The claims data of the Health Insurance Review and Assessment Service (HIRA) is an important source of information for healthcare service research. The claims data of HIRA is collected when healthcare service providers submit a claim to HIRA to be reimbursed for a service that they provided to patients. To improve the accessibility of healthcare service researchers to claims data of HIRA, HIRA has developed the Patient Samples which are extracted using a stratified randomized sampling method. The Patient Samples of HIRA consist of five tables: a table for general information (Table 20) containing socio-demographic information such as gender, age and medical aid, indicators for inpatient and outpatient services; a table for specific information on healthcare services provided (Table 30); a table for diagnostic information (Table 40); a table for outpatient prescriptions (Table 53) and a table for information on healthcare service providers (Table of providers). Researchers who are interested in using the Patient Sample data for research can apply via HIRA's website (https://www.hira.or.kr).
Delivery of Health Care ; Humans ; Inpatients ; Insurance, Health* ; National Health Programs ; Outpatients ; Prescriptions

Background: In 2018, the government increased the fee for the magnetic resonance imaging (MRI) image deciphering services of the external hospital to discourage the redundant MRI scan and to induce appropriate use of the MRI services. It is important to evaluate the effect of the policy to provide the basis for establishing other MRI-related policies. Methods: The healthcare data of the patients who had brain MRI scans were organized by episode and analyzed using the panel study in order to find out the effect of the MRI-related policy on the substitution effect and the medical expenses. Results: As a result of the increase in the fee of deciphering the MRI image, there has been an uplift in deciphering the MRI scan of the external hospital. It implies that more hospitals chose to use the MRI scan taken by other clinics or hospitals, rather than the MRI scan taken at their own facilities. Conclusion The research results imply that a policy that facilitates the exchange of the medical image data between the hospitals is needed in order to establish an efficient management system of the healthcare resources. Such improvement is expected to reduce the social cost and contribute to the stability in the finance of national health insurance.

Background/Aims: We investigated metabolic comorbidity status and patterns of medical institution utilization among breast cancer survivors using medical claims data from the Health Insurance Review and Assessment Service (HIRA). Methods: Using claims data obtained from the HIRA, we selected breast cancer survivors between 2010 and 2015. Descriptive statistics were calculated to determine the frequency of metabolic comorbidities, as well as to analyze patterns of medical institution utilization in accordance with disease status. Results: A total of 89,953 breast cancer survivors were identified. Among these, 12,364 (13.7%) had hypercholesterolemia, 20,754 (23.1%) had hypertension (HTN), and 11,102 (12.3%) had diabetes mellitus (DM). In particular, more than half of breast cancer survivors older than 60 years had HTN, and other diseases sharply increased beginning at age 50 years. For HTN, a total of 531,292 claims were submitted; more than 80% (n = 473,737) were from primary medical institutions, whereas only 2.4% (n = 12,551) were from tertiary medical institutions. The number of claims submitted for DM was 231,526; those from primary medical institutions accounted for 68.5% (n = 158,566), whereas claims from tertiary medical institutions accounted for 12.0% (n = 27,693). In subgroup analyses, the utilization of secondary and tertiary medical institutions was higher among patients with severe diseases and those diagnosed following their breast cancer diagnosis. Conclusions More than 10% of breast cancer survivors were diagnosed with a metabolic comorbidity. Through analysis of medical institution utilization patterns, we ascertained that a communication system linking secondary and tertiary medical institutions with primary medical institutions is needed.