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Comparison of the of Operative Treatment and Sclerotherapy Injection in the Management of Hemorrhoids: A Meta-Analysis of Randomized Controlled Trials Wiyardhani, Laras; Sander, Tara; Wibriansyah, Akbar
Jurnal Health Sains Vol. 6 No. 9 (2025): Journal Health Sains
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jhs.v6i9.2695

Abstract

Rubber-band ligation (RBL) and sclerotherapy are the two most widely used office-based interventions for symptomatic haemorrhoidal disease, yet their comparative benefits remain uncertain. This systematic review and meta-analysis evaluated the relative efficacy and safety of sclerotherapy versus operative treatments (primarily RBL and excisional procedures). The primary objective of this systematic review and meta-analysis was to evaluate the relative efficacy and safety of sclerotherapy versus operative treatments (primarily RBL and excisional procedures) in the management of hemorrhoidal disease. Treatment success was 78.2% in operative arms (701/896) versus 74.1% with sclerotherapy (665/897); pooled RR = 1.03 (95% CI 0.91–1.17; I² = 85%), indicating non-inferiority of sclerotherapy. Recurrence in two trials (n = 302) showed lower recurrence after sclerotherapy (12.9%) than after operative treatment (28.4%); RR = 2.22 (95% CI 1.37–3.58; I² = 0%). Pain in three trials (n = 335) reported a higher risk of significant pain following operative procedures (RR = 1.17, 95% CI 1.02–1.34; I² = 60%) and greater mean pain intensity (SMD = 0.96, 95% CI 0.22–1.71; I² = 89%). Sclerotherapy achieves comparable short-term symptom control to operative treatments while offering superior durability and a more favorable pain profile. Given its minimal invasiveness and ease of repetition, modern sclerotherapy should be considered a first-line option for grade I–III haemorrhoids. High between-study heterogeneity underscores the need for standardized protocols and longer follow-up.
Evaluation of The Effect of Completeness of Inpatient Medical Records on Patient Safety Incidents at Kendari City Hospital Sander, Tara; Sulistyowati, Yeny; Garnida, Aliefety Putu
Jurnal Health Sains Vol. 7 No. 2 (2026): Journal Health Sains
Publisher : Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/jhs.v7i2.2809

Abstract

Medical records are official documents that contain comprehensive information about a patient’s health condition, including medical history, examination results, diagnoses, medical procedures, and therapies provided. Incomplete medical records can hinder communication among healthcare professionals and increase the risk of patient safety incidents. This research aimed to evaluate the effect of medical record completeness on patient safety incidents at Kendari City General Hospital. The research employed a mixed-method approach with a population of 6,026 patients and a sample of 110 documents. The independent variable was medical record completeness, while the dependent variable was patient safety incidents. Data were collected through reviews of electronic medical records (EMR) and analyzed using multiple linear regression. The results showed that the completeness of inpatient medical records did not have a significant effect on patient safety incidents (regression coefficient = –0.036; p = 0.261). Authentication and digital signatures were the only indicators that significantly influenced patient safety incidents (B coefficient = –0.346; p = 0.000). These findings indicate that inpatient medical record completeness is not the sole factor contributing to patient safety incidents. In the short term, hospitals need to strengthen authentication procedures and conduct routine audits; in the medium term, integrating EMR technology with real-time authentication alerts and training on record completeness should be implemented; and in the long term, hospitals may adopt a fully integrated digital authentication system within EMR equipped with Artificial Intelligence (AI)-based automated verification.