Optimizing Interpreter Services Workflow

At Lucile Packard Children’s Hospital, interpretation is critical to patient experience. Interpretation has the power not only to transform patient equity but also to improve health outcomes. The Interpreter Services department impacts a wide variety of stakeholders including LPCH staff, patients, and families. For our patients and their families who are LEP (Limited English Proficiency) interpretation is the only thing that gives them voice. For this reason, the need for interpretation cannot be understated. The Interpreter Services department at LPCH must work to appropriately manage in-person interpretation requests while maintaining and providing virtual interpretation through iPads and telephones that are available throughout the hospital. 

The irreplaceable need for interpretation services at LPCH makes the appropriate allocation of the limited resource of both in-person and virtual interpreters of the utmost importance. Pinpointing unmet demand and opportunities to increase efficiency could yield huge improvements to patient experience at LPCH. 

This project aimed to achieve a better understanding of the system through a combination of qualitative and quantitative analysis of the interpreter services system at LPCH. The goals of this project were twofold. First, we set out to identify opportunities to increase efficiency in order to free up time of busy in-person interpreters and to optimize scheduling. Second, we worked to identify unmet patient needs to stop LEP patients from slipping through the cracks. Quantitatively, we analyzed interpreter data to understand trends in scheduling and wait times. Qualitatively, we interviewed a wide range of stakeholders to see the issue from all perspectives. 

The first finding from this project is the fact that within LPCH, there is a significant amount of unmet patient need. On average, English speaking patients and their families participate in significantly more conversational interactions with staff than LEP families. For example, in the PICU nurses report between 12 and 24 conversational interactions with English families in a 12 hour shift compared to just 2 conversational interactions with LEP families with the use of interpretation, virtual or in-person.  Second, our stakeholder interviews identified the need for increased availability of iPads for virtual interpretation, with stakeholders finding that increased iPads could help meet our unmet patient need. Third, we found there is a need for increased staff training to teach staff how to best use interpreter services. Fourth, system changes that increased transparency of requests and the status of interpreters was highly desired.

Interpreter services saw increased demand from 2020 to 2021, particularly with the proportion of telehealth visits completed. Through our analysis of the data, we discovered high rates of medical interpreter delays (~5% of total resolutions). Physicians often waited 30-40 min+ if not directed by dispatchers to use another modality. These delays correlated strongly with the demand of interpretation services, most frequently at 10am and between 2pm-3pm in 2021. We also discovered that the mean duration of the typical appointment was 56 min, a stark difference from the 30 min default scheduling time on Epic. We were able to compute the expected service time on a per unit basis to improve overall planning accuracy.

Next steps for this project include widely distributing a survey to disseminate our findings from our stakeholder interviews in order to affirm these findings on a larger scale. Further, next steps quantitatively include evaluating new scheduling alternatives to free up staff during peak hours. Moreover, we will evaluate the viability of initiatives like outsourcing elements such as AVS translation and interpretation to increase the availability of in-person interpreters.

We would like to give a special thank you to our project sponsors, Marina Persoglia Bell and Kimberley Browne, as well as the MS&E 463 teaching team. Their support and encouragement during this project was so appreciated. Thank you!

Haley Schwager

M.S. Management Science and Engineering


Alex Lin

M.S. Management Science and Engineering


Talia Stanley

B.S. Management Science and Engineering

David Scheinker

Founder & Director, SURF Stanford Medicine