
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39251861
72063
10.1038/s41598-024-72063-1
Article
Limitations of NHIC claim code-based surveillance and the necessity of UDI implementation in Korea
Choi Sooin 1
Kim Jin Kuk 2
Lee Jinhyoung 3
Choi Soo Jeong crystal@schmc.ac.kr

2
Lee You Kyoung cecilia@schmc.ac.kr

1
1 https://ror.org/03qjsrb10 grid.412674.2 0000 0004 1773 6524 Department of Laboratory Medicine and Genetics, Center for Medical Device Safety Monitoring, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, 170 Jomaru-ro, Bucheon, 14584 Republic of Korea
2 https://ror.org/03qjsrb10 grid.412674.2 0000 0004 1773 6524 Department of Internal Medicine, Center for Medical Device Safety Monitoring, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, 170 Jomaru-ro, Bucheon, 14584 Republic of Korea
3 https://ror.org/03qjsrb10 grid.412674.2 0000 0004 1773 6524 Department of Medical Engineering, Soonchunhyang University Bucheon Hospital, Bucheon, Republic of Korea
9 9 2024
9 9 2024
2024
14 2101416 1 2024
3 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
The E-Health Big Data Evidence Innovation Network (FeederNet) in Korea, based on the observational medical outcomes partnership (OMOP) common data model (CDM), had 72.3% participation from tertiary hospitals handling severe diseases as of October 2022. While this contributes to the activation of multi-institutional research, concerns about the comprehensiveness of device data persist due to the adoption of national health insurance corporation (NHIC) claim codes as device identifiers in the medical device field. This study critically evaluated the effectiveness and compatibility of NHIC claim codes and unique device identifier (UDI) within FeederNet to identify the optimal identifier for efficient Post-market surveillance (PMS). Specifically, this study addressed three main questions: (1) the number of UDIs classified as NHIC-covered items, (2) the number of UDIs included in each NHIC claim code, and (3) the number of NHIC claim codes each UDI covers. Among the 1,979,655 UDIs registered domestically, only 36.02% (712,983) were classified as covered by National Health Insurance. NHIC-covered medical devices were limited to categories (A) medical devices, (B) medical supplies, and (C) dental materials, excluding most software and in vitro diagnostics (IVD). Multiple UDIs could be registered under a single NHIC claim code, and a single UDI could be registered under multiple NHIC claim codes. Only 32.62% (13,756/42,171) of NHIC claim codes had registered UDIs, with an average of 53 UDIs per claim code. Of the UDIs listed as NHIC covered, 92.39% (659,046/713,341) had one claim code, while 7.25% (51,652) had multiple claim codes. Additionally, 2643 UDIs were listed as NHIC covered but had no registered claim codes. Due to this complex relationship, NHIC claim code-based PMS may pool safe and unsafe models or disperse problematic models across multiple claim codes, leading to a lower problem rate or insignificant differences between claim codes, thus reducing signal detection sensitivity compared to UDI-based PMS. In conclusion, NHIC claim code-based PMS has limitations in granularity and signal detection sensitivity, necessitating the adoption of UDI-based PMS to address these issues. The UDI system can enhance the accuracy of medical device identification and tracking, playing a crucial role in generating real-world evidence (RWE) by integrating data from various sources. Future research should explore specific strategies for integrating and utilizing UDI with NHIC claim codes, contributing to the implementation of a more reliable and comprehensive PMS in Korea’s healthcare system.

Subject terms

Health care
Medical research
Risk factors
Soonchunhyang University Research FundMinistry of Food and Drug Safety, Korea21173-MFDS-245 Lee You Kyoung issue-copyright-statement© Springer Nature Limited 2024
==== Body
pmcIntroduction

Enhancing the safety of medical devices is a critical aspect of the healthcare industry. The introduction of the European Union (EU) medical device regulation (MDR) mandates manufacturers to continuously monitor and collect data throughout the lifecycle of medical devices, necessitating more stringent safety evaluations1. Systematic data collection of device malfunctions and adverse events through real-world evidence (RWE) gathered from various sources is essential for effective post-market surveillance (PMS)2–5. Databases such as the manufacturer and user facility device experience (MAUDE) by the U.S. Food and Drug Administration (FDA), the database of adverse event notifications (DAEN) by the Australian Therapeutic Goods Administration (TGA), and the European Database on Medical Devices (EUDAMED) play a standard role in safety signal detection6. To strengthen PMS, Korea has established 19 medical device safety information monitoring centers7,8. However, considering the limitations of voluntary reporting, such as underreporting and bias, integrating active surveillance methods is essential9,10.

Active surveillance methods include establishing registries, electronic health records, safety evaluation sites, claims databases, social networks, and literature1,11. The CORE-MD PMS tool automatically searches and aggregates web-accessible safety notices such as device alerts and recalls according to specific device categories and the European Medical Device Nomenclature (EMDN)6. The FDA-led Sentinel Initiative and The National Evaluation System for health Technology (NEST) focus on using real-world data (RWD) and RWE for active surveillance to address FDA’s top priority of timely and accurate detection of medical device safety signals12–14. For RWE studies involving multiple institutions, standardizing and integrating data related to medical devices and electronic health records (EHRs) remains a significant challenge9,15,16. Various common data models (CDM) have been developed to provide a standardized approach for storing and organizing such clinical research data17–19.

