Language Discordance Raises Risk of Hospital Readmissions, U.S. Study Finds

 A June 2024 meta-analysis published in BMJ Quality & Safety was recently brought back into the spotlight by Dr. Lucy Shi, who discussed its findings in an article for The Hospitalist. The study, conducted by Chu et al., examined the link between language discordance and unplanned hospital or emergency department (ED) readmissions.

US Study Finds that Language Discordance Increases Risk of Hospital Readmissions

The researchers also evaluated whether interpretation services could help reduce disparities in these outcomes between patients who speak a non-dominant language and those who do not. Their analysis was based on a literature search of PubMed, Embase, and Google Scholar, initially conducted on January 21, 2021, and updated on October 27, 2022.

Extensive research has shown that patients and families with non-dominant language preferences often face challenges in communication, understanding medical information, and accessing care. Language discordance can contribute to adverse events and poorer outcomes during critical care transitions, such as hospital discharge.

The authors of the paper note that previous research on the effects of language discordance on hospital readmissions and emergency department (ED) revisits has produced mixed results — differences they partially attribute to variations in study criteria and methodologies.

The studies included in the meta-analysis were primarily conducted in Switzerland and English-speaking countries such as the the US, Australia, and Canada. These studies reported data on patient or parental language skills or preferences and measured outcomes such as unplanned hospital readmissions or ED revisits.

To maintain consistency, the authors excluded non-English studies, those lacking primary data, and studies that did not stratify patient outcomes by language preference or use of interpretation services. Ultimately, the analysis included data from 18 adult studies focused on 28- or 30-day hospital readmissions, seven adult studies on 30-day ED revisits, and five pediatric studies examining 72-hour or seven-day ED revisits.

Findings
The meta-analysis revealed that adult patients with language discordance had higher odds of hospital readmission. Specifically, the data showed a statistically significant increase in 28- or 30-day readmission rates for adults with a non-dominant language preference (OR 1.11; 95% CI: 1.04 to 1.18).

Importantly, the impact of interpretation services was notable. In the four studies that confirmed the use of interpretation services during patient-clinician interactions, there was no significant difference in readmission rates. In contrast, studies that did not specify whether interpretation services were provided showed higher odds of readmission for language-discordant patients.

Adult patients with a non-dominant language preference also faced higher odds of emergency department (ED) readmission compared to those who spoke the dominant language. Specifically, the meta-analysis found a statistically significant increase in unplanned ED visits within 30 days among language-discordant adults.

However, this trend was not observed in studies where the use of interpretation services was verified. The authors concluded that “providing interpretation services may mitigate the impact of language discordance and reduce hospital readmissions among adult patients.”

For pediatric patients, the analysis indicated that children whose parents were language-discordant with providers had higher odds of ED readmission within 72 hours and seven days, compared to children whose parents spoke the dominant language fluently.

That said, the authors noted that a meta-analysis for pediatric hospital readmissions was not conducted due to the limited number of studies and inconsistencies in study design. The individual pediatric studies reviewed did not yield statistically significant results.

The study highlights key limitations in the current evidence base — particularly regarding pediatric readmissions and the effectiveness of language access interventions on clinical outcomes. Variability in how language discordance is defined and measured across studies was also identified as a limitation.

The authors recommend developing a more standardized approach to identifying patients facing language-related barriers to care and determining whose language preferences — whether the patient’s or a parent’s — are most influential in shaping clinical outcomes.

Dealmaker Stuns with $10M Donation for Translation Education

Florian and Esther discuss the language industry news of the week, breaking down Slator’s 2025 Language Service Provider Index (LSPI), which features nearly 300 LSPs and reports 6.6% combined growth in 2024 revenues, totaling USD 8.4bn.

Florian touches on a surprise USD 10m donation from private equity executive Mario Giannini to launch a new MA translation and interpreting program at California State University, Long Beach. The duo talks about McKinsey’s State of AI report, which continues to classify translators as AI-related roles and shows that hiring them has become slightly easier.

In Esther’s M&A corner, TransPerfect announced two acquisitions, Technicolor Games and Blu Digital Group, further expanding its presence in gaming and media localization. In Israel, BlueLion and GATS merged to form TransNarrative, and Brazilian providers Korn Translations and Zaum Langs joined forces under the Idlewild Burg group.

