Building a National Electronic Medical Record Exchange System – Experiences in Taiwan

Li, Yu-Chuan; Yen, Ju‐Chuan; Chiu, Wen-Ta; Jian, Wen-Shan; Syed-Abdul, Shabbir; Hsu, Min‐Huei

doi:10.1016/j.cmpb.2015.04.013

Cited by 56 publications

(46 citation statements)

References 28 publications

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“…The use of EMR in hospitals has been promoted by Taiwan's government since 2000 and has laid a great foundation for the electronic exchange of health care data. 25 To our knowledge, CGRD is the first and largest EMR database covering multiple medical institutions in Taiwan and could serve as a model for other hospitals to integrate their data. We believe that collaboration between CGRD and EMR databases from other hospitals will provide an opportunity to establish a large-scale epidemiological research system in Taiwan.…”

Section: Future Opportunities Of Cgrdmentioning

confidence: 99%

The Chang Gung Research Database—A multi‐institutional electronic medical records database for real‐world epidemiological studies in Taiwan

Shao

Chan

Yang

et al. 2019

Pharmacoepidemiology and Drug

244

222

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Purpose The Chang Gung Research Database (CGRD), the largest multi‐institutional electronic medical records (EMR) collection in Taiwan, provides good access for researchers to efficiently use the standardized patient‐level data. This study evaluates the capacity and representativeness of the CGRD to promote secondary use of EMR data for clinical research with more accurate estimates. Methods The National Health Insurance Research Database (NHIRD) which covers over 99.9% of the Taiwanese population served as the comparator in this study. We compare the data components of the CGRD with the NHIRD, including records for health care facilities, patients, diagnoses, drugs, and procedures. Using the chi‐square test, we compared the distributions of age categories and sex of patients, and the rates of their health conditions between NHIRD and CGRD based on the year 2015. Results The CGRD contains more clinical information such as pathological and laboratory results than the NHIRD. The CGRD includes 6.1% of outpatients and 10.2% of hospitalized patients from the NHIRD. We found the CGRD includes more elderly outpatients (23.5% vs 12.5%) and pediatric inpatients (19.7% vs 14.4%) compared with the NHIRD. We found patients' sex distributions were similar between CGRD and NHIRD, but coverage rates of severe conditions, such as cancer, were higher than other health conditions in CGRD. Conclusions The CGRD could serve as the basis for accurate estimates in medical studies. However, researchers should pay special attention to selection biases since patients' characteristics from CGRD differ from those of the national database.

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Section: Future Opportunities Of Cgrdmentioning

confidence: 99%

The Chang Gung Research Database—A multi‐institutional electronic medical records database for real‐world epidemiological studies in Taiwan

Shao

Chan

Yang

et al. 2019

Pharmacoepidemiology and Drug

244

222

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“…Electronic medical records (EMRs) have been developed in Taiwan for more than a decade [1]. They have been implemented in most of the larger medical institutions to store information about encounters and events between patients and healthcare systems [2]. The implementation of EMRs not only enables large-scale storage and collection of patient data but also makes the exchange of healthcare information between healthcare facilities possible through the Electronic Medical Record Exchange Center [2].…”

Section: Introductionmentioning

confidence: 99%

A Natural Language Processing Approach to Automated Highlighting of New Information in Clinical Notes

Chao

Hung

et al. 2020

Applied Sciences

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Electronic medical records (EMRs) have been used extensively in most medical institutions for more than a decade in Taiwan. However, information overload associated with rapid accumulation of large amounts of clinical narratives has threatened the effective use of EMRs. This situation is further worsened by the use of “copying and pasting”, leading to lots of redundant information in clinical notes. This study aimed to apply natural language processing techniques to address this problem. New information in longitudinal clinical notes was identified based on a bigram language model. The accuracy of automated identification of new information was evaluated using expert annotations as the reference standard. A two-stage cross-over user experiment was conducted to evaluate the impact of highlighting of new information on task demands, task performance, and perceived workload. The automated method identified new information with an F1 score of 0.833. The user experiment found a significant decrease in perceived workload associated with a significantly higher task performance. In conclusion, automated identification of new information in clinical notes is feasible and practical. Highlighting of new information enables healthcare professionals to grasp key information from clinical notes with less perceived workload.

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“…Even though they are developing during the last half century, their acceptance from the potential users did not always go smoothly (2). Globally, the trend of acceptance of medical information systems and their efficient use starts mid nineties (3), while the final expansion was actually during the first decade of the 21 st century (4). Massive use of the medical information systems within the primary healthcare of the Republic of Serbia starts from 2010-2011 with the great support of the Ministry of Health.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Level of Use and Accepta Nce of the Medical Information System in Primary Health Car E

Rajkovic¹,

Janković²,

Milenković³

et al. 2018

AMM

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This paper presents the analysis of use and acceptance of the medical information system (MIS) within the primary healthcare. Analysis is mostly based on data from the Health Care Center Niš, although the conclusion was made on data from a dozen health care centers which use the medical information system MEDIS.NET developed within the Laboratory for Medical Informatics at the Faculty of Electronic Engineering in Niš. Analysis of the use of MIS is based on calculating the percentage of successfully entered records of visits, provided medical services, recipes, referral letters and physical examinations. In the context of the analysis of the use of MIS, successfully entered medical service is actually the service that was not changed or deleted later. Results of this analysis are significant for further technical development of the medical information system, and support the identification of these functionalities that are hardly accepted by the end-users and should be further developed. The acceptance of MIS is analyzed in the light of the technology acceptance model. Registration of provided services and keeping the record of physical examinations are taken as representative functionalities. Registration of provided services has been observed as a functionality that is accepted by the users due to simplicity of use (perceived ease of use), while the registration of physical examinations is observed as functionality is presumed to be accepted by the users as useful (perceived usefulness). For the functionalities with the expected acceptance based on the simplicity of use, the rate of correct data input is over 90% in each of the category. However, the rate of correct data inputs for visits and provided services is more than 99%. This is very significant having in mind the fact that these functionalities are often used and the high rate of incorrect inputs would slow down the work of doctors. On the other hand, the percentage of use of special functionalities for input of physical examinations varies considerably. Specially designed functionality for the most common physical examinations of children is used in more than two thirds of cases (sometimes more than 97%), while for the registration of adult's physical examinations the percentage is lower than 20%. Since the users could input data on physical examinations using the form for visit input, as well as with special form, they will probably use the other option only when the frequency of use is high enough or when the improved functionality of the specialized form provides improved system performances. Under users of MIS we consider the medical staff which uses MIS functionalities in accordance with their duties and privileges (doctors, nurses, medical technicians, etc.). Acta Medica Medianae 2018;57(4):122-136.

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Building a National Electronic Medical Record Exchange System – Experiences in Taiwan

Cited by 56 publications

References 28 publications

The Chang Gung Research Database—A multi‐institutional electronic medical records database for real‐world epidemiological studies in Taiwan

The Chang Gung Research Database—A multi‐institutional electronic medical records database for real‐world epidemiological studies in Taiwan

A Natural Language Processing Approach to Automated Highlighting of New Information in Clinical Notes

Analysis of the Level of Use and Accepta Nce of the Medical Information System in Primary Health Car E

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