Objective: Awareness of the importance of social security systems continues to grow in Indonesia, as mandated by the amendment of the 1945 Indonesian Constitution Article 34 paragraph 2, which states the obligation of the Indonesian government to develop and implement a social security system for all Indonesian people. This study aims to evaluate the effectiveness of applying failure modes and effects analysis (FMEA) in managing inpatient medical records at the Dr. M. Djamil Padang Central General Hospital.
Material Methods: This is a comparative research study that uses a retrospective approach and compares the data between 2017 and 2018 inpatient National Health Insurance (NHI) patient medical records. Study samples include randomly selected 24,005 files.
Results: The results showed a decrease in problematic claims by 13 percent and an increase in receipt of claims paid by 87 percent. There is a significant difference between the data in 2017 and 2018 in problematic claim decrease (p=0.000) and claim acceptance increase (p=0.000).
Discussion: It was found that the redesign process of the formation of hospital claims will make hospitals more organized, precise, effective, and efficient, therefore positively impacting hospital income. In addition, the redesign was carried out because of the large number of Social Security Administrator for Health patients; thus, it greatly affected hospital income.
Implication For Health Policies: The FMEA medical record flow process is very effective and can thus be implemented in hospitals.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9335167 | PMC |
BioData Min
January 2025
Fondazione Bruno Kessler, Trento, Italy.
Biomedical datasets are the mainstays of computational biology and health informatics projects, and can be found on multiple data platforms online or obtained from wet-lab biologists and physicians. The quality and the trustworthiness of these datasets, however, can sometimes be poor, producing bad results in turn, which can harm patients and data subjects. To address this problem, policy-makers, researchers, and consortia have proposed diverse regulations, guidelines, and scores to assess the quality and increase the reliability of datasets.
View Article and Find Full Text PDFBMC Med Educ
January 2025
The First Clinical Medicine School of Guangdong Pharmaceutical University, Guangdong, People's Republic of China.
Objective: This study examines a novel teaching model that integrates the development and use of a Medical Cloud Dictionary with project-based learning (PBL). We investigate whether this integrated approach improves teaching effectiveness, enhances student learning outcomes, and reduces teaching pressure compared to traditional PBL.
Methods: One hundred student volunteers were randomly assigned to an experimental group (n = 50) and a control group (n = 50).
BMC Geriatr
January 2025
Graduate Institute of Clinical Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Rd., Zhongzheng Dist., Taipei, 100025, Taiwan.
Background: To identify cardiovascular (CV) risk factors in Asian elderly aged 75 years and older and subsequently develop and validate a sex-specific five-year CV risk assessment tool for this population.
Methods: This study included 12,174 patients aged ≥ 75 years without a prior history of cardiovascular disease at a single hospital in Taiwan. Electronic health records were linked to the National Health Insurance Research Database and the National Death Registry to ensure comprehensive health information.
BMC Bioinformatics
January 2025
Centro de Salud Retiro, Hospital Universitario Gregorio Marañon, C/Lope de Rueda, 43, 28009, Madrid, Spain.
Background: Natural language processing (NLP) enables the extraction of information embedded within unstructured texts, such as clinical case reports and trial eligibility criteria. By identifying relevant medical concepts, NLP facilitates the generation of structured and actionable data, supporting complex tasks like cohort identification and the analysis of clinical records. To accomplish those tasks, we introduce a deep learning-based and lexicon-based named entity recognition (NER) tool for texts in Spanish.
View Article and Find Full Text PDFKorean J Ophthalmol
January 2025
Department of Ophthalmology, Seoul National University Bundang Hospital, Seongnam, Korea.
Purpose: To evaluate the accuracy of toric intraocular lens (IOL) axis prediction between two preoperative measurement devices: the optical biometry (IOLMaster 500 or 700) and the dual Scheimpflug topography (Galilei G4).
Methods: Medical records of 64 eyes from 44 patients who underwent phacoemulsification and posterior chamber toric IOL (Zeiss AT TORBI 709M) implantation between July 2017 and January 2022 were reviewed. All patients underwent preoperative evaluation by optical biometry (IOLMaster 500 or IOLMaster 700) and Galilei G4.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!