Association between Full Electronic Medical Record System Adoption and Drug Use: Antibiotics and Polypharmacy

Park, Young‐Taek; Kim, Donghwan; Park, Rae Woong; Atalag, Koray; Kwon, In Ho; Yoon, Dukyong; Choi, Mona

doi:10.4258/hir.2020.26.1.68

Cited by 10 publications

(4 citation statements)

References 32 publications

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“…Therefore, this study is meaningful because it used EMR data to investigate long-term clinical outcomes in PAD patients. Second, as the study data were collected from a tertiary hospital's EMRs, the generalizability may be limited; however, this tertiary hospital adopted a full EMR system in which rich clinical documents are stored electronically [31]. Finally, as this was a retrospective longitudinal study, we could not control other potential confounding variables during the follow-up period.…”

Section: Discussionmentioning

confidence: 99%

Major Adverse Events in Patients with Peripheral Artery Disease after Endovascular Revascularization: A Retrospective Study

Kim

Yang

et al. 2022

JCM

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Objective: For peripheral artery disease (PAD) patients, after endovascular revascularization, it is crucial to manage associated factors that can affect the risk of major adverse events. We aimed to investigate the associated factors of major adverse events in these patients. Materials and Methods: We conducted a retrospective longitudinal analysis using the electronic medical records from a tertiary hospital in Korea and included the data of 1263 patients. Eligible patients were categorized into four groups based on diabetes mellitus (DM) and regular exercise. The major adverse events included major adverse limb events and major adverse cardiovascular events. Major adverse events-free survival was assessed using the Kaplan–Meier method, and associated factors of major adverse events were analyzed using Cox proportional hazards analyses. Results: Kaplan–Meier survival curves showed that patients with DM and non-regular exercise had a shorter major adverse events-free survival. The Cox regression analysis showed that for patients with critical limb ischemia or chronic kidney disease, the risk of major adverse events increased, while group variables were not significant. Conclusion: Target management of patients with DM, critical limb ischemia, and chronic kidney disease is essential to reduce major adverse events after endovascular revascularization in patients with PAD.

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Section: Discussionmentioning

confidence: 99%

Major Adverse Events in Patients with Peripheral Artery Disease after Endovascular Revascularization: A Retrospective Study

Kim

Yang

et al. 2022

JCM

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“…Furthermore, ERMS can improve operational efficiency and support decision-making that can improve business-related outcomes. ERMS, if implemented with BDM, will create a special connection with users and production growth (Dong et al, 2021;Park et al, 2020;Saffady, 2021;.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Big Data Management on Organizational Performance in Organizations: The Role of Electronic Records Management System Potentiality

