OBJECTIVE: CDA (Clinical Document Architecture) is a markup standard for clinical document exchange. In order to increase the semantic interoperability of documents exchange, the clinical statements in the narrative blocks should be encoded with code values. Natural language processing (NLP) is required in order to transform the narrative blocks into the coded elements in the level 3 CDA documents. In this paper, we evaluate the accuracy of text mapping methods which are based on NLP. METHODS: We analyzed about one thousand discharge summaries to know their characteristics and focused the syntactic patterns of the diagnostic sections in the discharge summaries. According to the patterns, different rules were applied for matching code values of Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). RESULTS: The accuracy of matching was evaluated using five-hundred discharge summaries. The precision was as follows: 86.5% for diagnosis, 61.8% for chief complaint, 62.7%, for problem list, and 64.8% for discharge medication. CONCLUSION: The text processing method based on the pattern analysis of a clinical statement can be effectively used for generating CDA entries.
Diagnosis ; Natural Language Processing ; Semantics ; Systematized Nomenclature of Medicine

Purpose: This study aimed to understand how changes in income due to the COVID-19 pandemic have affected the health behavior and mental health status of self-employed individuals. Methods: We compared the health behavior and mental health status of regular wage workers and self-employed individuals with no change in income, with that of self-employed individuals with reduced income due to the spread of COVID-19. Results Smoking status, average amount of smoking per day, changes in the amount of smoking and drinking due to COVID-19, drinking frequency per year, monthly binge drinking experiences, subjective stress, and suicidal thoughts experienced by self-employed individuals with decreased income were not only higher than those of wage workers and self-employed individuals with maintained income, but their happiness index was also lower than the latter group. Conclusion: This study suggests that the change in total household income due to COVID-19 adversely affects the health behavior and mental health status of self-employed individuals. However, COVID-19-related policies focus only on economic loss compensation, and the health behavior and mental health management for self-employed individuals is insufficient. Therefore, it is necessary to establish policies for health behavior and mental health management of self-employed individuals.

Purpose: This study uses data from the 12th~17th Korea Welfare Panel (2017~2022) to analyze changes in depression scores due to the COVID-19 outbreak and the factors that influenced depression scores according to employment type. Methods: The difference in depression scores according to employment types before COVID-19 (12th~14th) and after COVID-19 (15th~17th) was analyzed. A fixed-effect model analysis was conducted before and after the occurrence of COVID-19. Results: After the outbreak of COVID-19, job satisfaction and family life satisfaction influenced the depression scores of regular wage workers. After the outbreak of COVID-19, annual income, health status, and satisfaction with family life affected the depression scores of non-regular wage workers. After the outbreak of COVID-19, leisure life satisfaction and family relationship satisfaction influenced the depression scores of self-employed. Self-esteem played a role as a control variable in lowering the depression scores of regular and non-regular workers, but did not play a role as a control variable for self-employed. Conclusion Rather than the direct impact of infectious diseases such as COVID-19, social and economic changes resulting from policies implemented to prevent the spread affect workers' depression, and the impact varies depending on the type of employment. When implementing policies to prevent the spread of infectious diseases in the future, policies that take employment type into consideration rather than uniform policies should be prepared, and measures for mental health also need to be prepared.

Background: The coronavirus disease 2019 (COVID-19) pandemic has altered daily behavioral patterns based on government healthcare policies, including consumption and movement patterns. We aimed to examine the extent to which changes in the government's healthcare policy have affected people's lives, primarily focusing on changes in consumption and population movements. Methods: We collected consumption data using weekly credit card transaction data from the Hana Card Corporation and population mobility data using mobile phone data from SK Telecom in Seoul, South Korea. Interrupted time-series analysis was used to calculate the relative risk ratio and perform the intervention effects when government healthcare policy changes. Results: We found that leisure and outside movements were the most immediately affected by changes in government healthcare policies. It took over 2 years and 11 months, respectively, for these sectors to return to their pre-COVID-19 routines. Conclusion Enhancing healthcare policies presents advantages and disadvantages.Although such policies help prevent the spread of COVID-19, they also reduce consumption and mobility, extending the time needed to return to pre-COVID-19 levels. Government healthcare policymakers should consider not only disease prevention but also the impact of these policies on social behaviors, economic activity, and mobility.

