Treatment costs for patients with Streptococcus suis infection in Northern Thailand: a hospital-based observational
Ajaree Rayanakorn1,2, Wasan Katip3, Zanfina Ademi4,5
1Faculty of Public Health, Chiang Mai University, 239 Huay Kaew Road, Tambon Suthep, Muang District, Chiang Mai, 50200, Thailand. ajaree.rayanakorn@cmu.ac.th.
Background:
Streptococcus suis (S.suis) is a neglected zoonotic disease that imposes a significant economic burden on healthcare and society. To our knowledge, studies estimating the cost of illness associated with S.suis treatment are limited, and no study focuses on treatment costs and potential key drivers in Thailand. This study aimed to estimate the direct medical costs associated with S.suis treatment in Thailand and identify key drivers affecting high treatment costs from the provider's perspective.
Methods:
A retrospective analysis of the 14-year data from 2005-2018 of confirmed S.suis patients admitted at Chiang Mai University Hospital (CMUH) was conducted. Descriptive statistics were used to summarize the data of patients' characteristics, healthcare utilization and costs. The multiple imputation with predictive mean matching strategy was employed to deal with missing Glasgow Coma Scale (GCS) data. Generalized linear models (GLMs) were used to forecast costs model and identify determinants of costs associated with S.suis treatment. The modified Park test was adopted to determine the appropriate family. All costs were inflated applying the consumer price index for medical care and presented to the year 2019.
Results:
Among 130 S.suis patients, the average total direct medical cost was 12,4675 Thai baht (THB) (US$ 4,016), of which the majority of expenses were from the "others" category (room charges, staff services and medical devices). Infective endocarditis (IE), GCS, length of stay, and bicarbonate level were significant predictors associated with high total treatment costs. Overall, marginal increases in IE and length of stay were significantly associated with increases in the total costs (standard error) by 132,443 THB (39,638 THB) and 5,490 THB (1,715 THB), respectively. In contrast, increases in GCS and bicarbonate levels were associated with decreases in the total costs (standard error) by 13,118 THB (5,026 THB) and 7,497 THB (3,430 THB), respectively.
Conclusions:
IE, GCS, length of stay, and bicarbonate level were significant cost drivers associated with direct medical costs. Patients' clinical status during admission significantly impacts the outcomes and total treatment costs. Early diagnosis and timely treatment were paramount to alleviate long-term complications and high healthcare expenditures.