To achieve the goal of “PMS for medical devices” through CDMs, two essential elements are necessary: (1) medical device identification information, and (2) safety information related to medical devices. When medical devices are used in patient care at medical institutions in Korea, two types of medical device identification data with different purposes are generated (Fig. 1). The first type is the National Health Insurance Corporation (NHIC) claim code used for insurance reimbursement when NHIC-covered medical devices are used. NHIC claim codes are assigned to various medical services, such as diagnosis, examination, treatment, surgery, and other healthcare activities within the health insurance system. While the costs for many medical materials are generally considered part of medical services and classified as “non-separately calculated” materials, some items are classified as medical materials for treatment (MMT) and receive specific NHIC claim codes for separate reimbursement by the NHIC20. For example, when a medical device considered as MMT, such as the ACRIVA BB UDM 611 model (VSY Biotechnology, Amsterdam, Netherlands), is used in surgery, the clinical department records the device usage and medical service provision in the EHR. The insurance claims department then files an insurance claim using the NHIC claim codes (S5117_Intraocular lens implantation, and I1201101_ACRIVA BB) (Fig. 1a). For non-covered medical devices like the Acriva Reviol BB MFM 611 (VSY Biotechnology, Amsterdam, Netherlands), patients pay the device cost directly, and there is no NHIC claim code; only the medical service (S5117_Intraocular lens implantation) is claimed to the NHIC (Fig. 1b). For some medical devices like the FX CorDiax 100 (Fresenius Medical Care AG & Co. KGaA, Frankfurt, Germany) used in hemodialysis, the device cost is considered part of the medical service cost (in this case, O7020_Hemodialysis), and only the medical service (O7020_Hemodialysis) is claimed to the NHIC (Fig. 1c). The second type of medical device identification data is the unique device identifier (UDI), used to report the consumption details of medical devices to the Ministry of Food and Drug Safety (MFDS). The MFDS oversees the approval and regulatory compliance of medical devices and mandates the UDI system to manage the entire lifecycle of medical devices, ensuring patient safety and enhancing the traceability of medical devices21. In Korea, starting with class 4 medical devices in 2019, by 2022, all medical devices manufactured and imported must display the UDI in the form of a barcode on the exterior and packaging22. Additionally, Korean hospitals are obligated to report UDI data for all purchased medical devices to the MFDS in the form of a medical device supply report, which does not include patient information. Consequently, when the logistics department purchases medical devices from manufacturers, they report the consumption of these devices to the MFDS using UDI codes (08718802039211, model ACRIVA BB UDM 611; 08718802040460, model Acriva Reviol BB MFM 611; 04039361104207, model FX CorDiax 100) (Fig. 1a–c).Fig. 1 The workflow of medical device data reporting in Korean medical institutions, detailing the processes for both National Health Insurance Corporation (NHIC) and Ministry of Food and Drug Safety (MFDS); (a) for medical devices considered MMT (materials for medical treatment), usage is claimed to NHIC using an NHIC claim code. (b) For non-covered medical devices, the cost is borne by patients, and only the medical service is claimed to NHIC. (c) For medical devices that cannot be separately calculated from the medical service, the cost is included in the service fee. Hospitals report UDI information for all purchased medical devices to the MFDS in a medical device supply report (excluding patient information). UDI unique device identification.

In Korea, the Federated E-Health Big Data for Evidence Renovation Network (FeederNet), based on the observational medical outcomes partnership (OMOP) CDM, was launched in 201923. OMOP is an international collaboration aimed at creating and applying open-source data analysis solutions for large health database networks24–26. As of October 2022, FeederNet includes 57 tertiary or secondary general hospitals27, with 72.3% (34/47) of tertiary hospitals handling severe diseases participating28,29. Despite ongoing efforts to utilize FeederNet's nationwide distributed research network for medical device PMS, concerns exist about the comprehensiveness of device data due to the adoption of NHIC claim codes as device identifiers within FeederNet19,30. While NHIC claim codes integrate smoothly within the Korean context, they lack global accessibility. Moreover, attractive alternatives such as the UDI, designed specifically for device identification, suggest that relying on NHIC claim codes may not be the optimal approach for medical device identification data.

Therefore, this study seeks to critically evaluate the effectiveness and compatibility of NHIC claim codes and UDIs within FeederNet, aiming to determine the most reliable and globally applicable method for medical device identification in Korea. By addressing this critical issue, we aim to enhance the robustness and international compatibility of PMS for medical devices.

Materials and methods

Data collection

This study utilized data from two primary sources: the NHIC claim code data for MMT and the UDI data.

NHIC claim code

NHIC claim codes are assigned to MMT, which includes consumable medical devices and certain quasi-drugs like gauze and bandages. These codes are structured into three levels: major class, subclass, and minor class, based on characteristics like purpose and function. The NHIC classifies MMT into the following classes: (1) nuclear medicine examination use, (2) suture use, (3) bone fusion and fracture fixation use, (4) soft tissue fixation for arthroscopic surgery, (5) artificial joint, (6) spinal material, (7) thoracic surgery use, (8) neurosurgery use, (9) ophthalmology, otolaryngology, and head and neck surgery use, (10) hemostasis use, (11) general material 1, (12) general material 2, (13) general material 3, (14) bundled cost items, (15) traditional Korean medicine material, (16) human tissue, (17) selective cost items. Additionally, for some not-covered medical devices, fixed price, not-covered codes are assigned to prevent excessive medical cost increases. It ensures that all medical institutions charge patients the same usage fee about these items. For this study, the May 2022 version of the health insurance review and assessment service: therapeutic material master file was used, which included information on reimbursement and non-reimbursement for treatment materials31.

UDI

The MFDS classifies medical devices based on their characteristics into the following groups: (A) medical instruments, (B) medical supplies, (C) dental materials, (E) software as a medical device, (I) devices for sample preparation, (J) devices for clinical chemistry, (K) devices for clinical immunology, (L) devices for blood transfusion, (M) devices for clinical microbiology, (N) devices for molecular diagnostics, (O) devices for immuno cyto/histo chemistry, (P) in vitro diagnostics (IVD) software. Additionally, medical devices in Korea are classified into four grades based on their potential risk to the human body32. The classification is as follows: class 1: devices with minimal potential harm, class 2: devices with low potential harm, class 3: devices with moderate potential harm, class 4: devices with high potential harm. The medical device integrated information system in Korea registers the UDIs of all medical devices currently being sold. The March 2023 version of the medical device standard code notification files in the medical device integrated information system was used, containing details such as company name, item name, grade, model name, UDI-DI code, NHIC covered/not-covered and NHIC claim code33. This system ensures that any medical devices which have had their certification or approval revoked are marked accordingly within the registry, rather than being removed. As a result, the system includes the UDIs of both approved and currently used devices as well as those that have been discontinued.

Study design

This study is a retrospective analysis aiming to evaluate the integration and coverage of UDIs within the NHIC system. Specifically, the study addressed three primary questions:Number of UDIs classified as NHIC-covered items: we extracted data on all medical devices categorized under NHIC coverage. This included all device types, ranging from simple consumables to complex diagnostic equipment.

Number of UDIs included in each NHIC claim code: each NHIC claim code, which represents a specific medical device or group of devices, was matched against the UDI database. The total number of UDIs associated with each claim code was quantified.

Number of NHIC claim codes each UDI is registered under: conversely, the registration of each UDI across different NHIC claim codes was analyzed to identify overlaps and multiple registrations of the same device under various codes.

Statistical analysis

All statistical analyses were performed using Analyse-it v5.10 (Analyse-it Software, Leeds, UK) and Microsoft Excel 2019 (Microsoft, Redmond, WA, USA). This study did not require Institutional Review Board approval as it did not involve human subjects or access to identifiable private information.