Background: The coronavirus disease 2019 (COVID-19) pandemic has altered daily behavioral patterns based on government healthcare policies, including consumption and movement patterns. We aimed to examine the extent to which changes in the government's healthcare policy have affected people's lives, primarily focusing on changes in consumption and population movements. Methods: We collected consumption data using weekly credit card transaction data from the Hana Card Corporation and population mobility data using mobile phone data from SK Telecom in Seoul, South Korea. Interrupted time-series analysis was used to calculate the relative risk ratio and perform the intervention effects when government healthcare policy changes. Results: We found that leisure and outside movements were the most immediately affected by changes in government healthcare policies. It took over 2 years and 11 months, respectively, for these sectors to return to their pre-COVID-19 routines. Conclusion Enhancing healthcare policies presents advantages and disadvantages.Although such policies help prevent the spread of COVID-19, they also reduce consumption and mobility, extending the time needed to return to pre-COVID-19 levels. Government healthcare policymakers should consider not only disease prevention but also the impact of these policies on social behaviors, economic activity, and mobility.

Background: The coronavirus disease 2019 (COVID-19) pandemic has altered daily behavioral patterns based on government healthcare policies, including consumption and movement patterns. We aimed to examine the extent to which changes in the government's healthcare policy have affected people's lives, primarily focusing on changes in consumption and population movements. Methods: We collected consumption data using weekly credit card transaction data from the Hana Card Corporation and population mobility data using mobile phone data from SK Telecom in Seoul, South Korea. Interrupted time-series analysis was used to calculate the relative risk ratio and perform the intervention effects when government healthcare policy changes. Results: We found that leisure and outside movements were the most immediately affected by changes in government healthcare policies. It took over 2 years and 11 months, respectively, for these sectors to return to their pre-COVID-19 routines. Conclusion Enhancing healthcare policies presents advantages and disadvantages.Although such policies help prevent the spread of COVID-19, they also reduce consumption and mobility, extending the time needed to return to pre-COVID-19 levels. Government healthcare policymakers should consider not only disease prevention but also the impact of these policies on social behaviors, economic activity, and mobility.

Background: The coronavirus disease 2019 (COVID-19) pandemic has altered daily behavioral patterns based on government healthcare policies, including consumption and movement patterns. We aimed to examine the extent to which changes in the government's healthcare policy have affected people's lives, primarily focusing on changes in consumption and population movements. Methods: We collected consumption data using weekly credit card transaction data from the Hana Card Corporation and population mobility data using mobile phone data from SK Telecom in Seoul, South Korea. Interrupted time-series analysis was used to calculate the relative risk ratio and perform the intervention effects when government healthcare policy changes. Results: We found that leisure and outside movements were the most immediately affected by changes in government healthcare policies. It took over 2 years and 11 months, respectively, for these sectors to return to their pre-COVID-19 routines. Conclusion Enhancing healthcare policies presents advantages and disadvantages.Although such policies help prevent the spread of COVID-19, they also reduce consumption and mobility, extending the time needed to return to pre-COVID-19 levels. Government healthcare policymakers should consider not only disease prevention but also the impact of these policies on social behaviors, economic activity, and mobility.

