Ye-Eun Park

Background: Electronic medical record (EMR) certification programs have traditionally focused on product-level requirements, such as interoperability, security, and core functionality. However, growing evidence suggests that many patient safety risks associated with EMRs arise after implementation and are closely related to system configuration, workflow integration, and real-world use. Despite the presence of a national EMR product certification system in Korea, a systematic evaluation of how certified systems are implemented and used in clinical practice is still lacking. Objective: This study aimed to develop and validate a self-assessment checklist for EMR use certification, focused on patient safety-critical functions, and to evaluate its content validity and expert-assessed practical applicability across health care institutions of different sizes. Methods: A convergent mixed methods design was used. A self-assessment checklist comprising 10 patient safety–related EMR functions was developed by adapting the US Office of the National Coordinator for Health Information Technology self-assessment templates to the Korean EMR certification context. Content validity was quantitatively assessed using the Content Validity Index across 4 dimensions (relevance, usefulness, clarity, and importance) by a panel of 24 experts with experience in EMR implementation and certification. Qualitative feedback was collected through open-ended survey questions to examine feasibility, anticipated challenges, and differentiation between product and use certification across tertiary referral hospitals, general hospitals, and clinics. Results: The overall Scale-Level Content Validity Index was 0.921, indicating strong content validity for the proposed checklist. Although most items demonstrated high agreement, lower ratings were observed for certain functions, particularly in clinic-level settings, reflecting structural and resource-related constraints rather than limited recognition of patient safety priorities. Qualitative findings highlighted challenges related to staffing, system governance, and the feasibility of assembling multidisciplinary assessment teams in smaller institutions. Conclusions: The self-assessment checklist demonstrated high content validity and was perceived as relevant for evaluating patient safety–critical aspects of EMR use. However, expert-assessed feasibility varied across health care institution types, particularly in clinic-level settings. Further empirical testing is needed to assess the checklist’s reliability, usability, and applicability in real-world certification processes.

Background: Patient-generated health data (PGHD) are increasingly recognized as valuable for clinical care and secondary use; however, physicians’ perspectives remain heterogeneous and context-dependent. Objective: This study aimed to examine physicians’ perceptions, intentions, and concerns about the clinical and nonclinical use of PGHD and to compare responses between tertiary hospitals and other institutions. Methods: A cross-sectional survey was conducted involving 157 physicians (81 from a tertiary hospital and 76 from other health care institutions), supplemented by in-depth interviews. Between-group differences were assessed using chi-square tests and Wilcoxon rank-sum tests. Priority-ranking items were analyzed using weighted scores. Results: Overall, 64% (100/157) of the physicians reported prior use of PGHD, most commonly in handwritten or printed form, with no significant institutional differences; physiological measurements were the most frequent type of data. Among nonusers, 78.9% (45/57) reported that they had never received PGHD from patients, while poor system integration was identified as a major barrier to clinical use. Physicians cited clinical necessity and user-friendly integration as the strongest motivators. Perceived benefits focused on enriched decision-making, whereas key concerns included data accuracy, increased workload, and insufficient evidence. For nonclinical use, research and public health were viewed as most valuable. Across institutions, secure and transparent governance was prioritized. Differences between tertiary and nontertiary settings appeared to reflect physician demographics rather than divergent attitudes. Interviews further revealed that PGHD use was highly context dependent, with older adults’ limited digital literacy and discrepancies between patient- and caregiver-reported data identified as distinctive barriers in routine practice. Conclusions: Physicians recognize the potential of PGHD to support outpatient care, shared decision-making, and research, but express strong concerns about data reliability, workflow burden, and insufficient infrastructure. Differences between tertiary and nontertiary physicians reflect demographic and career stage imbalances, but both groups converge on the need for standardization, secure integration, and supportive governance frameworks. Broad adoption will require not only technical integration but also regulatory reform and trust-building strategies to advance biomedical research and health care delivery.

BACKGROUND Electronic medical record (EMR) certification programs have traditionally focused on product-level requirements such as interoperability, security, and core functionality. However, growing evidence suggests that many patient safety risks associated with EMRs arise after implementation, and are closely related to system configuration, workflow integration, and real-world use. Despite the presence of a national EMR product certification system in Korea, a systematic evaluation of the implementation and use of certified systems in clinical practice is lacking. OBJECTIVE This study aimed to develop and validate a self-assessment checklist for EMR -use certification focused on patient safety–critical functions and to evaluate its content validity and practical applicability across healthcare institutions of different sizes. METHODS A convergent mixed methods design was used. A self-assessment checklist comprising ten patient safety–related EMR functions was developed by adapting the United States Office of the National Coordinator for Health Information Technology self-assessment templates to the Korean EMR certification context. Content validity was quantitatively assessed using the content validity index across four dimensions (relevance, usefulness, clarity, and importance) by a panel of 24 experts with experience in EMR implementation and certification. Qualitative feedback was collected through open-ended survey questions to examine the feasibility, anticipated challenges, and differences between product and use certifications across tertiary hospitals, general hospitals, and clinics. RESULTS The overall scale-level content validity index was 0.92, indicating strong content validity of the proposed checklist. While most items demonstrated high agreement, lower ratings were observed for certain functions, particularly in clinical settings, reflecting structural and resource-related constraints rather than limited recognition of patient safety priorities. The qualitative findings highlighted challenges related to staffing, system governance, and the feasibility of assembling multidisciplinary assessment teams in smaller institutions. CONCLUSIONS These findings support the feasibility and relevance of EMR-use certification as a complement to product certification. A context-sensitive, tiered certification approach, with scenario-based evaluation tools and policy-level support, may promote safe and effective EMR use across diverse healthcare settings. This study provides empirical evidence for the development of EMR-use certification frameworks aimed at strengthening patient safety in real-world clinical environments.

