Archetype-based data warehouse environment to enable the reuse of electronic health record data

Marco-Ruiz, Luis; Moner, David; Maldonado, José Alberto; Kolstrup, Nils; Bellika, Johan Gustav

doi:10.1016/j.ijmedinf.2015.05.016

Cited by 42 publications

(29 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This critical barrier only occurred in the literature once for the U.S., and only recently [ 27 ]. Several other articles were identified worldwide on the subject [ 28 – 30 ]. Providers have voiced their discontent with the lack of interoperability established by government agencies, which enables the static nature of EHR development at the vendor [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Barriers to Electronic Health Record Adoption: a Systematic Literature Review

et al. 2016

View full text Add to dashboard Cite

Federal efforts and local initiatives to increase adoption and use of electronic health records (EHRs) continue, particularly since the enactment of the Health Information Technology for Economic and Clinical Health (HITECH) Act. Roughly one in four hospitals not adopted even a basic EHR system. A review of the barriers may help in understanding the factors deterring certain healthcare organizations from implementation. We wanted to assemble an updated and comprehensive list of adoption barriers of EHR systems in the United States. Authors searched CINAHL, MEDLINE, and Google Scholar, and accepted only articles relevant to our primary objective. Reviewers independently assessed the works highlighted by our search and selected several for review. Through multiple consensus meetings, authors tapered articles to a final selection most germane to the topic (n = 27). Each article was thoroughly examined by multiple authors in order to achieve greater validity. Authors identified 39 barriers to EHR adoption within the literature selected for the review. These barriers appeared 125 times in the literature; the most frequently mentioned barriers were regarding cost, technical concerns, technical support, and resistance to change. Despite federal and local incentives, the initial cost of adopting an EHR is a common existing barrier. The other most commonly mentioned barriers include technical support, technical concerns, and maintenance/ongoing costs. Policy makers should consider incentives that continue to reduce implementation cost, possibly aimed more directly at organizations that are known to have lower adoption rates, such as small hospitals in rural areas.

show abstract

Section: Discussionmentioning

confidence: 99%

Barriers to Electronic Health Record Adoption: a Systematic Literature Review

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Thus, it is possible to support cohort selection of appropriate study patients across various sites and to collect patient informed consent only in a second step for the finally selected patients. Another technically interesting approach from the Scandinavian countries relies on the use of openEHR to extract data from several source EHRs [110]. It has long been recognized that data transfer between different EHR systems relies on both syntactic and semantic constraints (Fig 2) [ 111,112].…”

Section: Data Integration Interoperability and Systems Federationmentioning

confidence: 99%

Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress

Meystre¹,

Lovis²,

Bürkle³

et al. 2017

Yearb Med Inform

156

View full text Add to dashboard Cite

SummaryObjective: To perform a review of recent research in clinical data reuse or secondary use, and envision future advances in this field. Methods: The review is based on a large literature search in MEDLINE (through PubMed), conference proceedings, and the ACM Digital Library, focusing only on research published between 2005 and early 2016. Each selected publication was reviewed by the authors, and a structured analysis and summarization of its content was developed. Results: The initial search produced 359 publications, reduced after a manual examination of abstracts and full publications. The following aspects of clinical data reuse are discussed: motivations and challenges, privacy and ethical concerns, data integration and interoperability, data models and terminologies, unstructured data reuse, structured data mining, clinical practice and research integration, and examples of clinical data reuse (quality measurement and learning healthcare systems). Conclusion: Reuse of clinical data is a fast-growing field recognized as essential to realize the potentials for high quality healthcare, improved healthcare management, reduced healthcare costs, population health management, and effective clinical research.

show abstract

“…Our EHRS approach consists of the same XML database architecture, comparable to another archetype-based data warehouse environment [22]. Because we want to build up the EHRS on W3C standards, we extended the REST architecture using the W3C XForm method for a binding of EHR elements to web form items, like already done in the Single Source Architecture of x4T [23,24] for CDISC ODM.…”

Section: Archetype-based Ehr-development Frameworkmentioning

confidence: 99%