Current Status and Key Issues of Data Management in Tertiary Hospitals: A Case Study of Seoul National University Hospital / 대한의료정보학회지

Objectives@#In the era of the Fourth Industrial Revolution, where an ecosystem is being developed to enhance the quality of healthcare services by applying information and communication technologies, systematic and sustainable data management is essential for medical institutions. In this study, we assessed the data management status and emerging concerns of three medical institutions, while also examining future directions for seamless data management. @*Methods@#To evaluate the data management status, we examined data types, capacities, infrastructure, backup methods, and related organizations. We also discussed challenges, such as resource and infrastructure issues, problems related to government regulations, and considerations for future data management. @*Results@#Hospitals are grappling with the increasing data storage space and a shortage of management personnel due to costs and project termination, which necessitates countermeasures and support. Data management regulations on the destruction or maintenance of medical records are needed, and institutional consideration for secondary utilization such as long-term treatment or research is required. Government-level guidelines for facilitating hospital data sharing and mobile patient services should be developed. Additionally, hospital executives at the organizational level need to make efforts to facilitate the clinical validation of artificial intelligence software. @*Conclusions@#This analysis of the current status and emerging issues of data management reveals potential solutions and sets the stage for future organizational and policy directions. If medical big data is systematically managed, accumulated over time, and strategically monetized, it has the potential to create new value.

Accuracy of Cloud-Based Speech Recognition Open Application Programming Interface for Medical Terms of Korean

Background@#There are limited data on the accuracy of cloud-based speech recognition (SR) open application programming interfaces (APIs) for medical terminology. This study aimed to evaluate the medical term recognition accuracy of current available cloud-based SR open APIs in Korean. @*Methods@#We analyzed the SR accuracy of currently available cloud-based SR open APIs using real doctor–patient conversation recordings collected from an outpatient clinic at a large tertiary medical center in Korea. For each original and SR transcription, we analyzed the accuracy rate of each cloud-based SR open API (i.e., the number of medical terms in the SR transcription per number of medical terms in the original transcription). @*Results@#A total of 112 doctor–patient conversation recordings were converted with three cloud-based SR open APIs (Naver Clova SR from Naver Corporation; Google Speech-toText from Alphabet Inc.; and Amazon Transcribe from Amazon), and each transcription was compared. Naver Clova SR (75.1%) showed the highest accuracy with the recognition of medical terms compared to the other open APIs (Google Speech-to-Text, 50.9%, P < 0.001; Amazon Transcribe, 57.9%, P < 0.001), and Amazon Transcribe demonstrated higher recognition accuracy compared to Google Speech-to-Text (P< 0.001). In the sub-analysis, Naver Clova SR showed the highest accuracy in all areas according to word classes, but the accuracy of words longer than five characters showed no statistical differences (Naver Clova SR, 52.6%; Google Speech-to-Text, 56.3%; Amazon Transcribe, 36.6%). @*Conclusion@#Among three current cloud-based SR open APIs, Naver Clova SR which manufactured by Korean company showed highest accuracy of medical terms in Korean, compared to Google Speech-to-Text and Amazon Transcribe. Although limitations are existing in the recognition of medical terminology, there is a lot of rooms for improvement of this promising technology by combining strengths of each SR engines.

Safety and Effectiveness of Endoscopic Ear Surgery: Systematic Review / 대한이비인후과학회지

