Topics Toward Efficient Case Data Recording and Collection in Clinical Trials -HL7 Utilization of data linkage based on standardization of electronic medical record data such as FHIR-.

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The use of data linkage with electronic medical records is expected to reduce the workload and improve the efficiency of transcribing and collating case data in clinical trials. In addition, standardization is gaining momentum, with data exchange methods based on technologies commonly used on the Web being adopted as a new standard in the field of healthcare information by the Ministry of Health, Labor and Welfare, to enable electronic sharing and viewing of medical information necessary for medical treatment and other purposes among medical institutions at any time. We will present an overview of the deliverables*1 that we have compiled based on our research of these trends and findings from experts. We will also propose a problem-solving approach to realize data linkage with electronic medical records with the aim of improving the efficiency of case data recording and collection operations in clinical trials.

Issues in the field related to recording and collecting case data in clinical trials

Currently, in clinical research and trials, case data of participants are transferred from clinical data created and stored by medical institutions, such as electronic medical records, paper medical records, and worksheets (hereinafter referred to as "source documents"), to a system for electronically capturing clinical trial data (Electronic Data Capture, EDC), and to clinical trial data (clinical trial data) (hereinafter referred to as "clinical trial data"), which are stored in the clinical data management system (EDC). The data is recorded and collected by the Clinical Research Coordinator (CRC), who manually transcribes and inputs the data into the EDC system. This transcription work, or double entry of data, places a heavy burden on medical institutions, and because it is a manual process, transcription errors can occur.

On the other hand, at pharmaceutical companies, Clinical Research Associates (CRAs) spend a great deal of time and effort to verify the consistency between the data in the source documents and the data entered into EDC (Source Data Verification, SDV).

In this way, case data in clinical trials are manually recorded and collected by CRCs, CRAs, and other related personnel, which currently imposes a heavy burden and takes a lot of time. These burdens are one of the factors that result in increased clinical development costs and hinder the acceleration of new drug development.

Expectations and actual conditions for data linkage between electronic medical records and EDC, etc.

Electronic Data Capture (EDC) data linkage is a system for transferring clinical data from electronic medical records of medical institutions to EDC and other systems owned by pharmaceutical companies in clinical research and trials. The direct transfer of data reduces the workload on medical institutions, such as transcription from electronic medical records to EDC, as well as SDV by pharmaceutical companies. In addition, it avoids the deterioration of case data quality due to transcription errors, and has been attracting attention in recent years as a method to improve the efficiency of the clinical trial data collection process. The requirement for "using a system that automatically transcribes data from electronic medical records to case report forms" was added in the July 2021 revision of the GCP Guidance*2.

It is expected that the efficiency and quality improvement of clinical trial operations will allow more focus on patient care for those participating in clinical trials, as well as reduce the cost of drug development, leading to earlier development of new drugs and improvement of the international competitiveness of the pharmaceutical industry. However, as of January 2022, the use of data linkage between electronic medical records and EDC for clinical research and trials in Japan was limited, with only one of the 50 pharmaceutical companies having already introduced such a system*3. 3 The reasons for this are the increase in setup man-hours for data linkage, the increase in implementation costs, and the lack of sufficient infrastructure at medical institutions.

Many of the current electronic medical records are customized for each medical institution and have been developed to be uniquely adapted to each medical institution, with a lot of data freely written by physicians. In addition, electronic medical records have focused on convenience of input rather than output of data according to standards, making it difficult to efficiently extract data that meets the objectives of clinical trials, and thus the introduction and spread of data linkage such as electronic medical records-EDC has not progressed.

Figure 1 Recording and collection of case data using data linkage between electronic medical records and EDC, etc. Current (left) and future (right)

Future vision of efficient data linkage utilizing medical information exchange standards

Data exchange methods based on technologies commonly used on the Web have been adopted as a new standard in the field of healthcare information by the Ministry of Health, Labour and Welfare. In June 2023, the government's Headquarters for Promoting Medical DX proposed the "standardization of electronic medical record information" as a measure, and standardization is gaining momentum.

In Japan and other countries, as the development of networks that allow medical institutions to share and view medical information electronically with each other progresses, the use of HL7 FHIR as a standard for exchanging medical information has begun and is expected to expand in the future. This trend will further promote the exchange of medical data, making it more convenient for patients and healthcare professionals, for example, enabling doctors to consult a patient's past medical information when visiting a medical institution for the first time.

