Artificial Intelligence
Conditions
Keywords
Limited English Proficiency, Machine Learning, Language Barrier, Complex Medical Needs
Brief summary
This is a pragmatic trial that will measure if the use of AI to identify patients with complex care needs and language barriers, as well as active reaching out to clinicians to offer the use of interpreter services will improve the frequency of interpreter use and reduce the time to first interpreter use
Interventions
OTHERComplexity score and implementation
AI machine learning model to identify patients with complex care needs and implementation with active reaching out to clinicians to offer interpreter services
Sponsors
Mayo Clinic
Study design
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Intervention model description
This is a pragmatic clinical trial-a stepped wedge cluster randomized control trial
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Adults with limited English proficiency and requiring an interpreter and having complex medical care needs (includes admitted to the ICU, prolonged hospital stay, requiring palliative care) * Have research authorization
Exclusion criteria
\- Do not require an interpreter
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Number of interpreters | 12 months | the number of interpreters used among patients with LEP and complex care needs |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Change in time to interpreter use | 12 months | The time measured in hours and minutes for an interpreter to be used for patients with LEP |
Countries
United States
Outcome results
None listed