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1.
Med J Malaysia ; 78(7): 865-869, 2023 Dec.
Article in English | MEDLINE | ID: mdl-38159919

ABSTRACT

INTRODUCTION: There are two data acquisition methods for computed tomography (CT) scans, namely sequence and helical. Each of them has two ways of measuring the volume of bleeding in a head CT scan, namely by manual and automatic methods. So, it is necessary to have an analysis for measurement accuracy with these two methods in two data acquisitions. The purpose of this study was to compare and evaluate bleeding volumetric measurement accuracy of sequence and helical on head CT acquisition using manual and automatic methods. MATERIALS AND METHODS: This is quantitative research with a true experimental approach. Actual bleeding volume was simulated by an acrylic phantom containing Iodine contrast media (5 ml, 10 ml, 15 ml, and 20 ml). The phantom was scanned using routine CT protocol using the helical and sequence technique. Bleeding volume from each technique was measured manually using the Broderick formula and automatic software (ROI based). Accuracy was assessed by comparing the volume measurement result to the actual bleeding volume. Data was analysed using the Friedman test and by Wilcoxon. RESULTS: The standard deviation of measured bleeding volume from the manual and automatic measurements compared to the actual bleeding volume were (0.220; 0.236; 0.351; 0.057) and (0.139; 0.270; 0.315; 0.329) in helical technique, and (0.333; 0.376; 0.447; 0.476) and (0.139; 0.242; 0.288; 0,376) in sequence technique. There are differences in the measurement results from the helical and sequence techniques (p <0.05) and using manual and automatic methods (p <0.05). CONCLUSION: The measurement of bleeding volume that has a standard deviation value compared to the actual volume is more accurate in the helical technique using the automatic method, while the sequence technique is the manual method.


Subject(s)
Software , Tomography, X-Ray Computed , Humans , Tomography, X-Ray Computed/methods , Radionuclide Imaging , Phantoms, Imaging
2.
Appl Health Econ Health Policy ; 17(1): 65-76, 2019 02.
Article in English | MEDLINE | ID: mdl-30178267

ABSTRACT

OBJECTIVES: The aim was to estimate the long-term cost-effectiveness of improved family planning interventions to reduce the unmet need in low- and middle-income countries, with Indonesia and Uganda as reference cases. METHODS: The analysis was performed using a Markov decision analytic model, where current situation and several scenarios to reduce the unmet need were incorporated as the comparative strategies. Country-specific evidence was synthesized from the demographic and health survey and published studies. The model simulated the sexual and reproductive health experience of women in the reproductive age range over a time horizon of women's reproductive years, from the healthcare payer perspective. Modeled outcomes included clinical events, costs and incremental cost-effectiveness ratios (ICERs) expressed as cost per disability-adjusted life year (DALY) averted. Deterministic and probabilistic sensitivity analyses were conducted to assess the impact of parameter uncertainty on modeled outcomes. RESULTS: In the hypothetical cohort of 100,000 women, scenarios to reduce the unmet need for family planning would result in savings within a range of US$230,600-US$895,100 and US$564,400-US$1,865,900 in Indonesia and Uganda, respectively. The interventions would avert an estimated 1859-3780 and 3705-12,230 DALYs in Indonesia and Uganda, respectively. The results of our analysis indicate that scaling up family planning dominates the current situation in all scenarios in both countries, with lower costs and fewer DALYs. These results were robust in sensitivity analyses. CONCLUSION: Scaling up family planning interventions could improve women's health outcomes substantially and be cost-effective or even cost saving across a range of scenarios compared to the current situation.


Subject(s)
Family Planning Services/standards , Models, Economic , Quality Improvement/economics , Adolescent , Adult , Cost-Benefit Analysis , Female , Health Surveys , Humans , Indonesia , Markov Chains , Middle Aged , Uganda , Young Adult
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