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Kang D, Kim N, Kim H, Lee AY, Park J, Kim S, Ahn JS, Shim YM, Cho J. Emulating trial to evaluate the effectiveness of routine supportive care on mortality among cancer patients experiencing distress at the time of diagnosis. J Affect Disord 2024; 354:519-525. [PMID: 38484885 DOI: 10.1016/j.jad.2024.03.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 03/04/2024] [Accepted: 03/09/2024] [Indexed: 03/26/2024]
Abstract
INTRODUCTION Few studies have evaluated the effectiveness of interventions for distress during cancer diagnosis on clinical outcomes in a real-world setting. We aimed to evaluate whether routine information and psychosocial support to patients experiencing distress at the time of diagnosis could decrease the risk of mortality within 1 and 3 years after diagnosis. MATERIAL AND METHODS We conducted a retrospective cohort study of 4880 newly diagnosed cancer patients who reported distress scores of ≥4 using the tablet or kiosk-based screening between July 2014 and December 2017 at a university-affiliated cancer center in Seoul, South Korea. We performed an emulated target trial with two groups: those that received information and psychosocial support and those that did not. Cox proportional hazards models were used to identify the associations between information and psychosocial support and all-cause mortality. RESULTS Of all the patients, 16.6 % had routine information and psychosocial support. The hazard ratio (HR) for one-year mortality comparing participants with information and psychosocial support to those without it were 0.73 (95 % confidence interval (CI) = 0.54, 0.99). Age < 50 and 50 - <60 group had a stronger effect of information and psychosocial support on reducing mortality within one-year than these in age ≥ 60 (p for interaction = 0.03). In terms of three-year mortality, the HR comparing participants with information and psychosocial support to those without it was 0.93 (95 % CI = 0.76, 1.14). CONCLUSION This large-scale real-world study suggests that timely psychosocial care benefits newly diagnosed cancer patients who had distress during pre-treatment period.
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Affiliation(s)
- Danbee Kang
- Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul 06351, Republic of Korea; Center for Clinical Epidemiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Nayoen Kim
- Cancer Education Center, Samsung Comprehensive Cancer Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Hoyoung Kim
- Cancer Education Center, Samsung Comprehensive Cancer Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - A Young Lee
- Cancer Education Center, Samsung Comprehensive Cancer Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Joungwon Park
- Division of Social Work, Samsung Comprehensive Cancer Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Sooyeon Kim
- Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul 06351, Republic of Korea; Center for Clinical Epidemiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Jin Seok Ahn
- Division of Hematology/Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Young Mog Shim
- Department of Thoracic and Cardiovascular Surgery, Sungkyunkwan University School of Medicine, Samsung Medical Center, Seoul 06351, Republic of Korea
| | - Juhee Cho
- Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul 06351, Republic of Korea; Center for Clinical Epidemiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; Cancer Education Center, Samsung Comprehensive Cancer Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea; Departments of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.
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El-Ghandour NMF. Commentary: From Text to Insight: A Natural Language Processing-Based Analysis of Topics and Trends in Neurosurgery. Neurosurgery 2024; 94:e46-e47. [PMID: 37988063 DOI: 10.1227/neu.0000000000002764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 10/11/2023] [Indexed: 11/22/2023] Open
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Kang D, Cho J, Park S, Kim HJ, Kim SW, Lee JE, Yu J, Lee SK, Kim JY, Nam SJ, Park YH. Pretreatment endocrine symptoms and recurrence-free survival among young premenopausal patients with breast cancer: a prospective cohort study. Ther Adv Med Oncol 2023; 15:17588359231189421. [PMID: 37547446 PMCID: PMC10399274 DOI: 10.1177/17588359231189421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 07/05/2023] [Indexed: 08/08/2023] Open
Abstract
Background Pretreatment endocrine symptoms in premenopausal patients might be considered as a potential marker of poor prognosis. We conducted a cohort study to evaluate the association between endocrine symptoms prior to treatment and recurrence-free survival (RFS) among premenopausal patients with breast cancer aged ⩽40 years. Methods Data were obtained from a prospective cohort study (NCT03131089) conducted at the Samsung Medical Center from 2013 to 2021. We included patients aged ⩽40 years who had been diagnosed with breast cancer. The primary outcome measure was RFS. Endocrine symptoms were measured using the Functional Assessment of Cancer Therapy - Endocrine Symptoms (FACT-ES). We also calculated the hazard ratio (HR) for recurrence or all-cause mortality by comparing the tertiles of the FACT-ES score at diagnosis. Results Among the 977 participants, the mean (standard deviation) age was 35.3 (3.9) years. At diagnosis, 17.2% of the patients had at least one severe endocrine symptom. During 3512 person-years of follow-up, the high symptom group had a worse RFS than the low-symptom group [HR = 2.05; 95% confidence interval (CI) = 1.19-3.54]. In particular, hot flashes (HR = 5.59; 95% CI = 1.96-15.93) and breast sensitivity (HR = 1.82; 95% CI = 1.00-3.32) were associated with reduced RFS. Conclusion Close monitoring of pretreatment endocrine symptoms may be important in patients diagnosed with breast cancer at a young age.
