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Medicor : Journal of Health Informatics and Health Policy
Published by PT Penerbit Ilmiah Indonesia
ISSN : -     EISSN : 30309166     DOI : https://doi.org/10.61978/medicor
Core Subject : Health,
Health Professions Public Health
Medicor : Journal of Health Informatics and Health Policy with ISSN Number 3030-9166 (Online) published by Indonesian Scientific Publication, published original scholarly papers across the whole spectrum of Health Informatics and Health Policy Research. The journal attempts to assist in the understanding of the present and potential ability Health Informatics and Health Policy Research
Arjuna Subject : Kedokteran - Informatika Kesehatan
Articles 54 Documents
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Willing but Not Ready? Documentation Quality as a Barrier to Artificial Intelligence Adoption in Nigerian Healthcare Chukwuemeka, Prince; Ime, Aaron; Obodo, Prosper; Ochimana, David; Chukwu, Josephate
Medicor : Journal of Health Informatics and Health Policy Vol. 4 No. 2 (2026): April 2026
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/medicor.v4i2.1306

Abstract

Nigeria has demonstrated a commitment towards nationwide integration of artificial intelligence products into healthcare. However, concerns remain regarding feasibility due to historic challenges with data quality. Currently, there are no guidelines for scrotal ultrasound documentation—a prerequisite for generating high-quality data, and robust models. This study was carried out to assess routine scrotal ultrasound documentation quality as a proxy measure for AI readiness in Nigerian healthcare. To achieve this, we conducted a retrospective, descriptive cross-sectional study of scrotal ultrasonographic reports retrieved from health institutions in South Eastern Nigeria. Three hundred reports, generated between 2020 and 2025 were randomly selected and assessed for documentation quality across four domains using a de-novo structured checklist. Overall and domain specific compliance scores were then computed. Overall documentation quality was suboptimal, with a mean compliance score of 56·41 ± 8·45%. Removing the demographic elements of the reports resulted in a notable decline in mean compliance scores (49·05%), suggesting that overall completeness is inflated by administrative fields rather than clinically informative content. Tertiary institutions demonstrated higher compliance than secondary institutions (61·72% vs 53·76%; 95% CI: 6·24–9·75), though deficiencies persisted across all domains. Documentation quality was highest in the demographic domain. Our findings suggest that current documentation practices may undermine robust model performance and equitable deployment. Addressing this through standardized reporting and regulatory alignments are prerequisites for producing usable, trustworthy evidence in the digital health era.
The Effect of Providing Family Center Care Education Using Booklets on the Knowledge Level of NICU Nurses in Hospitals Dewi, Tungga; Oktavia, Alfonsa Reni; Fitriany, Heny; Ernawaty, Ety; Octo, Vania; Riantini, Sus Dwi; Buka, Sisilia Sisilia Prima Yanuaria
Medicor : Journal of Health Informatics and Health Policy Vol. 4 No. 1 (2026): January 2026
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/medicor.v4i1.1226

Abstract

Family-Centered Care (FCC) is an important approach to care in the Neonatal Intensive Care Unit (NICU) because it actively involves families in infant care. However, the implementation of FCC still requires increased understanding among nursing staff. This study aimed to determine the effect of providing family-centered care education using a booklet on the knowledge level of NICU nurses in a hospital. Preliminary study showed that only 40% of nurses at MHJS hospital understood the concept of Family-Centered Care. The aim was to assess the effectiveness of FCC education using booklet media on the level of knowledge of NICU nurses at MHJS. This study applied a quasi-experimental design with measurements before (pre-test) and after (post-test) the intervention. Eighteen NICU nurses were included using a total sampling technique. The intervention consisted of Family-Centered Care (FCC) education delivered through a booklet. Data were collected in January 2021 using a 15-question questionnaire to assess nurses' knowledge before and after the intervention. Before completing the questionnaire, researchers provided an explanation and obtained informed consent from all respondents. The findings demonstrate that the average pre-test score was 22.6 out of 30, while the post-test score increased to 26.5 out of 30. Statistical analysis showed a significant increase in knowledge after the intervention, with a statistically significant increase in knowledge Asymp. Sig. (2-tailed); p value = 0.000 (Wilcoxon Signed Rank). Using the booklet media in FCC education significantly increased the knowledge of NICU nurses.
Data-Driven Approaches to Fraud Detection in Health Insurance Claims: A Systematic Review of Medical and Pharmaceutical Services Rukayah, Sri; Kristina, Susi Ari
Medicor : Journal of Health Informatics and Health Policy Vol. 4 No. 2 (2026): April 2026
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/medicor.v4i2.1352

