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This study presents a deep learning model to predict phlebitis in patients with peripheral intravenous catheter (PIVC) insertions. Leveraging electronic health record data from 27,532 admissions and 70,293 PIVC events at a hospital in Seoul, South Korea, the study involved analyzing patient demographics, PIVC-specific features, and drug-related information. The developed deep learning model was benchmarked against various machine learning models, demonstrating superior performance with an accuracy of 0.93 and an AUC of 0.89. This highlights its potential as an effective tool for early detection of phlebitis, promising enhanced patient outcomes and healthcare efficiency.
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Cateterismo Periférico , Aprendizado Profundo , Flebite , Humanos , Flebite/etiologia , Cateterismo Periférico/efeitos adversos , República da Coreia , Registros Eletrônicos de Saúde , Masculino , Feminino , Pessoa de Meia-IdadeRESUMO
OBJECTIVES: Education in biomedical and health informatics is essential for managing complex healthcare systems, bridging the gap between healthcare and information technology, and adapting to the digital requirements of the healthcare industry. This review presents the current status of biomedical and health informatics education domestically and internationally and proposes recommendations for future development. METHODS: We analyzed evidence from reports and papers to explore global trends and international and domestic examples of education. The challenges and future strategies in Korea were also discussed based on the experts' opinions. RESULTS: This review presents international recommendations for establishing education in biomedical and health informatics, as well as global examples at the undergraduate and graduate levels in medical and nursing education. It provides a thorough examination of the best practices, strategies, and competencies in informatics education. The review also assesses the current state of medical informatics and nursing informatics education in Korea. We highlight the challenges faced by academic institutions and conclude with a call to action for educators to enhance the preparation of professionals to effectively utilize technology in any healthcare setting. CONCLUSIONS: To adapt to the digitalization of healthcare, systematic and continuous workforce development is essential. Future education should prioritize curriculum innovations and the establishment of integrated education programs, focusing not only on students but also on educators and all healthcare personnel in the field. Addressing these challenges requires collaboration among educational institutions, academic societies, government agencies, and international bodies dedicated to systematic and continuous workforce development.
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Citrus cultivation plays a pivotal role, making a significant contribution to global fruit production and dietary consumption. Accurate identification of viral pathogens is imperative for the effective management of plant viral disease in citrus crops. High-throughput sequencing serves as an alternative approach, enabling comprehensive pathogen identification on a large scale without requiring pre-existing information. In this study, we employed HTS to investigate viral pathogens infecting citrus in three different regions of South Korea: Jejudo (Jeju), Wando-gun (Wando), and Dangjin-si (Dangjin). The results unveiled diverse viruses and viroids that exhibited regional variations. Notably, alongside the identification of well-known citrus viruses such as satsuma dwarf virus, citrus tatter leaf virus, and citrus leaf blotch virus (CLBV), this study also uncovered several viruses and viroids previously unreported in Korean citrus. Phylogenetic analysis revealed that majority of identified viruses exhibited the closest affilations with isolates from China or Japan. However, CLBV and citrus viroid-I-LSS displayed diverse phylogenetic positions, reflecting their regional origins. This study advances our understanding of citrus virome diversity and regional dynamics through HTS, emphasizing its potential in unraveling intricate viral pathogens in agriculture. Consequently, it significantly contributes to disease management strategies, ensuring the resilience of the citrus industry.
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Phalaenopsis orchids are one of the most popular ornamental plants. More than thirty orchid viruses have been reported, and virus-infected Phalaenopsis orchids significantly lose their commercial value. Therefore, the development of improved viral disease detection methods could be useful for quality control in orchid cultivation. In this study, we first utilized the MinION, a portable sequencing device based on Oxford Nanopore Technologies (ONT) to rapidly detect plant viruses in Phalaenopsis orchids. Nanopore sequencing revealed the presence of three plant viruses in Phalaenopsis orchids: odontoglossum ringspot virus, cymbidium mosaic virus, and nerine latent virus (NeLV). Furthermore, for the first time, we detected NeLV infection in Phalaenopsis orchids using nanopore sequencing and developed the reverse transcription-recombinase polymerase amplification (RT-RPA)-CRISPR/Cas12a method for rapid, instrument-flexible, and accurate diagnosis. The developed RT-RPA-CRISPR/Cas12a technique can confirm NeLV infection in less than 20 min and exhibits no cross-reactivity with other viruses. To determine the sensitivity of RT-RPA-CRISPR/Cas12a for NeLV, we compared it with RT-PCR using serially diluted transcripts and found a detection limit of 10 zg/µL, which is approximately 1000-fold more sensitive. Taken together, the ONT platform offers an efficient strategy for monitoring plant viral pathogens, and the RT-RPA-CRISPR/Cas12a method has great potential as a useful tool for the rapid and sensitive diagnosis of NeLV.