FHIR (Fast Healthcare Interoperability Resources) is the latest standard created by HL7 International and designed to enable the exchange of healthcare-related information. FHIR is also expected to be adopted in Japan in March 2022 as a standard for exchanging medical information such as health checkup result reports, and data exchange using FHIR is expected to progress in the future.

When data formats and contents differ among medical institutions and electronic medical records, data received from medical institutions must be converted one by one into a format that can be linked to EDC. In the future, when standardized output in FHIR format is implemented in electronic medical records as a basic function, efficient data linkage to EDC of pharmaceutical companies can be expected using FHIR format data in clinical trials, as shown in Figure 1. The availability of data in FHIR format with a standardized data structure will also facilitate data linkage, taking advantage of the characteristics of FHIR, which allows data to be received in the same format from multiple medical institutions and electronic medical records, making application linkage very easy.

On the other hand, regardless of whether FHIR is used or not, the utilization of data in clinical trials also requires the establishment of several processes, such as anonymization by conversion of patient names into trial participant identification codes, etc., and the selection and extraction of data items required in clinical trials.

Information recorded in electronic medical records under general medical care, such as patient background and laboratory tests, are items for which data linkage is easy to achieve. However, as shown in Figure 2, test item name information may differ from medical institution to medical institution, and data linkage cannot be performed without modification.

Information that is essential for the evaluation of investigational drugs, such as disease-specific information such as staging, treatment course/results, and adverse events, is often written in free text, so the information may vary among physicians and medical institutions, or may not be recorded in electronic medical records. In addition, although the names of injuries and illnesses and prescriptions are recorded in electronic medical records, there are cases in which clinical trial data must be identified based on physician judgment, for example, excluding drugs that were prescribed but not taken, making it difficult to utilize the information as it is. In order to achieve efficient data linkage of such difficult-to-use information and information specific to clinical trials, it is necessary to record data in a form that is formatted into a predefined structure using an input function such as an electronic medical record template that defines input data.

Thus, efficient data linkage is expected to be realized by enabling data collection and recording in a unified flow using FHIR format data with a standardized data structure, electronic medical record template input functions, standard codes, and the like.

Figure 2 Issues in data linkage among multiple medical institutions

Proposed approaches to solving issues through collaboration among relevant stakeholders to realize the future vision

Amid concerns about the hollowing out of clinical trials and drug loss, it is important to ensure the public's access to new drugs. As standardization of electronic medical records and exchange of medical information advances in the medical industry in the future, it is expected that electronic medical records-EDC and other data linkage using those technologies will become widespread in clinical trials as well.

In order to achieve this, it is important to use codes, etc., that have been adopted as standards by the Ministry of Health, Labour and Welfare in the standardization of electronic medical record data. However, many medical institutions use codes and local codes associated with insurance claims that are not standardized by the Ministry of Health, Labor and Welfare (MHLW), creating the burden of inputting or converting standard codes. It is expected that medical institutions that are able to do so (e.g., those that conduct many clinical trials) will take the initiative in using standard codes (e.g., by installing them as standard equipment in electronic medical records or offering incentives for their use).

In addition, it is sometimes difficult to utilize data in electronic medical records because it is not recorded, or it is spelled out as text, or the definition of the data is inconsistent. In the future, it is expected that a system for recording and utilizing data as structured data (e.g., input using electronic medical record templates) will be introduced in electronic medical records.

In addition, if data linkage between electronic medical records and EDC, etc. becomes possible, it is expected to reduce the workload and efficiency of transcribing case data and collating data in clinical trials, as well as improve data quality. The approaches shown in Figure 3 are expected to solve the issues toward the realization of the future vision, and consensus building among a wide range of stakeholders, including not only the pharmaceutical industry but also government agencies, academia/medical institutions, and system vendors, is indispensable. We will work together among stakeholders toward the same goal of realizing the future vision.

Figure 3 Problem solving through collaboration among relevant stakeholders to realize the future vision

The Data Science (DS) Subcommittee of the Drug Evaluation Committee of the Pharmaceutical Manufacturers Association of Japan (PMAJ) will work with each stakeholder to promote and develop data linkage between electronic medical records (EDC) and other data. If you are interested in our activities as described in this article and have any questions or suggestions, please contact us at https://www.jpma.or.jp/inquiry/.

( Yoshinori Ito, Rina Ohata, Hiroshi Harami, Emi Shibusawa, and Sho Hibino, Data Science Subcommittee, Pharmaceutical Evaluation Committee)

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