Use of interpreters in primary care: characterising the population and its association with all-cause mortality and major adverse cardiovascular events.

Priya Sarkar

Keywords: Interpreters, all-cause mortality; major adverse cardiovascular events.

Background:

Given the diverse cultural composition of the U.K. and especially West Midlands, an increasing number of clinical consultations must be carried out with interpreter. Since general practice is the first point of access to healthcare in the U.K, this is an especially important issue in this sector.
Interpreters may improve a clinician's understanding of the patient's symptoms, and vice versa the patient's understanding of a clinician's advice. Alternatively, the need for an interpreter may be a marker of a particular disadvantage the patient faces in managing their health and wellbeing.

Research questions:

Does the population needing interpreters in primary care have the same all-cause mortality and MACE rates as those without interpreters?

The aim is to understand the characteristics associated with use of interpreters (ethnicities/socioeconomic background/age/sex/gender/region) in primary care and to explore the whether needing an interpreter is associated with mortality and major adverse cardiac events (MACE)
P: Adult (>18 years) English population
I: Use of interpreter in GP consultations
C: Population not requiring interpreters
O: All-cause mortality and MACE

Method:

This will be a retrospective matched cohort study using CPRD (Clinical Practice Research Datalink) Aurum primary care database.
Data will be extracted from CPRD (patients coded as requiring/using interpreters) and then matched with those not using interpreters according to risk factors for MACE (hypertension, diabetes mellitus, hyperlipidaemia, smoking, chronic kidney disease, obesity, sex, age, ethnicity, socioeconomic status (SES) and practice. Date and cause of death will be used to compare these outcomes between my two groups. A matching ratio of 10:1 has been proposed.

STATA will be used for statistical analysis/Iogistic regression to assess how these two cohorts vary in sociodemographic characteristics. Subgroup analysis will also be carried out (ethnicity, age, sex, SES, practice area location).

Results:

Conclusions:

Use results to explore and improve health inequalities in patients using interpreters in future healthcare planning.

Points for discussion:

What results would you expect in your country/region?

What is your experience of using interpreters in primary care?

What policy recommendations are needed for interpreter services in healthcare systems, especially in primary care?

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