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Amaryllidaceae , Infecção Latente , Sequenciamento por Nanoporos , Orchidaceae , Sistemas CRISPR-Cas , Reações Cruzadas , RecombinasesRESUMO
This study examined the effects of language differences between Korean and English on the performance of natural language processing in the classification task of identifying inpatient falls from unstructured nursing notes.
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Aprendizado Profundo , Humanos , Acidentes por Quedas/prevenção & controle , Pacientes Internados , Registros Eletrônicos de Saúde , Idioma , Processamento de Linguagem NaturalRESUMO
Inpatient falls are frequent adverse events, with various injuries occurring in one-third of falls. International practice guidelines recommend multifaceted risk assessment and risk-targeted interventions through multifactorial activities. However, the effectiveness is mixed for such recommendations implemented using traditional approaches. This study proposed a well-designed systemic and clinical decision support approach using machine learning techniques to leverage the implementation of preventive activities of nursing processes leading to outcome changes.
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Acidentes por Quedas , Pacientes Internados , Humanos , Acidentes por Quedas/prevenção & controle , Aprendizado de Máquina , Medição de RiscoRESUMO
Citrus tristeza virus (CTV) is a highly destructive viral pathogen posing a significant threat to citrus crops worldwide. The disease management and crop protection strategies necessitate the development of rapid and accurate detection methods. In this study, we employed Oxford Nanopore sequencing (ONT) to detect CTV in Citrus unshiu samples. Subsequently, we developed a specific and sensitive detection assay combining CRISPR/Cas12a with reverse transcription-recombinase polymerase amplification. The CRISPR-Cas12a assay exhibited exceptional specificity for CTV, surpassing conventional RT-PCR by at least 10-fold in sensitivity. Remarkably, the developed assay detected CTV in field samples, with zero false negatives. This diagnostic approach is user-friendly, cost-effective, and offers tremendous potential for rapid on-site detection of CTV. Therefore, the CRISPR-Cas12a assay plays a significant role in managing and preserving citrus trees that are free from viruses in the industry.
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OBJECTIVES: Standardized nursing terminologies (SNTs) are necessary to ensure consistent knowledge expression and compare the effectiveness of nursing practice across settings. This study investigated whether SNTs can support semantic interoperability and outcoming tracking over time by implementing an AI-powered CDS tool for fall prevention across multiple EMR systems. MATERIALS AND METHODS: The study involved 3 tertiary academic hospitals and 1 public hospital with different EMR systems and nursing terms, and employed an AI-powered CDS tool that determines the fall risk within the next hour (prediction model) and recommends tailored care plans (CDS functions; represented by SNTs). The prediction model was mapped to local data elements and optimized using local data sets. The local nursing statements in CDS functions were mapped using an ICNP-based inpatient fall-prevention catalog. Four implementation models were compared, and patient outcomes and nursing activities were observed longitudinally at one site. RESULTS: The postimplementation approach was practical for disseminating the AI-powered CDS tool for nursing. The 4 hospitals successfully implemented prediction models with little performance variation; the AUROCs were 0.8051-0.9581. The nursing process data contributed markedly to fall-risk predictions. The local nursing statements on preventing falls covered 48.0%-86.7% of statements. There was no significant longitudinal decrease in the fall rate (P = .160, 95% CI = -1.21 to 0.21 per 1000 hospital days), but rates of interventions provided by nurses were notably increased. CONCLUSION: SNTs contributed to achieving semantic interoperability among multiple EMR systems to disseminate AI-powered CDS tools and automatically track nursing and patient outcomes.
