Clinical Documentation Challenges

We are on a path to roll out a large swathe of Electronic Health Records (EHR) but a recent report published on the AISHealth.com Audits of Electronic Health Records Cloning Reveal Documentation Problems That Put Compliance at Risk will give many folks reasons to pause and consider their strategy in rolling out electronic medical records and reconsider how they capture information in these systems.

Interestingly the article suggests that EHR's "can reduce the time it takes physicians to document patient encounters" but there is a fair amount of research suggesting that EHR can increase the burden and time taken to document. A study in the Healthcare Ledger in March 2009 showed an increase of ~ 4x when documenting using the EHR and there is increasing concern that the current burden of clerical work being required of medical residents is limiting the educational opportunities and failing to teach our future doctors the process of reflection and distillation of a patient history that is an essential part of the diagnostic process (Doll and Arora 2010). Add to that that many EHR systems limit the potential for capturing the complete clinical story of the patient as outlined in a recent study “Communication of Clinically Relevant Information in Electronic Health Records: A Comparison between Structured Data and Unrestricted Physician Language” (Resnik, Niv et al 2010) in a systematic comparison between free natural language dictations and information codified by structured categories in an EHR demonstrated a failure to capture clinically significant information. Even in the most conservative estimate the study demonstrated 25% clinical omissions that rated 4-5 on a 1–5 scale of seriousness (1 being minimal severity and 5 meaning severe).

However the access to real time information and improved legibility deliver significant benefits and advances into our healthcare system. But as Nina Youngstrom points out:

CMS and Medicare contractors are wary of classic EHR physician documentation shortcuts — cloning (cut and paste), macros and templates — and audits are bearing out their concerns

As the audit demonstrated "Each note should contain individualized data that supports the medical necessity of the visit or procedure.” and problems stem from EHR documentation shortcuts:

• Cloning (cutting and pasting): Physicians copy information from previous patient encounters (e.g., demographic, history of present illness, exam, medical decision making) and paste it in the current encounter.
• Templates: Physicians fill out templates for patient encounters that cover a lot of ground with a few key strokes. The review of systems is pre-filled with the term “negative” for each organ system. For positive answers, physicians must change “negative” to reflect the positive response given by the patient.
• Macros: Macros are a type of EHR shortcut that allows the entry of generous customized data quickly. Though initially CMS resisted the use of macros, the agency gave its approval for their use by teaching physicians (see Medicare Transmittal 811). With macros, teaching physicians, for instance, type in “.liv” to convey “liver exam,” which triggers a drop-down menu of choices for the next step.

So avoiding these pitfalls and capturing the essence of the clinical consultation in the "Medical decision making" which is the cognitive process and is hard to document with templates and macros is key to both good quality documentation as well as avoiding potential CMS audits and challenges in the future.

There is no one size fits all to these challenges and in different clinical circumstances different solutions will be beneficial but providing tools to document the complete narrative and extract key data elements will help drive clinically actionable data into the EHR while maintaining the decision making process that includes taking and documenting a full history without burdening the physician with mundane data entry tasks. Clinical Language Understanding offers to bridge this divide capturing the voice with proven voice recognition Technology (Dragon Medical) and the exciting addition of Clinical Language Understanding: The video demonstrates the CLU in action offering an alternative path for clinicians weary from screen based data entry:



Or you can see the video here, and can see Paul Ricci on CNBC "Street Signs” hosted by Erin Burnett "Nuance Partners with IBM":




and read about the collaboration with IBM here. What would you rather be doing? Manual data entry or dictating. This announcement and the work underway offers a solution that bridges the divide between the need for clinically actionable data and physicians desire to capture the complete clinical story for the patient.