IN-GROUP/OUT-GROUP – DOES IT MAKE A DIFFERENCE? GENDER, ETHNICITY, RACE AND FACE-TIME

Purpose: There has long been concern that people in socially disadvantageous positions, e.g., minorities, receive fewer healthcare resources or time spent with their clinicians. With the advent of Real-time location systems (RTLS) we are able to ask–does clinician/patient time together differ if the patient and clinician are congruent or not congruent with regard to gender, ethnicity or race. We hypothesized the non-congruent pairings will spend less time together than congruent pairings.

Method: From 2008-2011, 5 local clinics have had varying lengths of experience using RTLS. In these clinics, all clinical staff wore RTLS transponders and all patients were assigned transponders for the visit duration. Wait time was calculated as time from registration to time entering exam room/office, Face time was the duration clinicians and patients were physically co-located in the same exam room/office and flow time was the duration from patient tag registration to its unregistration. A sample from the clinic with the longest continuous experience was drawn from 1/2010 to 1/2011. This process data was then paired where possible with data from the local EMR where demographic information on both the patient and clinicians was extracted. Data was analyzed using standard single and multivariable statistical methods.

Result: 665 patient encounters were identified in the RTLS that could be readily paired with EMR data. This clinic had 6 Clinicians (3M/3F), 4 residents (2M/2F). The patients were age: Mean = 44, 25%-75% = 32-55, max =88, Gender: M 35%/F65%, Income: Mean = 55.6K, 25%-75% = 41-63, min = 26, max =154. Ethnicity: Cauc (82%),Afr-amer (7.4%), Asian( 5.5%), Hisp (3%), Unk(2.1%). Lang: English (95%)/Limited or no English (5%)

Conclusion: In our clinics face time did not seem to vary with gender or ethnic congruency. In fact traditionally underserved groups seemed to have on average longer face time and more affluent patients had on average shorter face times. One potential explanation may be that group congruency may result in faster communication and thus shorter face-times. Traditionally underserved groups did however experience longer flow times. One potential explanation is that this may result from system issues such as inefficient interactions with the insurance system, bureaucracy or nonclinical staff.