• Journal of Preventive Medicine and Public Health
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• v.50 no.5
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• pp.294-302
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• 2017

Objectives: The objectives of this study were to investigate the agreement between medical history questionnaire data and claims data and to identify the factors that were associated with discrepancies between these data types. Methods: Data from self-reported questionnaires that assessed an individual's history of hypertension, diabetes mellitus, dyslipidemia, stroke, heart disease, and pulmonary tuberculosis were collected from a general health screening database for 2014. Data for these diseases were collected from a healthcare utilization claims database between 2009 and 2014. Overall agreement, sensitivity, specificity, and kappa values were calculated. Multiple logistic regression analysis was performed to identify factors associated with discrepancies and was adjusted for age, gender, insurance type, insurance contribution, residential area, and comorbidities. Results: Agreement was highest between questionnaire data and claims data based on primary codes up to 1 year before the completion of self-reported questionnaires and was lowest for claims data based on primary and secondary codes up to 5 years before the completion of self-reported questionnaires. When comparing data based on primary codes up to 1 year before the completion of selfreported questionnaires, the overall agreement, sensitivity, specificity, and kappa values ranged from 93.2 to 98.8%, 26.2 to 84.3%, 95.7 to 99.6%, and 0.09 to 0.78, respectively. Agreement was excellent for hypertension and diabetes, fair to good for stroke and heart disease, and poor for pulmonary tuberculosis and dyslipidemia. Women, younger individuals, and employed individuals were most likely to under-report disease. Conclusions: Detailed patient characteristics that had an impact on information bias were identified through the differing levels of agreement.

• Tuberculosis and Respiratory Diseases
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• v.87 no.3
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• pp.213-220
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• 2024

The continuously increasing prevalence of severe asthma has imposed an increasing burden worldwide. Despite the emergence of novel therapeutic agents, management of severe asthma remains challenging. Insights garnered from big data may be helpful in the effort to determine the complex nature of severe asthma. In the field of asthma research, a vast amount of big data from various sources, including electronic health records, national claims data, and international cohorts, is now available. However, understanding of the strengths and limitations is required for proper utilization of specific datasets. Use of big data, along with advancements in artificial intelligence techniques, could potentially facilitate the practice of precision medicine in management of severe asthma.

• Korean Journal of Clinical Pharmacy
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• v.22 no.1
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• pp.81-86
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• 2012

This study was aimed to examine the prescribing patterns of antivirals in outpatients with chronic hepatitis B (CHB), using National Health Insurance adjudicated claims data (total 1,426,065 claims) dated March 19, 2008 submitted from nationwide healthcare providers to Health Insurance Review and Assessment Service. From the data, there were 2,965 claims with CHB diagnosis (ICD-10 code B18.0 and B18.1), and 44.2% (1,311 claims) of the CHB related claims included antivirals such as lamivudine, clevudine, adefovir and entecavir. Lamivudine, adefovir, clevudine and entecavir shared 54.9%, 19.9%, 13.2% and 11.9%, respectively, among antiviral prescriptions. Adefovir and entecavir 1mg presumed as the 2nd line therapy for HBV resistant cases were shared 23.3% of overall antiviral prescriptions. There were statistically significant difference in prescription patterns according to age and institution type: Lamivudine usage was higher in younger (< 20 years old) and older age group (> 70 years old) than the others (p = 0.016), and adefovir and entecavir, which were relatively newer antivirals, had higher prescription rates in higher level of institutions such as tertiary hospitals than the others (p < 0.001). This study would be of help to make an appropriate drug therapy plan for patients with CHB.

• Journal of Gastric Cancer
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• v.21 no.3
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• pp.279-297
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• 2021

Purpose: Various changes in nutrition, metabolism, immunity, and psychological status occur through multiple mechanisms after gastrectomy. The purpose of this study was to predict disease status after gastrectomy by analyzing diseases pattern that occur or change after gastrectomy. Materials and Methods: A retrospective cohort study was conducted using nationwide claims data. Patients with gastric cancer who underwent gastrectomy or endoscopic resection were included in the study. Eighteen target diseases were selected and categorized based on their underlying mechanism. The incidence of each target disease was compared by dividing the study sample into those who underwent gastrectomy (cases) and those who underwent endoscopic resection for early gastric cancer (controls). The cases were matched with controls using propensity score matching. Thereafter, Cox proportional hazard models were used to evaluate intergroup differences in disease incidence after gastrectomy. Results: A total of 97,634 patients who underwent gastrectomy (84,830) or endoscopic resection (12,804) were included. The incidence of cholecystitis (P<0.0001), pancreatitis (P=0.034), acute kidney injury (P=0.0083), anemia (P<0.0001), and inguinal hernia (P=0.0007) were higher after gastrectomy, while incidence of dyslipidemia (P<0.0001), vascular diseases (ischemic heart disease, stroke, and atherosclerosis; P<0.0001, P<0.0001, and P=0.0005), and Parkinson's disease (P=0.0093) were lower after gastrectomy. Conclusions: This study identifies diseases that may occur after gastrectomy in patients with gastric cancer.