Abstract

Fraud in health insurance claims continues to impose significant financial and operational burdens on healthcare systems, especially as the volume and complexity of claims increase. Conventional rule-based detection mechanisms, although widely used, have limited adaptability to evolving fraud patterns and high-dimensional data environments. This limitation has driven a shift toward data-driven analytical approaches capable of identifying suspicious patterns more effectively. This systematic review synthesizes peer-reviewed, open-access studies published between 2020 and 2025 that applied rule-based, supervised, unsupervised, or hybrid methods for fraud detection in health insurance claims. A comprehensive search across major databases yielded fourteen eligible studies representing diverse systems, datasets, and methodological designs. The findings indicate a clear transition from traditional rule-based systems to machine learning approaches, particularly in addressing challenges such as label scarcity, class imbalance, and complex fraud patterns. Most studies focused on integrated medical claims, where pharmaceutical fraud was embedded rather than analyzed independently, highlighting a gap in service-specific research. Significant heterogeneity was observed in fraud definitions, preprocessing techniques, labeling strategies, and evaluation metrics, limiting cross-study comparability and emphasizing the need for greater methodological transparency. Across the literature, data-driven approaches are consistently positioned as decision-support tools rather than definitive solutions, reinforcing their role in complementing expert judgment and regulatory oversight. Overall, effective implementation requires context-aware design, reliable labeling, and rigorous real-world validation. Future research should prioritize domain-specific analyses, particularly in pharmaceutical fraud, and improve transparency to support scalable and responsible deployment.
Longitudinal Diagnostic Reassessment of Schizoaffective Disorder in Chronic Psychosis: A Case Report Putra, Tegar Narindra; Algristian, Hafid; Huda, Miftakhul
Medicor : Journal of Health Informatics and Health Policy Vol. 4 No. 2 (2026): April 2026
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/medicor.v4i2.1364

Abstract

Differentiating schizophrenia from schizoaffective disorder remains a significant diagnostic challenge due to substantial symptom overlap and reliance on cross-sectional assessment. This case illustrates how systematic longitudinal reconstruction of mood symptom trajectories supported diagnostic revision after prolonged treatment under an initial schizophrenia diagnosis. A descriptive clinical case approach was employed, involving comprehensive patient interview, collateral family interview, longitudinal symptom mapping, and reassessment based on DSM-5-TR criteria. The patient was a 33-year-old woman with a 13-year history of chronic psychosis initially diagnosed as paranoid schizophrenia. Retrospective reconstruction identified five recurrent major depressive episodes lasting approximately 6–12 months each, accounting for an estimated 6–7 years of the illness course. In addition, at least one documented period of persistent psychosis lasting more than two weeks occurred in the absence of mood symptoms, fulfilling DSM-5-TR criteria for schizoaffective disorder, depressive type. Following diagnostic revision, antidepressant augmentation and structured psychosocial intervention were initiated. At three-month follow-up, depressive symptoms decreased, passive suicidal ideation resolved, and functional status improved as measured by the Personal and Social Performance (PSP) scale (from 40 to 60), with no rehospitalization. This case underscores the importance of longitudinal assessment in chronic psychosis and highlights its implications for diagnostic accuracy and treatment planning.

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