Converting clinical document architecture documents to the common data model for incorporating health information exchange data in observational health studies: CDA to CDM.

BACKGROUND: Utilization of standard health information exchange (HIE) data is growing due to the high adoption rate and interoperability of electronic health record (EHR) systems. However, integration of HIE data into an EHR system is not yet fully adopted in clinical research. In addition, data quality should be verified for the secondary use of these data. Thus, the aims of this study were to convert referral documents in a Health Level 7 (HL7) clinical document architecture (CDA) to the common data model (CDM) to facilitate HIE data availability for longitudinal data analysis, and to identify data quality levels for application in future clinical studies. METHODS: A total of 21,492 referral CDA documents accumulated for over 10 years in a tertiary general hospital in South Korea were analyzed. To convert CDA documents to the Observational Medical Outcomes Partnership (OMOP) CDM, processes such as CDA parsing, data cleaning, standard vocabulary mapping, CDA-to-CDM mapping, and CDM conversion were performed. The quality of CDM data was then evaluated using the Achilles Heel and visualized with the Achilles tool. RESULTS: Mapping five CDA elements (document header, problem, medication, laboratory, and procedure) into an OMOP CDM table resulted in population of 9 CDM tables (person, visit_occurrence, condition_occurrence, drug_exposure, measurement, observation, procedure_occurrence, care_site, and provider). Three CDM tables (drug_era, condition_era, and observation_period) were derived from the converted table. From vocabulary mapping codes in CDA documents according to domain, 98.6% of conditions, 68.8% of drugs, 35.7% of measurements, 100% of observation, and 56.4% of procedures were mapped as standard concepts. The conversion rates of the CDA to the OMOP CDM were 96.3% for conditions, 97.2% for drug exposure, 98.1% for procedure occurrence, 55.1% for measurements, and 100% for observation. CONCLUSIONS: We examined the possibility of CDM conversion by defining mapping rules for CDA-to-CDM conversion using the referral CDA documents collected from clinics in actual medical practice. Although mapping standard vocabulary for CDM conversion requires further improvement, the conversion could facilitate further research on the usage patterns of medical resources and referral patterns.

Perspectives of Patients, Health Care Professionals, and Developers Toward Blockchain-Based Health Information Exchange: Qualitative Study.

BACKGROUND: Although the electronic health record system adoption rate has reached 96% in the United States, implementation and usage of health information exchange (HIE) is still lagging behind. Blockchain has come into the spotlight as a technology to solve this problem. However, there have been no studies assessing the perspectives of different stakeholders regarding blockchain-based patient-centered HIE. OBJECTIVE: The objective of this study was to analyze the awareness among patients, health care professionals, and information technology developers toward blockchain-based HIE, and compare their different perspectives related to the platform using a qualitative research methodology. METHODS: In this qualitative study, we applied grounded theory and the Promoting Action on Research Implementation in the Health Service (PARiHS) framework. We interviewed 7 patients, 7 physicians, and 7 developers, for a total of 21 interviewees. RESULTS: Regarding the leakage of health information, the patient group did not have concerns in contrast to the physician and developer groups. Physicians were particularly concerned about the fact that errors in the data cannot be easily fixed due to the nature of blockchain technology. Patients were not against the idea of providing information for clinical trials or research institutions. They wished to be provided with the results of clinical research rather than being compensated for providing data. The developers emphasized that blockchain must be technically mature before it can be applied to the health care scene, and standards of medical information to be exchanged must first be established. CONCLUSIONS: The three groups' perceptions of blockchain were generally positive about the idea of patients having the control of sharing their own health information. However, they were skeptical about the cooperation among various institutions and implementation for data standardization in the establishment process, in addition to how the service will be employed in practice. Taking these factors into consideration during planning, development, and operation of a platform will contribute to establishing practical treatment plans and tracking in a more convenient manner for both patients and physicians. Furthermore, it will help expand the related research and health management industry based on blockchain.

Integrating Clinical Data and Medical Imaging in Lung Cancer: Feasibility Study Using the Observational Medical Outcomes Partnership Common Data Model Extension.

