The objective of this study is to predict the volume of the elderly in different health status categories in Thailand in the next ten years (2020–2030). Multistate modelling was performed. We defined four states of elderly patients (aged ≥ 60 years) according to four different levels of Activities of Daily Living (ADL): social group; home group; bedridden group; and dead group. The volume of newcomers was projected by trend extrapolation methods with exponential growth. The transition probabilities from one state to another was obtained by literature review and model optimization. The mortality rate was obtained by literature review. Sensitivity analysis was conducted. By 2030, the number of social, home, and bedridden groups was 15,593,054, 321,511, and 152,749, respectively. The model prediction error was 1.75%. Sensitivity analysis with the change of transition probabilities by 20% caused the number of bedridden patients to vary from between 150,249 and 155,596. In conclusion, the number of bedridden elders will reach 153,000 in the next decade (3 times larger than the status quo). Policy makers may consider using this finding as an input for future resource planning and allocation. Further studies should be conducted to identify the parameters that better reflect the transition of people from one health state to another.
Introduction Necrotizing fasciitis (NF) is a rare skin and soft-tissue bacterial infection with high morbidity and mortality. Knowledge about the prevalence and incidence of NF in Thailand is quite sparse. The objective of this study was to determine the prevalence of NF in Thailand and factors that may be potentially associated with NF morbidity and mortality. Methods A cross-sectional study using secondary data from Thailand’s national health databases between 2014 and 2018 was conducted. Descriptive statistics using median and percentage formats were used. This was complemented by multivariable logistic regression to determine the association between various factors (such as age and underlying diseases) with NF morbidity and mortality. Univariate spatial data analysis was exercised to identify the geographical hot spots in which the disease appeared. Results During 2014–2018, we found 90,683 NF cases. About 4.86% of the cases died. The median age for all cases was 59.39 years old. The annual incidence of NF demonstrated an upward trend (from 26.08 per 100,000 population in 2014 to 32.64 per 100,000 population in 2018). The monthly incidence was highest between May and August. A high incidence cluster (as indicated by local Moran’s I) was found in the north-eastern region of Thailand. The most infected sites were on the ankles and feet (43.18%) with an amputation rate of 7.99% in all cases. Multivariable logistic regression indicated that the significant risk factor for amputation was a presence of underlying diseases, namely diabetes (OR 7.94, 95% CI 7.34–8.61). Risk factors for mortality included being elderly (OR 1.82, 95% CI 1.68–1.98) and a presence of underlying hypertension (OR 1.16, 95% CI 1.07–1.27), cirrhosis (OR 4.67, 95% CI 4.17–5.21), and malignancy (OR 1.88, 95% CI 1.55–2.26). Discussion and Conclusion As the elderly and those with chronic underlying diseases are likely to face non-preferable health outcomes from NF, healthcare providers should pay great attention to these groups of patients. Early and intensive treatment might be considered in these groups of patients. Further studies that aim to validate the volume of actual NF cases and reported NF cases are recommended.
Thailand is classified by the World Health Organization as one of a few countries in the world with the highest tuberculosis (TB) burden. The Thai Ministry of Public Health has implemented the ‘Tuberculosis Case Management’ (TBCM) as the main database for the national TB surveillance. TBCM is designed for case registration and management as well as case reporting and notification. This study thus aimed to evaluate TBCM for its surveillance function. A cross-sectional descriptive study was conducted to review the surveillance function of TBCM during 1 Jan to 30 Jun 2017 at Mae Sot Hospital, Thailand. The study team reviewed the protocols and guidelines of TBCM. The practice of health personnel at the TB clinic was observed to determine the data flow of TBCM. Qualitative and quantitative study methods were employed in accordance with the Center for Disease Control and Prevention’s Guidelines for Evaluating Surveillance Systems. We found that TBCM reporting system at Mae Sot Hospital was acceptable, stable and useful in achieving the objectives of TB control program. Sensitivity and positive predictive value of TBCM accounted for 80.8% and 99.4% respectively. The most common reason of miss-reporting was a loss to follow-up after admission or after health exam, particularly amongst non-Thai patients. Timeliness and data quality were concerned attributes that required improvement. TBCM and the in-house medical recording system should be harmonized to mitigate the risk of erroneous coding.
Necrotizing fasciitis (NF) is a serious skin and soft tissue infection that can lead to disabilities and mortalities. A study was carried out to describe demographic characteristics of NF patients, and determine factors associated with disability and mortality. Information on all patients who were diagnosed as NF from 1 Jan to 31 Dec 2018 were extracted from the databases of Health Data Center in Thailand. Univariate and multivariate analyses using logistic regression were performed to determine the associated factors. In 2018, of total 19,071 NF cases, 6.3% died. Median age was 59.7 years old (Q1-Q3 = 49.1-69.5 years). Most of the cases developed NF at ankle and foot (43.0%), followed by lower leg (28.2%). The amputation rate among the cases was 8.2%. Multivariable analysis showed the significant risk factor for amputation as having diabetes mellitus (adjusted OR 6.81, 95% CI 5.97-7.77). Risk factors for mortality included being elderly (OR 1.81, 95% CI 1.56-2.11), and having hypertension (OR 1.17, 95% CI 1.00-1.36), cirrhosis (OR 4.26, 95% CI 3.42-5.28) or cancer (OR 1.88, 95% CI 1.33-2.59). Morbidity and mortality among NF patients were significant in Thailand. Health workers should be trained for early diagnosis and intensive treatment for NF, especially among elderly and patients with chronic diseases in order to prevent the subsequent complications.
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