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Processo de Enfermagem , Terminologia Padronizada em Enfermagem , Humanos , Pacientes Internados , Inteligência ArtificialRESUMO
In April 2022, leaves showing virus-like symptoms including mosaic, feathery chlorotic mottle and distortions were observed on calla lilies (Zantedeschia sp.) growing in a greenhouse in Jeolla province, South Korea. Leaf samples from nine symptomatic plants from the same greenhouse were collected and tested for Zantedeschia mosaic virus (ZaMV), Zantedeschia mild mosaic virus (ZaMMV) and Dasheen mosaic virus (DaMV) by reverse transcription-polymerase chain reaction (RT-PCR) with specific primers, ZaMV-F/R (Wei et al. 2008), ZaMMV-F/R (5'-GACGATCAGCAACAGCAGCAACAGCAGAAG-3'/5'-CTGCAAGGCTGAGATCCCGAGTAGCGAGTG-3') and DsMV-CPF/CPR, respectively. In previous surveys, ZaMV and ZaMMV were detected in calla lily fields in South Korea. Of 9 symptomatic samples, 8 were positive for ZaMV and ZaMMV but no PCR product was obtained from the ninth sample, which showed a yellow feather-like pattern. To identify the causal virus, total RNA from a leaf sample of the symptomatic calla lily was extracted using an RNeasy Plant Mini Kit (Qiagen, Germany) and analyzed by high-throughput sequencing. Ribosomal RNA was removed and a cDNA library was prepared using an Illumina TruSeq Stranded Total RNA LT Sample Prep Kit (Plants) and sequenced on an Illumina NovaSeq 6000 system (Macrogen, Korea), yielding 150 nt paired end reads. De novo assembly of the 88,171,036 reads was performed using Trinity software (r20140717) while the 113,140 initially assembled contigs were screened against the NCBI viral genome database using BLASTN. One contig of 10,007 bp (GenBank LC723667) shared 79.89-87.08% nucleotide (nt) identities to the available genomes of other DsMV isolates including Colocasia esculenta isolates Et5 (MG602227, 87.08%; Ethiopia) and CTCRI-II-14 (KT026108, 85.32%; India), and a calla lily isolate (AJ298033, 84.95%; China). No contigs representing other plant viruses were identified. To confirm the presence of DsMV, and because the virus was not detected using DsMV-CPF/CPR, RT-PCR was performed using new virus-specific primers DsMV-F/R (5'-GATGTCAACGCTGGCACCAGT-3'/5'-CAACCTAGTAGTAACGTTGGAGA-3'), designed based on the contig sequence. PCR products of the expected 600 bp were obtained from the symptomatic plant, cloned into the pGEM-T Easy Vector (Promega, USA), and two independent clones were bidirectionally sequenced (BIONEER, Korea), and shown to be identical. The sequence was deposited in GenBank as acc. no. LC723766, and shared 100% nt identity to the full-length contig LC723667, and 91.83% identity to the Chinese calla lily DsMV isolate (AJ298033). DsMV, a member of the genus Potyvitus in the family Potyviridae, is one of the major viruses infecting taro in South Korea, showing mosaic and chlorotic feathering symptoms (Kim et al. 2004); however, there is no record in the literature of the identification of this virus in South Korea in ornamental species including calla lily. To survey the sanitary status of other calla lilies, 95 samples with or without symptoms were collected from other regions and subjected to RT-PCR detection for DsMV. Ten of these samples were positive with primers DsMV-F/R, including seven mixed infections (DsMV+ZaMV or DsMV+ZaMV+ZaMMV). To our knowledge, this is the first report of DsMV infecting calla lilies in South Korea. The virus is easily spread by vegetative propagation (Babu et al. 2011) and by aphids (Reyes et al. 2006). This study will help the management of viral diseases on calla lilies in South Korea.
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The global climate change and international trade have facilitated the movement of plants across borders, increasing the risk of introducing novel plant viruses in new territories. Ixora coccinea exhibited virus-like foliar symptoms, including mosaic and mild mottle. An Oxford Nanopore Technologies-based compact and portable MinION platform was used to identify the causal viral pathogen. The complete genome sequence of jasmine virus H (JaVH; 3867 nt, JaVH-CNU) was determined and found to share 88.4-90.3% nucleotide identity with that of Jasminum sambac JaVH isolate in China. Phylogenetic analysis based on the complete amino acid sequences of RNA-dependent RNA polymerase and coat protein revealed that JaVH-CNU was grouped separately with other JaVH isolates. This is the first report of a natural JaVH infection of >i<I. coccinea. The application of rapid nanopore sequencing for plant virus identification was demonstrated and is expected to provide accurate and rapid diagnosis for virus surveillance.