BACKGROUND AND OBJECTIVES@#This study aims to evaluate that usefulness of the endoscopic ear surgery (EES) through the systematic review.SUBJECTS AND METHOD: We searched literatures in literature databases (MEDLINE, EMBASE, Cochrane Library, etc.). Inclusion criteria is 1) studies of patients with chronic otitis media, otitis media with effusion, cholesteatoma, conductive hearing loss, mixed hearing loss etc. 2) studies in which a transcanal endoscopic surgery was performed; and 3) studies in which one or more of the appropriate medical outcomes have been reported. We excluded that 1) non-human studies and pre-clinical studies; 2) non-original articles, for example, non-systematic reviews; editorial, letter and opinion pieces; 3) research not published in Korean and English; and 4) grey literature. Finally, 65 articles were selected and those results were analyzed.@*RESULTS@#The safety of the EES was reported in 61 articles. Some studies reported damaged facial nerve or perilymph gusher but these are the complications that can arise due to the characteristics of the disease and not due to the EES and other reported complications were of similar or lower level in the intervention group rather than the microscopy group. The effectiveness of the EES was reported in 23 articles. The EES tended to show improved effects in terms of graft uptake status, cholesteatoma removal, and hearing improvement although effective outcomes of most studies reported no significant difference between EES and microscopic ear surgery.@*CONCLUSION@#EES is a safe and effective technique and as it is less invasive than the microscopic ear surgery.

AI in Medicine: Need of Orchestration for High-Performance / 대한의료정보학회지

No abstract available.

Safety and Effectiveness of Endoscopic Ear Surgery: Systematic Review / 대한이비인후과학회지

BACKGROUND AND OBJECTIVES: This study aims to evaluate that usefulness of the endoscopic ear surgery (EES) through the systematic review. SUBJECTS AND METHOD: We searched literatures in literature databases (MEDLINE, EMBASE, Cochrane Library, etc.). Inclusion criteria is 1) studies of patients with chronic otitis media, otitis media with effusion, cholesteatoma, conductive hearing loss, mixed hearing loss etc. 2) studies in which a transcanal endoscopic surgery was performed; and 3) studies in which one or more of the appropriate medical outcomes have been reported. We excluded that 1) non-human studies and pre-clinical studies; 2) non-original articles, for example, non-systematic reviews; editorial, letter and opinion pieces; 3) research not published in Korean and English; and 4) grey literature. Finally, 65 articles were selected and those results were analyzed. RESULTS: The safety of the EES was reported in 61 articles. Some studies reported damaged facial nerve or perilymph gusher but these are the complications that can arise due to the characteristics of the disease and not due to the EES and other reported complications were of similar or lower level in the intervention group rather than the microscopy group. The effectiveness of the EES was reported in 23 articles. The EES tended to show improved effects in terms of graft uptake status, cholesteatoma removal, and hearing improvement although effective outcomes of most studies reported no significant difference between EES and microscopic ear surgery. CONCLUSION: EES is a safe and effective technique and as it is less invasive than the microscopic ear surgery.

Temporal Segmentation for Capturing Snapshots of Patient Histories in Korean Clinical Narrative / 대한의료정보학회지

OBJECTIVES: Clinical discharge summaries provide valuable information about patients' clinical history, which is helpful for the realization of intelligent healthcare applications. The documents tend to take the form of separate segments based on temporal or topical information. If a patient's clinical history can be seen as a consecutive sequence of clinical events, then each temporal segment can be seen as a snapshot, providing a certain clinical context at a specific moment. This study aimed to demonstrate a temporal segmentation method of Korean clinical narratives for identifying textual snapshots of patient history as a proof-of-a-concept. METHODS: Our method uses pattern-based segmentation to approximate human recognition of the temporal or topical shifts in clinical documents. We utilized rheumatic patients' discharge summaries and transformed them into sequences of constituent chunks. We built 97 single pattern functions to denote whether a certain chunk has attributes that indicate that it can be a segment boundary. We manually defined the relationships between the pattern functions to resolve multiple pattern matchings and to make a final decision. RESULTS: The algorithm segmented 30 discharge summaries and processed 1,849 decision points. Three human judges were asked whether they agreed with the algorithm's prediction, and the agreement percentage on the judges' majority opinion was 89.61%. CONCLUSIONS: Although this method is based on manually constructed rules, our findings demonstrate that the proposed algorithm can achieve fairly good segmentation results, and it may be the basis for methodological improvement in the future.

National Rules for Drug–Drug Interactions: Are They Appropriate for Tertiary Hospitals?

