Understanding ethnic and other socio-demographic differences in patient experience of primary care: evidence from the English General Practice Patient Survey

Abstract

BackgroundEthnic minorities and some other patient groups consistently report lower scores on patient surveys, but the reasons for this are unclear. This study examined whether low scores of ethnic minority and other socio-demographic groups reflect their concentration in poorly performing primary care practices, and whether any remaining differences are consistent across practices.MethodsUsing data from the 2009 English General Practice Patient Survey (2 163 456 respondents from 8267 general practices) this study examined associations between patient socio-demographic characteristics and 11 measures of patient-reported experience.FindingsSouth Asian and Chinese patients, younger patients, and those in poor health reported a less positive primary care experience than White patients, older patients and those in better health. For doctor communication, about half of the overall difference associated with South Asian patients (ranging from −6 to −9 percentage points) could be explained by their concentration in practices with low scores, but the other half arose because they reported less positive experiences than White patients in the same practices. Practices varied considerably in the direction and extent of ethnic differences. In some practices ethnic minority patients reported better experience than White patients. Differences associated with gender, Black ethnicity and deprivation were small and inconsistent.ConclusionSubstantial ethnic differences in patient experience exist in a national healthcare system providing universal coverage. Improving the experience of patients in low-scoring practices would not only improve the quality of care provided to their White patients but it would also substantially reduce ethnic group differences in patient experience. There were large variations in the experiences reported by ethnic minority patients in different practices: practices with high patient experience scores from ethnic minority patients could be studied as models for quality improvement.

Cancer patients’ respect experiences in relation to perceived communication behaviours from hospital staff: analysis of the 2012–2013 National Cancer Patient Experience Survey

“…Observed differences in reported respect by age, gender and ethnicity are consistent with past studies on cancer patients' experiences of respect [25] and overall care [28] and similar disparities in patient experience of healthcare professional communication by age, gender and/or ethnicity have been observed in the general UK patient population [29,30]. Past studies with US general patient samples have likewise shown younger and non-White patients to be less likely to report always being treated with respect and dignity but no difference by gender [12,13].…”

“…However, this is unlikely to explain all differences in reported respect since differences in patient experience of care remain after adjusting for care site [29,33]. Differences in reported respect could be due to some patient groups being treated with less respect, possibly because of less respectful attitudes towards certain patients [24,35] and/or to differences in patient groups' conceptions and expectations of quality care [30].…”

The acute effects of physical activity on cigarette cravings: Exploration of potential moderators, mediators and physical activity attributes using individual participant data (IPD) meta-analyses

“…All craving measures were taken immediately before the intervention and immediately after (16 studies) or 5 minutes after the intervention (3 studies). To facilitate the use of linear regression modelling and to assist with interpretation of the results, all responses on the 1-7 scale were linearly rescaled to a range of 0-100 (Lyratzopoulos et al 2012). Thus, a mean difference between groups of -10 would indicate that post-intervention cravings were 10 percentage points lower in the intervention group compared with the control group.…”

“…Changes in affect were suggested to mediate the acute effects of PA on cigarette cravings (Taylor et al 2007), hence we included measures of affect (FAS and FS) as potential mediators in our analyses. Similarly to the cravings outcomes, to facilitate interpretation of results and to calculate change scores for affect, both FS (measured on a Likert scale of -5 to +5) and FAS (measured on a Likert scale of 1-6) scores, were linearly rescaled to 0-100 (Lyratzopoulos et al 2012). …”

“…Mixed linear regression models (Higgins et al 2001) were used, adjusted for baseline values of the outcome variable (DtS/SoD for cravings analyses, and FS/FAS for affect analyses), with a fixed effect on study, random intercept on participant (adjustment for multiple observations within participant for cross-over trials) and random effect on treatment (allowing the treatment effect to vary across studies). An approximate 95% mid-range of the effect size across studies (assuming a normal distribution of treatment effects across studies) was derived using the mean difference between the intervention and control groups and the standard deviation for intervention effect across studies (Lyratzopoulos et al 2012). If the fixed effect is given by a and the standard deviation (SD) of the random effect is given by b, then a 95% midrange is given by a -1.96b; a +1.96b.…”