Background: Artificial intelligence (AI)–enabled clinical decision support systems (CDSSs) are increasingly embedded within electronic health record (EHR) environments; however, their introduction can disrupt existing workflows and raise patient safety concerns, particularly in high-stakes settings such as surgical transfusion. Limited qualitative evidence exists regarding how frontline professionals anticipate the clinical, organizational, and workflow implications of such systems before wider deployment. Objective: This study aims to qualitatively examine the anticipated clinical, organizational, and workflow-level implications of implementing personalized Maximum Surgical Blood Order Schedule—Thoracic Surgery (pMSBOS-TS), an AI-enabled CDSS for personalized surgical blood ordering, before large-scale deployment. Methods: We conducted a consensual qualitative study with 14 multidisciplinary health care professionals involved in transfusion-related tasks at a large tertiary hospital. Following 1 pilot focus group to refine the interview guide and workflow diagram, 2 semistructured focus group discussions were held with 14 participants (5 physicians, 6 nurses, and 3 blood bank staff). Transcripts were analyzed using the Systems Engineering Initiative for Patient Safety (SEIPS) 101 framework, focusing on People, Environment, Tools, and Tasks, and were supported by task- and workflow-based analyses of transfusion processes. Member checking was conducted with participants and external clinicians to enhance validity. Results: A total of 189 semantic units and 61 core ideas were identified across 18 subdomains and 7 overarching domains. Participants anticipated that pMSBOS-TS could reduce unwarranted variation in blood ordering and planning, provided that algorithmic performance is reliable and the interface is tightly integrated into existing EHR workflows. At the same time, they expressed concerns regarding increased verification burden, system limitations in unexpected clinical scenarios, and potential communication bottlenecks between clinical units and the blood bank. Organizational culture, governance structures, and local transfusion logistics were viewed as critical determinants of whether the system would reduce or inadvertently increase workload and blood product waste. Conclusions: This preimplementation, SEIPS-based qualitative evaluation suggests that the successful adoption of an AI-enabled transfusion CDSS depends not only on predictive performance but also on sociotechnical readiness, including user trust, workflow fit, and organizational support. These findings provide practice-based insights to inform staged implementation, training, and governance strategies aimed at safely integrating predictive transfusion CDSSs into EHR-supported surgical workflows.

BACKGROUND Patient-generated health data (PGHD) are increasingly recognized as valuable for clinical care and secondary use; however, physicians’ perspectives remain heterogeneous and context-dependent. OBJECTIVE This study aimed to examine physicians’ perceptions, intentions, and concerns about the clinical and nonclinical use of PGHD and to compare responses between tertiary hospitals and other institutions. METHODS A cross-sectional survey was conducted involving 157 physicians (81 from a tertiary hospital and 76 from other health care institutions), supplemented by in-depth interviews. Between-group differences were assessed using chi-square tests and Wilcoxon rank-sum tests. Priority-ranking items were analyzed using weighted scores. RESULTS Overall, 64% (100/157) of the physicians reported prior use of PGHD, most commonly in handwritten or printed form, with no significant institutional differences; physiological measurements were the most frequent type of data. Among nonusers, 78.9% (45/57) reported that they had never received PGHD from patients, while poor system integration was identified as a major barrier to clinical use. Physicians cited clinical necessity and user-friendly integration as the strongest motivators. Perceived benefits focused on enriched decision-making, whereas key concerns included data accuracy, increased workload, and insufficient evidence. For nonclinical use, research and public health were viewed as most valuable. Across institutions, secure and transparent governance was prioritized. Differences between tertiary and nontertiary settings appeared to reflect physician demographics rather than divergent attitudes. Interviews further revealed that PGHD use was highly context dependent, with older adults’ limited digital literacy and discrepancies between patient- and caregiver-reported data identified as distinctive barriers in routine practice. CONCLUSIONS Physicians recognize the potential of PGHD to support outpatient care, shared decision-making, and research, but express strong concerns about data reliability, workflow burden, and insufficient infrastructure. Differences between tertiary and nontertiary physicians reflect demographic and career stage imbalances, but both groups converge on the need for standardization, secure integration, and supportive governance frameworks. Broad adoption will require not only technical integration but also regulatory reform and trust-building strategies to advance biomedical research and health care delivery.

