Exposing Exposure: Enhancing Patient Safety through Automated Data Mining of Nuclear Medicine Reports for Quality Assurance and Organ Dose Monitoring

AbstractThe Fingolimod Patient Support Program (F-PSP) is an interprofessional specialty pharmacy service designed to ensure responsible use of fingolimod by promoting patient safety and medication adherence. This study aims to evaluate the safety and medication adherence of patients who joined the F-PSP between 2013 and 2016. Sociodemographic and medical characteristics, patient safety data (patient-reported symptoms, discontinuations due to adverse events (AEs), repeated first-dose monitoring), and medication adherence (implementation, persistence, reasons for discontinuation, influence of covariates, barriers and facilitators) were described. Sixty-seven patients joined the F-PSP. Patients reported a high frequency of symptoms. Due to AEs, 7 patients discontinued fingolimod, 3 took therapeutic breaks, and 1 reduced the regimen temporarily. Three patients repeated the first-dose monitoring. Patients had a high medication adherence over the 18-month analysis period: implementation decreased from 98.8 to 93.7%, and fingolimod persistence was 83.2% at 18 months. The patients’ level of education, professional situation, and living with child(ren) influenced implementation. Patients reported more facilitators of medication adherence than barriers. The F-PSP seems valuable for supporting individual patients (ensuring responsible use of fingolimod and inviting patients for shared-decision making) and public health (indirectly gathering real-world evidence).

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Computed Radiography Dose Data Mining and Surveillance as an Ongoing Quality Assurance Improvement Process

American Journal of Roentgenology ◽

10.2214/ajr.06.1232 ◽

2007 ◽

Vol 189 (1) ◽

pp. 7-11 ◽

Cited By ~ 15

Author(s):

Brent K. Stewart ◽

Kalpana M. Kanal ◽

James R. Perdue ◽

Frederick A. Mann

Keyword(s):

Data Mining ◽

Quality Assurance ◽

Computed Radiography ◽

Improvement Process ◽

Ongoing Quality Assurance

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Quality assurance and patient safety protocols for breast and gynecologic pathology in an Academic Women’s Hospital

Applied Cancer Research ◽

10.1186/s41241-016-0002-8 ◽

2016 ◽

Vol 36 (1) ◽

Author(s):

David J. Dabbs ◽

Catherine T. Stoos ◽

Abbie Mallon

Keyword(s):

Quality Assurance ◽

Patient Safety

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Effect of I-131 Radioisotope Activities on Organ Dose Used in Nuclear Medicine

Afyon Kocatepe Üniversitesi Uluslararası Mühendislik Teknolojileri ve Uygulamalı Bilimler Dergisi ◽

10.53448/akuumubd.986161 ◽

2021 ◽

Vol 4 (2) ◽

pp. 87-92

Author(s):

Timur KOCA ◽

İsmail Hakkı SARPÜN ◽

Cengiz ÖZSOY ◽

Vedat AYDIN ◽

Selcan ŞAHİN

Keyword(s):

Nuclear Medicine ◽

Organ Dose

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IS PATIENT SAFETY AT THE HEART OF MEDICAL EDUCATION IN INDONESIA? REFLECTION ON THE IMPACT OF THE NATIONAL EXAMINATION

Jurnal Pendidikan Kedokteran Indonesia The Indonesian Journal of Medical Education ◽

10.22146/jpki.48759 ◽

2019 ◽

Vol 8 (3) ◽

pp. 153

Author(s):

Rachmadya Nur Hidayah

Keyword(s):

Medical Education ◽

Quality Assurance ◽

Patient Safety ◽

Focus Groups ◽

Patient Care ◽

Medical Schools ◽

Theory Approach ◽

High Stakes ◽

Teachers And Students ◽

The Impact

ABSTRACT Background: National examinations in Indonesia (UKMPPD) has been implemented since 2007 as a quality assurance method for medical graduates and medical schools. The impact of UKMPPD has been studied since then, where one of the consequences were related to how it affected medical education and curricula. This study explored the consequences of UKMPPD, focusing on how the students, teachers, and medical schools’ leaders relate the examination with patient care. This study aimed to explore the impact of UKMPPD on medical education, which focusing on the issue of patient safety. Methods: This study was part of a doctoral project, using a qualitative method with a modified grounded theory approach. The perspectives of multiple stakeholders on the impact of the UKMPPD were explored using interview and focus groups. Interviews were conducted with medical schools’ representatives (vice deans/ programme directors), while focus groups were conducted with teachers and students. A sampling framework was used by considering the characteristics of Indonesian medical schools based on region, accreditation status, and ownership (public/ private). Data was analysed using open coding and thematic framework as part of the iterative process. Results: The UKMPPD affected how the stakeholders viewed this high-stakes examination and the education delivered in their medical schools. One of the consequences revealed how stakeholders viewed the UKMPPD and its impact on patient care. Participants viewed the UKMPPD as a method of preparation for graduates’ real clinical practice. The lack of reference for patient safety as the impact of the UKMPPD in this study showed that there were missing links in how stakeholders perceived the examination as part of quality assurance in health care. Conclusion: The UKMPPD as a high-stakes examination has a powerful impact in changing educational policy and programmes in Indonesia. However, in Indonesia, the examination brought in the reflection on how the “patient” element was lacking from medical education. This research offers an insight on the concept of patient safety in Indonesia and how the stakeholders could approach the issue. Keywords: UKMPPD, national licensing examination, impact, competence, patient safety, curriculum

