In 2013, I'm focused on 5 major work streams:

• Meaningful Use Stage 2, including Electronic Medication Administration Records
• ICD10, including clinical documentation improvement and computer assisted coding
• Replacement of all Laboratory Information Systems
• Compliance/Regulatory priorities, including security program maturity
• Supporting the IT needs of our evolving Accountable Care Organization including analytics for care management

I've written about some of these themes in previous posts and each has their uncharted territory.

One component that crosses several of my goals is how electronic documentation should support structured data capture for ICD10 and ACO quality metrics.

How are most inpatient progress notes documented in hospitals today? The intern writes a note that is often copied by the resident which is often copied by the attending which informs the consultants who may not agree with content. The chart is a largely unreadable and sometimes questionably useful document created via individual contributions and not by the consensus of the care team. The content is sometimes typed, sometimes dictated, sometimes templated, and sometimes cut/pasted. There must be a better way.

I recently attended a two day retreat to brainstorm about novel approaches to clinical documentation.

Imagine the following -- the entire care team jointly authors a daily note for each patient using a novel application inspired by Wikipedia editing and Facebook communication. Data is captured using disease specific templates to ensure appropriate quality indicators are recorded. At the end of each day, the primary physician responsible for the patient's care signs the note on behalf of the care team and the note is locked. Gone are the "chart wars", redundant statements, and miscommunication among team members. As the note is signed, key concepts described in the note are codified in SNOMED-CT. The SNOMED-CT concepts are reduced to a selection of suggested ICD-10 billing codes. A rules engine reports back to the clinician where additional detail is needed to justify each ICD-10 code  i.e. a fracture must have the specifics of right/left, distal/proximal, open/closed, simple/comminuted.  

You can imagine that the moving parts I've described are modular components provided by different companies via cloud hosted web services (similar to the decision support service provider idea)

Module 1  - disease specific templates

Module 2  - technology to capture free text and populate the templates i.e. my Wikipedia/Facebook concept describe above.

Module 3  - natural language processing to codify SNOMED-CT concepts

Module 4  - mapping of SNOMED-CT concepts to ICD10 codes

Module 5  - rules to ensure documentation is complete enough to justify the ICD10 codes

We've been speaking industry leaders such as m*modal, 3M, and Optum about these ideas.

Early adopters including Kaiser, Geisinger and Mayo are already working on elements of this approach.