Taiping Hospital, formerly known as Yong Wah Hospital was one of the first hospitals established in Malaysia. Located at Jalan Taming Sari (Main Road) near the commercial town centre, it is one of the biggest hospitals in Malaysia and is the second biggest in the State of Perak. The hospital is strategically situated 80 km from Ipoh and 85 km from Penang and was able to serve the northern states of Malaysia.
The Malaysian public healthcare system is under growing strain, which is driven by an aging population and the rising burden of chronic non-communicable diseases (NCDs). These shifts have placed added pressure on hospitals, particularly in handling inpatient discharges. To respond to this challenge, the study set out to build a machine learning-based forecasting model that can predict discharge volumes. Hospital Taiping, one of the key government hospitals in northern Malaysia, was selected as the case study. Monthly inpatient discharge data from 2019 to 2023 formed the foundation for building predictive models. To strengthen the dataset, additional temporal features were engineered, including lagged discharge counts, rolling averages and seasonal indicators. Three machine learning models, namely Random Forest (RF), XGBoost and Support Vector Regression (SVR), were then trained and fine-tuned through Bayesian Optimization. Model performance was evaluated using coefficient of determination (R²), Root Mean Square Error (RMSE), Mean Absolute Scaled Error (MASE) and Mean Absolute Percentage Error (MAPE). The best-performing model was prospectively validated with actual discharge data from 2024. The Random Forest model demonstrated the lowest RMSE of 177.85, a MAPE of 3.23% and the highest R² of 0.43. Prospective validation using 2024 data confirmed its robustness in forecasting inpatient discharges. The study developed and validated a machine learning model to forecast inpatient discharge volumes in government hospitals across the Northern Region of Malaysia. It also contributes to both methodology and practical application by providing a forecasting framework that supports more informed hospital planning and resource management.
BACKGROUND AND AIM:Proton pump inhibitors (PPIs) are integral to managing many gastrointestinal conditions. However, the prevalent inappropriate PPI prescription across Southeast Asia (SEA) is concerning. Given the absence of locally tailored recommendations to inform clinical practice, this consensus document aims to provide recommendations for PPI rationalization to healthcare providers in the region. METHODS:The SEA PPI Rationalization Working Group is steered by 14 experts practicing across Malaysia, Thailand, Singapore, Vietnam, the Philippines, and Indonesia. The experts convened to review existing evidence and develop recommendations and to conduct an anonymous voting as per the modified Delphi method. RESULTS:Twenty statements were formulated, focusing on areas of (i) extent and impact of PPI overprescription (four statements), (ii) benefits and barriers to PPI rationalization (two statements), (iii) START/STOPP criteria for PPI (nine statements), and (iv) PPI rationalization strategies (five statements). The consensus document underscores the widespread inappropriate long-term PPI prescription across SEA, which may have adverse clinical outcomes. Although rationalizing PPI use may be beneficial, the experts acknowledge the challenges of implementing PPI rationalization. The experts also outlined specific indications to guide PPI initiation and advised regular review to rationalize a PPI when no longer indicated. This is followed by PPI rationalization strategies, including shared decision-making, prescribing alginate as a rescue therapy in gastroesophageal reflux disease, and further evaluation for reinitiation of PPI when clinically warranted. CONCLUSIONS:This consensus document serves to improve PPI prescribing and deprescribing practices in SEA and to provide recommendations on rationalization strategies.
Primary external auditory canal cholesteatoma (EACC) is a rare condition characterized by keratinizing squamous epithelium causing progressive bony erosion of the external auditory canal. Bilateral primary EACC is exceptionally uncommon. We report a 49-year-old woman who presented with progressive bilateral hearing loss, intermittent otorrhea, and dull otalgia. Otoscopic examination revealed keratin debris and canal wall erosion in both ears. High-resolution computed tomography demonstrated bilateral posterior canal wall erosion without middle ear involvement. She had no history of ear surgery, trauma, or systemic disease. The left ear was managed with examination under anesthesia and toileting, while the right ear required modified radical mastoidectomy with type III tympanoplasty and mastoid cavity obliteration. Histopathology confirmed cholesteatoma. This case highlights the importance of distinguishing EACC from other external canal pathologies and emphasizes early imaging and individualized management to prevent complications and ensure favorable outcomes.
