Electronic Health Record Data Collection Practices to Advance Standardization and Interoperability of Patient...

Area of Science:

• Health Informatics
• Health Services Research
• Patient-Centered Care

Background:

• Patients with a non-English language preference (NELP) experience poorer health outcomes.
• Interpreter use is low despite a growing need, impacting care quality.
• Standardized data collection can improve access to language assistance services.

Purpose of the Study:

• Examine practices for collecting and exchanging patient interpreter preferences in electronic health records (EHRs).
• Assess the implementation maturity of data standards for interpreter needs.
• Identify use cases, challenges, and opportunities for standardizing interpreter data.

Main Methods:

• Conducted a narrative review of terminology standards for documenting interpreter preferences in EHRs.
• Held key informant discussions with EHR developers, health systems, clinicians, and federal agencies.
• Synthesized findings to identify implementation gaps and opportunities.

Main Results:

• Healthcare organizations recognize the value of standardized collection of patient language assistance needs.
• Identified use cases include person-centered care, transitions of care, and health care administration.
• Interpreter data fields exist in EHRs but lack mapping to standard terminologies (e.g., LOINC, SNOMED-CT), limiting electronic exchange.

Conclusions:

• Documenting patient interpreter preferences enhances service quality, patient experience, and health equity.
• Routine collection of interpretation needs occurs, but lack of standardization impedes data exchange.
• Advancing standardization is crucial for facilitating patient-centered care and improving health equity.