scholarly journals The Association between Charlson Comorbidity Index and the Medical Care Cost of Cancer: A Retrospective Study

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Seok-Jun Yoon ◽  
Eun-Jung Kim ◽  
Hyun-Ju Seo ◽  
In-Hwan Oh

Background. This study compared comorbidity-related medical care cost associated with different types of cancer, by examining breast (N=287), colon (N=272), stomach (N=614), and lung (N=391) cancer patients undergoing surgery.Methods. Using medical benefits claims data, we calculated Charlson Comorbidity Index (CCI) and total medical cost. The effect of comorbidity on the medical care cost was investigated using multiple regression and logistic regression models and controlling for demographic characteristics and cancer stage.Results. The treatment costs incurred by stomach and colon cancer patients were 1.05- and 1.01-fold higher, respectively, in patients with higher CCI determined. For breast cancer, the highest costs were seen in those with chronic obstructive pulmonary disease (COPD), but the increase in cost reduced as CCI increased. Colon cancer patients with diabetes mellitus and a CCI = 1 score had the highest medical costs. The lowest medical costs were incurred by lung cancer patients with COPD and a CCI = 2 score.Conclusion. The comorbidities had a major impact on the use of medical resources, with chronic comorbidities incurring the highest medical costs. The results indicate that comorbidities affect cancer outcomes and that they must be considered strategies mitigating cancer’s economic and social impact.

2009 ◽  
Vol 19 (4) ◽  
pp. 18-32 ◽  
Author(s):  
Se-Won Kim ◽  
Seok-Jun Yoon ◽  
Min-Ho Kyung ◽  
Young-Ho Yun ◽  
Young-Ae Kim ◽  
...  

2018 ◽  
Vol 146 (16) ◽  
pp. 2122-2130 ◽  
Author(s):  
H. G. Ternavasio-de la Vega ◽  
F. Castaño-Romero ◽  
S. Ragozzino ◽  
R. Sánchez González ◽  
M. P. Vaquero-Herrero ◽  
...  

AbstractThe objective was to compare the performance of the updated Charlson comorbidity index (uCCI) and classical CCI (cCCI) in predicting 30-day mortality in patients with Staphylococcus aureus bacteraemia (SAB). All cases of SAB in patients aged ⩾14 years identified at the Microbiology Unit were included prospectively and followed. Comorbidity was evaluated using the cCCI and uCCI. Relevant variables associated with SAB-related mortality, along with cCCI or uCCI scores, were entered into multivariate logistic regression models. Global model fit, model calibration and predictive validity of each model were evaluated and compared. In total, 257 episodes of SAB in 239 patients were included (mean age 74 years; 65% were male). The mean cCCI and uCCI scores were 3.6 (standard deviation, 2.4) and 2.9 (2.3), respectively; 161 (63%) cases had cCCI score ⩾3 and 89 (35%) cases had uCCI score ⩾4. Sixty-five (25%) patients died within 30 days. The cCCI score was not related to mortality in any model, but uCCI score ⩾4 was an independent factor of 30-day mortality (odds ratio, 1.98; 95% confidence interval, 1.05–3.74). The uCCI is a more up-to-date, refined and parsimonious prognostic mortality score than the cCCI; it may thus serve better than the latter in the identification of patients with SAB with worse prognoses.


Surgery Today ◽  
2018 ◽  
Vol 48 (6) ◽  
pp. 632-639 ◽  
Author(s):  
Kotaro Yamashita ◽  
Masayuki Watanabe ◽  
Shinji Mine ◽  
Ian Fukudome ◽  
Akihiko Okamura ◽  
...  

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260169
Author(s):  
Jorge Enrique Machado-Alba ◽  
Luis Fernando Valladales-Restrepo ◽  
Manuel Enrique Machado-Duque ◽  
Andrés Gaviria-Mendoza ◽  
Nicolás Sánchez-Ramírez ◽  
...  

Introduction Coronavirus disease 2019 (COVID-19) has affected millions of people worldwide, and several sociodemographic variables, comorbidities and care variables have been associated with complications and mortality. Objective To identify the factors associated with admission to intensive care units (ICUs) and mortality in patients with COVID-19 from 4 clinics in Colombia. Methods This was a follow-up study of a cohort of patients diagnosed with COVID-19 between March and August 2020. Sociodemographic, clinical (Charlson comorbidity index and NEWS 2 score) and pharmacological variables were identified. Multivariate analyses were performed to identify variables associated with the risk of admission to the ICU and death (p<0.05). Results A total of 780 patients were analyzed, with a median age of 57.0 years; 61.2% were male. On admission, 54.9% were classified as severely ill, 65.3% were diagnosed with acute respiratory distress syndrome, 32.4% were admitted to the ICU, and 26.0% died. The factors associated with a greater likelihood of ICU admission were severe pneumonia (OR: 9.86; 95%CI:5.99–16.23), each 1-point increase in the NEWS 2 score (OR:1.09; 95%CI:1.002–1.19), history of ischemic heart disease (OR:3.24; 95%CI:1.16–9.00), and chronic obstructive pulmonary disease (OR:2.07; 95%CI:1.09–3.90). The risk of dying increased in those older than 65 years (OR:3.08; 95%CI:1.66–5.71), in patients with acute renal failure (OR:6.96; 95%CI:4.41–11.78), admitted to the ICU (OR:6.31; 95%CI:3.63–10.95), and for each 1-point increase in the Charlson comorbidity index (OR:1.16; 95%CI:1.002–1.35). Conclusions Factors related to increasing the probability of requiring ICU care or dying in patients with COVID-19 were identified, facilitating the development of anticipatory intervention measures that favor comprehensive care and improve patient prognosis.


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