The application of appropriate rules for drug–drug interactions (DDIs) could substantially reduce the number of adverse drug events. However, current implementations of such rules in tertiary hospitals are problematic as physicians are receiving too many alerts, causing high override rates and alert fatigue. We investigated the potential impact of Korean national DDI rules in a drug utilization review program in terms of their severity coverage and the clinical efficiency of how physicians respond to them. Using lists of high-priority DDIs developed with the support of the U.S. government, we evaluated 706 contraindicated DDI pairs released in May 2015. We evaluated clinical log data from one tertiary hospital and prescription data from two other tertiary hospitals. The measured parameters were national DDI rule coverage for high-priority DDIs, alert override rate, and number of prescription pairs. The coverage rates of national DDI rules were 80% and 3.0% at the class and drug levels, respectively. The analysis of the system log data showed an overall override rate of 79.6%. Only 0.3% of all of the alerts (n = 66) were high-priority DDI rules. These showed a lower override rate of 51.5%, which was much lower than for the overall DDI rules. We also found 342 and 80 unmatched high-priority DDI pairs which were absent in national rules in inpatient orders from the other two hospitals. The national DDI rules are not complete in terms of their coverage of severe DDIs. They also lack clinical efficiency in tertiary settings, suggesting improved systematic approaches are needed.

Future Directions for Next-Generation Hospital Information System / 대한의료정보학회지

No abstract available.

Seasonal Variation in Hemoglobin A1c in Korean Patients with Type 2 Diabetes Mellitus

A seasonal variation of glucose homeostasis in humans has been reported in various geographic regions. In this study, we examined seasonal variations in hemoglobin A1c (HbA1c) in patients with type 2 diabetes living in Korea. We analyzed 57,970 HbA1c values from 4,191 patients and the association of these values with ambient temperature for 3.5 yr. Overall, HbA1c exhibited its highest values from February to March and its lowest values from September to October (coefficient for cos t = -0.0743, P = 0.058) and the difference between the peak and nadir in a year was 0.16%-0.25%. A statistically significant seasonal variation was observed in the patients who were taking oral anti-diabetic drugs (OADs) without insulin treatment (coefficient for cos t = -0.0949, P < 0.05). The Spearman correlation coefficient between daily HbA1c values and the corresponding 3-month moving average ambient temperature was -0.2154 (95% confidence interval [CI]: -0.2711, -0.1580; P < 0.05). In conclusion, HbA1c values exhibited a seasonal variation in Korean patients with type 2 diabetes, with the highest values during the cold season, particularly in those who were treated with OADs, which should be taken into account in clinical practice for stable glucose control during the cold season.

Improving the Performance of Text Categorization Models used for the Selection of High Quality Articles / 대한의료정보학회지

OBJECTIVES: Machine learning systems can considerably reduce the time and effort needed by experts to perform new systematic reviews (SRs). This study investigates categorization models, which are trained on a combination of included and commonly excluded articles, which can improve performance by identifying high quality articles for new procedures or drug SRs. METHODS: Test collections were built using the annotated reference files from 19 procedure and 15 drug systematic reviews. The classification models, using a support vector machine, were trained by the combined even data of other topics, excepting the desired topic. This approach was compared to the combination of included and commonly excluded articles with the combination of included and excluded articles. Accuracy was used for the measure of comparison. RESULTS: On average, the performance was improved by about 15% in the procedure topics and 11% in the drug topics when the classification models trained on the combination of articles included and commonly excluded, were used. The system using the combination of included and commonly excluded articles performed better than the combination of included and excluded articles in all of the procedure topics. CONCLUSIONS: Automatically rigorous article classification using machine learning can reduce the workload of experts when they perform systematic reviews when the topic-specific data are scarce. In particular, when the combination of included and commonly excluded articles is used, this system will be more effective.