Results

Proportion of NHIC covered medical devices

The UDI of all medical devices registered in Korea was 1,979,655, of which 36.02% (712,983) were classified as NHIC covered (Table 1). NHIC covered medical devices were limited to (A) medical devices, (B) medical supplies, and (C) dental materials based on the MFDS item group. Software such as (E) software as a medical device, (P) IVD software, or IVDs such as (I) devices for sample preparation to (O) devices for immuno cyto/histochemistry were not classified as NHIC covered. However, among (J) devices for clinical chemistry, the two UDIs for pregnancy endocrine substance test items for clinical testing were classified as NHIC covered. However, since there was no registered NHIC billing code, it was assumed that a clerical error occurred when entering NHIC covered status. When explained by class, 8.92% of class 1 (39,083/438,334), 22.44% of class 2 (188,441/839,731), 75.03% of class 3 (402,650/536,677), and 50.21% of class 4 (82,809/164,913) were classified as NHIC covered. Because a significant number of UDIs (95,912) were not updated to the current MFDS item group and remained as an outdated group, the authors marked them as undefined, and 27.75% (26,617/95,912) of them were classified as NHIC covered.Table 1 Percentage of UDIs with NHIC claim codes across different medical device categories (number of UDIs with NHIC claim codes/total UDI).

MFDS group	Class I	Class II	Class III	Class IV	Total	
(A) Medical instruments	2.41 (7141/295,773)	21.57 (85,563/396,729)	11.77 (4518/38,389)	90.10 (17,589/19,522)	15.30 (114,811/750,413)	
(B) Medical supplies	59.23 (25,635/43,282)	58.60 (17,148/29,264)	87.03 (339,553/390,148)	42.03 (51,490/122,511)	74.13 (433,826/585,205)	
(C) Dental materials	0.00 (0/43,625)	20.73 (79,019/381,174)	57.60 (57,211/99,332)	51.89 (1497/2885)	26.13 (137,727/527,016)	
(E) Software as a medical device	0.00 (0/48)	0.00 (0/358)	0.00 (0/4)	NA (0/0)	0.00 (0/410)	
(I) Devices for sample preparation	0.00 (0/2281)	0.00 (0/17)	NA (0/0)	NA (0/0)	0.00 (0/2298)	
(J) Devices for clinical chemistry	0.00 (0/2322)	0.04 (2/4564)	0.00 (0/751)	NA (0/0)	0.03 (2/7637)	
(K) Devices for clinical immunology	0.00 (0/253)	0.00 (0/3221)	0.00 (0/2208)	0.00 (0/327)	0.00 (0/6009)	
(L) Devices for blood transfusion	0.00 (0/23)	NA (0/0)	0.00 (0/126)	0.00 (0/53)	0.00 (0/202)	
(M) Devices for clinical microbiology	0.00 (0/942)	0.00 (0/557)	0.00 (0/32)	NA (0/0)	0.00 (0/1531)	
(N) Devices for molecular diagnostics	0.00 (0/11)	0.00 (0/169)	0.00 (0/1163)	0.00 (0/22)	0.00 (0/,365)	
(O) Devices for immuno cyto/histo chemistry	0.00 (0/409)	0.00 (0/1219)	0.00 (0/28)	NA (0/0)	0.00 (0/1656)	
(P) IVD software	NA (0/0)	NA (0/0)	0.00 (0/1)	NA (0/0)	0.00 (0/1)	
Undefined	12.78 (6307/49,365)	29.87 (6709/22,459)	30.43 (1368/4495)	62.44 (12,233/19,593)	27.75 (26,617/95,912)	
Total	8.92 (39,083/438,334)	22.44 (188,441/839,731)	75.03 (402,650/536,677)	50.21 (82,809/164,913)	36.02 (712,983/1,979,655)	
MMT materials for medical treatment, NHIC National Health Insurance Corporation, IVD in vitro diagnostics, MFDS ministry of food and drug safety, UDI unique device identification, NA not applicable.

Analysis of UDI registrations per NHIC claim code

There are 42,171 NHIC claim codes related to MMT, and with 1,979,655 UDIs, it can be expected that multiple UDIs are registered under a single NHIC claim code. To illustrate the concept of multiple UDIs being registered under a single NHIC claim code, we present the example of NHIC subclass 078020 (single chamber ventricular defibrillator—MRI compatible device) (Table 2). This subclass includes a total of 15 claim codes. For each claim code, between 1 and 8 UDIs were registered. However, one NHIC claim code (G8301517) had no registered UDIs.Table 2 Registration of UDIs under NHIC claim codes for single chamber ventricular defibrillators—MRI compatible.

NHIC claim code	Product name	UDI	
G8301119	IFORIA VR-T (Biotronik SE & Co., Berlin, Germany)	04035479127107	04035479127169			
G8301133	PLATINIUM, EDIS, ULYS (MicroPort CRM S.r.l, Saluggia, Italy)	08031527018478				
G8301219	IFORIA VR-T DX (Biotronik SE & Co., Berlin, Germany)	04035479127220				
G8301403	EVERA MRI XT ICD VR (Medtronic Inc., MN, USA)	00763000612047	00763000612207	00763000612030	00763000612191	
G8301417	AUTOGEN, PERCIVA, RESONATE EL, MOMENTUM MRI ICD VR (Boston Scientific Corporation, MN, USA)	00802526557590	00802526594540	00802526594403	00802526558160	
00802526558146	00802526557613	00802526594113	00802526594502	
G8301503	COBALT MRI XT ICD VR (Medtronic Inc., MN, USA)	00763000711344	00763000711351			
G8301519	INTICA VR-T & RIVACOR VR-T (Biotronik SE & Co., Berlin, Germany)	04035479142216	04035479142223	04035479156817		
G8301617	EMBLEM S-ICD MRI (Boston Scientific Corporation, MN, USA)	00802526585401				
G8301619	INTICA VR-T DX & RIVACOR VR-T DX (Biotronik SE & Co., Berlin, Germany)	04035479142209	04035479156800			
G8301719	INTICA NEO 7 VR-T (Biotronik SE & Co., Berlin, Germany)	04035479156862				
G8301721	ELLIPSE VR MRI (Q TYPE) (Abbott Medical, CA, USA)	05414734507646	05414734507653	05415067031990		
G8301819	INTICA NEO 7 VR-T DX (Biotronik SE & Co., Berlin, Germany)	08800215900001				
G8301319	IPERIA 7 VR-T (Biotronik SE & Co., Berlin, Germany)	04035479129491				
G8301419	IPERIA 7 VR-T DX (Biotronik SE & Co., Berlin, Germany)	04035479129453				
G8301517	RESONATE EL MRI ICD VR (Boston Scientific Corporation, MN, USA)	No				
NHIC National Health Insurance Corporation, UDI unique device identification.

