DESIGN: Death-related data were retrospectively and prospectively assessed in a longitudinal regional cohort study.
METHODS: Children under routine HIV care at sites in Cambodia, India, Indonesia, Malaysia, Thailand, and Vietnam between 2008 and 2017 were followed. Causes of death were reported and then independently and centrally reviewed. Predictors were compared using competing risks survival regression analyses.
RESULTS: Among 5918 children, 5523 (93%; 52% male) had ever been on combination antiretroviral therapy. Of 371 (6.3%) deaths, 312 (84%) occurred in those with a history of combination antiretroviral therapy (crude all-cause mortality 9.6 per 1000 person-years; total follow-up time 32 361 person-years). In this group, median age at death was 7.0 (2.9-13) years; median CD4 cell count was 73 (16-325) cells/μl. The most common underlying causes of death were pneumonia due to unspecified pathogens (17%), tuberculosis (16%), sepsis (8.0%), and AIDS (6.7%); 12% of causes were unknown. These clinical diagnoses were further grouped into AIDS-related infections (22%) and noninfections (5.8%), and non-AIDS-related infections (47%) and noninfections (11%); with 12% unknown, 2.2% not reviewed. Higher CD4 cell count and better weight-for-age z-score were protective against death.
CONCLUSION: Our standardized cause of death assessment provides robust data to inform regional resource allocation for pediatric diagnostic evaluations and prioritization of clinical interventions, and highlight the continued importance of opportunistic and nonopportunistic infections as causes of death in our cohort.
Materials and Methods: A retrospective cohort study was conducted in the ED of the largest tertiary medical center in Taiwan. Trends of adult, non-trauma patients who visited the ED during February-April 2019 were compared with those during February-April 2020. The number of visits, their dispositions, crowding parameters, and turnover rates were analyzed. The primary outcome was the change in ED attendance between the two periods. The secondary outcomes were changes in hospital admission rates, crowding parameters, and turnover rates.
Results: During the outbreak, there were decreased non-trauma ED visits by 33.45% (p < 0.001) and proportion of Taiwan Triage and Acuity Scale (TTAS) 3 patients (p=0.02), with increased admission rates by 4.7% (p < 0.001). Crowding parameters and turnover rate showed significant improvements.
Conclusion: Comparison of periods before and during the COVID-19 outbreak showed an obvious decline in adult, non-trauma ED visits. The reduction in TTAS 3 patient visits and the increased hospital admission rates provide references for future public-health policy-making to optimise emergency medical resource allocations globally.
METHODS: Research impact of universal access and quality healthcare projects funded by the National Institutes of Health Malaysia were assessed based on the modified Payback Framework, addressing categories of informing policy, knowledge production, and benefits to health and health sector. For the HRPS process, the Child Health and Nutrition Research Initiative methodology was adapted and adopted, with the incorporation of stakeholder values using weights and monetary allocation survey. Workshop discussions and interviews with stakeholders and research groups were conducted to identify research gaps, with the use of conceptual frameworks to guide the search.
RESULTS: Seventeen ongoing and 50 completed projects were identified for research funding impact analysis. Overall, research fund allocation differed from stakeholders' expectation. For research impact, 48 out of 50 completed projects (96.0%) contributed to some form of policy-making efforts. Almost all completed projects resulted in outputs that contributed to knowledge production and were expected to lead to health and health sector benefits. The HRPS process led to the identification of research priority areas that stemmed from ongoing and new issues identified for universal access and quality healthcare.
CONCLUSION: The concerted efforts of evaluation of research funding impact, prioritisation, dissemination and policy-maker involvement were valuable for optimal health research resource utilisation in a resource constrained developing country. Embedding impact evaluation into a priority setting process and funding research based on national needs could facilitate health research investment to reach its potential.
METHODS: A decision-analytic Markov model was developed to simulate the impact of S. suis infection and its major complications: death, meningitis and infective endocarditis among Thai people in 2019 with starting age of 51 years. Transition probabilities, and inputs pertaining to costs, utilities and productivity impairment associated with long-term complications were derived from published sources. A lifetime time horizon with follow-up until death or age 100 years was adopted. The simulation was repeated assuming that the cohort had not been infected with S.suis. The differences between the two set of model outputs in years of life, QALYs, and PALYs lived reflected the impact of S.suis infection. An annual discount rate of 3% was applied to both costs and outcomes. One-way sensitivity analyses and Monte Carlo simulation modeling technique using 10,000 iterations were performed to assess the impact of uncertainty in the model.
KEY RESULTS: This cohort incurred 769 (95% uncertainty interval [UI]: 695 to 841) years of life lost (14% of predicted years of life lived if infection had not occurred), 826 (95% UI: 588 to 1,098) QALYs lost (21%) and 793 (95%UI: 717 to 867) PALYs (15%) lost. These equated to an average of 2.46 years of life, 2.64 QALYs and 2.54 PALYs lost per person. The loss in PALYs was associated with a loss of 346 (95% UI: 240 to 461) million Thai baht (US$11.3 million) in GDP, which equated to 1.1 million Thai baht (US$ 36,033) lost per person.
CONCLUSIONS: S.suis infection imposes a significant economic burden both in terms of health and productivity. Further research to investigate the effectiveness of public health awareness programs and disease control interventions should be mandated to provide a clearer picture for decision making in public health strategies and resource allocations.
Methods: We applied a retrospective approach using a top-down costing method to estimate the cost of health care services. Clinical and Administrative departments divided into cost centres, and the unit cost was calculated by dividing the total cost of final care cost centres into the total number of patients discharged in one year. The average cost of inpatient services was calculated based on the average cost of each ward and the number of patients treated.
Results: The average cost per patient stayed in KFCH was SAR 19,034, with the highest cost of SAR 108,561 for patients in the Orthopedic ward. The average cost of the patient in the Surgery ward, Plastic surgery, Neurosurgery, Medical ward, Pediatric ward and Gynecology ward was SAR 33,033, SAR 29,425, SAR 23,444, SAR 20,450, SAR 9579 and SAR 8636 respectively.
Conclusion: This study provides necessary information about the cost of health care services in a tertiary care setting. This information can be used as a primary tool and reference for further studies in other regions of the country. Hence, this data can help to provide a better understanding of tertiary hospital costing in the region to achieve the privatization objective.