Meanwhile, in funding, Teleperformance invested USD 13m in Sanas, a startup offering real-time accent translation for call centers to improve global communication. Lingo.dev raised USD 4.2m, while Dubformer secured USD 3.6m to develop the ‘Photoshop of AI dubbing’.

Florian shares insights from Slator’s 2025 Localization Buyer Survey, which found that over half of buyers want strategic AI support from vendors and many cite inefficient automation as a key challenge.

Private Equity Executive Donates $10M to Launch New MA in Translation Program

Amid growing uncertainty about translation careers due to AI advancements and sensationalized headlines, one California university is celebrating a transformative donation.

On March 11, 2025, California State University, Long Beach (CSULB) announced that Mario Giannini, Executive Co-Chairman of private equity firm Hamilton Lane, has gifted $10 million to establish a Master of Arts program in Translation and Interpreting. The program is set to launch in the fall of 2026.

This isn’t Giannini’s first significant contribution to CSULB. In January 2017, he donated $1.75 million to establish The Clorinda Donato Center for Global Romance Languages and Translation Studies, named after its current director.

CSULB Center Expands Translation Studies with Additional $5.25M Gift

Housed within CSULB’s College of Liberal Arts, The Clorinda Donato Center for Global Romance Languages and Translation Studies serves as a hub for both pedagogical research and instruction in Romance languages.

Students can pursue a minor or graduate certificate in translation studies, while a major in translation is available through collaboration with the Department of Linguistics. The Center has also hosted internship programs, with growing demand from students across disciplines—ranging from speech-language therapy and the arts to politics—seeking on-campus experience.

In 2022, Giannini contributed an additional $5.25 million to The Center, marking the largest gift in the history of CSULB’s College of Liberal Arts. A write-up at the time highlighted The Center’s uniqueness, stating, “The Center is unique in the State of California, offering world-class training in translation studies at state university prices.”

Born in France to Italian-speaking parents, Giannini graduated from Cal State Northridge in 1973 with a BA in English and has credited the CSU system as “a huge influence” on his career. He currently serves as CEO of Hamilton Lane and sits on the firm’s investment committees.

According to Director Clorinda Donato, who also teaches Italian and French, most of the new funds will be used to create scholarships for students admitted to the master’s program.

CSULB to Revive Translation Program with Advanced AI Integration

CSULB’s original translation and interpreting program, founded in the 1980s by renowned legal interpreter Alexander Rainof, was retired when he stepped down. CSULB later proposed reviving the program and presented the idea to Mario Giannini, who was chosen for his connection as a CSU alumnus.

The current undergraduate program, along with the new two-track MA program, aims to train students in diverse areas such as audiovisual, community, educational, legal, literary, and medical translation and interpreting. According to Director Clorinda Donato, the curriculum will take an applied approach by integrating advanced AI, large language models (LLMs), and data science.

“We will proudly offer generous funding to each year’s cohort of prospective students to help reduce the costs of their graduate education,” Donato said. Annual tuition is $18,972 for undergraduates and $17,922 for graduate students, excluding room and board.

SlatorCon Remote March 2025 Offers Essential Insights on the Language Industry and AI

 A Pinch, a Twitch, and Everything in Between: Pinch’s Christian Safka and Twitch’s Susan Maria Howard were among the top language industry leaders who joined hundreds of attendees on March 18, 2025, for the first SlatorCon Remote conference of the year.

Kicking off the day’s events, Slator’s Head of Advisory, Esther Bond, welcomed attendees and invited Managing Director Florian Faes to share the latest findings and insights in his highly anticipated 'industry health check.

In his presentation, Faes began by reflecting on the challenges of 2024. He discussed data from Slator’s 2025 Language Service Provider Index (LSPI) and highlighted the growth of interpreting-focused companies, contrasted with the struggles faced by small, undifferentiated agencies and the rapid rise of language AI, driven by companies like ElevenLabs and DeepL.

Faes also highlighted key findings from Slator’s 2025 Localization Buyer Survey, including the challenges buyers face in implementing AI and the growing need for AI partners to address inefficiencies. He also noted the mixed outlook for the industry in the year ahead.