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Affiliation(s)
- Danbee Kang
- Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Center for Clinical Epidemiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Juhee Cho
- Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Center for Clinical Epidemiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Seri Park
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Hyo Jung Kim
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Seok Won Kim
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jeong Eon Lee
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jonghan Yu
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Se Kyung Lee
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Ji-Yeon Kim
- Division of Hematology and Oncology, Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Seok Jin Nam
- Division of Breast Surgery, Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Yeon Hee Park
- Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, South Korea
- Division of Hematology and Oncology, Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-dong, Kangnam-gu, Seoul 06351, South Korea
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Salem M, Elkaseer A, El-Maddah IAM, Youssef KY, Scholz SG, Mohamed HK. Non-Invasive Data Acquisition and IoT Solution for Human Vital Signs Monitoring: Applications, Limitations and Future Prospects. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22176625. [PMID: 36081081 PMCID: PMC9460364 DOI: 10.3390/s22176625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 08/22/2022] [Accepted: 08/30/2022] [Indexed: 05/06/2023]
Abstract
The rapid development of technology has brought about a revolution in healthcare stimulating a wide range of smart and autonomous applications in homes, clinics, surgeries and hospitals. Smart healthcare opens the opportunity for a qualitative advance in the relations between healthcare providers and end-users for the provision of healthcare such as enabling doctors to diagnose remotely while optimizing the accuracy of the diagnosis and maximizing the benefits of treatment by enabling close patient monitoring. This paper presents a comprehensive review of non-invasive vital data acquisition and the Internet of Things in healthcare informatics and thus reports the challenges in healthcare informatics and suggests future work that would lead to solutions to address the open challenges in IoT and non-invasive vital data acquisition. In particular, the conducted review has revealed that there has been a daunting challenge in the development of multi-frequency vital IoT systems, and addressing this issue will help enable the vital IoT node to be reachable by the broker in multiple area ranges. Furthermore, the utilization of multi-camera systems has proven its high potential to increase the accuracy of vital data acquisition, but the implementation of such systems has not been fully developed with unfilled gaps to be bridged. Moreover, the application of deep learning to the real-time analysis of vital data on the node/edge side will enable optimal, instant offline decision making. Finally, the synergistic integration of reliable power management and energy harvesting systems into non-invasive data acquisition has been omitted so far, and the successful implementation of such systems will lead to a smart, robust, sustainable and self-powered healthcare system.
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Affiliation(s)
- Mahmoud Salem
- Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
- Correspondence: ; Tel.: +49-0-721-608-25632
| | - Ahmed Elkaseer
- Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
- Karlsruhe Nano Micro Facility, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
- Faculty of Engineering, Port Said University, Port Said 42526, Egypt
| | | | - Khaled Y. Youssef
- Faculty of Navigation Science and Space Technology, Beni-Suef University, Beni-Suef 2731070, Egypt
| | - Steffen G. Scholz
- Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
- Karlsruhe Nano Micro Facility, Karlsruhe Institute of Technology, 76344 Eggenstein-Leopoldshafen, Germany
- College of Engineering, Swansea University, Swansea SA2 8PP, UK
| | - Hoda K. Mohamed
- Faculty of Engineering, Ain Shams University, Cairo 11535, Egypt
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Kwon H, An S, Lee HY, Cha WC, Kim S, Cho M, Kong HJ. Review of Smart Hospital Services in Real Healthcare Environments. Healthc Inform Res 2022; 28:3-15. [PMID: 35172086 PMCID: PMC8850169 DOI: 10.4258/hir.2022.28.1.3] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 01/15/2022] [Indexed: 11/23/2022] Open
Abstract
Objectives: Smart hospitals involve the application of recent information and communications technology (ICT) innovations to medical services; however, the concept of a smart hospital has not been rigorously defined. In this study, we aimed to derive the definition and service types of smart hospitals and investigate cases of each type. Methods: A literature review was conducted regarding the background and technical characteristics of smart hospitals. On this basis, we conducted a focus group interview with experts in hospital information systems, and ultimately derived eight smart hospital service types.Results: Smart hospital services can be classified into the following types: services based on location recognition and tracking technology that measures and monitors the location information of an object based on short-range communication technology; high-speed communication network-based services based on new wireless communication technology; Internet of Things-based services that connect objects embedded with sensors and communication functions to the internet; mobile health services such as mobile phones, tablets, and wearables; artificial intelligence-based services for the diagnosis and prediction of diseases; robot services provided on behalf of humans in various medical fields; extended reality services that apply hyper-realistic immersive technology to medical practice; and telehealth using ICT. Conclusions: Smart hospitals can influence health and medical policies and create new medical value by defining and quantitatively measuring detailed indicators based on data collected from existing hospitals. Simultaneously, appropriate government incentives, consolidated interdisciplinary research, and active participation by industry are required to foster and facilitate smart hospitals.