Expanding the analysis to a broader context, Table 3 provides comprehensive information on the number of NHIC claim codes for each MMT class and the number of UDIs registered per NHIC claim code. Only 32.62% (13,756) of NHIC claim codes have UDIs registered. The average number of UDIs registered per NHIC claim code was 53, with a median of 7. The NHIC claim code with the most registered UDIs was F0018185 (Jasper Spinal Fixed System Screw Set, GBS Commonwealth, Seoul, Korea) with 38,873 UDIs. NHIC claim codes with no registered UDIs are likely (1) codes no longer in use, (2) non-medical devices such as quasi-drugs. NHIC class (11) general material 1 had the highest number of NHIC claim codes with 7232, but only 18.72% (1354) had UDIs registered. None of the 2676 NHIC claim codes in NHIC class (16) human tissue had registered UDIs. The NHIC class with the highest registration rate was (2) suture use, with UDIs registered for 59.97% of claim codes.Table 3 Analysis of UDI registration rates and quantities per NHIC claim code across NHIC classes.

NHIC classification	Percent of NHIC claim codes with UDI	Number of UDIs per NHIC claim code	
Mean	Median	Max	
(1) Nuclear medicine examination use	25.0 (1/4)	1	1	1	
(2) Suture use	59.97 (1224/2041)	21	7	415	
(3) Bone fusion and fracture fixation use	45.96 (2574/5601)	31	8	1998	
(4) Soft tissue fixation for arthroscopic surgery	57.18 (215/376)	11	5	148	
(5) Artificial joint	49.43 (869/1758)	41	15	1108	
(6) Spinal material	39.48 (820/2077)	275	30	38,873	
(7) Thoracic surgery use	42.97 (489/1138)	9	4	398	
(8) Neurosurgery use	45.44 (364/801)	6	2	156	
(9) Ophthalmology, otolaryngology and head and neck surgery use	44.31 (249/562)	29	8	268	
(10) Hemostasis use	54.92 (1896/3452)	47	12	2466	
(11) General material 1	18.72 (1354/7232)	27	4	8783	
(12) General material 2	49.58 (1226/2473)	106	7	12,265	
(13) General material 3	33.1 (1820/5498)	22	3	2784	
(14) Bundled cost items	45.37 (103/227)	378	36	8190	
(15) Traditional Korean medicine material	16.67 (2/12)	6	6	7	
(16) Human tissue	0.0 (0/2676)	0	0	0	
(17) Selective cost items	N/A (0/0)	0	0	0	
Fixed cost, not-covered	8.81 (550/6243)	26	5	1239	
Total	32.62 (13,756/42,171)	53	7	38,873	
MMT materials for medical treatment, NHIC National Health Insurance Corporation, UDI unique device identification.

Using the product EMBLEM S-ICD (Boston Scientific Corporation, MN, USA) as an example, we simulated the difference that NHIC claim code and UDI-based PMS could make in detecting medical device adverse event signals (Fig. 2). In this scenario, two models (A219 and A209) are included, both registered with the MFDS under the product name “EMBLEM S-ICD and EMBLEM MRI S-ICD” without distinction. A219 is considered an MMT and is assigned NHIC claim code G8301617, while A209 is not. Performing PMS using NHIC claim code G8301617 would pool the three UDIs associated with A219 without distinction, while A209 would not be captured in this surveillance. Among the A219 models, UDI 00802526590405 indicates a higher rate of pacing issues, suggesting potential quality issues with the device. However, NHIC claim code-based PMS may underestimate the increased pacing issue rate caused by UDI 0080252659405 because it cannot distinguish different UDIs within the same claim code.Fig. 2 Hypothetical comparison of UDI-based and NHIC claim code-based PMS in detecting adverse event signals for single chamber ventricular defibrillator devices. PMS post-market surveillance, NHIC National Health Insurance Corporation, MMT materials for medical treatment, UDI unique device identification, DI device identifier.

Analysis of NHIC claim code registrations per UDI

In principle, there is no limit to the number of NHIC claim codes for which an UDI can be registered, but a maximum of five NHIC claim codes are listed in the UDI file for each UDI (Table 4). A total of 713,341 UDIs classified as ‘NHIC covered’ were enrolled. 92.39% (659,046/713,341) of UDIs had only one NHIC claim code registered each, whereas 51,652 UDIs had multiple NHIC claim codes registered. Total 2,643 UDIs had no NHIC claim code registered.Table 4 Analysis of multiple NHIC claim code registrations for UDIs.

NHIC classification	Number of UDI with NHIC claim code	Number of NHIC claim codes registered per UDI (%)	
0	1	2	3	4	5	
(1) Nuclear medicine examination use	1	0 (0.0%)	1 (100.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	
(2) Suture use	25,113	0 (0.0%)	25,018 (99.62%)	95 (0.38%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	
(3) Bone fusion and fracture fixation use	78,761	0 (0.0%)	76,874 (97.6%)	1205 (1.53%)	287 (0.36%)	321 (0.41%)	74 (0.09%)	
(4) Soft tissue fixation for arthroscopic surgery	2263	0 (0.0%)	2263 (100.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	
(5) Artificial joint	33,787	0 (0.0%)	32,643 (96.61%)	592 (1.75%)	248 (0.73%)	304 (0.9%)	0 (0.0%)	
(6) Spinal material	223,389	0 (0.0%)	218,287 (97.72%)	1,981 (0.89%)	1203 (0.54%)	1918 (0.86%)	0 (0.0%)	
(7) Thoracic surgery use	4493	0 (0.0%)	4493 (100.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	
(8) Neurosurgery use	2020	0 (0.0%)	1,902 (94.16%)	78 (3.86%)	38 (1.88%)	2 (0.1%)	0 (0.0%)	
(9) Ophthalmology, otolaryngology and head and neck surgery use	7100	0 (0.0%)	7062 (99.46%)	0 (0.0%)	38 (0.54%)	0 (0.0%)	0 (0.0%)	
(10) Hemostasis use	87,216	0 (0.0%)	82,064 (94.09%)	5,020 (5.76%)	54 (0.06%)	60 (0.07%)	18 (0.02%)	
(11) General material 1	36,272	0 (0.0%)	36,034 (99.34%)	232 (0.64%)	0 (0.0%)	0 (0.0%)	6 (0.02%)	
(12) General material 2	128,618	0 (0.0%)	115,869 (90.09%)	12,692 (9.87%)	7 (0.01%)	0 (0.0%)	50 (0.04%)	
(13) General material 3	39,982	0 (0.0%)	31,353 (78.42%)	6757 (16.9%)	611 (1.53%)	0 (0.0%)	1261 (3.15%)	
(14) Bundled cost items	28,348	0 (0.0%)	11,986 (42.28%)	202 (0.71%)	3646 (12.86%)	5361 (18.91%)	7153 (25.23%)	
(15) Traditional Korean medicine material	12	0 (0.0%)	12 (100.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	
(16) Human tissue	0	0 (NA)	0 (NA)	0 (NA)	0 (NA)	0 (NA)	0 (NA)	
(17) Selective cost items	0	0 (NA)	0 (NA)	0 (NA)	0 (NA)	0 (NA)	0 (NA)	
Fixed cost, not-covered	13,323	0 (0.0%)	13,185 (98.96%)	114 (0.86%)	0 (0.0%)	24 (0.18%)	0 (0.0%)	
No NHIC claim code*	2643	2643 (100.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	0 (0.0%)	
Total	713,341	2,643 (0.37%)	659,046 (92.39%)	28,968 (4.06%)	6132 (0.86%)	7990 (1.12%)	8562 (1.2%)	
*The 2643 UDIs marked as ‘NHIC covered’ actually have no registered NHIC claim codes. This discrepancy is presumed to be due to clerical errors made by manufacturers/importers when entering UDI information into the integrated medical device information system.

