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“Copy and Paste” Notes and Autopopulated Text in the Electronic Health Records

Scott MacDonald, MD | October 31, 2023
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The Cases

Case #1: A 56-year-old man being treated for hypertension and diabetes requested a copy of his medical records before moving to a different state. The clinic staff gathered the necessary information, and before providing it to the patient, left the file on a physician’s desk for review. When the physician (who was new to this practice) reviewed the records, he noticed “h/o C section followed by hysterectomy” documented in the patient’s electronic problem list, along with a detailed gynecological history. Upon further review, the physician found that this history had been recorded in the patient’s record for several years. During a thorough review of the electronic health records, clinic staff found that the patient’s wife frequently visited the clinic with her husband, and that her medical history had been copied and pasted into his medical record. The patient was notified of the error before receiving a copy of his medical records with corrected information.

Case #2: A 38-year-old man was brought to the hospital with altered mental status after crashing while riding a motorcycle. On hospital day 2, the primary trauma surgery team ordered magnetic resonance imaging (MRI) of the brain, due to concern regarding possible hypoxic-ischemic encephalopathy, and spine consultants requested imaging of the spine. These studies, completed on hospital day 6, showed no evidence of traumatic or hypoxic brain injury and no vertebral or ligamentous injury; the radiologist noted “minimal cervical spine epidural blood or fluid with no compromise of the spinal cord.” This incidental finding was not documented in any progress notes.

In the meantime, the patient slowly regained consciousness and the ability to intermittently follow commands in his primary language. On hospitals days 5 through 10, the primary team’s progress notes documented identical examinations, each autopopulated from a previous note, including the phrase “moves all extremities.” However, nursing notes disagreed: a nurse documented that the patient withdrew his lower extremities (LE) to stimuli on day 7, but not on day 8. On hospital day 9, a nurse documented “unable to move BLE [bilateral LE], sensation intact, team aware.” Not until day 13 did the patient undergo a repeat MRI study, which showed a large C3-C7 epidural hematoma with cord compression. The patient underwent emergency laminectomy and decompression but had virtually complete paralysis below the C7 level upon hospital discharge and at follow-up six months later.

The Commentary

By Scott MacDonald, MD


These cases illustrate several types of Electronic Health Record (EHR) errors, with a common thread of erroneous use of electronic text-generation functionality, such as copy/paste, copy forward, and using “smart phrases” to automatically pull information from other electronic sources to populate clinical notes.

EHRs are useful tools that often support efforts to improve safety. The data captured by these systems allow analysis of trends and factors contributing to events. At the point of care, decision support interventions can help avoid medication errors1 and increase awareness of underused interventions.2 However, they are known to facilitate other types of errors that may lead to patient harm, mediated by many factors, such as inadequate usability,3,4 alert fatigue,5 and insufficient support of the diagnostic process.6 Continual refinement of EHRs, both by vendors and individual health systems, can mitigate many of these concerns.

In the first case, the previous physician may have erroneously entered the patient’s wife’s gynecologic history into the “past medical history” or “problem list” section of the EHR, and then pulled it into subsequent notes, or he could have propagated an initial error of copy/pasting information from the wife’s record and then copying that note forward. Regardless, the presence of inaccurate information demonstrates a failure to review and correct relevant notes before signing them. This behavior is unprofessional at best, and dangerous at worst. Although this error merely created embarrassment and irritation, if the patient had been transgender and did have a gynecologic history, then a similar error could have offended the patient by misgendering them. This event would then further erode trust in the physician-patient relationship and the healthcare system. Electronic propagation of less obviously incorrect information from another patient’s record could lead to significant medical consequences, such as unnecessary treatment or monitoring for a nonexistent condition or medication. This practice might also lead to undertreatment by misleading the clinician about a contraindication that did not really exist.

The second case shows errors of omission and commission. Not commenting on the epidural fluid visible on the MRI may reflect the teams’ failure to notice the radiologist’s potentially significant finding, or simply a reliance on their own interpretation of the imaging studies. Including the entire MRI report in a note is undesirable as it leads to note ‘bloat.’ At minimum, acknowledging the radiologist’s finding and documenting the judgment that it did not require intervention would have been prudent.

