Information Models Offer Value to Standardize Electronic Health Record Flowsheet Data: A Fall Prevention Exemplar

Area of Science:

• Health Informatics
• Nursing Informatics
• Data Standardization

Background:

• Rapid electronic health record (EHR) implementation led to data standardization issues, hindering secondary data use.
• Nurses and healthcare organizations struggle with usable documentation data output from EHR systems.
• Lack of standardized data limits quality improvement initiatives and big data research in healthcare.

Purpose of the Study:

• To describe a method for standardizing EHR flowsheet documentation data using information models (IMs).
• To support data exchange, quality improvement, and big data research through standardized EHR data.
• To validate a fall prevention IM using EHR flowsheet metadata from multiple organizations.

Main Methods:

• A consensus-based, qualitative, descriptive approach identified essential fall prevention data concepts.
• Retrospective, observational study mapped and analyzed nursing flowsheet metadata from eight health systems using FloMap software.
• Iterative refinement involved subject matter experts, published evidence, and current documentation standards.

Main Results:

• Analyzed EHR data represented 6.6 million patients, 27 million encounters, and 683 million observations.
• The fall prevention IM was refined, adding five classes, reducing concepts by 14 (to 43), and adding 157 value set items.
• The final IM included 11 fall risk screening tools and a fall event details class with 14 concepts.

Conclusions:

• Iterative refinement and validation of the fall prevention IM enable semantic exchange and comparison of fall prevention data.
• This method standardizes flowsheet data as coded data for information exchange and big data research.
• Standardized IMs within EHRs can expand interoperability of nurse-sensitive data, requiring collaboration with EHR vendors and policymakers.