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Peripheral venous catheterization (PVC) is the most commonly used invasive technique, and its importance to patient safety is increasing. And phlebitis is a common complication which can lead to increased costs and extended hospital stays. This study attempted to characterize the current status of phlebitis based on incident reports in the Korea Patient Safety Reporting & Learning System. This retrospective descriptive study analysed 259 phlebitis cases reported in that system from 1 July 2017 to 31 December 2019. The analysis results were summarized using numbers and percentages or means with standard deviations. Among the reported phlebitis cases, antibiotics and high-osmolarity fluids comprised 48.2% of the intravenous inflammatory drugs used. All reported cases presented blood-flow infections. Insufficient observation or management was the most common cause of phlebitis. It was found that interventions for phlebitis were inconsistent with those recommended in evidence-based guidelines. Recommendations for nurses to alleviate complications in PVC must be promoted and educated. It is necessary to provide feedback from the incident reports analysis.
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Cateterismo Periférico , Flebite , Humanos , Cateterismo Periférico/efeitos adversos , Cateterismo Periférico/métodos , Estudos Retrospectivos , Flebite/epidemiologia , Flebite/etiologia , Gestão de Riscos , Hospitais , República da Coreia/epidemiologiaRESUMO
Objectives: To assess whether a fall-prevention clinical decision support (CDS) approach using electronic analytics that stimulates risk-targeted interventions is associated with reduced rates of falls and injurious falls. Materials and Methods: The CDS intervention included a machine-learning prediction algorithm, individual risk-factor identification, and guideline-based prevention recommendations. After a 5-month plan-do-study-act quality improvement initiative, the CDS intervention was implemented at an academic tertiary hospital and compared with the usual care using a pretest (lasting 24 months and involving 23 498 patients) and posttest (lasting 13 months and involving 17 341 patients) design in six nursing units. Primary and secondary outcomes were the rates of falls and injurious falls per 1000 hospital days, respectively. Outcome measurements were tested using a priori Poisson regression and adjusted with patient-level covariates. Subgroup analyses were conducted according to age. Results: The age distribution, sex, hospital and unit lengths of stay, number of secondary diagnoses, fall history, condition at admission, and overall fall rate per 1000 hospital days did not differ significantly between the intervention and control periods before (1.88 vs 2.05, respectively, P = .1764) or after adjusting for demographics. The injurious-falls rate per 1000 hospital days decreased significantly before (0.68 vs 0.45, P = .0171) and after (rate difference = -0.64, P = .0212) adjusting for demographics. The differences in injury rates were greater among patients aged at least 65 years. Conclusions: This study suggests that a well-designed CDS intervention employing electronic analytics was associated with a decrease in fall-related injuries. The benefits from this intervention were greater in elderly patients aged at least 65 years. Trial Registration: This study was conducted as part of a more extensive study registered with the Clinical Research Information Service (CRIS) (KCT0005378).
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BACKGROUND: Falls are one of the major adverse events affecting older adults that can result in serious injuries. Hospitalizations and deaths because of fall-related injuries have been increasing. Nevertheless, there is a dearth of studies examining the physical condition and current exercise habits of older adults. Moreover, studies analyzing the role of factors related to fall risk by age and gender in large populations are also scarce. PURPOSE: This study was designed to investigate the prevalence of falls among community-dwelling older adults and elucidate the effects of age and gender on the related factors using a biopsychosocial model. METHODS: This cross-sectional study utilized data from the 2017 National Survey of Older Koreans. On the basis of the biopsychosocial model, the biological factors related to falls included chronic diseases, number of medications, visual difficulties, activity of daily living (ADL) dependence, lower-limb muscle strength, and physical performance; psychological factors included depression, cognitive ability, regular smoking, alcohol consumption, nutritional status, and exercise; and the social factors included educational level, annual income, living conditions, and instrumental ADL dependence. RESULTS: Of the 10,073 older adults surveyed, 57.5% were women and approximately 15.7% had experienced falls. The results of the logistic regression showed that, in men, falls were significantly associated with taking more medications and being able to climb 10 stair steps; in women, falls were significantly associated with poor nutritional status and instrumental ADL dependence; and in both genders, falls were significantly associated with greater depression, ADL dependence, and the presence of more chronic diseases and negatively associated with physical performance. CONCLUSIONS/IMPLICATIONS FOR PRACTICE: The results suggest that practicing kneeling and squatting is the most effective strategy for reducing fall risk in older adult men and that improving nutritional status and strengthening physical ability is the most effective strategy for reducing fall risk in older adult women.
