Residents report using different modes of communication with LEP patients depending on the clinical encounter.

Variation in professional interpreter use by type of clinical encounter and not clinical site or patient language underscores the importance of resident decision-making in determining whether LEP patients receive professional interpreter services.

Our findings confirm prior research which suggests there is considerable underuse of professional interpreters among resident physicians caring for LEP patients.

In addition, we found that residents perceive that their communication with hospitalized LEP patients to be worse compared to their communication with clinically similar English-speaking patients.

To improve provider interpreter training efforts, future studies with larger samples sizes are needed to determine how resident characteristics such as specialty, hours of training, and growing up speaking a non-English language at home predict resident physicians’ interpreter use when caring for LEP patients.

From Admission to Discharge:Patterns of Interpreter Use Among Resident Physicians

Amy Shen1, BA; Jenna Kruger1,2, MPH; Judy Quan1,2, PhD; Alicia Fernandez1,2, MD1UCSF School of Medicine, 2 Division of General Internal Medicine, University of California, San Francisco, CA

Communication with hospitalized LEP patients relies on individual providers’ decisions to use professional interpreters.

Underuse of professional interpreters adversely affects quality of care to patients with limited English proficiency (LEP).

AIM To assess resident physicians’ patterns

of communication with LEP patients by hospital encounter type.

To identify predictors of professional interpreter use.

RESULTS

Partial support from R25MD006832 NIH-NIMHD.

Special thanks to UCSF internal medicine, family medicine, and general surgery residency programs for their support and participation in this study.

ACKNOWLEDGEMENTS

Study DesignCross-sectional survey. Resident physicians reported on interpreter use with their last hospitalized LEP patient with whom they experienced a language barrier.

Participants Internal medicine, general surgery, and family medicine resident physicians from one academic medical institution who care for LEP patients across three hospitals.

Data Analysis Descriptive statistics were performed to

ascertain residents’ percent use of professional interpretation, perceived quality of communication, and patterns of interpreter use for six routine hospital encounters. Logistic regression models were used to determine the independent contribution of clinical site, patient characteristics, and physician characteristics to resident physician use of professional interpreters.

BACKGROUND

Table 1. Characteristics of Resident Physicians (N= 149)

Characteristic N (%)*++

Age, range (mean) 25-37 (28.7)

Female 84 (56)

Level of training

PGY-1 85 (57)

PGY-2 34 (23)PGY-3+ 25 (17)

Residency program

Internal Medicine 108 (73)General Surgery 22 (15)Family Medicine 19 (13)

Race/Ethnicity

White 80 (54)

Asian/Pacific Islander 42 (28)

Hispanic/Latino 16 (11)Black 5 (3)Other 4 (3)

Spoke non-English language at home 52 (35)

Proficiency in non-English language+++

(“Speak well enough to provide care”) 80 (54)

Spanish 52 (65) Mandarin 7 (9) Hindi 6 (8) Other 17 (21)Completed international medical work 80 (54)

Hours of interpreter training

0 hours 33 (22)1-3 hours 57 (38)3-5 hours 37 (25)>5 hours 15 (10)

% Patients with LEP, range (mean) 10-70 (35)

Language of LEP patient

Cantonese 75 (50)Spanish 30 (20)Russian 15 (10)Other 29 (21)

Hospital of LEP patient

Private hospital 73 (49)Public hospital 72 (48)Other 4 (3)

DISCUSSION

Admission history Daily rounds Updates/check-ins Procedure consents

Family meetings Discharge instructions

0102030405060708090

100

61

42 43

85

73

60

2113 16

611 1418

45 41

916

26

Professional only

Professional+got by

Got by

In our sample, most residents (91%) reported that their quality of communication with hospitalized LEP patients was "slightly worse" (62%) or "much worse" (29%) compared to their communication with clinically similar English-speaking patients. Only patient language with adjusted odds ratio of 3.57 (95% Cl: 1.01, 12.67) was shown to be a significant, but borderline, predictor of much worse vs. other quality of communication rating in logistic regression models.

% u

se b

y re

siden

t phy

sicia

ns%

resi

dent

phy

sicia

ns

% professional interpreter use

Much worse Slightly worse Same Slightly better Much better0

10203040506070

29

62

71 1

% re

siden

t phy

sici

ans

0-20 21-40 41-60 61-80 81-10005

1015202530

23

28

20 19

11

In our sample, 71% of residents reported using professional interpreters for less than 60% of hospital clinical encounters. Professional interpreter use was dichotomized with different percentage cut-offs for different logistic regression models. There were no consistently significant predictors of professional interpreter use, through physician specialty, hours of interpreter training and growing up speaking a non-English language were associated with interpreter use in some models.

Quality of communication

Figure 3. Patterns of interpreter use among resident physicians for common hospital encounters.

*The survey response rate was 73%.++Total percentages may not add up to 100 due to rounding.+++Total numbers add up to > 80 because subjects could specify more than one non-English language spoken.

Figure 1. Resident physicians’ percent use of professional interpretation during the hospital course of an LEP patient.

Figure 2. Resident physicians’ self-rated quality of communication with an LEP patient compared to an English-speaking patient.

Patterns of professional interpreter use substantially varied by type of clinical encounter, with more residents reporting getting by with ad-hoc interpreters, their own language skills or not talking to the patient due to time constraints during routine daily rounds and check-ins than during “high-stakes” planned encounters such as procedure consents or family meetings (45% and 41% vs. 9% and 16%, p-value<0.005).

METHODS