Details

Autor(en) / Beteiligte

• Evans, R. S.

Titel

Electronic Health Records: Then, Now, and in the Future

Ist Teil von

• Yearbook of medical informatics, 2016-05, Vol.25 (S 01), p.S48-S61

Ort / Verlag

Stuttgart: Georg Thieme Verlag KG

Erscheinungsjahr

2016

Quelle

MEDLINE

Beschreibungen/Notizen

• Summary Objectives: Describe the state of Electronic Health Records (EHRs) in 1992 and their evolution by 2015 and where EHRs are expected to be in 25 years. Further to discuss the expectations for EHRs in 1992 and explore which of them were realized and what events accelerated or disrupted/derailed how EHRs evolved. Methods: Literature search based on “Electronic Health Record”, “Medical Record”, and “Medical Chart” using Medline, Google, Wikipedia Medical, and Cochrane Libraries resulted in an initial review of 2,356 abstracts and other information in papers and books. Additional papers and books were identified through the review of references cited in the initial review. Results: By 1992, hardware had become more affordable, powerful, and compact and the use of personal computers, local area networks, and the Internet provided faster and easier access to medical information. EHRs were initially developed and used at academic medical facilities but since most have been replaced by large vendor EHRs. While EHR use has increased and clinicians are being prepared to practice in an EHR-mediated world, technical issues have been overshadowed by procedural, professional, social, political, and especially ethical issues as well as the need for compliance with standards and information security. There have been enormous advancements that have taken place, but many of the early expectations for EHRs have not been realized and current EHRs still do not meet the needs of today’s rapidly changing healthcare environment. Conclusion: The current use of EHRs initiated by new technology would have been hard to foresee. Current and new EHR technology will help to provide international standards for interoperable applications that use health, social, economic, behavioral, and environmental data to communicate, interpret, and act intelligently upon complex healthcare information to foster precision medicine and a learning health system.