NHIC National Health Insurance Corporation, UDI unique device identification, NA not applicable.

Discussion

Under the leadership of the government, major hospitals in Korea have invested substantial resources to establish FeederNet, adopting NHIC claim codes as the data source for medical device identification. Consequently, NHIC claim codes extracted from each hospital’s EHR are mapped to standardized codes in FeederNet according to preset rules, significantly facilitating multi-institutional research17,20,23,26,27,34. As of 2016, 97.1% of the Korean population is covered by National Health Insurance, and NHIC claim codes offer a systematic and nationally standardized data source30, making their adoption logical. This study aimed to predict whether NHIC claim code-based medical device identification information within FeederNet could enable accurate and efficient PMS by examining the relationship between all distributed UDIs and NHIC claim codes in Korea.

NHIC claim code-based medical device PMS can only be performed on a limited number of devices registered as MMT (36.02%, 712,983/1,979,655) (Table 1). Specifically, PMS is impossible for all software and IVD, and only 8.92% (39,083/438,334) of Class I medical devices would be eligible. Given the low risk associated with Class I devices, the exclusion of the majority (91.08%) from PMS might not seem critical. However, Class I devices, due to their low risk, undergo less stringent safety evaluation criteria at the approval stage, such as sales notification and good manufacturing practice (GMP) procedures if sufficient equivalence with existing devices is assured35,36. The authors express significant concern that Class I devices, which are not thoroughly evaluated at the approval stage, cannot be adequately monitored at the PMS stage. Additionally, newly developed or rare medical devices often require manufacturers to submit post-market data on safety and efficacy, including adverse events and safety information from both domestic and international sources, as these devices typically have more limited pre-market clinical data35. To verify the safety and efficacy of the product, the manufacturer must provide sufficient clinical evidence demonstrating that the medical device performs adequately under normal use conditions and maintains an acceptable minimum rate of adverse effects, considering the predictable risks and frequencies in relation to the benefits provided37. However, administrative processing times for assigning NHIC claim codes to these devices can delay PMS. Moreover, high-cost devices that pose a financial burden on NHIC or those with a limited patient population may not receive NHIC claim codes.

NHIC claim code-based PMS is expected to lack the granularity and signal detection sensitivity compared to UDI-based PMS. NHIC claim codes may group multiple device models under the same code, obscuring distinctions at the UDI level (Tables 2 and 3). As illustrated in Fig. 2, NHIC claim codes can pool safe and unsafe models, potentially underestimating problem rates due to the larger denominator. Additionally, multiple NHIC claim codes may be assigned to a single UDI (Table 4), further complicating signal detection and increasing the likelihood of failing to identify safety signals. This reduced sensitivity could impact the detection of defects in specific lots or batches and the differentiation of safety profiles between models.

An ideal nomenclature for medical devices should be clear, unambiguous, comprehensive, structured yet flexible, finely granulated, and specific, ensuring interoperability across various healthcare entities to guarantee effective PMS38. The UDI system is designed to ensure precise identification and tracking of medical devices, facilitating effective communication among stakeholders throughout the device lifecycle39. It provides a standard format for linking device information across registries, datasets, and information technology systems, enhancing data integration and analysis from diverse sources40, and playing a crucial role in establishing RWE for medical devices37. The ThermoCool project, for instance, used UDI linked to EHR to identify patients exposed to specific catheters16,41. Thus, while NHIC claim codes serve a purpose, the inherent limitations in signal detection sensitivity highlight the necessity of UDI-based PMS for accurate and reliable tracking30.

Despite its potential, the UDI system remains largely disconnected from the rest of Korea’s medical system, such as NHIC claims. While MFDS’s UDI database provides NHIC claim code information for each UDI, NHIC does not require UDI submission during claims processing, limiting the generation of patient-specific device usage data. Enhancing the availability of medical device data requires recognizing the value of UDI and making conscious decisions to integrate it within EHRs42. Starting June 2022, MFDS mandated biannual submission of patient usage records for certain high-risk devices, including silicone gel breast implants and metal-on-metal hip implants, by all medical institutions43. This includes patient information and device details (UDI and usage date), ensuring that UDI information is recorded for these devices. To further promote UDI adoption, it is proposed to integrate UDI data capture into the Korean Health and Medical Certification Institute’s medical device management certification criteria44 and to mandate UDI submission in NHIC claims15. Expanding UDI recording within EHRs offers comprehensive insights into patient health and device safety and efficacy. However, simply adjusting the NHIC claim system or modifying EHRs to record UDI alone will not spontaneously create an effective PMS system.

This study has several limitations. Firstly, the data sources used are specific to the Korean healthcare system, which benefits from a largely unified national data infrastructure due to the extensive coverage of the National Health Insurance. Additionally, NHIC claim codes are more granular than the current procedural terminology (CPT) codes used in other countries. Variations in regulations, healthcare practices, and data availability across different countries could yield different results, making it challenging to generalize the findings globally. Secondly, the study acknowledges data integrity issues, particularly potential inaccuracies or inconsistencies within the NHIC claim code and UDI databases, but does not extensively address or mitigate these concerns. Some devices in the UDI data were classified as ‘undefined’ due to outdated categorization by MFDS (Table 1). As shown in Table 4, 2643 UDIs marked as ‘NHIC covered’ lacked registered EDI codes due to clerical errors during data entry. Inaccurate medical device information can introduce biases or limitations affecting PMS outcomes. Regulatory authorities must ensure the reliability of information through data accuracy verification and monitoring processes. Lastly, while the study proposes integrating UDI into NHIC claim forms to enhance PMS, it does not delve into the feasibility or potential challenges associated with this implementation. Future research should focus on addressing logistical, technological, and regulatory hurdles to achieve effective integration.

In conclusion, while NHIC claim code-based PMS has limitations in granularity and signal detection sensitivity, UDI-based PMS is essential for accurate and reliable tracking. The UDI system enhances medical device identification and tracking accuracy, facilitating data integration from diverse sources to generate RWE. Future research should explore specific strategies for integrating and utilizing UDI with NHIC claim codes, contributing to a more reliable and comprehensive PMS in Korea’s healthcare system.

