From 3M Health Information Systems
The Oops Factor Part 2: Noncritical Errors
Back in September, I wrote a blog about documentation errors and listed various types of critical errors that could potentially impact patient safety, care, or treatment. Clearly, errors that can cause harm are the first and most important to detect and resolve. Some errors don’t carry such severe potential consequences, but they still impact documentation quality.
Why should we be concerned about noncritical errors if their presence does not hurt the patient? First, these errors can affect perception about the author and/or organization if they are not addressed and corrected, especially if frequent or habitual. No physician or administrator wants to be questioned in court concerning incomplete, inaccurate, or just plain sloppy documentation because it introduces doubt regarding the attention to detail and professionalism of the organization and individuals providing care to the patient.
Second, so-called minor errors can cause problems in interpretation of the patient’s story and use of the information downstream for reporting and decision making. Addressing noncritical errors may be a lower priority in today’s healthcare environment, but as the focus shifts further down the documentation cycle towards reimbursement, analytics, and clinical decision support, it becomes clearer that the quality of the input (documentation) has a huge impact upon the output (coding, reimbursement, reporting, etc.).
Here are some examples of noncritical errors commonly detected by healthcare documentation specialists who either review transcribed documents or content entered directly into the EHR:
Misspelling: Noncritical misspellings don’t change the intended meaning, but they are still errors that could call the document into question. For example, the medication Imdur may be incorrectly spelled Indur, or erythema may be misspelled as erythemia.
Wrong word form: Similar to misspelling, incorrect word forms are very common in healthcare documentation, such as staff/staph, obstructing/obstructive, feel/fill/fell, dissent/descent, and many more.
Unapproved abbreviations: Each healthcare organization may designate specific abbreviations that should not be used in addition to the JCAHO list I mentioned in my previous post. Examples include PPX for prophylaxis, “dispo” for disposition, SAR for subacute rehab, and so on. It’s a good idea to expand most abbreviations, especially if they are not widely known or could be misunderstood.
Transposition of names/dates/other demographics: With so much information floating around in the healthcare setting, it is very easy to commit a minor demographics error. If patient Martin Curtis is referred to in a document as “Mr. Martin,” the reader probably won’t assume a mismatch between the document and the patient, but he may be confused and conduct some otherwise unnecessary research to verify the patient’s identity.
Failure to edit/failure to flag: This error category is commonly used in medical transcription and speech recognition editing to evaluate and provide feedback on the work of the healthcare documentation specialist or author. If the dictation or speech recognition output is questionable, the transcriptionist or reviewer should flag these areas for clarification. For example, if the physician dictates, “The patient has been suffering from (garbled dictation) for the past two years,” the location of the garbled dictation should be flagged so that the physician can provide the correct information before signing the document. If a flag is not inserted, then the document could potentially be signed with incorrect or missing information.
Selection of incorrect template or protocol: This type of error occurs when either the author or healthcare documentation specialist chooses incorrect formatting or does not follow the standards set for the document type, physician, department, etc. Often EHRs and other electronic systems will have specific requirements for interoperability such as sharing ADT, uploading and matching documents to patient accounts, importing documents from transcription service organizations, and so on. Failure to follow these requirements impacts whether or not the document and associated data can be shared successfully across systems.
After reading this list, you can probably come up with several examples that fit within each category, and you may even come up with some additional categories I haven’t covered. And you may also be wondering, as I am, where the line is drawn between a critical and noncritical error, because in some cases the potential impact on the patient and the subsequent care provided is a grey area. It’s clear to me that we need to continue the dialog about documentation quality across the healthcare industry, especially as emerging technologies continue to change how documentation is captured, shared, and used. We have a lot to discuss and many standards to define, but fortunately, AHDI and AHIMA have started the ball rolling.
Jill Devrick, product solutions advisor with 3M Health Information Systems, is Immediate Past President of the Association for Healthcare Documentation Integrity (AHDI).