Analysing ethnicity data Tools and methods Martin Bardsley Assistant Director. Office for Information on Health Care Performance

Overview  Data quality in NHS  Using research evidence to estimate local needs  Using incomplete data – making the best of a bad job

Problems in looking at quantitative ethnic data  Defining ethnicity – variables of interest  Heterogeneity of ethnic groups  Information available  Small numbers  Denominators – especially between Census

Coding and recording ethnic group  Limited implementation across NHS information systems  Hospital based PAS/HES  Primary and community care  Workforce Statistics  Clinical databases  Completeness and accuracy of coding  Relative priority given to looking at diversity  Spiral of information neglect  Needs for monitoring/encouragement

Completeness of ethnic coding in MH Trusts

% not known on HES vs % non–white population

Estimating Differential Needs  Known difference in disease prevalence by ethnic group from research studies  Use local population structures to estimate differences in underlying needs  Extend to look at population projections and change

Estimating prevalence of diabetes in London  Clinically diagnosed diabetes 4-5 times higher Black and S Asian ethnic groups vs ‘White group’ (Williams & Farrar, 2000)  Expect differences in diabetes by borough to range about London mean –20% to +48%  If estimated prevalence for ‘White groups’ 4.4% with ethnic mix in London, prevalence expected around 4.9% in 1999, rising to 5.3% in 2011

Proportional Admission Ratios  Basically same methods as Proportional Mortality Ratios  Looks at differential hospital admission by ethnic group - where codes recorded  Compares observed % admissions for given diagnoses/treatments by ethnic group with expected based on all groups  Indirectly standardises for age and sex

Calculation Proportional Admission Ratios PAR = Observed Admissions/Expected Admissions Observed= No.admissions for diagnosis x, for ethnic group y Expected = Reference % admissions for diagnosis x (from all ethnic groups) * Total admissions for ethnic group y PAR values>1 indicate higher admissions than expected, values <1 indicate lower admissions

Calculating Expected Admissions For a given and and sex group eg males All admissions for ethnic group y all diagnoses in Trust A =1000 No. asthma admissions in ethnic group y in Trust A = 32 (3.2%) % admissions for asthma across all trusts/ethnic groups = 1.6% Expected admissions = 16 Sum observed and expected across age/sex groups

PAR for asthma admissions London

Proportional admissions for CABG/PTCA

Caveats  Assumes cases where we have an ethnic group recorded are representative of the total  Need large numbers of total diagnoses  Assumes standard case mix – not specialist trusts  Numbers of observed admissions can still be small  Effects of ‘not knowns’  Understanding the expected values

Examples of differences in admission pattern by ethnic group Census Group High % admissionsLow % admissions White Cancers Musculoskeletal Dis. Diabetes Cerebrovascular Disease Black Caribbean Diabetes Disease of blood Infectious Diseases Injury and poisoning IndianTuberculosis CHD Cancers Mental Disorders

General Comments  Key issues around completeness and quality of data  Need to use available information in different ways – and occasionally make some bold assumptions  Importance of integrating information from research studies into local settings  Process measurement/assessments may often be the best choice

Importance of Process Measures Example of CHI questions in Clinical Governance Reviews  Please give a brief description of committee responsibilities (and staff responsibilities) for ensuring that the trust complies with its duties under the Race Relations (Amendment) Act including in particular its duty relating to racial harassment  Please outline the extent of any training in managing equality and diversity within the trust, including that received by the trust board.

Examples from CHI document request  Trust strategy on equal opportunities and latest board level reports on progress in implementation  The trust’s ethnic monitoring data for staff over the last 12 months  Latest information on uptake of training in cultural competence/awareness and equal opportunities, by staff group

Comparing workforce to populations

Comparing % non-white on HES to populations