The practice of copying previous notes, including physical examination findings that may not have been observed, could lead a quality investigator to conclude that the team ignored the nursing documentation or simply didn’t examine the patient. However, there may also be structural barriers that make it difficult for physicians to efficiently review nursing documentation, which may seem like looking for the proverbial needle in a haystack. Not accurately representing a patient’s condition in a note is often unsafe, always unethical, and may also represent billing fraud, especially if the physician is claiming to have examined the patient more thoroughly than was actually done. When a patient is stable and the exam doesn’t change day-to-day, then copying forward or autopopulating from a template may be reasonable, with the caveat that the text must be reviewed for accuracy prior to signing the note. However, the time and cognitive effort required to review a block of pasted text may exceed the time and effort involved in using EHR tools to simply document the current and accurate exam.

Finally, the nursing documentation of ‘team aware’ implies unprofessionalism if the physician team continued to document normal exams despite being aware of deterioration of the patient’s neurological state. Alternatively, it is possible that the nurse did not actually communicate the new finding of paralysis, or communicated it to a team that was not responsible for the patient. The delay in ordering a repeat MRI also raises concern for a breakdown in communication within or between care teams.

Inaccurate documentation impairs the investigation of patient safety incidents and the identification of system improvements to prevent recurrence. Much EHR data is locked in free text notes, so analytic tools are unable to leverage it for quality improvement. Thus, the accuracy of text in clinicians’ notes is critical to help elucidate the sequence of events. Good clinical documentation should provide narratives that clearly illustrate the arc of a patient’s story, as well as the details that make the story rich, so that subsequent readers can understand a patient’s condition, how it evolved, and what thought processes affected clinical decision-making. High-quality notes also have good narrative structure and omit unnecessary information.

Computerized analysis of note content is not yet mature; simple text comparisons or more advanced tools such as natural language processing (NLP) could be used to monitor patterns of excessive copy-paste that doesn’t incorporate editing or addition of content. Some EHR vendors already track detailed metadata for notes that can be used to analyze documentation patterns.7

A key motivator for using copy/paste or copy-forward EHR tools is to facilitate efficiently performing the sometimes-onerous documentation duties inherent to American medicine. Many studies have shown the significant amount of time US physicians spend on documentation, when compared with colleagues in other countries.8 This phenomenon is similar for nurses and other providers such as nurse practitioners and physician assistants.9-11 There is limited evidence comparing time spent generating paper documentation versus EHR documentation, but other new requirements associated with EHRs such as capturing data for quality metrics or responding to messages from patients through portals certainly add pressure to save time whenever possible. Unfortunately, reviewing automatically populated notes is time consuming, so little incentive exists to assure quality, despite providers’ intrinsic motivation and ethical imperative to document accurately.

Approaches to Improving Safety

Changes in documentation guidelines from CMS in 2021/202312 were intended to decrease this burden, but provider behavior has been slow to change. Comparing notes in one of the leading EHR platforms before and after the guideline change, time spent documenting has decreased somewhat but note length continued to increase.13 This change may reflect greater efficiency in generating large amounts of text, regardless of its accuracy and value to patient care. These data suggest that providers follow different approaches to generating notes; some have shortened their notes and saved time, while others are spending more time writing longer notes. Another finding from the same research was that use of tools to generate specific snippets of text (e.g., dot phrases or macros instead of copy/paste) was associated with shorter notes.

Little systematic data allow us to compare the quality of note content before and after the CMS policy change. Not only are there technical barriers, but there is not yet a consensus on how to define high-quality notes, given that notes serve many purposes, including communicating with current and future providers, justifying payment, and managing risk.14

The new CMS guidelines for evaluation and management codes emphasize documenting the assessment or response of symptoms to therapy, not the presence of data points, such as history or review of systems, in the note.