Acknowledgements

The authors would like to express gratitude to Gyeongha Seo, Jiyeon Kim, and Sanghyeop Mun, National Institute of Medical Device Safety Information (NIDS), for their invaluable collaboration and support in providing us with medical device information.

Author contributions

Conceptualization, Y.K.L; methodology, S.C and J.L; investigation, S.C and S.J.C; writing—original draft preparation, S.C; writing—review and editing, Y.K.L, S.J.C, and J.K.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Soonchunhyang University Research Fund and a research grant (grant number: 21173-MFDS-245) from the Ministry of Food and Drug Safety, Korea.

Data availability

The data supporting the findings of this study are publicly available and were obtained from the websites of the Ministry of the Interior and Safety and the Ministry of Food and Drug Safety. Detailed webpage addresses where these data can be accessed are provided in the Materials and Methods section of this article.

Competing interests

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
References

1. Pane J EU postmarket surveillance plans for medical devices Pharmacoepidemiol. Drug Saf. 2019 28 1155 1165 10.1002/pds.4859 31318470
Pane, J. et al. EU postmarket surveillance plans for medical devices. Pharmacoepidemiol. Drug Saf. 28, 1155–1165 (2019).31318470 10.1002/pds.4859
2. Fraser AG Implementing the new European regulations on medical devices—Clinical responsibilities for evidence-based practice: A report from the regulatory affairs committee of the European Society of Cardiology Eur. Heart J. 2020 41 2589 2596 10.1093/eurheartj/ehaa382 32484542
Fraser, A. G. et al. Implementing the new European regulations on medical devices—Clinical responsibilities for evidence-based practice: A report from the regulatory affairs committee of the European Society of Cardiology. Eur. Heart J. 41, 2589–2596 (2020).32484542 10.1093/eurheartj/ehaa382
3. Wang X Endovascular aneurysm repair devices as a use case for postmarketing surveillance of medical devices JAMA Intern. Med. 2023 183 1090 1097 10.1001/jamainternmed.2023.3562 37603326
Wang, X. et al. Endovascular aneurysm repair devices as a use case for postmarketing surveillance of medical devices. JAMA Intern. Med. 183, 1090–1097 (2023).37603326 10.1001/jamainternmed.2023.3562
4. Choi S Choi SJ Kim JK Lee Y-W Lee YK Real-world evidence of point-of-care glucometers: Enhanced passive surveillance and adverse event reporting status in Korea and the United States Ann. Lab. Med. 2023 43 515 519 10.3343/alm.2023.43.5.515 37080755
Choi, S., Choi, S. J., Kim, J. K., Lee, Y.-W. & Lee, Y. K. Real-world evidence of point-of-care glucometers: Enhanced passive surveillance and adverse event reporting status in Korea and the United States. Ann. Lab. Med. 43, 515–519 (2023).37080755 10.3343/alm.2023.43.5.515
5. Choi S Choi SJ Kim JK Lee J Lee YK adverse events associated with the use of leukocyte reduction filters and blood transfusion sets: Experience of a single institute in Korea and status of adverse event reporting in Korea and the United States Korean J. Blood Transfus. 2022 33 161 170 10.17945/kjbt.2022.33.3.161
Choi, S., Choi, S. J., Kim, J. K., Lee, J. & Lee, Y. K. adverse events associated with the use of leukocyte reduction filters and blood transfusion sets: Experience of a single institute in Korea and status of adverse event reporting in Korea and the United States. Korean J. Blood Transfus. 33, 161–170 (2022).10.17945/kjbt.2022.33.3.161
6. Ren Y Bertoldi M Fraser AG Caiani EG Validation of CORE-MD PMS support tool: A novel strategy for aggregating information from notices of failures to support medical devices’ post-market surveillance Ther. Innov. Regul. Sci. 2023 57 589 602 10.1007/s43441-022-00493-y 36652105
Ren, Y., Bertoldi, M., Fraser, A. G. & Caiani, E. G. Validation of CORE-MD PMS support tool: A novel strategy for aggregating information from notices of failures to support medical devices’ post-market surveillance. Ther. Innov. Regul. Sci. 57, 589–602 (2023).36652105 10.1007/s43441-022-00493-y
7. Choi S Which health impacts of medical device adverse event should be reported immediately in Korea? J. Patient Saf. 2022 18 e591 10.1097/PTS.0000000000000877 34091493
Choi, S. et al. Which health impacts of medical device adverse event should be reported immediately in Korea?. J. Patient Saf. 18, e591 (2022).34091493 10.1097/PTS.0000000000000877
8. Choi SJ The establishment of the Korean medical device safety information monitoring center: Reviewing ten years of experience Health Policy 2021 125 941 946 10.1016/j.healthpol.2021.04.017 33994214
Choi, S. J. et al. The establishment of the Korean medical device safety information monitoring center: Reviewing ten years of experience. Health Policy 125, 941–946 (2021).33994214 10.1016/j.healthpol.2021.04.017
9. Chung G Etter K Yoo A Medical device active surveillance of spontaneous reports: A literature review of signal detection methods Pharmacoepidemiol. Drug Saf. 2020 29 369 379 10.1002/pds.4980 32128936
Chung, G., Etter, K. & Yoo, A. Medical device active surveillance of spontaneous reports: A literature review of signal detection methods. Pharmacoepidemiol. Drug Saf. 29, 369–379 (2020).32128936 10.1002/pds.4980
10. Drozda JP Jr Testing a cloud-based model for active surveillance of medical devices with analyses of coronary stent safety using the data extraction and longitudinal trend analysis (DELTA) system Med. Devices Evid. Res. 2024 17 97 105 10.2147/MDER.S445160
Drozda, J. P. Jr. et al. Testing a cloud-based model for active surveillance of medical devices with analyses of coronary stent safety using the data extraction and longitudinal trend analysis (DELTA) system. Med. Devices Evid. Res. 17, 97–105 (2024).10.2147/MDER.S445160
11. Pane J Coloma PM Verhamme KMC Sturkenboom MCJM Rebollo I Evaluating the safety profile of non-active implantable medical devices compared with medicines Drug Saf. 2017 40 37 47 10.1007/s40264-016-0474-1 27928726
Pane, J., Coloma, P. M., Verhamme, K. M. C., Sturkenboom, M. C. J. M. & Rebollo, I. Evaluating the safety profile of non-active implantable medical devices compared with medicines. Drug Saf. 40, 37–47 (2017).27928726 10.1007/s40264-016-0474-1