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Acidentes por Quedas , Vida Independente , Humanos , Masculino , Feminino , Idoso , Fatores Sexuais , Fumar , Estudos TransversaisRESUMO
BACKGROUND AND OBJECTIVES: A government-driven standardization of nursing terminology including the Clinical Care Classification (CCC) was endorsed in South Korea in 2015, but the number of hospitals who have adopted this standard terminology remains unknown. This study aimed to determine the CCC awareness, adoption, and utilization statuses and its association with patient experience in South Korea. DESIGN, SETTING, AND PARTICIPANTS: A nationwide telephone survey was conducted from January 13 to February 12, 2022 among 217 tertiary and secondary hospitals participating in the health information exchange network. The survey questionnaire included 22 items in 3 categories: current status of electronic nursing records, awareness and adoption of standard terminology, and open-ended questions regarding standard usage and dissemination. General characteristics and experience scores of the patients of the surveyed hospitals were collected from the publicly available data sources. Data analysis was performed using descriptive statistics, t-test, and generalized linear regression. MAIN OUTCOMES AND MEASURES: The rates of awareness and adoption in hospitals to the nursing terminology standard of the CCC were calculated, and the current status of electronic nursing records used in practice was examined. The relationships between CCC awareness and the characteristics of hospitals in their patient experiences of health services were also identified. RESULTS: The survey response rate was 24.9 % (54/217). Two out of three hospitals (68.5 %) were aware of the CCC. These hospitals had 800 beds or more, and higher scores for patient experience. CCC awareness was significantly related to increases in the overall scores for patient experiences (t = 2.70, p =.0103), but no significance with sub-score for nursing service (t = 1.23, p =.1594). CONCLUSIONS: With a high adoption rate of electronic medical record systems, two-third hospitals acknowledged their CCC awareness, but were still lagged in adoption and usage of it in practice with operational challenges. The CCC awareness has potential relationships with positive patient experience.
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Registros Eletrônicos de Saúde , Terminologia Padronizada em Enfermagem , Humanos , Registros de Enfermagem , Hospitais , República da CoreiaRESUMO
Pepper mild mottle virus (PMMoV), one of the most prevalent viruses in chili pepper (Capsicum annuum L.) is a non-enveloped, rod-shaped, single-stranded positive-sense RNA virus classified in the genus Tobamovirus. The supernatants of five bacterial cultures (Pseudomonas putida [PP], Bacillus licheniformis [BLI], P. fluorescens [PF], Serratia marcescens [SER], and B. amyloliquifaciens [BA]) were analyzed to find novel antiviral agents to PMMoV in chili pepper. Foliar spraying with supernatants (1:1, v/v) obtained from Luria-Bertani broth cultures of PP, BLI, PF, SER, and BA inhibited PMMoV infection of chili pepper if applied before the PMMoV inoculation. Double-antibody sandwich enzyme-linked immunosorbent assay showed that treatments of five supernatants resulted in 51-66% reductions in PMMoV accumulation in the treated chili pepper. To identify key compounds in supernatants of PP, BLI, PF, SER, and BA, the supernatants were subjected to gas chromatography-mass spectrometry. The 24 different types of compounds were identified from the supernatants of PP, BLI, PF, SER, and BA. The compounds vary from supernatants of one bacterial culture to another which includes simple compounds-alkanes, ketones, alcohols, and an aromatic ring containing compounds. The compounds triggered the inhibitory effect on PMMoV propagation in chili pepper plants. In conclusion, the cultures could be used to further conduct tissue culture and field trial experiments as potential bio-control agents.
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OBJECTIVES: This study explored the current status of nursing informatics education in South Korea and developed a standardized curriculum for it. METHODS: Data were collected in two stages: first, an online survey conducted from December 2020 to February 2021 among 60 nursing schools to analyze the current status of nursing informatics education; and second, a two-round Delphi survey with 15 experts from March to April 2021 to determine the mean and standard deviation of the demand for each learning objective in nursing informatics education. A standardized curriculum proposal was developed based on the results of the two-round Delphi survey. RESULTS: Nursing informatics was most commonly taught in the fourth year (34%), with two credits. The proportion of elective major subjects was high in undergraduate and graduate programs (77.4% and 78.6%, respectively), while the proportion of nursing informatics majors was low (21.4%). The curriculum developed included topics such as nursing information system-related concepts, definitions and components of healthcare information systems, electronic medical records, clinical decision support systems, mobile technology and health management, medical information standards, personal information protection and ethics, understanding of big data, use of information technology in evidence-based practice, use of information in community nursing, genome information usage, artificial intelligence clinical information systems, administrative management systems, and information technology nursing education. CONCLUSIONS: Nursing informatics professors should receive ongoing training to obtain recent medical information. Further review and modification of the nursing informatics curriculum should be performed to ensure that it remains up-to-date with recent developments.