OBJECTIVES: Breast cancer incidence and mortality rates in Korea are increasing. This study analyzed income-based inequalities in the incidence and mortality of women breast cancer from 2006 to 2015, using national data that covered all Korean women. METHODS: We used the National Health Information Database from 2006 to 2015. For women aged 20 and older, the age-standardized incidence and mortality rates of breast cancer per 100,000 by income quintile per year were calculated using the direct method. The rate ratio and rate difference (RD) of the age-standardized incidence and mortality rates of breast cancer per 100,000 between the top and bottom income quintiles were calculated as relative and absolute measures for inequalities. RESULTS: When comparing 2006 and 2015, both the incidence and mortality rates of breast cancer increased. The lowest income quintile experienced higher mortality rates despite having lower incidence rates. In 2015, the income-based RD in incidence and mortality rates between the highest and lowest income quintiles (Q1-Q5) was -19.9 (95% confidence interval [CI], -24.3 to -15.5) and 4.4 (95% CI, 2.9 to 5.8), respectively. Throughout this period, there was no statistically significant trend in income-based disparities in breast cancer incidence and mortality. The age-specific contributions to the absolute magnitude of inequality (RD) in incidence and mortality were more pronounced among middle-aged women than among older women. CONCLUSIONS This study found that breast cancer in Korea exhibited pro-rich inequalities in mortality despite pro-poor inequalities in incidence. More equitable policies for screening and treatment of breast cancer are needed.

OBJECTIVES: Breast cancer incidence and mortality rates in Korea are increasing. This study analyzed income-based inequalities in the incidence and mortality of women breast cancer from 2006 to 2015, using national data that covered all Korean women. METHODS: We used the National Health Information Database from 2006 to 2015. For women aged 20 and older, the age-standardized incidence and mortality rates of breast cancer per 100,000 by income quintile per year were calculated using the direct method. The rate ratio and rate difference (RD) of the age-standardized incidence and mortality rates of breast cancer per 100,000 between the top and bottom income quintiles were calculated as relative and absolute measures for inequalities. RESULTS: When comparing 2006 and 2015, both the incidence and mortality rates of breast cancer increased. The lowest income quintile experienced higher mortality rates despite having lower incidence rates. In 2015, the income-based RD in incidence and mortality rates between the highest and lowest income quintiles (Q1-Q5) was -19.9 (95% confidence interval [CI], -24.3 to -15.5) and 4.4 (95% CI, 2.9 to 5.8), respectively. Throughout this period, there was no statistically significant trend in income-based disparities in breast cancer incidence and mortality. The age-specific contributions to the absolute magnitude of inequality (RD) in incidence and mortality were more pronounced among middle-aged women than among older women. CONCLUSIONS This study found that breast cancer in Korea exhibited pro-rich inequalities in mortality despite pro-poor inequalities in incidence. More equitable policies for screening and treatment of breast cancer are needed.

OBJECTIVES: Breast cancer incidence and mortality rates in Korea are increasing. This study analyzed income-based inequalities in the incidence and mortality of women breast cancer from 2006 to 2015, using national data that covered all Korean women. METHODS: We used the National Health Information Database from 2006 to 2015. For women aged 20 and older, the age-standardized incidence and mortality rates of breast cancer per 100,000 by income quintile per year were calculated using the direct method. The rate ratio and rate difference (RD) of the age-standardized incidence and mortality rates of breast cancer per 100,000 between the top and bottom income quintiles were calculated as relative and absolute measures for inequalities. RESULTS: When comparing 2006 and 2015, both the incidence and mortality rates of breast cancer increased. The lowest income quintile experienced higher mortality rates despite having lower incidence rates. In 2015, the income-based RD in incidence and mortality rates between the highest and lowest income quintiles (Q1-Q5) was -19.9 (95% confidence interval [CI], -24.3 to -15.5) and 4.4 (95% CI, 2.9 to 5.8), respectively. Throughout this period, there was no statistically significant trend in income-based disparities in breast cancer incidence and mortality. The age-specific contributions to the absolute magnitude of inequality (RD) in incidence and mortality were more pronounced among middle-aged women than among older women. CONCLUSIONS This study found that breast cancer in Korea exhibited pro-rich inequalities in mortality despite pro-poor inequalities in incidence. More equitable policies for screening and treatment of breast cancer are needed.