BACKGROUND: Digital transformation, particularly the integration of medical imaging with clinical data, is vital in personalized medicine. The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) standardizes health data. However, integrating medical imaging remains a challenge. OBJECTIVE: This study proposes a method for combining medical imaging data with the OMOP CDM to improve multimodal research. METHODS: Our approach included the analysis and selection of digital imaging and communications in medicine header tags, validation of data formats, and alignment according to the OMOP CDM framework. The Fast Healthcare Interoperability Resources ImagingStudy profile guided our consistency in column naming and definitions. Imaging Common Data Model (I-CDM), constructed using the entity-attribute-value model, facilitates scalable and efficient medical imaging data management. For patients with lung cancer diagnosed between 2010 and 2017, we introduced 4 new tables-IMAGING_STUDY, IMAGING_SERIES, IMAGING_ANNOTATION, and FILEPATH-to standardize various imaging-related data and link to clinical data. RESULTS: This framework underscores the effectiveness of I-CDM in enhancing our understanding of lung cancer diagnostics and treatment strategies. The implementation of the I-CDM tables enabled the structured organization of a comprehensive data set, including 282,098 IMAGING_STUDY, 5,674,425 IMAGING_SERIES, and 48,536 IMAGING_ANNOTATION records, illustrating the extensive scope and depth of the approach. A scenario-based analysis using actual data from patients with lung cancer underscored the feasibility of our approach. A data quality check applying 44 specific rules confirmed the high integrity of the constructed data set, with all checks successfully passed, underscoring the reliability of our findings. CONCLUSIONS: These findings indicate that I-CDM can improve the integration and analysis of medical imaging and clinical data. By addressing the challenges in data standardization and management, our approach contributes toward enhancing diagnostics and treatment strategies. Future research should expand the application of I-CDM to diverse disease populations and explore its wide-ranging utility for medical conditions.

Design of a Hospice Referral System for Terminally Ill Cancer Patients Using a Standards-Based Health Information Exchange System.

OBJECTIVES: The demand for hospice has been increasing among patients with cancer. This study examined the current hospice referral scenario for terminally ill cancer patients and created a data form to collect hospice information and a modified health information exchange (HIE) form for a more efficient referral system for terminally ill cancer patients. METHODS: Surveys were conducted asking detailed information such as medical instruments and patient admission policies of hospices, and interviews were held to examine the current referral flow and any additional requirements. A task force team was organized to analyze the results of the interviews and surveys. RESULTS: Six hospices completed the survey, and 3 physicians, 2 nurses, and 2 hospital staff from a tertiary hospital were interviewed. Seven categories were defined as essential for establishing hospice data. Ten categories and 40 data items were newly suggested for the existing HIE document form. An implementation guide for the Consolidated Clinical Document Architecture developed by Health Level 7 (HL7 CCDA) was also proposed. It is an international standard for interoperability that provides a framework for the exchange, integration, sharing, and retrieval of electronic health information. Based on these changes, a hospice referral scenario for terminally ill cancer patients was designed. CONCLUSIONS: Our findings show potential improvements that can be made to the current hospice referral system for terminally ill cancer patients. To make the referral system useful in practice, governmental efforts and investments are needed.

Technology and Policy Challenges in the Adoption and Operation of Health Information Exchange Systems.

OBJECTIVES: This study aimed to identify problems and issues that arise with the implementation of online health information exchange (HIE) systems in a medical environment and to identify solutions to facilitate the successful operation of future HIE systems in primary care clinics and hospitals. METHODS: In this study, the issues that arose during the establishment and operation of an HIE system in a hospital were identified so that they could be addressed to enable the successful establishment and operation of a standard-based HIE system. After the issues were identified, they were reviewed and categorized by a group of experts that included medical information system experts, doctors, medical information standard experts, and HIE researchers. Then, solutions for the identified problems were derived based on the system development, operation, and improvement carried out during this work. RESULTS: Twenty-one issues were identified during the implementation and operation of an online HIE system. These issues were then divided into four categories: system architecture and standards, documents and data items, consent of HIE, and usability. We offer technical and policy recommendations for various stakeholders based on the experiences of operating and improving the online HIE system in the medical field. CONCLUSIONS: The issues and solutions identified in this study regarding the implementation and operate of an online HIE system can provide valuable insight for planners to enable them to successfully design and operate such systems at a national level in the future. In addition, policy support from governments is needed.