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OBJECTIVES: Academic electronic medical records (AEMRs) can be utilized for a variety of educational programs that can enhance nursing students' nursing informatics and clinical reasoning competencies. This study aimed to identify the applicability and effectiveness of simulation education incorporating AEMRs. METHODS: We developed simulation education scenarios incorporating AEMRs and evaluated them with 76 third- and fourth-year nursing students from five nursing schools using a mixed-methods design. We incorporated three simulation case scenarios involving preeclampsia, diabetes mellitus, and myocardial infarction into the AEMRs. After the simulation education, participants' feedback on the usability of the AEMR system and their self-efficacy for AEMR utilization were collected via self-reported surveys. Subsequently, the simulation education incorporating AEMRs was evaluated through a focus group interview. The survey data were examined using descriptive statistics, and thematic analysis was done for the focus group interview data. RESULTS: The average mean scores for the AEMR system's usability and participants' self-efficacy for AEMR utilization were 5.36 of 7 and 3.96 of 5, respectively. According to the focus group interviews, the participants were satisfied with the simulation education incorporating AEMRs and recognized their confidence in AEMR utilization. In addition, participants addressed challenges to simulation education incorporating AEMRs, including the need for pre-education and AEMR utilization difficulties. CONCLUSIONS: Nursing students were satisfied with and recognized the value of simulation education incorporating AEMRs. Although the actual application of simulation education incorporating AEMRs remains challenging, further research can help develop and implement this approach for nursing students.
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Lilies (Lilium spp.) are one of the most important ornamental flower crops grown in Korea. Most viral diseases in lilies are transmitted by infected bulbs, which cause serious economic losses due to reduced yields. Various diagnostic techniques and high-throughput sequencing methods have been used to detect lily viruses. According to Oxford Nanopore Technologies (ONT), MinION is a compact and portable sequencing device. In this study, three plant viruses, lily mottle, lily symptomless, and plantago asiatica mosaic virus, were detected in lily samples using the ONT platform. As a result of genome assembly of reads obtained through ONT, 100% coverage and 90.3-93.4% identity were obtained. Thus, we show that the ONT platform is a promising tool for the diagnosis and characterization of viruses that infect crops.
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BACKGROUND: A clinical decision support system (CDSS) is recognized as a technology that enhances clinical efficacy and safety. However, its full potential has not been realized, mainly due to clinical data standards and noninteroperable platforms. OBJECTIVE: In this paper, we introduce the common data model-based intelligent algorithm network environment (CANE) platform that supports the implementation and deployment of a CDSS. METHODS: CDSS reasoning engines, usually represented as R or Python objects, are deployed into the CANE platform and converted into C# objects. When a clinician requests CANE-based decision support in the electronic health record (EHR) system, patients' information is transformed into Health Level 7 Fast Healthcare Interoperability Resources (FHIR) format and transmitted to the CANE server inside the hospital firewall. Upon receiving the necessary data, the CANE system's modules perform the following tasks: (1) the preprocessing module converts the FHIRs into the input data required by the specific reasoning engine, (2) the reasoning engine module operates the target algorithms, (3) the integration module communicates with the other institutions' CANE systems to request and transmit a summary report to aid in decision support, and (4) creates a user interface by integrating the summary report and the results calculated by the reasoning engine. RESULTS: We developed a CANE system such that any algorithm implemented in the system can be directly called through the RESTful application programming interface when it is integrated with an EHR system. Eight algorithms were developed and deployed in the CANE system. Using a knowledge-based algorithm, physicians can screen patients who are prone to sepsis and obtain treatment guides for patients with sepsis with the CANE system. Further, using a nonknowledge-based algorithm, the CANE system supports emergency physicians' clinical decisions about optimum resource allocation by predicting a patient's acuity and prognosis during triage. CONCLUSIONS: We successfully developed a common data model-based platform that adheres to medical informatics standards and could aid artificial intelligence model deployment using R or Python.