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Affiliation(s)
- Hyuktae Kwon
- Department of Family Medicine, Seoul National University Hospital, Seoul, Korea
| | - Sunhee An
- Transdisciplinary Department of Medicine and Advanced Technology, Seoul National University Hospital, Seoul, Korea
| | - Ho-Young Lee
- Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Won Chul Cha
- Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea
| | - Sungwan Kim
- Transdisciplinary Department of Medicine and Advanced Technology, Seoul National University Hospital, Seoul, Korea
- Institute of Medical & Biological Engineering, Medical Research Center, Seoul National University College of Medicine, Seoul, Korea
- Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea
| | - Minwoo Cho
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea
| | - Hyoun-Joong Kong
- Transdisciplinary Department of Medicine and Advanced Technology, Seoul National University Hospital, Seoul, Korea
- Institute of Medical & Biological Engineering, Medical Research Center, Seoul National University College of Medicine, Seoul, Korea
- Department of Medicine, Seoul National University College of Medicine, Seoul, Korea
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Kim S, Ku S, Kim T, Cha WC, Jung KY. Effective Use of Mobile Electronic Medical Records by Medical Interns in Real Clinical Settings: Mixed Methods Study. JMIR Mhealth Uhealth 2020; 8:e23622. [PMID: 33320098 PMCID: PMC7772071 DOI: 10.2196/23622] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 10/16/2020] [Accepted: 11/30/2020] [Indexed: 11/13/2022] Open
Abstract
Background In South Korea, most graduated medical students undertake a 1-year internship before beginning residency and specialization. Interns usually work in a tertiary hospital and rotate between different, randomly assigned departments to be exposed to different medical specialties. Their jobs are mostly simple and repetitive but are still essential for the patient care process. However, owing to the lack of experience and overwhelming workload, interns at tertiary hospitals in South Korea are usually inefficient, often delaying the entire clinical process. Health care providers have widely adopted mobile electronic medical records (mEMRs) as they have been shown to improve workflow efficiency. Objective This study investigates the association between the frequency of mEMR usage and the clinical task completion interval time among interns in a tertiary hospital. Methods This mixed methods study was conducted at the Samsung Medical Center, Seoul, South Korea. Interns who worked at the Samsung Medical Center from March 2018 to February 2019 were included. The hospital electronic medical record (EMR) system known as DARWIN (Data Analysis and Research Window for Integrated kNowledge) was launched with PC and mobile. Both versions are actively used in hospitals by personnel in various positions. We collected the log data from the mEMR server and the intern clinical task time-series data from the EMR server. Interns can manage the process of identifying patients, assigning the clinical task, finishing the requested clinical intern tasks, etc, through the use of the mEMR system. We compared the clinical task completion interval among 4 groups of interns divided by the mEMR frequency quantile. Then, System Usability Score (SUS) questionnaires and semistructured interviews were conducted. Results The regular mEMR users were defined as those who logged in more than once a day on average and used the mEMR until the level after login. Among a total of 87 interns, 84 used the mEMR to verify the requested clinical tasks. The most frequently used item was “Intern task list.” Analysis of the 4 intern groups revealed an inverse relationship between the median time of the task completion interval and the frequency of mEMR use. Correlation analysis showed that the intern task completion time interval had a significant inverse relationship with the individual frequency of mEMR usage (coefficient=-0.27; 95% CI -0.46 to -0.04; P=.02). In the additional survey, the mean SUS value was 81.67, which supported the results of the data analysis. Conclusions Our findings suggest that frequent mEMR use is associated with improved work efficiency in hospital interns with good usability of the mEMR. Such finding supports the idea that the use of mEMR improves the effectiveness and workflow efficiency of interns working in hospitals and, more generally, in the context of health care.