An Evaluation of Multiple Query Representations for the Relevance Judgments used to Build a Biomedical Test Collection / 대한의료정보학회지

OBJECTIVES: The purpose of this study is to validate a method that uses multiple queries to create a set of relevance judgments used to indicate which documents are pertinent to each query when forming a biomedical test collection. METHODS: The aspect query is the major concept of this research; it can represent every aspect of the original query with the same informational need. Manually generated aspect queries created by 15 recruited participants where run using the BM25 retrieval model in order to create aspect query based relevance sets (QRELS). In order to demonstrate the feasibility of these QRELSs, The results from a 2004 genomics track run supported by the National Institute of Standards and Technology (NIST) were used to compute the mean average precision (MAP) based on Text Retrieval Conference (TREC) QRELSs and aspect-QRELSs. The rank correlation was calculated using both Kendall's and Spearman's rank correlation methods. RESULTS: We experimentally verified the utility of the aspect query method by combining the top ranked documents retrieved by a number of multiple queries which ranked the order of the information. The retrieval system correlated highly with rankings based on human relevance judgments. CONCLUSIONS: Substantial results were shown with high correlations of up to 0.863 (p < 0.01) between the judgment-free gold standard based on the aspect queries and the human-judged gold standard supported by NIST. The results also demonstrate that the aspect query method can contribute in building test collections used for medical literature retrieval.

Evaluation of Co-occurring Terms in Clinical Documents Using Latent Semantic Indexing / 대한의료정보학회지

OBJECTIVES: Measurement of similarities between documents is typically influenced by the sparseness of the term-document matrix employed. Latent semantic indexing (LSI) may improve the results of this type of analysis. METHODS: In this study, LSI was utilized in an attempt to reduce the term vector space of clinical documents and newspaper editorials. RESULTS: After applying LSI, document similarities were revealed more clearly in clinical documents than editorials. Clinical documents which can be characterized with co-occurring medical terms, various expressions for the same concepts, abbreviations, and typographical errors showed increased improvement with regards to a correlation between co-occurring terms and document similarities. CONCLUSIONS: Our results showed that LSI can be used effectively to measure similarities in clinical documents. In addition, correlation between the co-occurrence of terms and similarities realized in this study is an important positive feature associated with LSI.

Recognizing Temporal Information in Korean Clinical Narratives through Text Normalization / 대한의료정보학회지

OBJECTIVES: Acquiring temporal information is important because knowledge in clinical narratives is time-sensitive. In this paper, we describe an approach that can be used to extract the temporal information found in Korean clinical narrative texts. METHODS: We developed a two-stage system, which employs an exhaustive text analysis phase and a temporal expression recognition phase. Since our target document may include tokens that are made up of both Korean and English text joined together, the minimal semantic units are analyzed and then separated from the concatenated phrases and linguistic derivations within a token using a corpus-based approach to decompose complex tokens. A finite state machine is then used on the minimal semantic units in order to find phrases that possess time-related information. RESULTS: In the experiment, the temporal expressions within Korean clinical narratives were extracted using our system. The system performance was evaluated through the use of 100 discharge summaries from Seoul National University Hospital containing a total of 805 temporal expressions. Our system scored a phrase-level precision and recall of 0.895 and 0.919, respectively. CONCLUSIONS: Finding information in Korean clinical narrative is challenging task, since the text is written in both Korean and English and frequently omits syntactic elements and word spacing, which makes it extremely noisy. This study presents an effective method that can be used to aquire the temporal information found in Korean clinical documents.

