Purpose: The South Korean government in 2014 introduced various policies to enhance accessibility of pharmaceuticals. This study sought to examine whether positive reimbursement recommendations of pharmaceuticals have increased since 2014.Methods: Industry submissions evaluated from January 2007 to December 2018 were identified, and characteristics relevant to reimbursement recommendations were extracted. Logistic regression analyses with robust SEs were used to quantify the likelihood of positive recommendations for pharmaceuticals, after controlling for relevant factors influencing the recommendations.Findings: During the study period, 355 (72.9%) of 487 submissions were positively recommended; the drugs evaluated after 2014 (77.8%) were significantly more likely to receive positive reimbursement recommendations than the drugs evaluated before 2014 (69.5%). In the multivariable logistic regression analysis, several factors (labeled a noncancer drug, priced less than alternatives, considered clinically superior, and having budget impact >10 billion South Korean won) were significantly associated with positive recommendations (P < 0.05). When considering interaction effects between evaluation year and other variables, only the interaction between comparative clinical benefit and evaluation year was significant. Specifically, clinically noninferior drugs evaluated after 2014 had 2.85 times the odds of receiving positive recommendations compared with the clinically noninferior drugs evaluated earlier.Implications: Recently evaluated drugs are more likely to receive positive reimbursement recommendations, especially those drugs whose comparative clinical benefits are noninferior (Clin Ther.

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To summarize utility estimates of breast cancer and to assess the relative impacts of study characteristics on predicting breast cancer utilities. We searched Medline, Embase, RISS, and KoreaMed from January 1996 to April 2019 to find literature reporting utilities for breast cancer. Thirty-five articles were identified, reporting 224 utilities. A hierarchical linear model was used to conduct a meta-regression that included disease stages, assessment methods, respondent type, age of the respondents, and scale bounds as explanatory variables. The utility for early and late-stage breast cancer, as estimated by using the time-tradeoff with the scales anchored by death to perfect health with non-patients, were 0.742 and 0.525, respectively. The severity of breast cancer, assessment method, and respondent type were significant predictors of utilities, but the age of the respondents and bounds of the scale were not. Patients who experienced the health states valued 0.142 higher than did non-patients (p < 0.001). Besides the disease stage, the respondent type had the highest impact on breast cancer utility.

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