Information Management

Purpose

This document provides guidance to assist perioperative nurses in

• designing patient health care record (HCR) information systems (eg, electronic medical record [EMR], electronic health record [EHR], medical record documentation) and tools,

• evaluating health information technology (HIT),

• documenting patient care information, and

• using perioperative patient information management for the safe delivery of perioperative care and quality improvement.¹ 

Highly reliable data collection processes are necessary not only to chronicle a patient’s response to nursing interventions and clinical improvement related to the patient’s health care, but also to demonstrate the health care organization’s progress in and dedication to improving health care outcomes, including those for individuals (ie, patient-centered care) and those for populations (ie, community health and national systems).² 

Federal regulations govern patient information management in the United States. The Privacy, Security, and Enforcement Rules in the Health Insurance Portability and Accountability Act (HIPAA) of 1996^3,4  include national standards for electronic transmission of health information, and the simplification provision requires protections for health information while reducing paperwork and streamlining business processes. With advancements in HIT, federal regulations including the Genetic Information Nondiscrimination Act of 2008, which prohibits employer discrimination based on health, and the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, which prohibits selling of health information, were enacted to protect health care professionals and patients from intentional or unintentional misuse of health information.⁵ 

Even after the passage of the HITECH Act, there has been inconsistency among health care settings related to advanced use of HIT capabilities. This can be seen in the ways that advanced EHR functions are accessed and used by personnel in different types of health care organizations (eg, critical access hospitals compared to urban hospitals) and by patients.⁶  Continuous modifications are being made to privacy, security, and enforcement rules and breach notification rules, and these rule modifications require health care organizations to update HCR data capture and maintenance processes.⁵  The 21st Century Cures Act of 2016 includes provisions to advance interoperability and support the access, exchange, and use of electronic health information by health care professionals and patients.⁷ 

This guideline represents a conceptual outline for a comprehensive perioperative documentation plan that includes nursing workflow, data capture, required components, and electronic platforms. It is not inclusive of all required HCR documentation elements, nor should it be seen as the only guideline to be followed when developing or revising clinical perioperative documentation policies and procedures.

This guideline is specific to patient information documentation guidelines; therefore, the following topics are outside the scope of this document: access to personal health information; accreditation requirements; HIT certification criteria; certification processes for EHR systems; data analytic requirements, EHR human factors science; EHR adoption processes; general or non-perioperative-specific nursing documentation; hand-over communication requirements and perioperative team communication (see the AORN Guideline for Team Communication⁸ ); health data reporting for the purpose of reimbursement; health information exchanges and interoperability requirements and facilitation; the processes used for obtaining informed consent (eg, shared decision making) or consent education aids (eg, audio-visual); information that is recorded or communicated outside of the patient HCR; mandatory quality reporting criteria and submission; nurse informaticists’ scope of practice and aspects of their job description (eg, use of the EHR to predict outcomes or treatments by developing clinical decision support [CDS] or use of artificial intelligence [AI], machine learning, and big data); patient information tracking devices; and verbal communication of the patient care plan.

Evidence Review

A medical librarian with a perioperative background conducted a systematic search of the databases Ovid MEDLINE, Ovid Embase, EBSCO CINAHL, and the Cochrane Database of Systematic Reviews. The search was limited to literature published in English from June 2015 through June 2020. At the time of the initial search, weekly alerts were created on the topics included in that search. Results from these alerts were provided to the lead author until July 2021. The lead author requested additional articles that either did not fit the original search criteria or were discovered during the evidence appraisal process. The lead author and the medical librarian also identified relevant guidelines from government agencies, professional organizations, and standards-setting bodies.

Search terms included Affordable Care Act, ambulatory facility, American Recovery and Reinvestment Act, ambulatory surgery center, analytics, big data, charting, charting by exception, clinical decision support systems, computer-assisted decision making, computerized patient records, consent (research), data analytics, data collection, data mining, data storage and retrieval, decision making (computer-assisted), decision support systems (clinical), documentation, electronic data interchange, electronic health records, electronic medical record, electronic signature, forms and records control, government regulations, Health Care Reform Act, health informatics, health information exchange, health information interoperability, health information system interoperability, HIT for economic and clinical health, Health Insurance Assistance for the Unemployed Act of 2009, Health Insurance Portability and Accountability Act, Health Level 7, Health Level Seven, Health Level Seven (organization), Health Level Seven International, HIPAA, HITECH Act, HL7, hospital information systems, information management, information retrieval, information storage, information storage and retrieval, informed consent, interoperability, Kassebaum Kennedy Act, machine learning, meaningful use, medical informatics, medical information exchange, medical records, Medicare and Medicaid electronic HCR, Medicare and Medicaid Health Information Technology for Economic and Clinical Health Act, multi hospital information systems, nursing informatics, Obamacare, office-based surgery, operating room, operating room information systems, operating suite, operating theater, paper charting, Patient Protection and Affordable Care Act, Public Law 104-191, Public Law 111-148, Public Law 111-5, records management, same day surgery, surg*, systems integration, TAA Health Coverage Improvement Act of 2009, and variance charting.

Included were research and non-research literature in English, complete publications, and publications with dates within the time restriction when available. Excluded were non-peer-reviewed publications and older evidence within the time restriction when more recent evidence was available. Editorials, news items, and other brief items were excluded. Low-quality evidence was excluded when higher-quality evidence was available, and literature outside the time restriction was excluded when literature within the time restriction was available (Figure 1).

Figure 1

Flow Diagram of Literature Search Results

Adapted from Moher D, Liberati A, Tetzlaff J, Atman DG; The PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA Statement. PLoS Med. 2009;6(6):e1000097.

Articles identified in the search were provided to the project team for evaluation. The team consisted of the lead author and one evidence appraiser. The lead author and the evidence appraiser reviewed and critically appraised each article using the AORN Research or Non-Research Evidence Appraisal Tools as appropriate. The literature was independently evaluated and appraised according to the strength and quality of the evidence. Each article was then assigned an appraisal score. The appraisal score is noted in brackets after each reference as applicable.

Each recommendation rating is based on a synthesis of the collective evidence, a benefit-harm assessment, and con­sideration of resource use. The strength of the recommen­dation was determined using the AORN Evidence Rating Model and the quality and consistency of the evidence sup­porting a recommendation. The recommendation strength rating is noted in brackets after each recommendation.

Note: The evidence summary table is available at http://www.aorn.org/evidencetables/.