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Affiliation(s)
- SuJin Kim
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea.,Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Seulji Ku
- Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Taerim Kim
- Department of Emergency Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Won Chul Cha
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea.,Department of Emergency Medicine, Samsung Medical Center, Seoul, Republic of Korea.,Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Kwang Yul Jung
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea.,Department of Emergency Medicine, Ewha Womans University Seoul Hospital, Seoul, Republic of Korea
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Temporal Change in Alert Override Rate with a Minimally Interruptive Clinical Decision Support on a Next-Generation Electronic Medical Record. ACTA ACUST UNITED AC 2020; 56:medicina56120662. [PMID: 33265954 PMCID: PMC7761179 DOI: 10.3390/medicina56120662] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 11/25/2020] [Accepted: 11/29/2020] [Indexed: 11/16/2022]
Abstract
Background and objectives: The aim of this study is to describe the temporal change in alert override with a minimally interruptive clinical decision support (CDS) on a Next-Generation electronic medical record (EMR) and analyze factors associated with the change. Materials and Methods: The minimally interruptive CDS used in this study was implemented in the hospital in 2016, which was a part of the new next-generation EMR, Data Analytics and Research Window for Integrated kNowledge (DARWIN), which does not generate modals, 'pop-ups' but show messages as in-line information. The prescription (medication order) and alerts data from July 2016 to December 2017 were extracted. Piece-wise regression analysis and linear regression analysis was performed to determine the temporal change and factors associated with it. Results: Overall, 2,706,395 alerts and 993 doctors were included in the study. Among doctors, 37.2% were faculty (professors), 17.2% were fellows, and 45.6% trainees (interns and residents). The overall override rate was 61.9%. There was a significant change in an increasing trend at month 12 (p < 0.001). We found doctors' positions and specialties, along with the number of alerts and medication variability, were significantly associated with the change. Conclusions: In this study, we found a significant temporal change of alert override. We also found factors associated with the change, which had statistical significance.
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Yoo J, Lee J, Rhee PL, Chang DK, Kang M, Choi JS, Bates DW, Cha WC. Alert Override Patterns With a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study. JMIR Med Inform 2020; 8:e23351. [PMID: 33146626 PMCID: PMC7673981 DOI: 10.2196/23351] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 09/12/2020] [Accepted: 10/21/2020] [Indexed: 11/13/2022] Open
Abstract
Background Physicians’ alert overriding behavior is considered to be the most important factor leading to failure of computerized provider order entry (CPOE) combined with a clinical decision support system (CDSS) in achieving its potential adverse drug events prevention effect. Previous studies on this subject have focused on specific diseases or alert types for well-defined targets and particular settings. The emergency department is an optimal environment to examine physicians’ alert overriding behaviors from a broad perspective because patients have a wider range of severity, and many receive interdisciplinary care in this environment. However, less than one-tenth of related studies have targeted this physician behavior in an emergency department setting. Objective The aim of this study was to describe alert override patterns with a commercial medication CDSS in an academic emergency department. Methods This study was conducted at a tertiary urban academic hospital in the emergency department with an annual census of 80,000 visits. We analyzed data on the patients who visited the emergency department for 18 months and the medical staff who treated them, including the prescription and CPOE alert log. We also performed descriptive analysis and logistic regression for assessing the risk factors for alert overrides. Results During the study period, 611 physicians cared for 71,546 patients with 101,186 visits. The emergency department physicians encountered 13.75 alerts during every 100 orders entered. Of the total 102,887 alerts, almost two-thirds (65,616, 63.77%) were overridden. Univariate and multivariate logistic regression analyses identified 21 statistically significant risk factors for emergency department physicians’ alert override behavior. Conclusions In this retrospective study, we described the alert override patterns with a medication CDSS in an academic emergency department. We found relatively low overrides and assessed their contributing factors, including physicians’ designation and specialty, patients’ severity and chief complaints, and alert and medication type.