12. Mofid S Bolislis WR Kühler TC Real-world data in the postapproval setting as applied by the EMA and the US FDA Clin. Ther. 2022 44 306 322 10.1016/j.clinthera.2021.12.010 35074209
Mofid, S., Bolislis, W. R. & Kühler, T. C. Real-world data in the postapproval setting as applied by the EMA and the US FDA. Clin. Ther. 44, 306–322 (2022).35074209 10.1016/j.clinthera.2021.12.010
13. Fleurence RL Shuren J Advances in the use of real-world evidence for medical devices: An update from the national evaluation system for health technology Clin. Pharmacol. Ther. 2019 106 30 10.1002/cpt.1380 30888048
Fleurence, R. L. & Shuren, J. Advances in the use of real-world evidence for medical devices: An update from the national evaluation system for health technology. Clin. Pharmacol. Ther. 106, 30 (2019).30888048 10.1002/cpt.1380
14. Cipriani A Generating comparative evidence on new drugs and devices after approval Lancet 2020 395 998 1010 10.1016/S0140-6736(19)33177-0 32199487
Cipriani, A. et al. Generating comparative evidence on new drugs and devices after approval. Lancet 395, 998–1010 (2020).32199487 10.1016/S0140-6736(19)33177-0
15. Dhruva, S. S., Ridgeway, J. L., Ross, J. S., Drozda, J. P. & Wilson, N. A. Exploring unique device identifier implementation and use for real-world evidence: a mixed-methods study with NESTcc health system network collaborators. BMJ Surg. Intervent. Health Technol. 5. e000167 (2023).
16. Dhruva SS Safety and effectiveness of a catheter with contact force and 6-hole irrigation for ablation of persistent atrial fibrillation in routine clinical practice JAMA Netw. Open 2022 5 e2227134 e2227134 10.1001/jamanetworkopen.2022.27134 35976649
Dhruva, S. S. et al. Safety and effectiveness of a catheter with contact force and 6-hole irrigation for ablation of persistent atrial fibrillation in routine clinical practice. JAMA Netw. Open 5, e2227134–e2227134 (2022).35976649 10.1001/jamanetworkopen.2022.27134
17. Choi S Choi SJ Shin JW Yoon YA Common data model-based analysis of selective leukoreduction protocol compliance at three hospitals Ann. Lab. Med. 2023 43 187 195 10.3343/alm.2023.43.2.187 36281513
Choi, S., Choi, S. J., Shin, J. W. & Yoon, Y. A. Common data model-based analysis of selective leukoreduction protocol compliance at three hospitals. Ann. Lab. Med. 43, 187–195 (2023).36281513 10.3343/alm.2023.43.2.187
18. Henke E Conceptual design of a generic data harmonization process for OMOP common data model BMC Med. Inform. Decis. Mak. 2024 24 58 10.1186/s12911-024-02458-7 38408983
Henke, E. et al. Conceptual design of a generic data harmonization process for OMOP common data model. BMC Med. Inform. Decis. Mak. 24, 58 (2024).38408983 10.1186/s12911-024-02458-7
19. Yu Y Integrating real-world data to assess cardiac ablation device outcomes in a multicenter study using the OMOP common data model for regulatory decisions: Implementation and evaluation JAMIA Open 2023 10.1093/jamiaopen/ooac108 38098478
Yu, Y. et al. Integrating real-world data to assess cardiac ablation device outcomes in a multicenter study using the OMOP common data model for regulatory decisions: Implementation and evaluation. JAMIA Open10.1093/jamiaopen/ooac108 (2023).38098478 10.1093/jamiaopen/ooac108
20. Choi Y Development of a mobile personal health record application designed for emergency care in Korea; integrated information from multicenter electronic medical records Appl. Sci. 2020 10 6711 10.3390/app10196711
Choi, Y. et al. Development of a mobile personal health record application designed for emergency care in Korea; integrated information from multicenter electronic medical records. Appl. Sci. 10, 6711 (2020).10.3390/app10196711
21. Lim S Jeong H Kwon B-J Strategy for linking data between the health insurance review & assessment service and the ministry of food and drug safety using the integrated medical device information system Health Insur. Rev. Assess. Serv. Res. 2024 4 34 48
Lim, S., Jeong, H. & Kwon, B.-J. Strategy for linking data between the health insurance review & assessment service and the ministry of food and drug safety using the integrated medical device information system. Health Insur. Rev. Assess. Serv. Res. 4, 34–48 (2024).
22. Kim D-S Song I A review on the post-market surveillance of medical devices in the United States and its Implication: A focus on real-world data using unique device identification of medical devices Health Insur. Rev. Assess. Serv. Res. 2023 3 22 36
Kim, D.-S. & Song, I. A review on the post-market surveillance of medical devices in the United States and its Implication: A focus on real-world data using unique device identification of medical devices. Health Insur. Rev. Assess. Serv. Res. 3, 22–36 (2023).
23. Lee GH Feasibility study of federated learning on the distributed research network of OMOP common data model Healthc. Inform. Res. 2023 29 168 173 10.4258/hir.2023.29.2.168 37190741
Lee, G. H. et al. Feasibility study of federated learning on the distributed research network of OMOP common data model. Healthc. Inform. Res. 29, 168–173 (2023).37190741 10.4258/hir.2023.29.2.168
24. Künnapuu K Trajectories: A framework for detecting temporal clinical event sequences from health data standardized to the observational medical outcomes partnership (OMOP) common data model JAMIA Open 2022 10.1093/jamiaopen/ooac021 35571357
Künnapuu, K. et al. Trajectories: A framework for detecting temporal clinical event sequences from health data standardized to the observational medical outcomes partnership (OMOP) common data model. JAMIA Open10.1093/jamiaopen/ooac021 (2022).35571357 10.1093/jamiaopen/ooac021
25. Kim JE The effect of statins on mortality of patients with chronic kidney disease based on data of the observational medical outcomes partnership common data model (OMOP-CDM) and Korea National Health Insurance Claims Database Front. Nephrol. 2022 1 821585 10.3389/fneph.2021.821585 37674813
Kim, J. E. et al. The effect of statins on mortality of patients with chronic kidney disease based on data of the observational medical outcomes partnership common data model (OMOP-CDM) and Korea National Health Insurance Claims Database. Front. Nephrol. 1, 821585 (2022).37674813 10.3389/fneph.2021.821585
26. Kim C Data resource profile: Health insurance review and assessment service Covid-19 observational medical outcomes partnership (HIRA Covid-19 OMOP) database in South Korea Int. J. Epidemiol. 2024 10.1093/ije/dyae062 38961644
