Optimizing electronic health records requires a thorough process evaluation, implementing standards that match clinical situations, creating design standards for screenshots that improve user experience, and eliminating data redundancy.
Some specific examples of the functional and design requirements of clinical documentation optimization include:
Clinical documentation should first be broken down into “phases” or “chunks” of process. This will allow the optimization team to apply evaluation of documentation needs and application of standards design to meet the defined optimization objectives.
Implementation of the “80/20” Rule
Most hospitals built their EHR modules to mimic paper-based documentation. And that paper-based format was designed to cover any patient type in and clinical situation and over-document with no concern given toward documentation overlap or documentation redundancy. Paper-based documentation was designed to lay one document or form over another in a historical chart fashion. EHR systems were not designed to capture data in that fashion.
Application of an “80/20” set of standards means that the documentation will be designed to capture 80 percent of the normal patient type and clinical scenario type found within that unit or within that facility. The optimization team will first analyze the typical patient demographic and clinical situations most common to the facility, and seek to align the documentation to these standards. An example of application of this rule surrounds dropdown menus that seek to cover virtually any conceivable patient answer when in fact the typical answer the majority of patients historically provide would be limited to half the number found within the documentation dropdown.
Utilization of the 80/20 rule when optimizing clinical documentation typically results in measurable impacts toward process streamlining. Structured data can always be built into documentation. This means that as patient population changes are realized in a community or regulatory requirements drive a need to add data sets into documentation, building structured data into documentation assures the optimization team enhancements can be made with little risk to essential data non-capture.
Implementation of screenshot design standards
The optimization team must also implement a set of screenshot design standards. It is often found that as the clinician tabs from one data field to another the tab moves up or down or left to right in random fashion. That is because as the template was being built and saved, the tab coding was not optimized for various screen sizes. Application of a standard that states tabbing will be from top to bottom or left to right helps to streamline the data entry process.
It is often found in optimization activities that screenshot “real estate” is not optimized, resulting in the clinician tabbing from one screen to another unnecessarily. Making data fields readable and utilizing real estate effectively in order to reduce the number of screens is an effective standard to implement.
Elimination of Data Redundancy
By treating optimization as holistic and breaking down clinical processes into chunks, the application of data redundancy takes on an effective role. Why ask the patient their allergies several times in their care continuum? Why require the clinician to input the patient DOB when auto population is available? Again, EHR systems are designed to capture data elements and prepopulate elsewhere. Another benefit associated with reduced data redundancy is reduced risk associated with incorrect multiple entries.