LLMs Are Just the Beginning

The first expert presentation was delivered by Sara Papi, a Postdoctoral Researcher at the Fondazione Bruno Kessler, who discussed the current state of research in simultaneous speech-to-text translation.

Papi highlighted discrepancies between the original definition and current practices in the speech translation field, identified through a review of expert literature. She specifically pointed out issues related to the use of pre-segmented speech and inconsistencies in terminology.

Slator’s Head of Research, Anna Wyndham, moderated the first panel of the day, featuring Simone Bohnenberger-Rich, Chief Product Officer at Phrase; Simon Koranter, Head of Global Production & Engineering at Compass Languages; and Matteo Nonne, Localization Program Manager at On.

The panelists discussed the evolving role of generative AI in localization, highlighting its shift from initial experimentation to scalable solutions that drive growth. They shared insights on how AI is transforming localization from a cost center into a strategic function by enabling customized, context-aware content adaptation and addressing challenges related to return on investment (ROI) and stakeholder expectations.

Slator’s Alex Edwards, Senior Research Analyst, moderated another panel discussion focused on the adoption of large language models (LLMs) for AI translation in enterprise workflows. Panelists Manuel Herranz, CEO of Pangeanic, and Bruno Bitter, CEO of Blackbird.io, explored whether LLMs truly represent the state of the art.

Herranz and Bitter emphasized that middleware and techniques like Retrieval-Augmented Generation (RAG) are more advanced, and highlighted the importance of fine-tuning smaller, domain-specific models. They also discussed the role of orchestration technology in effectively managing a range of AI tools.

In his presentation, Supertext’s CEO Samuel Läubli echoed insights shared by other speakers, emphasizing that LLMs generate fluent texts by considering broader context. He explored the implications of an AI-first era for translation, the rise of smaller competitive players, and the continued importance of human expertise.

Läubli highlighted that the new Supertext resulted from a 2024 merger between LSP Supertext and AI translation company Textshuttle. He remarked, “I’ve been working in this field for 10 years now, but I haven’t seen a system or AI agent that can guarantee a correct translation — and I’m quite sure I won’t see it in the next 10 years.”

Teresa Toronjo, Localization Manager at Malt, discussed collaboration within leaner localization teams, stressing the importance of diverse partnerships, scalable processes, and maintaining quality consistency with cost-effectiveness guided by experts.

If you missed SlatorCon Remote March 2025 in real-time, recordings will be available soon through our Pro and Enterprise plans.

AI Enhances Multilingual Patient Care with Insights from Jaide Health CEO Joe Corkery, MD

Joe Corkery, MD, CEO and Co-Founder of Jaide Health, joins SlatorPod to discuss how Jaide Health is driving medical interpreting and translation with AI, bridging communication gaps for limited English proficiency (LEP) patients and improving healthcare accessibility.

With a background in computer science, medicine, and AI product leadership at Google, Joe co-founded Jaide Health with Julie Wilner, RN, in 2023 to address a long-standing need for real-time, interactive communication for the LEP patient population.

Unlike older machine translation models, which worked sentence by sentence without context, Joe shares how generative AI can maintain coherence, track gender references, and infer meaning from prior context — crucial in medical settings.

The CEO remains pragmatic about Trump’s executive order designating English as the US’s official language and revoking previous language access mandates. He argues that such policies will not change the healthcare industry’s commitment to multilingual patient care but may push hospitals to seek more cost-effective solutions — potentially accelerating AI adoption.

Looking ahead, Jaide Health is focusing on expanding into document translation, particularly for discharge instructions and patient portal messaging, areas where current solutions are slow or impractical.

New Research Explores How to Boost Large Language Models’ Multilingual Performance

In a February 20, 2025 paper, researchers Danni Liu and Jan Niehues from the Karlsruhe Institute of Technology proposed a way to improve how large language models (LLMs) perform across different languages.

New Research Explores How to Boost Large Language Models’ Multilingual Performance

They explained that LLMs like Llama 3 and Qwen 2.5, show strong performance in tasks like machine translation (MT) but often struggle with low-resource languages due to limited available data. Current fine-tuning processes do not effectively bridge the performance gaps across diverse languages, making it difficult for models to generalize effectively beyond high-resource settings.

The researchers focus on leveraging the middle layers of LLMs to enable better cross-lingual transfer across multiple tasks, including MT.