Kim, C. et al. Data resource profile: Health insurance review and assessment service Covid-19 observational medical outcomes partnership (HIRA Covid-19 OMOP) database in South Korea. Int. J. Epidemiol.10.1093/ije/dyae062 (2024).38961644 10.1093/ije/dyae062
27. You SC Lee S Choi B Park RW Establishment of an international evidence sharing network through common data model for cardiovascular research Korean Circ. J. 2022 52 853 864 10.4070/kcj.2022.0294 36478647
You, S. C., Lee, S., Choi, B. & Park, R. W. Establishment of an international evidence sharing network through common data model for cardiovascular research. Korean Circ. J. 52, 853–864 (2022).36478647 10.4070/kcj.2022.0294
28. Health Insurance Review & Assessment Service, HIRA bigdata open portal. https://opendata.hira.or.kr/op/opc/olapYadmStatInfoTab1.do. Accessed 2 Jul 2024. (2023).
29. Evidnet. FeederNet. https://feedernet.com/. Accessed 14 Mar 2023. (2022).
30. Choi S Preliminary feasibility assessment of CDM-based active surveillance using current status of medical device data in medical records and OMOP-CDM Sci. Rep. 2021 11 1 13 10.1038/s41598-021-03332-6 33414495
Choi, S. et al. Preliminary feasibility assessment of CDM-based active surveillance using current status of medical device data in medical records and OMOP-CDM. Sci. Rep. 11, 1–13 (2021).33414495 10.1038/s41598-021-03332-6
31. Ministry of the Interior and Safety. Therapeutic material master file. Public data portal https://www.data.go.kr/data/15067463. Accessed 2 Apr 2023. (2022).
32. Chandran BV Venkatesh MP Krishna PD Comparison of medical device regulations in India, Japan and South Korea J. Pharm. Res. Int. 2021 33 8 23
Chandran, B. V., Venkatesh, M. P. & Krishna, P. D. Comparison of medical device regulations in India, Japan and South Korea. J. Pharm. Res. Int. 33, 8–23 (2021).
33. Ministry of Food and Drug Safety. Medical device standard code notification. UDI system http://udiportal.mfds.go.kr. Accessed 14 Mar 2023. (2023).
34. Byun J Analysis of treatment pattern of anti-dementia medications in newly diagnosed Alzheimer’s dementia using OMOP CDM Sci. Rep. 2022 12 4451 10.1038/s41598-022-08595-1 35292697
Byun, J. et al. Analysis of treatment pattern of anti-dementia medications in newly diagnosed Alzheimer’s dementia using OMOP CDM. Sci. Rep. 12, 4451 (2022).35292697 10.1038/s41598-022-08595-1
35. Cho Y Comparison of postmarket surveillance strategies of implantable medical devices in the United States, European Union, and South Korea J. Pharmacoepidemiol. Risk Manag. 2021 13 45 54 10.56142/2021.13.2.45
Cho, Y. et al. Comparison of postmarket surveillance strategies of implantable medical devices in the United States, European Union, and South Korea. J. Pharmacoepidemiol. Risk Manag. 13, 45–54 (2021).10.56142/2021.13.2.45
36. Jung YA Kim YJ Comparative study of ISO standards for an effective implementation of the domestic medical device GMP system J. Korean Soc. Qual. Manag. 2018 46 211 224
Jung, Y. A. & Kim, Y. J. Comparative study of ISO standards for an effective implementation of the domestic medical device GMP system. J. Korean Soc. Qual. Manag. 46, 211–224 (2018).
37. Cioeta R Cossu A Giovagnoni E Rigoni M Muti P A new platform for post-marketing surveillance and real-world evidence data collection for substance-based medical devices Front. Drug Saf. Regul. 2022 2 992359 10.3389/fdsfr.2022.992359
Cioeta, R., Cossu, A., Giovagnoni, E., Rigoni, M. & Muti, P. A new platform for post-marketing surveillance and real-world evidence data collection for substance-based medical devices. Front. Drug Saf. Regul. 2, 992359 (2022).10.3389/fdsfr.2022.992359
38. White J Carolan-Rees G Current state of medical device nomenclature and taxonomy systems in the UK: Spotlight on GMDN and SNOMED CT JRSM Short Rep. 2013 4 1 7 10.1177/2042533313483719 23885299
White, J. & Carolan-Rees, G. Current state of medical device nomenclature and taxonomy systems in the UK: Spotlight on GMDN and SNOMED CT. JRSM Short Rep. 4, 1–7 (2013).23885299 10.1177/2042533313483719
39. Jiang G Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report J. Am. Med. Inform. Assoc. 2021 28 2241 2250 10.1093/jamia/ocab117 34313748
Jiang, G. et al. Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report. J. Am. Med. Inform. Assoc. 28, 2241–2250 (2021).34313748 10.1093/jamia/ocab117
40. Wilson NA Drozda J Value of unique device identification in the digital health infrastructure JAMA 2013 309 2107 2108 10.1001/jama.2013.5514 23695480
Wilson, N. A. & Drozda, J. Value of unique device identification in the digital health infrastructure. JAMA 309, 2107–2108 (2013).23695480 10.1001/jama.2013.5514
41. Dhruva SS Using real-world data from health systems to evaluate the safety and effectiveness of a catheter to treat ischemic ventricular tachycardia J. Interv. Card. Electrophysiol. 2023 66 1817 1825 10.1007/s10840-023-01496-x 36738387
Dhruva, S. S. et al. Using real-world data from health systems to evaluate the safety and effectiveness of a catheter to treat ischemic ventricular tachycardia. J. Interv. Card. Electrophysiol. 66, 1817–1825 (2023).36738387 10.1007/s10840-023-01496-x
42. Song WJ Kang SG Seo BMF Choi NK Lee JH Pilot study of the Korean national breast implant registry: Experiences and lessons learned J. Plast. Reconstr. Aesth. Surg. 2022 75 1833 1841 10.1016/j.bjps.2022.01.024
Song, W. J., Kang, S. G., Seo, B. M. F., Choi, N. K. & Lee, J. H. Pilot study of the Korean national breast implant registry: Experiences and lessons learned. J. Plast. Reconstr. Aesth. Surg. 75, 1833–1841 (2022).10.1016/j.bjps.2022.01.024
43. NEWSIS, Management of Medical Devices for Tracking Made Easier. Guidelines Distributed https://www.akomnews.com/bbs/board.php?bo_table=news&wr_id=53188. Accessed 9 Jul 2024. (2023).
44. Campion TR Jr Johnson SB Paxton EW Mushlin AI Sedrakyan A Implementing unique device identification in electronic health record systems: Organizational, workflow, and technological challenges Med. Care 2014 52 26 31 10.1097/MLR.0000000000000012 24322986
Campion, T. R. Jr., Johnson, S. B., Paxton, E. W., Mushlin, A. I. & Sedrakyan, A. Implementing unique device identification in electronic health record systems: Organizational, workflow, and technological challenges. Med. Care 52, 26–31 (2014).24322986 10.1097/MLR.0000000000000012