• The Korean journal of internal medicine
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• v.39 no.2
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• pp.261-271
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• 2024

Background/Aims: Mucoprotective agents, such as eupatilin, are often prescribed to prevent gastrointestinal (GI) bleeding in addition to an acid suppressant despite the absence of a large-scale study. We evaluated the additional effect of eupatilin on the prevention of GI bleeding in both the upper and lower GI tract in concomitant aspirin and acid suppressant users using the nationwide database of national claims data from the Korean National Health Insurance Service (NHIS). Methods: An aspirin cohort was constructed using the NHIS claims data from 2013 to 2020. Patients who manifested with hematemesis, melena, or hematochezia were considered to have GI bleeding. A Cox proportional hazards regression model was used to determine the risk factors for GI bleeding associated with the concomitant use of GI drugs and other covariates among aspirin users. Results: Overall, a total of 432,208 aspirin users were included. The concurrent use of an acid suppressant and eupatilin (hazard ratio [HR] = 0.85, p = 0.016, vs. acid suppressant only) was a statistically significant preventive factor for GI bleeding. Moreover, a more than 3-month duration (HR = 0.88, p = 0.030) of acid suppressant and eupatilin prescription (vs. acid suppressant only) was a statistically significant preventive factor for GI bleeding. Conclusions: Eupatilin administration for ≥ 3 months showed additional preventive effect on GI bleeding in concomitant aspirin and acid suppressant users. Thus, cotreatment with eupatilin with a duration of 3 months or longer is recommended for reducing GI bleeding among aspirin plus acid suppressant users.

• Journal of Korean Neurosurgical Society
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• v.61 no.2
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• pp.219-223
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• 2018

Objective : To investigate nationwide statistics on flow-diverting stent usage for cerebral aneurysm treatment and related mortality data. Methods : We requested data extraction from the National Health Insurance Service claims database using electronic data interchange codes (J3207064, J3207073). Patient and hospital information as well as death statistics were collected from the database. Results : A total of 169 procedures were performed using flow-diverting stents for cerebral aneurysm treatment from November 2014 to December 2016 in Korea. The majority of primary diagnosis was unruptured intracranial aneurysm. During the study period, nine subjects died, including one patient initially diagnosed with subarachnoid hemorrhage. The crude mortality rate was 5.3%. Five patients died within one month after the procedure; therefore, the estimated periprocedural mortality rate was $3.0{\pm}1.3%$. The mortality rate as of the last day of 2016 was $6.3{\pm}2.1%$. Conclusion : In a 171 person-year follow-up in a Korean series, nine deaths occurred after flow-diverting stent treatment. The crude mortality rate in Korea (5.3%) was higher than that reported in a previous meta-analysis (3.8%).

• Journal of Preventive Medicine and Public Health
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• v.33 no.1
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• pp.76-82
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• 2000

Objectives : We attempted to assess He accuracy of ICD codes for cerebrovascular diseases in medical insurance claims (ICMIC) and to investigate the reasons for error. This study was designed as a preliminary study to establish a nationwide surveillance system. Methods : A total of 626 patients with medical insurance claims who indicated a diagnosis of cerebrovascular diseases during the period from 1993 to 1997 was selected from the Korea Medical Insurance Corporation cohort (KMIC cohort: 115,600 persons). The KMIC cohort was 10% of those insured who had taken health examinations in 1990 and 1992 consecutively. The registered medical record administrators were trained in the survey technique and gathered data from March to May 1999. The definition of cerebrovascular diseases in this study included cases which met ore of two criteria (Minnesota, WHO) or 'definite stroke' in CT/MRI finding. We questioned the medical record administrators to explain the error if the final diagnoses were not coded as stroke. Results : The accuracy rate of the ICMIC was 83.0% (425 cases) Medical records were not available for 8.2% (51 cases) due to the closing of hospitals, the absence of a computer system or omission of medical record, etc. Sixty-three cases (10.0%) were classified as impossible to interpret due to insufficient records in 'major clinical symptoms' or 'neurological deficits'. The most common reason was 'to meet review criteria of medical insurance benefits (52.9%)'. The department where errors in the ICMIC occurred most frequently was the department for medical insurance claims in the hospital. Conclusion : The accuracy rate of the ICMIC was 83.0%.