Patient education is crucial for understanding medical conditions, treatment options, and self-management techniques. Digital technology has revolutionised patient education, providing efficient and cost-effective alternatives to traditional methods. However, challenges persist in customising educational materials to specific clinical settings. We investigated the relationship between healthcare terminology standards and the Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) dictionary. Our aim was to provide practical mapping guidance and case examples to help users better understand how to map patient education materials (PEM) to SNOMED CT to generate consistent results across different institutions. We mapped the titles of PEM in a single hospital setting using SNOMED CT terms. We focused on materials made between October 1, 2018, and November 30, 2022, and found 1,271 matchable PEM titles. Keywords were identified and sorted into categories like Target, Time, Condition, and Procedure. Two researchers worked independently to match these keywords with SNOMED CT, and any differences were resolved through discussion or third-party review. Out of 1,271 PEM titles that were assigned to categories, only 3.9% remained unmapped. Most of the mapped titles were related to Procedure (93.3%), Condition (56.8%), Time (17.5%), and Target (12%); 2,688 keywords were mapped, with 62.4% single-mapped and 36.9% were multi-mapped. Among the keywords mapped to various categories, Procedures accounted for the highest proportion (49.4%). Examining the keywords mapped to each SNOMED CT concept in different categories provided valuable insights into how terms are distributed and improved our understanding of the specific terms used in PEM. When educational materials are mapped to standard clinical terminologies and integrated into the Electronic Health Record (EHR), patients receive personalised and relevant health information, potentially improving engagement and health outcomes. This approach may reduce the workload of healthcare personnel, reduce miscommunication, and improve overall healthcare efficiency.

BACKGROUND Artificial intelligence (AI)–enabled clinical decision support systems (CDSSs) are increasingly embedded within electronic health record (EHR) environments; however, their introduction can disrupt existing workflows and raise patient safety concerns, particularly in high-stakes settings such as surgical transfusion. Limited qualitative evidence exists regarding how frontline professionals anticipate the clinical, organizational, and workflow implications of such systems before wider deployment. OBJECTIVE This study aims to qualitatively examine the anticipated clinical, organizational, and workflow-level implications of implementing personalized Maximum Surgical Blood Order Schedule—Thoracic Surgery (pMSBOS-TS), an AI-enabled CDSS for personalized surgical blood ordering, before large-scale deployment. METHODS We conducted a consensual qualitative study with 14 multidisciplinary health care professionals involved in transfusion-related tasks at a large tertiary hospital. Following 1 pilot focus group to refine the interview guide and workflow diagram, 2 semistructured focus group discussions were held with 14 participants (5 physicians, 6 nurses, and 3 blood bank staff). Transcripts were analyzed using the Systems Engineering Initiative for Patient Safety (SEIPS) 101 framework, focusing on People, Environment, Tools, and Tasks, and were supported by task- and workflow-based analyses of transfusion processes. Member checking was conducted with participants and external clinicians to enhance validity. RESULTS A total of 189 semantic units and 61 core ideas were identified across 18 subdomains and 7 overarching domains. Participants anticipated that pMSBOS-TS could reduce unwarranted variation in blood ordering and planning, provided that algorithmic performance is reliable and the interface is tightly integrated into existing EHR workflows. At the same time, they expressed concerns regarding increased verification burden, system limitations in unexpected clinical scenarios, and potential communication bottlenecks between clinical units and the blood bank. Organizational culture, governance structures, and local transfusion logistics were viewed as critical determinants of whether the system would reduce or inadvertently increase workload and blood product waste. CONCLUSIONS This preimplementation, SEIPS-based qualitative evaluation suggests that the successful adoption of an AI-enabled transfusion CDSS depends not only on predictive performance but also on sociotechnical readiness, including user trust, workflow fit, and organizational support. These findings provide practice-based insights to inform staged implementation, training, and governance strategies aimed at safely integrating predictive transfusion CDSSs into EHR-supported surgical workflows.

Patient-generated health data (PGHD) enhance traditional healthcare by enabling continuous monitoring and supporting personalized care, yet concerns over privacy, security, and integration into existing systems hinder broader adoption. This study examined the perceptions, awareness, and concerns of patients and caregivers regarding PGHD and assessed their willingness to share such data for clinical, research, and commercial purposes. A cross-sectional survey was conducted from 6 to 12 November 2023, involving 400 individuals with experience using PGHD. Participants completed structured questionnaires addressing health information management, PGHD usage, and attitudes toward its application. PGHD was most commonly used by patients with chronic conditions and guardians of minors, with tethered personal health record apps frequently utilized. Respondents identified improved self-management and better access to information as key benefits. However, significant concerns about data privacy and security emerged, especially regarding non-clinical use. Younger adults, particularly those in their 20s, showed lower willingness to engage with PGHD due to heightened privacy concerns. These findings suggest that, while support for clinical use of PGHD is strong, barriers related to trust and consent remain. Addressing privacy concerns and simplifying consent processes will be essential to promote equitable and responsible PGHD utilization across diverse patient populations.

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