Browsing by Author "Tunku Kamarul Zaman Tunku Zainol Abidin"
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Publication The Impact Of Movement Control Order During Covid-19 Pandemic On Healthcare Utilisation: How Does The Projected Patient Workload Compared To The Actual Number Of Patients In Care?(Faculty of Medicine, Universiti Malaya, 2021) ;Amirah Azzeri ;Nur Farhan Abdul Hakim ;Mohd Hafiz Jaafar ;Maznah Dahlui ;Sajaratulnisah OthmanTunku Kamarul Zaman Tunku Zainol AbidinThe rising healthcare demand during COVID-19 outbreak may endanger patients and forces hospital to plan for future needs. Predictive analyses were conducted to monitor hospital resources at one of the gazetted COVID-19 hospitals in Malaysia. Simultaneously, a real-time observation on patient’s volume was conducted to understand the actual trend of healthcare resource utilisations. All the projections were directly compared to the actual number of patients in-care. This predictive study was done at University Malaya Medical Centre (UMMC) using various sources of data. The projections revealed a steady increase in the number of cumulative cases until April 2020 followed by an exponential increase in the number of cumulative positive cases in Malaysia. When a comparison between the projection and actual data was done, it was found that the initial projections estimated a range that is 50% to 70% higher during the first three phases of Movement Control Order (MCO) compared to the actual number of COVID-19 patients at UMMC. Subsequent projections were done by using recent estimations from the national database and it was estimated that the number of patients treated will be less than 10 each day up until the end of May 2020. The accuracy of this estimation is 95% when compared to the actual number of COVID-19 patients in care. In conclusion, the practice of continuous projections and real-time observation through predictive analysis using mathematical calculations and algorithms is one of the useful tools to facilitate hospital management to allocate adequate resource allocations. - Some of the metrics are blocked by yourconsent settings
Publication Prediction Of Disease Burden And Healthcare Resource Utilization Through Simple Predictive Analytics Using Mathematical Approaches, An Experience From University Of Malaya Medical Centre(Faculty of Medicine, Universiti Malaya, 2020) ;Amirah Azzeri ;Nur Farhan Abdul Hakim ;Mohd Hafiz Jaafar ;Maznah Dahlui ;Sajaratulnisah OthmanTunku Kamarul Zaman Tunku Zainol AbidinThe sudden surge in the number of healthcare utilizations compels the hospital to plan for its future needs. Several time-series projections of Covid-19 were conducted to forecast the disease burden and resources utilization through simple predictive analytics. The projections revealed a rapid increase in the number of cases and patient in care at the hospital. It was estimated that the number of patients in care to range from 62 to 81 and 89 to 121 patients daily in the second and third phase of movement control order respectively. It was estimated that more than 100,000 plastic aprons, 80,000 sterile and non-sterile isolation gowns, 40,000 masks N95 and face shields, 30,000 gloves and nearly 17,000 bottles of hand sanitizers are needed until late May. Hence, a simple mathematical algorithm is a helpful tool to manage hospital resources during the pandemic.