Scalable Infrastructure Supporting Reproducible Nationwide Healthcare Data Analysis Toward FAIR Stewardship

Overview

Journal Sci Data

Specialty Science

Date 2023 Oct 4

PMID 37794003

Authors

Ji-Woo Kim

Chungsoo Kim

Kyoung-Hoon Kim

Yujin Lee

Dong Han Yu

Jeongwon Yun

Hyeran Baek

Rae Woong Park

Seng Chan You

Affiliations

Soon will be listed here.

Abstract

Transparent and FAIR disclosure of meta-information about healthcare data and infrastructure is essential but has not been well publicized. In this paper, we provide a transparent disclosure of the process of standardizing a common data model and developing a national data infrastructure using national claims data. We established an Observational Medical Outcome Partnership (OMOP) common data model database for national claims data of the Health Insurance Review and Assessment Service of South Korea. To introduce a data openness policy, we built a distributed data analysis environment and released metadata based on the FAIR principle. A total of 10,098,730,241 claims and 56,579,726 patients' data were converted as OMOP common data model. We also built an analytics environment for distributed research and made the metadata publicly available. Disclosure of this infrastructure to researchers will help to eliminate information inequality and contribute to the generation of high-quality medical evidence.

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References

Schneeweiss S . Learning from big health care data. N Engl J Med. 2014; 370(23):2161-3. DOI: 10.1056/NEJMp1401111. View

Chan You S, Krumholz H . The Evolution of Evidence-Based Medicine: When the Magic of the Randomized Clinical Trial Meets Real-World Data. Circulation. 2022; 145(2):107-109. DOI: 10.1161/CIRCULATIONAHA.121.057931. View

Lo-Ciganic W, Donohue J, Yang Q, Huang J, Chang C, Weiss J . Developing and validating a machine-learning algorithm to predict opioid overdose in Medicaid beneficiaries in two US states: a prognostic modelling study. Lancet Digit Health. 2022; 4(6):e455-e465. PMC: 9236281. DOI: 10.1016/S2589-7500(22)00062-0. View

Nosrati E . Harnessing administrative data to study health inequality. Lancet Public Health. 2022; 7(9):e726-e727. DOI: 10.1016/S2468-2667(22)00172-4. View

Portuondo J, Harris A, Massarweh N . Using Administrative Codes to Measure Health Care Quality. JAMA. 2022; 328(9):825-826. DOI: 10.1001/jama.2022.12823. View

Vaughan Sarrazin M, Rosenthal G . Finding pure and simple truths with administrative data. JAMA. 2012; 307(13):1433-5. DOI: 10.1001/jama.2012.404. View

Kim J, Yoon S, Kim L, Kim D . Towards Actualizing the Value Potential of Korea Health Insurance Review and Assessment (HIRA) Data as a Resource for Health Research: Strengths, Limitations, Applications, and Strategies for Optimal Use of HIRA Data. J Korean Med Sci. 2017; 32(5):718-728. PMC: 5383602. DOI: 10.3346/jkms.2017.32.5.718. View

Suissa S, Garbe E . Primer: administrative health databases in observational studies of drug effects--advantages and disadvantages. Nat Clin Pract Rheumatol. 2007; 3(12):725-32. DOI: 10.1038/ncprheum0652. View

Steinbusch P, Oostenbrink J, Zuurbier J, Schaepkens F . The risk of upcoding in casemix systems: a comparative study. Health Policy. 2006; 81(2-3):289-99. DOI: 10.1016/j.healthpol.2006.06.002. View

10.

Chan You S, Lee S, Choi B, Park R . Establishment of an International Evidence Sharing Network Through Common Data Model for Cardiovascular Research. Korean Circ J. 2022; 52(12):853-864. PMC: 9742390. DOI: 10.4070/kcj.2022.0294. View

11.

Rho Y, Cho D, Son Y, Lee Y, Kim J, Lee H . COVID-19 International Collaborative Research by the Health Insurance Review and Assessment Service Using Its Nationwide Real-world Data: Database, Outcomes, and Implications. J Prev Med Public Health. 2021; 54(1):8-16. PMC: 7939755. DOI: 10.3961/jpmph.20.616. View

12.

Burn E, Chan You S, Sena A, Kostka K, Abedtash H, Abrahao M . Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study. Nat Commun. 2020; 11(1):5009. PMC: 7538555. DOI: 10.1038/s41467-020-18849-z. View

13.

Chan You S, Rho Y, Bikdeli B, Kim J, Siapos A, Weaver J . Association of Ticagrelor vs Clopidogrel With Net Adverse Clinical Events in Patients With Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention. JAMA. 2020; 324(16):1640-1650. PMC: 7592033. DOI: 10.1001/jama.2020.16167. View

14.

Wilkinson M, Dumontier M, Aalbersberg I, Appleton G, Axton M, Baak A . The FAIR Guiding Principles for scientific data management and stewardship. Sci Data. 2016; 3:160018. PMC: 4792175. DOI: 10.1038/sdata.2016.18. View

15.

Williams R, Markus A, Yang C, Duarte-Salles T, DuVall S, Falconer T . Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network. BMC Med Res Methodol. 2022; 22(1):35. PMC: 8801189. DOI: 10.1186/s12874-022-01505-z. View

16.

Blacketer C, Defalco F, Ryan P, Rijnbeek P . Increasing trust in real-world evidence through evaluation of observational data quality. J Am Med Inform Assoc. 2021; 28(10):2251-2257. PMC: 8449628. DOI: 10.1093/jamia/ocab132. View

17.

Ioannidis J . Why most published research findings are false. PLoS Med. 2005; 2(8):e124. PMC: 1182327. DOI: 10.1371/journal.pmed.0020124. View

18.

Fanelli D . How many scientists fabricate and falsify research? A systematic review and meta-analysis of survey data. PLoS One. 2009; 4(5):e5738. PMC: 2685008. DOI: 10.1371/journal.pone.0005738. View

19.

Miyakawa T . No raw data, no science: another possible source of the reproducibility crisis. Mol Brain. 2020; 13(1):24. PMC: 7033918. DOI: 10.1186/s13041-020-0552-2. View

20.

Haendel M, Chute C, Bennett T, Eichmann D, Guinney J, Kibbe W . The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment. J Am Med Inform Assoc. 2020; 28(3):427-443. PMC: 7454687. DOI: 10.1093/jamia/ocaa196. View