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Affiliation(s)
- Junsang Yoo
- Institution of Healthcare Resource, School of Nursing, Sahmyook University, Seoul, Republic of Korea
| | - Jeonghoon Lee
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Department of Digital Health, Sungkyunkwan University, Seoul, Republic of Korea
| | - Poong-Lyul Rhee
- Department of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Dong Kyung Chang
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Department of Digital Health, Sungkyunkwan University, Seoul, Republic of Korea.,Department of Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.,Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Mira Kang
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Department of Digital Health, Sungkyunkwan University, Seoul, Republic of Korea.,Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea.,Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jong Soo Choi
- Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea
| | - David W Bates
- Division of General Internal Meidicine and Primary Care, Brigham and Women's Hospital, Boston, MA, United States
| | - Won Chul Cha
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Department of Digital Health, Sungkyunkwan University, Seoul, Republic of Korea.,Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea.,Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
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Jung KY, Kim S, Kim K, Lee EJ, Kim K, Lee J, Choi JS, Kang M, Chang DK, Cha WC. Frequent Mobile Electronic Medical Records Users Respond More Quickly to Emergency Department Consultation Requests: Retrospective Quantitative Study. JMIR Mhealth Uhealth 2020; 8:e14487. [PMID: 32130157 PMCID: PMC7055754 DOI: 10.2196/14487] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 10/07/2019] [Accepted: 12/16/2019] [Indexed: 11/13/2022] Open
Abstract
Background Specialty consultation is a critical aspect of emergency department (ED) practice, and a delay in providing consultation might have a significant clinical effect and worsen ED overcrowding. Although mobile electronic medical records (EMR) are being increasingly used and are known to improve the workflow of health care providers, limited studies have evaluated their effectiveness in real-life clinical scenarios. Objective For this study, we aimed to determine the association between response duration to an ED specialty consultation request and the frequency of mobile EMR use. Methods This retrospective study was conducted in an academic ED in Seoul, South Korea. We analyzed EMR and mobile EMR data from May 2018 to December 2018. Timestamps of ED consultation requests were retrieved from a PC-based EMR, and the response interval was calculated. Doctors’ log frequencies were obtained from the mobile EMR, and we merged data using doctors’ deidentification numbers. Pearson’s product-moment correlation was performed to identify this association. The primary outcome was the relationship between the frequency of mobile EMR usage and the time interval from ED request to consultation completion by specialty doctors. The secondary outcome was the relationship between the frequency of specialty doctors’ mobile EMR usage and the response time to consultation requests. Results A total of 25,454 consultations requests were made for 15,555 patients, and 252 specialty doctors provided ED specialty consultations. Of the 742 doctors who used the mobile EMR, 208 doctors used it for the specialty consultation process. After excluding the cases lacking essential information, 21,885 consultations with 208 doctors were included for analysis. According to the mobile EMR usage pattern, the average usage frequency of all users was 13.3 logs/day, and the average duration of the completion of the specialty consultation was 51.7 minutes. There was a significant inverse relationship between the frequency of mobile EMR usage and time interval from ED request to consultation completion by specialty doctors (coefficient=–0.19; 95% CI –0.32 to –0.06; P=.005). Secondary analysis with the response time was done. There was also a significant inverse relationship between the frequency of specialty doctors’ mobile EMR usage and the response time to consultation requests (coefficient=–0.18; 95% CI –0.30 to –0.04; P=.009). Conclusions Our findings suggest that frequent mobile EMR usage is associated with quicker response time to ED consultation requests.
