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.
BackgroundDiabetes peer support, where one person with diabetes helps guide and support others, has been proposed as a way to improve diabetes management. We have tested whether different diabetes peer support strategies can improve metabolic and/or psychological outcomes.MethodsPeople with type 2 diabetes (n = 1,299) were invited to participate as either ‘peer’ or ‘peer support facilitator’ (PSF) in a 2x2 factorial randomised cluster controlled trial across rural communities (130 clusters) in England. Peer support was delivered over 8–12 months by trained PSFs, supported by monthly meetings with a diabetes educator. Primary end point was HbA1c. Secondary outcomes included quality of life, diabetes distress, blood pressure, waist, total cholesterol and weight. Outcome assessors and investigators were masked to arm allocation. Main factors were 1:1 or group intervention. Analysis was by intention-to-treat adjusting for baseline.ResultsThe 4 arms were well matched (Group n = 330, 1:1(individual) n = 325, combined n = 322, control n = 322); 1035 (79•7%) completed the mid-point postal questionnaire and 1064 (81•9%) had a final HbA1c. A limitation was that although 92.6% PSFs and peers were in telephone contact, only 61.4% of intervention participants attended a face to face session. Mean baseline HbA1c was 57 mmol/mol (7•4%), with no significant change across arms. Follow up systolic blood pressure was 2•3mm Hg (0.6 to 4.0) lower among those allocated group peer-support and 3•0mm Hg (1.1 to 5.0) lower if the group support was attended at least once. There was no impact on other outcomes by intention to treat or significant differences between arms in self-reported adherence or medication.ConclusionsGroup diabetes peer support over 8–12 months was associated with a small improvement in blood pressure but no other significant outcomes. Long term benefits should be investigated.Trial RegistrationISRCTN.com ISRCTN6696362166963621
Background/objectives To determine which aspects of primary care matter most to patients, we aim to identify those aspects of patient experience that show the strongest relationship with overall satisfaction and examine the extent to which these relationships vary by socio-demographic and health characteristics.
Martin Roland and Charlotte Paddison call for greater emphasis on continuity of care and clinical judgment to improve the experience of patients with multiple conditions
ObjectivesUncertainties exist about when and how best to adjust performance measures for case mix. Our aims are to quantify the impact of case-mix adjustment on practice-level scores in a national survey of patient experience, to identify why and when it may be useful to adjust for case mix, and to discuss unresolved policy issues regarding the use of case-mix adjustment in performance measurement in health care.Design/settingSecondary analysis of the 2009 English General Practice Patient Survey. Responses from 2 163 456 patients registered with 8267 primary care practices. Linear mixed effects models were used with practice included as a random effect and five case-mix variables (gender, age, race/ethnicity, deprivation, and self-reported health) as fixed effects.Main outcome measuresPrimary outcome was the impact of case-mix adjustment on practice-level means (adjusted minus unadjusted) and changes in practice percentile ranks for questions measuring patient experience in three domains of primary care: access; interpersonal care; anticipatory care planning, and overall satisfaction with primary care services.ResultsDepending on the survey measure selected, case-mix adjustment changed the rank of between 0.4% and 29.8% of practices by more than 10 percentile points. Adjusting for case-mix resulted in large increases in score for a small number of practices and small decreases in score for a larger number of practices. Practices with younger patients, more ethnic minority patients and patients living in more socio-economically deprived areas were more likely to gain from case-mix adjustment. Age and race/ethnicity were the most influential adjustors.ConclusionsWhile its effect is modest for most practices, case-mix adjustment corrects significant underestimation of scores for a small proportion of practices serving vulnerable patients and may reduce the risk that providers would ‘cream-skim’ by not enrolling patients from vulnerable socio-demographic groups.
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