Design and implementation of a privacy preserving electronic health record linkage tool in Chicago.
Objective: To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record (EHR) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical research.Methods: The authors developed and distributed a soft...
| Publicado en: | Journal of the American Medical Informatics Association Vol. 22; no. 5; pp. 1072 - 1081 |
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| Autores principales: | , , , , , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Oxford University Press / USA
Sep2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109640012&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109640012 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10675027 FZ9 jtl: Journal of the American Medical Informatics Association issn: 10675027 maglogo: N pubinfo: dt: Sep2015 vid: 22 iid: 5 pid: 622 pub: Oxford University Press / USA artinfo: ui: 109640012 NLM26104741 2013153162 10.1093/jamia/ocv038 NLM26104741 PMC5009931 109640012 ppf: 1072 ppct: 9 formats: tig: atl: Design and implementation of a privacy preserving electronic health record linkage tool in Chicago. aug: au: Kho, Abel N Cashy, John P Jackson, Kathryn L Pah, Adam R Goel, Satyender Boehnke, Jörn Humphries, John Eric Kominers, Scott Duke Hota, Bala N Sims, Shannon A Malin, Bradley A French, Dustin D Walunas, Theresa L Meltzer, David O Kaleba, Erin O Jones, Roderick C Galanter, William L sug: ab: Objective: To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record (EHR) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical research.Methods: The authors developed and distributed a software application that performs standardized data cleaning, preprocessing, and hashing of patient identifiers to remove all protected health information. The application creates seeded hash code combinations of patient identifiers using a Health Insurance Portability and Accountability Act compliant SHA-512 algorithm that minimizes re-identification risk. The authors subsequently linked individual records using a central honest broker with an algorithm that assigns weights to hash combinations in order to generate high specificity matches.Results: The software application successfully linked and de-duplicated 7 million records across 6 institutions, resulting in a cohort of 5 million unique records. Using a manually reconciled set of 11 292 patients as a gold standard, the software achieved a sensitivity of 96% and a specificity of 100%, with a majority of the missed matches accounted for by patients with both a missing social security number and last name change. Using 3 disease examples, it is demonstrated that the software can reduce duplication of patient records across sites by as much as 28%.Conclusions: Software that standardizes the assignment of a unique seeded hash identifier merged through an agreed upon third-party honest broker can enable large-scale secure linkage of EHR data for epidemiologic and public health research. The software algorithm can improve future epidemiologic research by providing more comprehensive data given that patients may make use of multiple healthcare systems. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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