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Affiliation(s)
- Kwang Yul Jung
- Department of Emergency Medicine, Inha University School of Medicine, Incheon, Republic of Korea
| | - SuJin Kim
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea
| | - Kihyung Kim
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea
| | - Eun Ju Lee
- Korea Health Industry Development Institute, Cheongju, Republic of Korea
| | - Kyunga Kim
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea.,Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
| | - Jeanhyoung Lee
- Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Jong Soo Choi
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea.,Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea
| | - Mira Kang
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea.,Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea.,Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Dong Kyung Chang
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea.,Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea.,Department Gastroenterology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Won Chul Cha
- Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea.,Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea.,Department of Emergency Medicine, Samsung Medical Center, Seoul, Republic of Korea
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Wang J, Deng H, Liu B, Hu A, Liang J, Fan L, Zheng X, Wang T, Lei J. Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed. J Med Internet Res 2020; 22:e16816. [PMID: 32012074 PMCID: PMC7005695 DOI: 10.2196/16816] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 12/05/2019] [Accepted: 12/15/2019] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Natural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and increasing importance of understanding and mining big data in the medical field, NLP is becoming more crucial. OBJECTIVE The goal of the research was to perform a systematic review on the use of NLP in medical research with the aim of understanding the global progress on NLP research outcomes, content, methods, and study groups involved. METHODS A systematic review was conducted using the PubMed database as a search platform. All published studies on the application of NLP in medicine (except biomedicine) during the 20 years between 1999 and 2018 were retrieved. The data obtained from these published studies were cleaned and structured. Excel (Microsoft Corp) and VOSviewer (Nees Jan van Eck and Ludo Waltman) were used to perform bibliometric analysis of publication trends, author orders, countries, institutions, collaboration relationships, research hot spots, diseases studied, and research methods. RESULTS A total of 3498 articles were obtained during initial screening, and 2336 articles were found to meet the study criteria after manual screening. The number of publications increased every year, with a significant growth after 2012 (number of publications ranged from 148 to a maximum of 302 annually). The United States has occupied the leading position since the inception of the field, with the largest number of articles published. The United States contributed to 63.01% (1472/2336) of all publications, followed by France (5.44%, 127/2336) and the United Kingdom (3.51%, 82/2336). The author with the largest number of articles published was Hongfang Liu (70), while Stéphane Meystre (17) and Hua Xu (33) published the largest number of articles as the first and corresponding authors. Among the first author's affiliation institution, Columbia University published the largest number of articles, accounting for 4.54% (106/2336) of the total. Specifically, approximately one-fifth (17.68%, 413/2336) of the articles involved research on specific diseases, and the subject areas primarily focused on mental illness (16.46%, 68/413), breast cancer (5.81%, 24/413), and pneumonia (4.12%, 17/413). CONCLUSIONS NLP is in a period of robust development in the medical field, with an average of approximately 100 publications annually. Electronic medical records were the most used research materials, but social media such as Twitter have become important research materials since 2015. Cancer (24.94%, 103/413) was the most common subject area in NLP-assisted medical research on diseases, with breast cancers (23.30%, 24/103) and lung cancers (14.56%, 15/103) accounting for the highest proportions of studies. Columbia University and the talents trained therein were the most active and prolific research forces on NLP in the medical field.
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Affiliation(s)
- Jing Wang
- School of Medical Informatics and Engineering, Southwest Medical University, Luzhou, China
| | - Huan Deng
- School of Medical Informatics and Engineering, Southwest Medical University, Luzhou, China
| | - Bangtao Liu
- School of Medical Informatics and Engineering, Southwest Medical University, Luzhou, China
| | - Anbin Hu
- School of Medical Informatics and Engineering, Southwest Medical University, Luzhou, China
| | - Jun Liang
- IT Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Lingye Fan
- Affiliated Hospital, Southwest Medical University, Luzhou, China
| | - Xu Zheng
- Center for Medical Informatics, Peking University, Beijing, China
| | - Tong Wang
- School of Public Health, Jilin University, Jilin, China
| | - Jianbo Lei
- School of Medical Informatics and Engineering, Southwest Medical University, Luzhou, China.,Center for Medical Informatics, Peking University, Beijing, China.,Institute of Medical Technology, Health Science Center, Peking University, Beijing, China
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The Korea Cancer Big Data Platform (K-CBP) for Cancer Research. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16132290. [PMID: 31261630 PMCID: PMC6651426 DOI: 10.3390/ijerph16132290] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Revised: 05/31/2019] [Accepted: 06/24/2019] [Indexed: 12/23/2022]
Abstract
Data warehousing is the most important technology to address recent advances in precision medicine. However, a generic clinical data warehouse does not address unstructured and insufficient data. In precision medicine, it is essential to develop a platform that can collect and utilize data. Data were collected from electronic medical records, genomic sequences, tumor biopsy specimens, and national cancer control initiative databases in the National Cancer Center (NCC), Korea. Data were de-identified and stored in a safe and independent space. Unstructured clinical data were standardized and incorporated into cancer registries and linked to cancer genome sequences and tumor biopsy specimens. Finally, national cancer control initiative data from the public domain were independently organized and linked to cancer registries. We constructed a system for integrating and providing various cancer data called the Korea Cancer Big Data Platform (K-CBP). Although the K-CBP could be used for cancer research, the legal and regulatory aspects of data distribution and usage need to be addressed first. Nonetheless, the system will continue collecting data from cancer-related resources that will hopefully facilitate precision-based research.
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