RESUMO
OBJECTIVES: Healthcare-associated infections (HAIs) represent a major threat to patient safety and are associated with significant economic burden. Calculating the costs attributable to HAIs is challenging given the various sources of bias. Although HAIs as a reasonably preventable medical harm should have been closely linked to medical insurance incentives, there was little linkage between HAIs and medicare in western China owing to the lack of economic evaluation data. The present study aimed to generate estimates of the attributable costs associated with HAIs and the magnitude of costs growth. METHODS: In this cohort study designed horizontally and vertically from 2016 to 2022, we compared outcomes of randomly sampling patients with HAIs and individually matched patients without HAIs in two cohorts at a 6-year interval at 34 hospitals in western China. The primary outcome was the direct medical cost for the entire hospital stay, converted to US dollars ($ for the benchmark year), discounted at 3% annually, and estimated separately in the full analysis set (FAS) and the per protocol set (PPS). We used multiple linear regression to adjust the discounted costs and to assess subgroups effects within each cohort. We nested a dynamic vertical comparison of costs attributable to HAIs between the front and rear cohorts. RESULTS: A total of 230 patients with HAIs in 2016 and 204 patients with HAIs in 2022 were enrolled. After a 1:1 match, all 431 pairs were recruited as FAS, of which 332 pairs as PPS met all matching restrictions. Compared to the 2016 cohort in FAS, the patients with HAIs in 2022 had a significantly older age (64.40 ± 16.45 years), higher repeat hospitalization rate (65 [32.02%] of 203), and lower immune function (69 [33.99%] of 203). The discounted costs and adjusted-discounted costs for patients with HAIs in the 2022 cohort were found to be significantly higher than those of patients without HAIs (discounted costs: $5484.60 [IQR 8426.03] vs $2554.04(4530.82), P < 0.001; adjusted-discounted costs: $5235.90 [3772.12] vs $3040.21(1823.36), P < 0.001, respectively), and also higher than those of patients with HAIs in the 2016 cohort (discounted costs: $5484.60 [8426.03] vs $3553.00 [6127.79], P < 0.001; adjusted-discounted costs: $5235.90 [3772.12] vs $3703.82 [3159.14], P < 0.001, respectively). In vertical comparison of PPS, the incremental costs of the 2022 cohort are 1.48 times higher than those of the 2016 cohort ($964.63(4076.15) vs $652.43 [2533.44], P = 0.084). CONCLUSIONS: This meticulously designed study in western China has successfully and accurately examined the economic burden attributable to HAIs. Their rapidly increasing tendency poses a serious challenge to patients, hospitals, and the medical insurance. A closer linkage between HAIs and ongoing motivating system changes is urgently needed in western China.
Assuntos
Infecção Hospitalar , Estresse Financeiro , Estados Unidos , Humanos , Idoso , Estudos de Coortes , Estudos Prospectivos , Medicare , Infecção Hospitalar/epidemiologia , Hospitais , China/epidemiologia , Atenção à SaúdeRESUMO
A new COVID-19 epidemic model with media coverage and quarantine is constructed. The model allows for the susceptibles to the unconscious and conscious susceptible compartment. First, mathematical analyses establish that the global dynamics of the spread of the COVID-19 infectious disease are completely determined by the basic reproduction number R0. If R0 ≤ 1, then the disease free equilibrium is globally asymptotically stable. If R0 > 1, the endemic equilibrium is globally asymptotically stable. Second, the unknown parameters of model are estimated by the MCMC algorithm on the basis of the total confirmed new cases from February 1, 2020 to March 23, 2020 in the UK. We also estimate that the basic reproduction number is R0 = 4.2816(95%CI: (3.8882, 4.6750)). Without the most restrictive measures, we forecast that the COVID-19 epidemic will peak on June 2 (95%CI: (May 23, June 13)) (Figure 3a) and the number of infected individuals is more than 70% of UK population. In order to determine the key parameters of the model, sensitivity analysis are also explored. Finally, our results show reducing contact is effective against the spread of the disease. We suggest that the stringent containment strategies should be adopted in the UK.