exchange patients’ data in an effective and secure way.

Motivations

There are several reasons why this study pursues centralized patients’ data:

· There is no centralized way of communication between hospitals regarding the patient’s data.

· There is no unified way for registering, accessing, monitoring and tracking patient’s data especially the one that benefits the low health literacy group.

· The workload is heavy for hospital personnel, so there should be a way for accessing patient’s data or processing it in an accurate and secure way. It could help to correctly diagnose and evaluate patients’ status in a proper way without causes any medical errors due to the misfiling of patients’ information.

In this study, we aim to design a workable prototype to centralize patients health records as a unified system for offering an efficient and secure way of handling patients’ information among healthcare sectors, which will ultimately benefit low health literacy group. That could be achieved by utilizing barcode techniques to encode patient’s information electronically and store their barcode in a unified server that uses an in-encryption method to secure patient’s data. Next section, we provide the information in terms of the components of the proposed prototype and its infrastructure that helps to achieve the main goal of centralizing patients’ data.

Related Work

To achieve the main goal of centralization and ensure its workability, several research papers were found regarding ensuring security and safety of patients’ data in healthcare sectors by integrating barcode techniques that are validated. Since most of the security concerns is around tackling user’s data, and privacy, security helps in offering the appropriate measurement for defending against any malicious attack that might be an unauthorized attempt to access data or services or to modify data, or it might be intended to deny service for legitimate users [1]. The attack against systems can be categorized as an attack against the CIA (Confidentiality, Integrity, and Availability) [1]. Another study validated the workability of barcode techniques in handling patients’ data. The “QRStream” method can help in archiving that. It is a secure and convenient method for transferring health data between users and health organizations [2] since the patient’ can ensure that he or she is the only one who is authorized to scan their QR code to view their own medical records from the healthcare sector. The last study evaluated that the cloud server can be a safe place to store patients’ data if it is used as an encryption method for protecting patients’ data. One of this method is “fog computing “in which it will be served a middle layer where it encrypts the data that is received from devices and send it directly to the cloud server by using Advanced Encryption Algorithm (AES) which uses a symmetric block cipher technique to encrypt and decrypt data [3]. The combination of all these studies proves that the suggested prototype techniques and methodologies are applicable and workable for ensuring the security and efficiency of the proposed prototype.

Thus, in our postposed prototype, we plan to ensure the server that will utilize advanced encryption methods for patients’ data. That patient’s data can be stored in the format of a barcode in that server. That server is accessible by all its legitimate users and in case of patients would like to exchange their medical records from one hospital to another; All the hospitals that have authorized access to the server can access and exchange patients’ records. In this way, the transferability, and the accessibility of patients’ data can be secure and efficient. The characteristics of each component of the proposed methodology have been evaluated based on the recent techniques and methodologies used. For the server infrastructure, we advised using “cloudlets” technology which helps to centralize all the server data in one cloud server, and it enables improved privacy and reduced latency, bandwidth, scalability, reliability, and energy efficiency [4]. Thus, increasing the number of cloudlets due to the caching at the cloudlets positively affects the performance of the system [4].

Our Prototype Concept

We focus on centralizing patients’ data by integrating barcode techniques and Advanced Encryption Algorithm methodologies that are applicable and workable for ensuring the security and efficiency of the prototype. The characteristics of each component of the proposed methodology have been evaluated based on the recent techniques and methodologies used. Thus, we plan to ensure the server that will utilize advanced encryption methods for patients’ data. That patient’s data can be stored in the format of a barcode in that server. That server is accessible by all its legitimate users and in case of patients would like to exchange their medical records from one hospital to another; All the hospitals that have authorized access to the server can access and exchange patients’ records. In this way, the transferability, and the accessibility of patients’ data can be safe and efficient. Our prototype concept can be used to save patients time when staying at the hospital and reduce medical input errors in filling the personal health information and medical history, which assists especially for a low literacy health group.

Novelty of the Approach

We suggest a novel approach by centralizing patients’ data leveraging barcoded techniques with an encrypted server that will offer a secure and efficient way of communication and data management among healthcare sectors. Our proposal will help in designing a unified system approach for handling patient data among different stakeholders lowering patient efforts.

Eman Alofi is a first-year Ph.D. student at Stevens Institute of Technology. Her research is geared towards systems engineering in association with education, healthcare, and industrial engineering. This position paper is proposed under the guidance of professor Sang Won Bae, from the Systems Engineering Applications to Healthcare course during the spring semester in 2021.

Sang Won Bae is an assistant professor in Engineering Management and a director of the Human-Computer Interaction Lab. at Stevens Institute of Technology. Her research interest areas are human-computer interaction, human-centered AI systems, and engineering management, mobile computing, and machine learning. She is interested in developing intelligent human-machine systems for solving real-world problems in the contexts of healthcare and education.

REFERENCE

1. Len Bass, Paul Clements and Rick Kazman, Software Architecture in Practice, 3rd Edition. Addison-Wesley, 2013.

2. H. Mao, C. Chi, J. Yu, P. Yang, C. Qian and D. Zhao, “QRStream: A Secure and Convenient Method for Text Healthcare Data Transferring,” 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 3458–3462.

3. Y. Winnie, U. E. and D. M. Ajay, “Enhancing Data Security in IoT Healthcare Services Using Fog Computing,” 2018 International Conference on Recent Trends in Advance Computing (ICRTAC), Chennai, India, 2018, pp. 200–205.

4. Uzun, Vassilya,”Performance Evaluation of the Cloud-based QR Code Identity Tag System with Cloudlets,”NISCAIR-CSIR, India, Dec-2020, pp. 1106–1109