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Background <p>Over 60 million patients in the USA have limited English proficiency (LEP) and experience barriers in care. Still, there exists no standardized method of monitoring the utilization of language interpreting services (LIS).</p> Objective <p>To introduce a methodological approach to systematically monitor utilization of LIS for LEP patients.</p> Design <p>We utilized a One-To-Many Match algorithm to align inpatient visits of LEP patients from the electronic health record (EHR) with corresponding calls from LIS billing logs, using a unique patient identifier (MRN) and LIS call dates within patient’s admit and discharge dates. Due to error when MRNs are recorded by LIS, the FuzzyWuzzy Probabilistic String-Matching technique was utilized to enhance match accuracy where exact matches were unattainable, addressing inherent complexities in language data matching.</p> Participants <p>The study involved 5823 inpatient encounters with a non-English preference in an urban hospital system in 2020, representing a linguistically diverse patient base, and attempted to match these against 183,655 LIS call logs.</p> Main Measures <p>Our approach successfully matched 83.1% (4389 out of 5823) of inpatient encounters to an LIS call.</p> Key Results <p>We observed significant language-specific disparities in LIS usage, with Spanish leading in call volume at 2737 calls (exact matches) and 845 (probabilistic matches). Concordance rates varied, exceeding 94% for all languages in exact matches and ranging from 53.9% for Arabic to 71.6% for Russian in probabilistic matches. The average frequency of LIS calls was about one call per day per language group in the inpatient setting.</p> Conclusions <p>The study provides vital insights into language service preferences, frequency, and duration.&#xa0;These findings emphasize the need for standard methods in monitoring LIS usage to enhance patient outcomes for LEP patients.</p>

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Monitoring Use of Language Interpreting Services for Patients with Limited English Proficiency: Methods to Match Patient Medical Records with Interpreter Billing Logs

  • 期刊论文

  • 发表日期：

    2025年1月28日

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  • Neha Mukherjee,
  • Roy Lee,
  • Nhat Ngyuen,
  • Nina Bickell,
  • Lynne D. Richardson,
  • Ka Ming Ngai

摘要

Background

Over 60 million patients in the USA have limited English proficiency (LEP) and experience barriers in care. Still, there exists no standardized method of monitoring the utilization of language interpreting services (LIS).

Objective

To introduce a methodological approach to systematically monitor utilization of LIS for LEP patients.

Design

We utilized a One-To-Many Match algorithm to align inpatient visits of LEP patients from the electronic health record (EHR) with corresponding calls from LIS billing logs, using a unique patient identifier (MRN) and LIS call dates within patient’s admit and discharge dates. Due to error when MRNs are recorded by LIS, the FuzzyWuzzy Probabilistic String-Matching technique was utilized to enhance match accuracy where exact matches were unattainable, addressing inherent complexities in language data matching.

Participants

The study involved 5823 inpatient encounters with a non-English preference in an urban hospital system in 2020, representing a linguistically diverse patient base, and attempted to match these against 183,655 LIS call logs.

Main Measures

Our approach successfully matched 83.1% (4389 out of 5823) of inpatient encounters to an LIS call.

Key Results

We observed significant language-specific disparities in LIS usage, with Spanish leading in call volume at 2737 calls (exact matches) and 845 (probabilistic matches). Concordance rates varied, exceeding 94% for all languages in exact matches and ranging from 53.9% for Arabic to 71.6% for Russian in probabilistic matches. The average frequency of LIS calls was about one call per day per language group in the inpatient setting.

Conclusions

The study provides vital insights into language service preferences, frequency, and duration. These findings emphasize the need for standard methods in monitoring LIS usage to enhance patient outcomes for LEP patients.