Evaluation of Term Ranking Algorithms for Pseudo-Relevance Feedback in MEDLINE Retrieval / 대한의료정보학회지

OBJECTIVES: The purpose of this study was to investigate the effects of query expansion algorithms for MEDLINE retrieval within a pseudo-relevance feedback framework. METHODS: A number of query expansion algorithms were tested using various term ranking formulas, focusing on query expansion based on pseudo-relevance feedback. The OHSUMED test collection, which is a subset of the MEDLINE database, was used as a test corpus. Various ranking algorithms were tested in combination with different term re-weighting algorithms. RESULTS: Our comprehensive evaluation showed that the local context analysis ranking algorithm, when used in combination with one of the reweighting algorithms - Rocchio, the probabilistic model, and our variants - significantly outperformed other algorithm combinations by up to 12% (paired t-test; p < 0.05). In a pseudo-relevance feedback framework, effective query expansion would be achieved by the careful consideration of term ranking and re-weighting algorithm pairs, at least in the context of the OHSUMED corpus. CONCLUSIONS: Comparative experiments on term ranking algorithms were performed in the context of a subset of MEDLINE documents. With medical documents, local context analysis, which uses co-occurrence with all query terms, significantly outperformed various term ranking methods based on both frequency and distribution analyses. Furthermore, the results of the experiments demonstrated that the term rank-based re-weighting method contributed to a remarkable improvement in mean average precision.

Implementation of Consolidated HIS: Improving Quality and Efficiency of Healthcare / 대한의료정보학회지

OBJECTIVES: Adoption of hospital information systems offers distinctive advantages in healthcare delivery. First, implementation of consolidated hospital information system in Seoul National University Hospital led to significant improvements in quality of healthcare and efficiency of hospital management. METHODS: The hospital information system in Seoul National University Hospital consists of component applications: clinical information systems, clinical research support systems, administrative information systems, management information systems, education support systems, and referral systems that operate to generate utmost performance when delivering healthcare services. RESULTS: Clinical information systems, which consist of such applications as electronic medical records, picture archiving and communication systems, primarily support clinical activities. Clinical research support system provides valuable resources supporting various aspects of clinical activities, ranging from management of clinical laboratory tests to establishing care-giving procedures. CONCLUSIONS: Seoul National University Hospital strives to move its hospital information system to a whole new level, which enables customized healthcare service and fulfills individual requirements. The current information strategy is being formulated as an initial step of development, promoting the establishment of next-generation hospital information system.

Development of u-House Gateway for u-Healthcare / 대한의료정보학회지

OBJECTIVE: Ubiquitous healthcare (u-Healthcare) is an emerging paradigm in the healthcare environment. One of the most promising applications for u-Healthcare is the ubiquitous home health monitoring system. This paper addresses two significant challenges in the successful application of the ubiquitous home health monitoring system: the uniform integration of measured biosignal data and easy access to monitored biosignal data. METHODS: We used the Medical waveform description Format Encoding Rule (MFER) standard to encode biosignal data. A web-based MFER upload ActiveX control was designed and implemented to transfer MFER files to the central repository server in a near real-time basis. All of the integrated biosignal data were then accessed and managed through the central repository server. RESULTS: We developed a u-House server that can serve as a uniform data transferer to integrate measured biosignal data from u-House homes into the remote central repository server. We developed user-friendly web services that allow users to easily search and view monitored biosignal data. CONCLUSION: The results of this study suggest that the MFER standard can be easily adapted to u-Healthcare systems and that a web-based ubiquitous home health monitoring system has advantages of ubiquitous access and scalability.

Toward the Automatic Generation of the Entry Level CDA Documents / 대한의료정보학회지

OBJECTIVE: CDA (Clinical Document Architecture) is a markup standard for clinical document exchange. In order to increase the semantic interoperability of documents exchange, the clinical statements in the narrative blocks should be encoded with code values. Natural language processing (NLP) is required in order to transform the narrative blocks into the coded elements in the level 3 CDA documents. In this paper, we evaluate the accuracy of text mapping methods which are based on NLP. METHODS: We analyzed about one thousand discharge summaries to know their characteristics and focused the syntactic patterns of the diagnostic sections in the discharge summaries. According to the patterns, different rules were applied for matching code values of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). RESULTS: The accuracy of matching was evaluated using five-hundred discharge summaries. The precision was as follows: 86.5% for diagnosis, 61.8% for chief complaint, 62.7%, for problem list, and 64.8% for discharge medication. CONCLUSION: The text processing method based on the pattern analysis of a clinical statement can be effectively used for generating CDA entries.

