Akram Ashyani Postdoctoral Researcher (Life science Platform)

Data integration in European projects and Taiwan’s capability in big data integration

Taiwan and EU scientific research column
Akram Ashyani Postdoctoral Researcher (Life science Platform) December 27, 2022

The COVID-19 pandemic call attention to the significance of a well-integrated primary healthcare system in a crisis. When the pandemic’s initial effects appeared in early 2020, health systems required a high-level view of what was happening throughout the hospital to understand the virus’s fluctuation effects. Managing the pandemic proactively could not happen without access to information from every data source. Health care systems had to respond to various areas based on disconnected data that did not show how a change in one area (e.g., ICU capacity) would affect another (e.g., emergency department capacity). [1]

COVID-19 has also emphasized the importance of immediate access to individual electronic medical records for preparation and prompt response to health threats and the safety of patients, decision-making, data analysis, research and innovation, and precision medicine. [2]

The EU has a lot of digitalized health data that is not being used to its full potential due to legal, interoperability, and data quality issues. As a result, the establishment of a European Health Data Space (EHDS) has been identified as one of the European Commission’s top objectives. The EHDS aims to create a common space to assist people in taking charge of their health data and to enable the usage of health records for an improved healthcare system, better government policy, and research and innovation. A secure and safe data transmission, usage, and reusing of health data will be made possible by the EHDS, allowing the EU to fully benefit from the health information potential. [3]

The European Council recognized the importance of prioritizing the European Health Data Space (EHDS), and as a result, considered allocating many projects related to the data integration in the “Horizon Europe Work Programme 2023-2024” in health topics as follows. These projects will be opened on 12 Jan 2023 with a Deadline of 13 Apr 2023 at 17:00:00 Brussels time [4]:

• “HORIZON-HLTH-2023-TOOL-05-05: Harnessing the potential of real-time data analysis and secure Point-of-Care computing for the benefit of person-centred health and care delivery
• HORIZON-HLTH-2023-IND-06-01: Supporting the uptake of innovative Health Technology Assessment (HTA) methodology and advancing HTA expertise across EU
• HORIZON-HLTH-2023-IND-06-04: Modelling and simulation to address regulatory needs in the development of orphan and paediatric medicines
• HORIZON-HLTH-2023-IND-06-05: Mapping the hurdles for the clinical applications of Advanced Therapy Medicinal Products (ATMPs)
• HORIZON-HLTH-2023-IND-06-07: Development and harmonisation of methodologies for assessing digital health technologies in Europe” [4]

Typically, hospitals and other healthcare institutions use a variety of different computer systems for everything from patient monitoring to billing data. As long as the healthcare individual get some new information or want to retrieve information, all the different systems should be able to communicate or interface with another. [5]

Furthermore, with the advancement of medical technology, the amount of data available has increase significantly. Healthcare technology evolves much faster than data sharing and integration. The amount of patient data collected from various sources such as health agencies, hospitals, and devices increased significantly daily (See figure 1). [6]

Figure 1 Sources of health data for and individual, Created by GoInvo (4×3) (CC BY-SA 4.0) Date 15 March 2018, Author: Brysonwong01 Source: [7].

There is no method to access data collected in one system in another without data integration [8]. The process of combining data from various sources to give people a coherent perspective is data integration which aims to increase the accessibility of data and make it simpler for users and systems to consume and process [9].

The importance of big data integration is to have access to all data across all healthcare systems, which will lead to a better understanding of the patients’ situation. It will also aid in understanding disease from a national perspective, as well as differences between different genes. It also aids in the generation of intelligent and actionable analytics and helps to have clean, easily accessible data.

To effectively do data integration in healthcare system, an infrastructure should be chosen that meets the needs of the most people. Instead of building a data solution for one person or one group of people, health systems should invest in data infrastructure and capabilities that is suitable for most of the policymakers. Additionally, data and analytical experts should ask the correct questions to identify the most significant data before delivering data to the policymakers. [1]

Users should have no trouble understanding the integrated system, which means these systems should share data and then show it through a user-friendly and comprehensive interface. Therefore, data interoperability is a crucial component of healthcare data sharing. Data interoperability refers to a broad concept that includes consistent confidentially data protection and integrity, consistent healthcare data transit and appearance, and consistency guarantee of a general quality level of system service. Some of the healthcare technical interoperability, which defines rules messages on structuring is provided by Health Level 7 International (HL7). [6]

The HL7 was launched in 1987 to establish a general structure and standards for the interchange, integration, transmission, and retrieval of electronic medical data that helps medical care as well as health care management, delivery, and assessment [10]. The data standards specified by HL7 International are intended to make it simpler for healthcare institutions to exchange clinical data to help reduce the likelihood of geographical isolation and being highly varied in medical care [5].

The primary benefits of integrating medical data in clinical practice are enabling electronic information exchange, simplifying and lowering the cost of developing system interfaces, providing personalized healthcare, and improving the healthcare system’s view of patient data. [6]

Clinicians also can benefit from the ability to search across healthcare systems in real-time to get a complete picture of an individual patient and the data can be shared with the patient’s healthcare provider right away. This can help to ensure that the receiving hospital is adequately prepared to provide time-sensitive care. [11]

Additionally, data integration results in having clean data that can clearly show the medication utilized in a health care system resulting in transferring these data to the industry automatically, as well as sorting lab data for standardization of tests, observation, panel, and assessment names. Moreover, clean data can merge disparate electronic health records (EHRs) and data of patients from independent sources to enable data exchange and to fully use data meaningfully. By speeding up data integration from multiple source systems, healthcare organizations can extract, transform, load, and analyze data more quickly and efficiently, allowing them to make better decisions quickly. [6]

Taiwan has a lot of potentials to participate in the European Commission’s projects about health big data given that Taiwan currently has so many health big data centers, including:

• “Research center of health Care Industry Data Science, College of Management, HCIDSRC
• Big Data Center at the China Medical University hospital
• Taiwan Society for Biopreservation and Biobanking (TSBB)
• Taiwan biobank
• Taiwan’s National Health Insurance Research Database (NHIRD)
• Health and Welfare Data Science Center (HWDSC) of the Ministry of Health and Welfare (MOHW)”

Just “Big Data Center at the China Medical University hospital” has gathered more than one million people’s outpatient and hospitalization records. The hospital took the lead in establishing the “Big Data Center” in the medical system of Taiwan to analyze unstructured data, such as text and images, for use in personalized disease prevention and treatment, demonstrating Taiwan’s capacity to join European projects successfully.  [12]

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