Hawash

Mukred

Mokhtar

et al. 2023

IJIKM

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Aim/Purpose: The use of digital technology, such as an electronic records management system (ERMS), has prompted widespread changes across organizations. The organization needs to support its operations with an automation system to improve production performance. This study investigates ERMS’s potentiality to enhance organizational performance in the oil and gas industry. Background: Oil and gas organizations generate enormous electronic records that lead to difficulties in managing them without any system or digitalization procedure. The need to use a system to manage big data and records affects information security and creates several problems. This study supports decision-makers in oil and gas organizations to use ERMS to enhance organizational performance. Methodology: We used a quantitative method by integrating the typical partial least squares (SEM-PLS) approach, including measurement items, respondents’ demographics, sampling and collection of data, and data analysis. The SEM-PLS approach uses a measurement and structural model assessment to analyze data. Contribution: This study contributes significantly to theory and practice by providing advancements in identity theory in the context of big data management and electronic records management. This study is a foundation for further research on the role of ERMS in operations performance and Big Data Management (BDM). This research makes a theoretical contribution by studying a theory-driven framework that may serve as an essential lens to evaluate the role of ERMS in performance and increase its potentiality in the future. This research also evaluated the combined impacts of general technology acceptance theory elements and identity theory in the context of ERMS to support data management. Findings: This study provides an empirically tested model that helps organizations to adopt ERMS based on the influence of big data management. The current study’s findings looked at the concerns of oil and gas organizations about integrating new technologies to support organizational performance. The results demonstrated that individual characteristics of users in oil and gas organizations, in conjunction with administrative features, are robust predictors of ERMS. The results show that ERMS potentiality significantly influences the organizational performance of oil and gas organizations. The research results fit the big ideas about how big data management and ERMS affect respondents to adopt new technologies. Recommendations for Practitioners: This study contributes significantly to the theory and practice of ERMS potentiality and BDM by developing and validating a new framework for adopting ERMS to support the performance and production of oil and gas organizations. The current study adds a new framework to identity theory in the context of ERMS and BDM. It increases the perceived benefits of using ERMS in protecting the credibility and authenticity of electronic records in oil and gas organizations. Recommendation for Researchers: This study serves as a foundation for future research into the function and influence of big data management on ERMS that support the organizational performance. Researchers can examine the framework of this study in other nations in the future, and they will be able to analyze this research framework to compare various results in other countries and expand ERMS generalizability and efficacy. Impact on Society: ERMS and its impact on BDM is still a developing field, and readers of this article can assist in gaining a better understanding of the literature’s dissemination of ERMS adoption in the oil and gas industry. This study presents an experimentally validated model of ERMS adoption with the effect of BDM in the oil and gas industry. Future Research: In the future, researchers may be able to examine the impact of BDM and user technology fit as critical factors in adopting ERMS by using different theories or locations. Furthermore, researchers may include the moderating impact of demographical parameters such as age, gender, wealth, and experience into this study model to make it even more robust and comprehensive. In addition, future research may examine the significant direct correlations between human traits, organizational features, and individual perceptions of BDM that are directly related to ERMS potentiality and operational performance in the future.

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“…Hospital management information systems are implemented for electronic medical record purposes that integrate information from pharmacies, radiology, and laboratories, thus providing access to information that presents a comprehensive picture of the patient's health, treatment, and background (Arvanitis and Loukis, 2016). SIM RS has capabilities that are increasingly integral to many work processes in health organizations and are proven to improve health services, reduce antibiotic use and make work easier (Ayaad et al, 2019;Park et al, 2020). Nevertheless, apart from the beneficial results regarding hospital driver's licenses and healthcare services for patients, the extensive integration of information systems in healthcare has also damaged the working conditions of healthcare professionals, especially doctors and nurses.…”

Section: Introductionmentioning

confidence: 99%

Early Detection of Health Problems through Artificial Intelligence (Ai) Technology in Hospital Information Management: A Literature Review Study

Cahyo

Astuti

2023

jmhs

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Early detection of health problems needs to be supported by optimal hospital service quality subsystems through an integrated Hospital Management Information System. Artificial intelligence (AI) as a modern technology has entered the mainstream of clinical medicine. Diagnostics has traditionally been one of the main areas of AI in medicine. AI will broadly transform diagnostic and predictive analysis of medical images in the coming years. Studies in the fields of pathology and dermatology have demonstrated the ability of AI to outperform human diagnostics in accurately detecting and classifying various types of cancer. Artificial intelligence technology in the health aspect is useful in disease diagnosis and can analyze medical images to identify certain diseases so that they are able to distinguish between benign and malignant diseases. AI can also help identify the risk of mental illness and identify the risk of suicide among patients with psychiatric disorders or among certain populations, such as prisoners and soldiers. This helps doctors quickly get disease information and provide a more accurate disease diagnosis, thereby saving time for disease treatment.

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Association between Full Electronic Medical Record System Adoption and Drug Use: Antibiotics and Polypharmacy

Cited by 10 publications

References 32 publications

Major Adverse Events in Patients with Peripheral Artery Disease after Endovascular Revascularization: A Retrospective Study

Major Adverse Events in Patients with Peripheral Artery Disease after Endovascular Revascularization: A Retrospective Study

The Influence of Big Data Management on Organizational Performance in Organizations: The Role of Electronic Records Management System Potentiality

Early Detection of Health Problems through Artificial Intelligence (Ai) Technology in Hospital Information Management: A Literature Review Study

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