Efficacy of a 14Fr Blake Drain for Pleural Drainage Following Video-Assisted Thoracic Surgery / 대한흉부외과학회지

BACKGROUND: Pleural drainage following video-assisted thoracic surgery has traditionally been achieved with large- bore, semi-rigid chest tubes. Recent trends in thoracic surgery have been toward less invasive approaches for a variety of diseases. The purpose of this study was to evaluate the safety and efficacy of drainage by means of small, soft, and flexible 14Fr Blake drains. MATERIAL AND METHOD: Between December 2007 and March 2008, 14Fr silastic Blake drains were used for drainage of the pleural cavity in 37 patients who underwent a variety of video- assisted thoracic surgical procedures at our institution. RESULT: The average postoperative length of hospital stay was 3.26 days (range, 2~12 days), Blake drains were left in the pleural space for an average of 3.15 days (range, 1~7 days), and the average amount of drainage was 43.8 ml/day. The maximal amount of blood removed daily by a Brake drain was as much as 290 mL. There were no drain-related complications. Blake drains seemed to cause less pain while in place, and particularly at the time of removal. CONCLUSION: The use of a Blake drain following minor thoracic surgery appeared to be safe and effective in drainage of fluid or air in the pleural space, and were associated with minimal discomfort.

The Expressive Power of SNOMED-CT Compared with the Discharge Summaries / 대한의료정보학회지

OBJECTIVE: The standard vocabularies need to cover a diverse and enriched field of medical content, thereby facilitating semantic information retrieval, clinical decision support and efficient care delivery. SNOMED-CT(Systematized Nomenclature of Human and Veterinary Medicine-Clinical Term) is a comprehensive and precise clinical reference terminology that provides unsurpassed clinical content and expressivity for clinical documentation and reporting. To investigate whether the SNOMED-CT can serve this function in Seoul National University Hospital(SNUH) environment, we evaluated the coverage of SNOMED-CT as compared with clinical terms in the discharge summary at SNUH. METHODS: We tested for discordance of clinical terms between SNUH discharge summary and those from SNOMED-CT. We extracted 9,554 concepts from 1,000 discharge summaries. From these concepts, we obtained 3,545 unique concepts which are normalized to map with SNOMED-CT. These normalized terms are mapped to concepts of SNOMED-CT with semi-automatic method. RESULTS: We found a degree of concordance between SNOMED-CT and the clinical terms used in the discharge summary. Approximately, 89% of medical terms in the discharge summary are matched and 11% of the concepts are not mapped to those of SNOMED-CT. CONCLUSION: Through this study, we confirmed that SNOMED-CT is appropriate reference terminology in SNUH environment.

Information Extraction Using Concept Node Analysis of Brain Radiology Reports Summarization / 대한의료정보학회지

OBJECTIVE: Electronic Medical Record contains the majority of clinical data in unstructured text. The information in the textual document can be stored in conceptual format and used to support clinical care by text summarization technique. In this study, we present Information Extraction(IE) using Concept Node(CN) which is extraction rule in case frame from brain radiology reports in SNUH(Seoul National University Hospital) for summarization. METHOD: Following steps are performed: design conceptual model to define semantic entities as extraction templates of brain radiology report, build CN dictionary based on statistical syntactic pattern and development of parser to extract relevant information based on defined templates. RESULTS: The three evaluation results shows that 19% precision improvement after post processing supplemental specified complex verb construction and 19.24~21.25% accurate semantic effectiveness with extracting additional Korean noun. The average of precision is 85.18%, average of recall is 93.71% and F-measure is 0.89. CONCLUSION: Our approach has advantageous elements for different language at the same sentence. We expect this IE technology can summarize vast amount radiology texts material for clinical decision support system effectively and hope this study helps the evolution of clinical data representation in Korean medical records and its integration into the EMR in the future.