  CMS Guidelines (1995/1997) CMS Guidelines (2021/2023)12
Time-based billing Only counselling time, if over 50% of total time All time spent on the patient’s management on the day of encounter
Subjective data Number of systems reviewed Only as relevant
Objective data Number of systems examined Only as relevant
Care process factors Not generally considered Many workflows contribute to complexity, reviewing data, collaborating with professionals and care partners
Risk of therapies Considered Key driver
Number and type of problems addressed Considered Key driver

This change does remove the incentive to pull excessive data into the note from the clinical database, using smart phrases or other templates. However, it will take time for the culture to change, as many younger providers were trained in the milieu of bloated notes. Health system and professional society educational efforts may be helpful in addressing this generational problem.15 Pressure from Federal and private payors, including financial rewards or audits, may be needed to further incentivize accurate but succinct notes.

An additional issue is the challenge of locating and reading narrative notes. Nurses commonly use free text to share information with other providers such as their degree of concern about the patient or other issues not captured in structured fields in the EHR. A recent literature review described several studies that revealed that nurses’ notes may not be read by most nurses or other providers.16 Using detailed audit trails, Hripcsak et al discovered that less than 20% of nurse’s notes were viewed by attending physicians and residents, while 38% were not even read by other nurses. Indeed, about 16% of all nurses’ notes reviewed in the study were never read by any other individual.17 This structural barrier to communication among nurses, physicians, and advanced practice providers should be addressed as efforts to improve EHR structures are implemented.

As with any tool, proper use of the EHR depends on adequate training, practice, and attention. Thoughtful use of copy/paste can save time and keystrokes, but it can lead to medical errors and patient safety events if it is done without mindfulness, or without proper review of the resulting notes. User-centered EHR design that addresses the underlying drivers of using risky tools may improve the accuracy of documentation. Examples include thoughtfully curated automatic data review tools that are more useful than simply autopopulating result data in notes, or emerging technologies that can abstract key prior events in a patient care.

Ironically, emerging technology may help to rescue us from a problem amplified by previous EHR technology. Machine learning in the form of large language models (LLM) may be on the cusp of transforming how clinical documentation is generated, while improving patients’ experience of health care. “Ambient” systems can use microphones in clinical care areas and perform both speech recognition and NLP to capture the clinical concepts that were verbalized during the visit, starting with the patient’s history and the provider’s description of physical findings. Any diagnostic or therapeutic interventions mentioned can be presented as orders for the provider to review and sign. Finally, structured information can be reformatted into coherent clinical documentation. This is an artificial intelligence (AI) version of a human ‘scribe,’ potentially working faster at lower cost. Although scribes can be trained not to inappropriately use copy/paste, they remain human and susceptible to human errors. An LLM system could have built-in guardrails to prevent documenting findings that were not actually spoken.

As this technology is deployed and refined, we will need to be alert for unintended consequences, but it is anticipated that the time savings will allow for appropriate review of each note. Current LLMs have a propensity to ‘hallucinate’ details of generated text,18 so training them on health care data, as opposed to general internet data, and carefully monitoring them for accuracy, will be important to ensure that they achieve their potential without causing other harms to patients.

Take Home Points
  • EHRs provide powerful tools, including copy/paste and autopopulated text features, to make it easy to write notes. However, inappropriate use of these tools may lead to patient harm.
  • It is generally safer and more parsimonious to use small ‘chunks’ of text (also known as dot phrases or macros within some EHR platforms) that can be thoughtfully invoked. For example, use a ‘normal lung exam’ macro instead of copy/pasting complete exams.
  • Understand the new documentation guidelines and how shorter notes can now justify the same evaluation and management codes that required longer notes in the past. Detailed review of systems, physical examinations, and regurgitation of results no longer contribute to the billing level. Examine and document only what is relevant to the patient’s situation, and your interpretation thereof.
  • AI tools to help capture documentation (based on speech recognition and natural language processing) are rapidly evolving and may eventually replace human scribes.

Scott MacDonald, MD
Chief Medical Information Officer for Clinical Informatics
UC Davis Health


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This project was funded under contract number 75Q80119C00004 from the Agency for Healthcare Research and Quality (AHRQ), U.S. Department of Health and Human Services. The authors are solely responsible for this report’s contents, findings, and conclusions, which do not necessarily represent the views of AHRQ. Readers should not interpret any statement in this report as an official position of AHRQ or of the U.S. Department of Health and Human Services. None of the authors has any affiliation or financial involvement that conflicts with the material presented in this report. View AHRQ Disclaimers
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