Purpose: : This study investigates the experiences of patients in intensive care units (ICUs), and the factors influencing these experiences.Method : We used a cross-sectional survey design to analyze previously collected cohort data from 891 patients who spent over 24 hours in 19 ICUs across four university hospitals in Busan, South Korea between June 2019 and July 2020. Within a week of ICU discharge, participants completed the Korean version of the Intensive Care Experience Questionnaire, covering four areas: “awareness of surroundings,” “frightening experiences,” “satisfaction with care,” and “recall of experiences.” We used multiple linear regression to identify factors associated with the ICU experience. Results: : Low income (β = -.08, p = .016), unplanned hospitalization (β = -.09, p = .006), sedation (β = -.16, p ＜ .001), and delirium (β = -.15, p ＜ .001) reduce patients’ awareness of their surroundings. Frightening experiences are associated with being female (β = -.07, p = .027), experiencing delirium (β = -.15, p ＜ .001), and longer stays in the ICU (β = -.14, p ＜ .001). Using sedatives decreases satisfaction with care (β = -.08, p = .048). Living alone (β = -.08, p = .013) and using painkillers (β = -.08, p = .020) reduces recall of experiences. Conclusion : Negative ICU experiences are significantly associated with being female, living alone, lower income, unplanned admission, using sedatives and painkillers, delirium, and longer stays in the ICU. Thus, improving ICU experiences requires interventions that address modifiable factors, such as delirium, medication, and length of ICU stays.

Purpose: In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data. Materials and Methods: This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes. Results: We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (>~90%) agreed that the ‘reserved’ condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next-generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization. Conclusion This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.

Purpose: In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data. Materials and Methods: This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes. Results: We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (>~90%) agreed that the ‘reserved’ condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next-generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization. Conclusion This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.

Purpose: In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data. Materials and Methods: This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes. Results: We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (>~90%) agreed that the ‘reserved’ condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next-generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization. Conclusion This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.

Purpose: In 2024, medical researchers in the Republic of Korea were invited to amend the health and medical data utilization guidelines (Government Publications Registration Number: 11-1352000-0052828-14). This study aimed to show the overall impact of the guideline revision, with a focus on clinical genomic data. Materials and Methods: This study amended the pseudonymization of genomic data defined in the previous version through a joint study led by the Ministry of Health and Welfare, the Korea Health Information Service, and the Korea Genome Organization. To develop the previous version, we held three conferences with four main medical research institutes and seven academic societies. We conducted two surveys targeting special genome experts in academia, industry, and institutes. Results: We found that cases of pseudonymization in the application of genome data were rare and that there was ambiguity in the terminology used in the previous version of the guidelines. Most experts (>~90%) agreed that the ‘reserved’ condition should be eliminated to make genomic data available after pseudonymization. In this study, the scope of genomic data was defined as clinical next-generation sequencing data, including FASTQ, BAM/SAM, VCF, and medical records. Pseudonymization targets genomic sequences and metadata, embedding specific elements, such as germline mutations, short tandem repeats, single-nucleotide polymorphisms, and identifiable data (for example, ID or environmental values). Expression data generated from multi-omics can be used without pseudonymization. Conclusion This amendment will not only enhance the safe use of healthcare data but also promote advancements in disease prevention, diagnosis, and treatment.