LLMs consist of multiple layers. The early (or bottom) layers handle basic patterns like individual words, while the final (or top) layers focus on producing a response. The middle layers play a key role in capturing the deeper meaning of sentences and how different words relate to each other.

Liu and Niehues found that these middle layers “exhibit the strongest potential for cross-lingual alignment,” meaning they help ensure that words and phrases with similar meanings are represented in a comparable way across languages. Strengthening this alignment helps the model transfer knowledge between languages more effectively.

By extracting embeddings (i.e., representations of text in vector form) from the model’s middle layers and adjusting them so that equivalent concepts are closer together across languages, the researchers aim to improve the model’s ability to understand and generate text in multiple languages.

Alternating Training Strategy

Rather than relying solely on task-specific fine-tuning, they introduce an “alternating training strategy” that switches between task-specific fine-tuning (e.g., for translation) and alignment training. Specifically, an additional step — middle-layer alignment — is integrated into the fine-tuning process to ensure that the representations learned in one language are more transferable to others.

Tests showed that this method improved both translation accuracy and performance across both high-resource and low-resource languages. Liu and Niehues noted that the models were also able to generalize their performance to languages not included in the initial alignment training.

One significant advantage of this method is its modular nature: “task-specific and alignment modules trained separately can be combined post-hoc to improve transfer performance” without requiring full model retraining. This makes it possible to improve existing models with enhanced multilingual capabilities while avoiding the high computational costs of retraining from scratch.

Additionally, this approach is faster and more cost-effective since “a few hundreds of parallel sentences as alignment data are sufficient.”

The researchers have made the code available on GitHub, allowing others to implement and test their approach.

CEOs React as Trump Declares English the Sole Official Language of the US

In response to President Trump’s executive order designating English as the official language of the US, SlatorPod gathered Dipak Patel, CEO of GLOBO, and Peter Argondizzo, CEO of Argo Translation, to discuss its implications for the US language industry.

The discussion highlighted that language access has long been a key part of US policy, particularly in healthcare, education, and legal services. Dipak pointed out that eliminating language services would create inefficiencies, making it harder for medical professionals to provide accurate care.

CEOs React as Trump Declares English the Sole Official Language of the US

Peter emphasized the broader uncertainty the order creates as many organizations rely on federal funding for language services, and a lack of clear guidance could lead to reduced support in schools, courts, and public services.

Both CEOs acknowledged that while this order presents challenges, the language services industry has historically adapted to change. Dipak suggested that financial pressures may push the industry to innovate, potentially accelerating AI adoption in interpreting.

CEOs React as Trump Declares English the Sole Official Language of the US

While the long-term impact remains unclear, the consensus is that language access will persist — driven by business needs and market demand.

Researchers Present DOLFIN, a New Test Set for AI Translation for Financial Content

On February 5, 2025, a team of researchers from Grenoble Alpes University and Lingua Custodia, a France-based company specializing in AI and natural language processing (NLP) for the finance sector, introduced DOLFIN, a new test set designed to evaluate document-level machine translation (MT) in the financial domain.

The researchers say that the financial domain presents unique challenges for MT due to its reliance on precise terminology and strict formatting rules. They describe it as “an interesting use-case for MT” since key terms often shift meaning depending on context.

For example, the French word couverture means blanket in a general setting but hedge in financial texts. Such nuances are difficult to capture without larger translation units.

Despite strong research interest in document-level MT, specialized test sets remain scarce, the researchers note. Most datasets focus on general topics rather than domains such as legal and financial translation.

Given that many financial documents “contain an explicit definition of terms used for the mentioned entities that must be respected throughout the document,” they argue that document-level evaluation is essential. 

DOLFIN allows researchers to assess how well MT models translate longer texts while maintaining context. 

Unlike traditional test sets that rely on sentence-level alignment, DOLFIN structures data into aligned sections, enabling the evaluation of broader linguistic challenges, such as information reorganization, terminology consistency, and formatting accuracy.

Context-Sensitive

To build the dataset, they sourced parallel documents from Fundinfo, a provider of investment fund data, and extracted and aligned financial sections rather than individual sentences. The dataset covers English-French, English-German, English-Spanish, English-Italian, and French-Spanish, with an average of 1,950 segments per language pair. 

