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All Journal Jurnal Epidemiologi Kesehatan Komunitas Jurnal Pendidikan Kedokteran Indonesia: The Indonesian Journal of Medical Education
Anis Fuad
Universitas Gadjah Mada
Health Professions Medicine & Pharmacology Public Health

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DEVELOPMENT OF MOBILE ECG APPLICATION TO IMPROVE ECG INTERPRETATION SKILLS OF GENERAL PRACTITIONERS AND MEDICAL STUDENTS Rizki Amalia Gumilang; Anis Fuad; Vita Arfiana Nurul Fatimah; Shofuro Hasana; Orisativa Kokasih; Putrika Prastuti Ratna Gharini
Jurnal Pendidikan Kedokteran Indonesia: The Indonesian Journal of Medical Education Vol 10, No 3 (2021): November
Publisher : Asosiasi Institusi Pendidikan Kedokteran Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jpki.62977

Abstract

ABSTRACT Background: Electrocardiogram (ECG) has become a crucial examination in the management of cardiac emergencies. Accordingly, improvement of ECG interpretation skills is mandatory for general practitioners as the front-liners in emergency cases. The Mobile ECG application was developed as mobile learning media to facilitate continuing improvement of ECG interpretation skills.Aims: This study aimed to investigate the impact of the Mobile ECG application toward ECG interpretation skills of general practitioners and medical students and evaluate its usability.Methods: A pilot quasi-experimental study was conducted in a 1-week timeframe using webinar and the Mobile ECG application. Subjects were recruited through consecutive sampling. They met the following criteria: 1) registered as general practitioners or medical students, 2) completed the basic ECG pre and post-tests, and 3) agreed to participate in the study. The Mobile ECG is a web-based application which consists of modules, quizzes, and gallery of ECG interpretations. Pre and post-test analysis and system usability scale (SUS) questionnaire were used to evaluate the impact and usability of the application.Results: A total of 252 subjects were recruited and 80.2% were general practitioners. There was a significant increase in post-test scores compared to pre-test (p=0.000) for all subjects. General practitioners significantly gained more score increment than medical students (1.08 vs 0.16, p=0.001). Based on the SUS score of 67.5, the application was marginally accepted by the users.Conclusion: To conclude, the implementation of the Mobile ECG application did improve basic ECG interpretation skills. According to the SUS score, this application still needs improvement.
Mengukur Perilaku Manusia dalam Skala Besar dan Secara Real-time: Studi Kasus Pola Mobilitas Penduduk dan Fase Awal Pandemi COVID-19 di Indonesia Aditya Lia Ramadona; Risalia Reni Arisanti; Anis Fuad; Muhammad Ali Imron; Citra Indriani; Riris Andono Ahmad
Jurnal Epidemiologi Kesehatan Komunitas Vol 8, No 2 : Agustus 2023
Publisher : Master of Epidemiology, School of Postgraduate Studies, Diponegoro University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jekk.v8i2.16646

Abstract

Background: Good decisions in policy-making rely on acquiring the best possible understanding at the fast pace of what is happening and what might happen next in the population. Immediate measurements and predictions of disease spread would help authorities take necessary action to mitigate the rapid geographical spread of potential emerging infectious diseases. Unfortunately, measuring human behavior in nearly real-time, specifically at a large scale, has been labor-intensive, time-consuming, and expensive. Consequently, measurements are often unfeasible or delayed in developing in-time policy decisions. The increasing use of online services such as Twitter generates vast volumes and varieties of data, often available at high speed. These datasets might provide the opportunity to obtain immediate measurements of human behavior. Here we describe how the patterns of population mobility can be associated with the number of COVID-19 cases and, subsequently, could be used to simulate the potential path of disease spreading.Methods: Our analysis of country-scale population mobility networks is based on a proxy network from geotagged Twitter data, which we incorporated into a model to reproduce the spatial spread of the early phase COVID-19 pandemic in Indonesia. We used aggregated province-level mobility data from January through December 2019 for the baseline mobility patterns from DKI Jakarta as the origin of the 33 provinces' destinations in Indonesia.Result: We found that population mobility patterns explain 62 percent of the variation in the occurrence of COVID-19 cases in the early phases of the pandemic. In addition, we confirm that online services have the potential to measure human behavior in nearly real time.Conclusion: We believe that our work contributes to previous research by developing a scalable early warning system for public health decision-makers in charge of developing mitigation policies for the potential spread of emerging infectious diseases.
Co-Authors Aditya Lia Ramadona Gharini, Putrika Prastuti Ratna Gumilang, Rizki Amalia Muhammad Ali Imron Orisativa Kokasih Riris Andono Ahmad Risalia Reni Arisanti Shofuro Hasana Vita Arfiana Nurul Fatimah