{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T17:40:24Z","timestamp":1787506824233,"version":"build-2736575974"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T00:00:00Z","timestamp":1715040000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T00:00:00Z","timestamp":1715040000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Health Serv Res"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Medical narcotics must be administered under medical supervision because of their potential for misuse and abuse, leading to more dangerous and addictive substances. The control of medical narcotics requires close monitoring to ensure that they remain safe and effective. This study proposes a methodology that can effectively identify the overprescription of medical narcotics in hospitals and patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Social network analysis (SNA) was applied to prescription networks for medical narcotics. Prescription data were obtained from the Narcotics Information Management System in South Korea, which contains all data on narcotic usage nationwide. Two-mode networks comprising hospitals and patients were constructed based on prescription data from 2019 to 2021 for the three most significant narcotics: appetite suppressants, zolpidem, and propofol. Two-mode networks were then converted into one-mode networks for hospitals. Network structures and characteristics were analyzed to identify hospitals suspected of overprescribing.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The SNA identified hospitals that overprescribed medical narcotics. Patients suspected of experiencing narcotic addiction seek treatment in such hospitals. The structure of the network was different for the three narcotics. While appetite suppressants and propofol networks had a more centralized structure, zolpidem networks showed a less centralized but more fragmented structure. During the analysis, two types of hospitals caught our attention: one with a high degree, meaning that potential abusers have frequently visited the hospital, and the other with a high weighted degree, meaning that the hospital may overprescribe. For appetite suppressants, these two types of hospitals matched 84.6%, compared with 30.0% for propofol. In all three narcotics, clinics accounted for the largest share of the network. Patients using appetite suppressants were most likely to visit multiple locations, whereas those using zolpidem and propofol tended to form communities around their neighborhoods.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The significance of this study lies in its analysis of nationwide narcotic use reports and the differences observed across different types of narcotics. The social network structure between hospitals and patients varies depending on the composition of the medical narcotics. Therefore, these characteristics should be considered when controlling medication with narcotics. The results of this study provide guidelines for controlling narcotic use in other countries.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12913-024-11005-z","type":"journal-article","created":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T03:01:47Z","timestamp":1715050907000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Social network analysis for medical narcotics in South Korea: focusing on patients and healthcare organizations"],"prefix":"10.1186","volume":"24","author":[{"given":"Sang-Yoon","family":"Kim","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nam-Wook","family":"Cho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,7]]},"reference":[{"key":"11005_CR1","doi-asserted-by":"publisher","DOI":"10.1186\/s12913-023-09060-z","author":"SY Kim","year":"2023","unstructured":"Kim SY, Cho NW, Yoo MS, Han SY, Oh JW. Narcotics information management system in South Korea: system development and innovation. BMC Health Serv Res. 2023. https:\/\/doi.org\/10.1186\/s12913-023-09060-z.","journal-title":"BMC Health Serv Res"},{"key":"11005_CR2","unstructured":"Ministry of Food and Drug Safety. https:\/\/mfds.go.kr\/brd\/m_218\/list.do?multi_itm_seq=0&board_id=data0013&seq=&data_stts_gubun=C9999&srchTp=0&srchWord=%EB%A7%88%EC%95%BD%EB%A5%98. Accessed 12 Jan 2023."},{"key":"11005_CR3","unstructured":"UNODC. World Drug Report 2015. 2015. https:\/\/www.unodc.org\/wdr2015\/. Accessed 8 Feb 2022."},{"key":"11005_CR4","unstructured":"NAMSDL, NAMSDL. Model Prescription Monitoring Program (PMP) Act. 2015. https:\/\/namsdl.org\/topics\/pdmp\/. Accessed 8 Feb 2022."},{"key":"11005_CR5","volume-title":"Prescription monitoring programs in Canada: Best practice and program review","author":"B Sproule","year":"2015","unstructured":"Sproule B. Prescription monitoring programs in Canada: Best practice and program review. 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