The goal, according to the researchers, was to develop “a test set rich in context-sensitive phenomena to challenge MT models.”

To assess the usefulness of DOLFIN, the researchers evaluated large language models (LLMs) including GPT-4o, Llama-3-70b, and their smaller counterparts. They tested these models in two settings: translating sentence by sentence versus translating full document sections. 

They found that DOLFIN effectively distinguishes between context-aware and context-agnostic models, while also exposing model weaknesses in financial translation.

Larger models benefited from more context, producing more accurate and consistent translations, while smaller models often struggled. “For some segments, the generation enters a downhill, and with every token, the model’s predictions get worse,” the researchers observed, describing how smaller LLMs failed to maintain coherence over longer passages.

DOLFIN also reveals persistent weaknesses in financial MT, particularly in formatting and terminology consistency. Many models failed to properly localize currency formats, defaulting to English-style notation instead of adapting to European conventions.

The dataset is publicly available on Hugging Face.

Authors: Mariam Nakhlé, Marco Dinarelli, Raheel Qader, Emmanuelle Esperança-Rodier, and Hervé Blanchon

Why Interpreting Remains a Growth Market with Boostlingo CEO Bryan Forrester

Bryan Forrester, Co-founder and CEO of Boostlingo, returns to SlatorPod for round 2 to talk about the company’s growth, the US interpreting market, and the evolving role of AI.

Bryan shares how the company has tripled in size since he last appeared on the pod, driven by strategic acquisitions, including VoiceBoxer and Interpreter Intelligence, and a rebranding effort to unify its product portfolio.

Bryan explains how Boostlingo balances innovation with practicality, ensuring that new features align with customer needs. He highlights the company’s three-pronged strategy: retaining existing customers, enabling growth, and making long-term bets on emerging trends.

While tools like real-time captions and transcription enhance efficiency, Bryan stresses that AI alone cannot replace human interpreters in complex industries like healthcare. He highlights privacy, compliance, and the nuanced expertise of human interpreters as critical factors, positioning AI as a supportive tool rather than a replacement.

https://youtu.be/fMNcJ5EV2zk

Bryan discusses market dynamics and regulatory changes, including how those under the new US administration could influence language access demand, particularly in areas like healthcare and public services. 

He describes Boostlingo’s strategy of leveraging third-party AI models, optimizing them with proprietary data, and rigorously testing to ensure quality and reliability. Looking ahead, Boostlingo plans to expand internationally and integrate AI ethically and effectively into its offerings, guided by its newly formed AI Advisory Board. 

AI in Interpreting: Slator Pro Guide

Slator's Pro Guide: AI in Interpreting is an absolute must-read for all providers of interpreting services and solutions. Here, the authors give a quick snapshot of what the newest applications of AI and large language models (LLMs) look like in interpreting.

This Slator Pro Guide will bring you up to speed on what value AI can bring to your company and the new interpreting workflows, service models, and speech AI capabilities now available to you.

The guide covers 10 one-page, actionable case studies-thematically designed and presented as vibrant infographics drawn from research and interviews with some of the leading interpreting service providers in the industry.

The ten use cases highlight new areas of growth, innovative models for service delivery, and novel workflows in interpretation made possible by the recent developments in LLMs, speech-to-text, and speech synthesis.

We will illustrate how AI speech translation solutions are being leveraged to open up language access across corporate, government, and healthcare settings, cutting across a wide variety of settings and service delivery models.

The guide also discusses AI as an interpreter tool and co-pilot, as well as its capability to optimize operations and extract insights from interpreted interactions.

Each use case describes the underlying concept and practical implications. An adoption and value-add score is also provided to reflect the industry's current level of uptake for the application as well as the additional value that it delivers to end clients.

We explain how the technology works and offer a brief list of leading AI solution providers currently on the market.

We expand on the new opportunities and benefits that each use case presents for interpreting stakeholders and carry out an impact analysis for the interpreting sector.

We also identify key risks and limitations to watch out for, which need to be considered in the adoption process.

The guide provides a higher-level overview of the key and impactful applications that can serve as a launching pad for stakeholders to make strategic decisions about adopting AI in interpreting technology and service models.

This Pro Guide is a must-read and time-saving briefing on how AI is revolutionizing the interpretation landscape.