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Combined data mining techniques based patient data outlier detection for healthcare safety

International Journal of Intelligent Computing and Cybernetics ◽

10.1108/ijicc-07-2015-0024 ◽

2016 ◽

Vol 9 (1) ◽

pp. 42-68 ◽

Cited By ~ 10

Author(s):

Gebeyehu Belay Gebremeskel ◽

Chai Yi ◽

Zhongshi He ◽

Dawit Haile

Keyword(s):

Data Mining ◽

Decision Making ◽

Patient Safety ◽

Outlier Detection ◽

Clinical Data ◽

Clinical Decision Making ◽

Clinical Decision ◽

Healthcare Services ◽

Content Type ◽

Outliers Detection

Purpose – Among the growing number of data mining (DM) techniques, outlier detection has gained importance in many applications and also attracted much attention in recent times. In the past, outlier detection researched papers appeared in a safety care that can view as searching for the needles in the haystack. However, outliers are not always erroneous. Therefore, the purpose of this paper is to investigate the role of outliers in healthcare services in general and patient safety care, in particular. Design/methodology/approach – It is a combined DM (clustering and the nearest neighbor) technique for outliers’ detection, which provides a clear understanding and meaningful insights to visualize the data behaviors for healthcare safety. The outcomes or the knowledge implicit is vitally essential to a proper clinical decision-making process. The method is important to the semantic, and the novel tactic of patients’ events and situations prove that play a significant role in the process of patient care safety and medications. Findings – The outcomes of the paper is discussing a novel and integrated methodology, which can be inferring for different biological data analysis. It is discussed as integrated DM techniques to optimize its performance in the field of health and medical science. It is an integrated method of outliers detection that can be extending for searching valuable information and knowledge implicit based on selected patient factors. Based on these facts, outliers are detected as clusters and point events, and novel ideas proposed to empower clinical services in consideration of customers’ satisfactions. It is also essential to be a baseline for further healthcare strategic development and research works. Research limitations/implications – This paper mainly focussed on outliers detections. Outlier isolation that are essential to investigate the reason how it happened and communications how to mitigate it did not touch. Therefore, the research can be extended more about the hierarchy of patient problems. Originality/value – DM is a dynamic and successful gateway for discovering useful knowledge for enhancing healthcare performances and patient safety. Clinical data based outlier detection is a basic task to achieve healthcare strategy. Therefore, in this paper, the authors focussed on combined DM techniques for a deep analysis of clinical data, which provide an optimal level of clinical decision-making processes. Proper clinical decisions can obtain in terms of attributes selections that important to know the influential factors or parameters of healthcare services. Therefore, using integrated clustering and nearest neighbors techniques give more acceptable searched such complex data outliers, which could be fundamental to further analysis of healthcare and patient safety situational analysis.

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Digital Marketing and E-Tailing Technological Innovations

Advances in Finance, Accounting, and Economics - Avatar-Based Models, Tools, and Innovation in the Digital Economy ◽

10.4018/978-1-7998-1104-6.ch003 ◽

2020 ◽

pp. 37-65

Author(s):

Alan D. Smith

Keyword(s):

Data Mining ◽

Quality Assurance ◽

Big Data ◽

Information Retrieval ◽

Customer Service ◽

Middle Level ◽

Purchase Decision ◽

Product Reviews ◽

Privacy Concerns ◽

Web Presence

In an age of public mistrust of the most basic institutions, businesses are not exempted. Essentially all e-tailers want to deliver personalized and real-time communications to customers that are tailored to their interests and preferences, and are based on big data mining that customers will value over privacy concerns. This is an era in which e-commerce retailers continue to dominate the marketplace and it is integral that consumers are able to trust the manufacturers, retailers, and the service/product reviews that they read online. Such trust is particularly important if their ultimate purchase decision is a successful one. A survey of middle-level managers was analyzed to identity the basic elements: e-personalization, namely online purchasing behaviors, personalized communications, information-retrieval services, degree of personal web presence, quality assurance of customer service, and the promotion of customization services. These elements were found to be conceptually and statistically related to retailer benefits of increased buying and customer loyalty.

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