In an EHR market rife with consolidation and replacement, healthcare delivery organizations (HDOs) have adopted healthcare data archival solutions to retire legacy systems. Archival allows for reduced costs (legacy system licensing, system support & maintenance), mitigation of risks (antiquated technology and security), and preservation of access. However, while substantial benefits may be achieved through legacy system retirement and archival, additional risks may be introduced due to missed data sets including contextual audit trails, referenced data in ancillary systems, data change & version history, and infrequently used, invisible fields or other metadata. This was recently addressed in a post by John Lynn, of Healthcare Scene, detailing the problematic nature of of EHR replacement driving lost data.

Attorneys and, in turn, judges have been grappling with the terms metadata and audit trails as EHRs and, more generally, electronically stored information, have become the subject of increased discovery requests and legal motions. The Doctors Company, the nation’s largest physician owned medical malpractice insurer, published a study in October of 2017, highlighting the rise of EHR-related malpractice suits. The study revealed that claims in which EHRs are a factor grew from just 2 in 2007 through 2019 to 161 from 2011 through December 2016. This is directly material to clinical data archival, as it is expected that the archival solution stores the same data as the legacy EHR it replaced.

Electronic Discovery, or e-Discovery, is the modern version of the traditional pre-trial process of an attorney requesting that the opposing party turn over copies of documents in hopes of finding valuable evidence. The scope of the searches related to e-discovery includes nearly anything electronic. Legacy or antiquated EHRs, and consequently the archival systems that replace them, are attractive targets for e-discovery because they contain so much potentially useful information, including patient demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data, and radiology reports. The danger is that archival systems used to persist this data in accordance with state requirements are not capturing all of the data needed to give a complete view of the circumstances surrounding patient care.

Healthcare delivery organizations are required to retain data for nearly a decade or more past the date of service and the costs of producing record for e-Discovery typically average $20K per gigabyte. In eDiscovery, the most frequently asked questions pertain to alerts (bypassed?), notes (who wrote it? who has reviewed it? when was it written? when was it signed? was it changed?), medication ordering, and lab review.

Groundbreaking cases include Griffith v Aultman Hospital, on March 23, 2016, where the Ohio Supreme Court deemed that the patient’s medical record is not limited to data in the medical records department. This pertained to cardiac strips but opens the door to the EHR. In addition, State laws now frequently addresses issues relating to eDiscovery: VA 32.1-127.1:03: “Health record” means any written, printed or electronically recorded material maintained by a health care entity in the course of providing health services to an individual concerning the individual and the services provided. Embedded metadata, such as notes revisions and versioning are generally hidden, but an integral part of electronic stored information, such as “track changes” or “comments.”

Healthcare delivery organizations have historically designated their HIM departments as the official “custodians of medical records.” Most HIM departments process and respond to subpoenas in state court, where the majority of medical-malpractice litigation occurs. As such, it is critical to incorporate consideration of commonly missed data sets into a healthcare delivery organization’s e-Discovery response approach and information governance program.

Download our free EHR Archival Strategy whitepaper to further understand how to address commonly missed data sets, the various approaches to extraction transformation & storage of the contents of clinical systems, and evaluation archival strategies including raw data backups, extracted schema stores, modeled document, and non-discrete indexed document.