• Health Policy and Management
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• v.31 no.4
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• pp.451-461
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• 2021

Background: Readmissions related to lack of quality care harm both patients and health insurance finances. If the factors affecting readmission are identified, the readmission can be managed by controlling those factors. This paper aims to identify factors that affect readmissions of convalescent rehabilitation patients. Methods: Health Insurance Review and Assessment Service claims data were used to identify readmissions of convalescent patients who were admitted in hospitals and long-term care hospitals nationwide in 2018. Based on prior research, the socio-demographics, clinical, medical institution, and staffing levels characteristics were included in the research model as independent variables. Readmissions for convalescent rehabilitation treatment within 30 days after discharge were analyzed using logistic regression and generalization estimation equation. Results: The average readmission rate of the study subjects was 24.4%, and the risk of readmission decreases as age, length of stay, and the number of patients per physical therapist increase. In the patient group, the risk of readmission is lower in the spinal cord injury group and the musculoskeletal system group than in the brain injury group. The risk of readmission increases as the severity of patients and the number of patients per rehabilitation medicine specialist increases. Besides, the readmission risk is higher in men than women and long-term care hospitals than hospitals. Conclusion: "Reducing the readmission rate" is consistent with the ultimate goal of the convalescent rehabilitation system. Thus, it is necessary to prepare a mechanism for policy management of readmission.

• Journal of Preventive Medicine and Public Health
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• v.42 no.2
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• pp.135-142
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• 2009

Objectives : An appropriate sampling strategy for estimating an epidemiologic volume of diabetes has been evaluated through a simulation. Methods : We analyzed about 250 million medical insurance claims data submitted to the Health Insurance Review & Assessment Service with diabetes as principal or subsequent diagnoses, more than or equal to once per year, in 2003. The database was re-constructed to a 'patient-hospital profile' that had 3,676,164 cases, and then to a 'patient profile' that consisted of 2,412,082 observations. The patient profile data was then used to test the validity of a proposed sampling frame and methods of sampling to develop diabetic-related epidemiologic indices. Results : Simulation study showed that a use of a stratified two-stage cluster sampling design with a total sample size of 4,000 will provide an estimate of 57.04%(95% prediction range, 49.83 - 64.24%) for a treatment prescription rate of diabetes. The proposed sampling design consists, at first, stratifying the area of the nation into "metropolitan/city/county" and the types of hospital into "tertiary/secondary/primary/clinic" with a proportion of 5:10:10:75. Hospitals were then randomly selected within the strata as a primary sampling unit, followed by a random selection of patients within the hospitals as a secondly sampling unit. The difference between the estimate and the parameter value was projected to be less than 0.3%. Conclusions : The sampling scheme proposed will be applied to a subsequent nationwide field survey not only for estimating the epidemiologic volume of diabetes but also for assessing the present status of nationwide diabetes control.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.31 no.4
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• pp.214-224
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• 2020

Objectives: This study aimed to examine the trend in diagnostic prevalence of psychiatric disorders in children and adolescents. Methods: Individuals aged 0-18 years were included in the study based on the National Health Insurance Claims Data. To investigate the trends in diagnosis and diagnostic prevalence of psychiatric disorders reflecting the decrease in the birth rate, data were analyzed from 2010 as a reference year to 2015. Results: The number of patients diagnosed with psychiatric disorder decreased annually, from 23,412 on 2010 to 18,821 on 2015. The most common disorder was hyperkinetic disorder in male and depressive episode in female. Although there was no significant change in overall diagnostic prevalence rate of psychiatric disorders, age groups <10 years and some disorders had significant changes in prevalence rate. This study classified the diagnostic prevalence by age into two unique patterns: group in which the diagnosis rate increases with age and group in which the diagnosis rate peaks at a certain age and then decreases. Conclusion: Diagnostic prevalence of psychiatric disorders was different according to age and sex. These patterns should be reflected in the formulation of policies related to mental health and in medical practice for pediatric patients. It is urgent to identify how these patterns change in young adults.