The choice of a documentation method can alter the balance between expressivity and structure in the resultant notes, hamper the healthcare provider's workflow, influence the process and products of recording clinical information, and influence how well the note can be incorporated into an EHR system in such a way that the note's contents can be automatically reused and analyzed.15
While structured documentation systems can facilitate data collection and reuse, they can be cumbersome to use during patient encounters and may lack the flexibility and expressivity required for general medical practices. Transcribed notes create documents useful for text processing, but can require a time delay for the transcription process to occur. The attributes associated with each documentation method influence how they are best used and adopted. While structured entry emphasizes data standardization and structure, human adoption of CBD systems requires an emphasis on expressivity, efficiency, flexibility, and being well adapted to a typical workflow.19
Both structured clinical documentation and text-processing algorithms for flexible documentation continue to evolve. The rates of evolution may not be the same for each, but we are not aware of clear evidence that shows that one approach is improving faster than the other. Furthermore, we do not intend to convey an impression that one is necessarily more advanced or has greater promise than the other. Each approach offers distinct advantages to the user. For example, because structured documentation systems can do more than just create data, it may be relatively appealing to clinicians in certain settings. A template-based structured documentation system may be useful for notes that have a standard and predictable content and format, such as those recording pediatric health maintenance visits, preoperative evaluations, formalized disability examinations, and reviews of systems. By contrast, in some settings, clinicians may prefer the flexibility of complex and nuanced narrative text to document the history of a present illness or a diagnostic impression.
We collectively have over 10 decades of personal experience in viewing or using a wide variety of computer-based documentation systems around the country in public, private and academic settings. We gained this experience in the settings of actual clinical use, observations during site visits, and direct reviews of vendor products at trade shows and professional conferences. Based on this experience, we have observed that typically, for a given site's implementation, computer-based documentation systems are usually configured to take clinical input primarily in narrative or structured form, but not both. Most computer-based documentation systems that the authors have seen do not support hybrid documentation in the way that we recommend in the current manuscript. We note that, in the case where structured clinical data are needed, information entered using structured entry would be immediately available, whereas narrative text would require processing via NLP algorithms to become similarly ‘structured.’ Nevertheless, we observe that in our experience, few nonacademic sites have NLP-based text processing systems readily available to harvest EHR system data, with the possible exception of NLP-type systems that help to extract billing codes from clinical records.
Priorities for structured documentation and text processing will likely vary in different settings and with different user groups, and the priorities may be informed by the tasks the documentation supports. Certain tasks may require that the EHR systems understand only structural information from the clinical document (eg, its metadata or header information), while others may require a deeper concept-level understanding. For example, a quality-assessment program evaluating whether inpatient progress notes are being placed in the chart in a timely manner may require only the document title and date. Any document that has the correct title, including scanned and tagged paper-based notes, could support this need. Tasks that depend on a deeper understanding of the document may require healthcare providers to document using structured documentation tools or to apply computer programs to process the natural language in narrative-text documents. For example, to implement an automated colorectal cancer screening advisor, the advisor system will need to know the patient's family and past medical history, whether a prior screening test had occurred, and the result of any screening tests. Gathering these data requires that healthcare providers document the relevant information using tools that can support data extraction and analysis, including CBD systems, structured entry tools, or narrative-text typing (either directly or via a dictation/transcription model) with a subsequent application of text processing. In addition, different healthcare providers may value structured data in EHR systems differently. Some providers may be willing to sacrifice a degree of CBD usability or efficiency for the sake of having key elements of their notes available immediately as structured data in EHR systems. Others may preferentially value documentation methods that allow them to express their impressions fluidly or create notes more quickly, without regard to how well the methods support other functions of EHR systems.
Given the tension between structure and flexible documentation, those implementing EHR systems should assume that multiple CBD products will be needed to meet the needs of clinician users, rather than attempting to find a single best documentation method. Factors to consider in selecting CBD products include the method's fitness for a given workflow, the content in the resultant notes, time efficiency to create a note, costs, ease of using the method, flexibility for using the method to document unforeseen clinical findings or in unexpected circumstances, and support for narrative expressivity, machine readability, and document structure.19
Certain documentation methods feature some attributes at the expense of others, such as promoting narrative expressivity at the expense of formal note structure. Rather than waiting until documentation tools can be created to accommodate all needs and workflows, or force complex clinical workflows to change to accommodate the EHR system rollout, we recommend that healthcare providers be able to access a variety of different documentation methods and select the one that best fits their documentation, data, and workflow needs. EHR system developers and users can weigh different documentation methods in terms of how they impact relevant documentation-related outcomes such as usability, efficiency, quality, and readability against their utility for EHR systems. The value of this approach is that it allows organizations considering EHR systems to prioritize development and implementation efforts around clinical documentation.