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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 4 Documents
 1 
Search results for , issue "Vol. 4 No. 2 (2026): April 2026" : 4 Documents clear
Anxiolytic and Antidepressant Properties of Alprazolam in Generalized Anxiety Disorder: A Systematic Literature Review Wijaya , Afira Febriani Surya; Algristian, Hafid; Suwarti , Ariyani Sri
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.v4i2.1174

Abstract

Generalized Anxiety Disorder (GAD) is a highly persistent condition characterized by excessive worry, impaired functioning, and frequent comorbidity with depressive symptoms. Although first-line treatments such as SSRIs and SNRIs are effective, their delayed therapeutic onset and early-treatment anxiogenic effects often lead to poor adherence and treatment discontinuation. This systematic review evaluates the short-term efficacy, safety, and neurobiological mechanisms of alprazolam as a rapid-acting therapeutic option for adults with GAD. Eight studies published between 2011 and 2024—comprising randomized trials, systematic reviews, cohort studies, and neuroimaging investigations—met inclusion criteria. Across clinical trials, alprazolam demonstrated consistent and clinically meaningful reductions in anxiety symptoms within days of initiation, supporting its role as a fast-onset anxiolytic agent. Neurobiological findings showed decreased amygdala hyper reactivity and enhanced prefrontal regulatory activity following alprazolam administration, suggesting mechanisms that align with its rapid clinical effects and potential secondary mood benefits. Adverse events were generally mild, including sedation and psychomotor slowing, and withdrawal symptoms were uncommon when alprazolam was prescribed short-term with supervised tapering. However, the evidence base remains limited by short follow-up periods, small mechanistic samples, and a lack of robust long-term comparative studies. Overall, the findings indicate that alprazolam may serve as a useful short-term adjunct during periods requiring rapid symptom stabilization, particularly when initiating antidepressant therapy. Further research is needed to clarify its long-term safety, functional outcomes, and optimal integration into contemporary treatment pathways.
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.
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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