Variations in dementia diagnosis in England and association with general practice characteristics.

OBJECTIVES: Improving dementia diagnosis rates in England has been a key strategic aim of the UK Government but the variation and low diagnosis rates are poorly understood. The aim of this study was to explore the variation in actual versus expected diagnosis of dementia across England, and how these variations were associated with general practice characteristics. METHOD: A cross-sectional, ecological study design using secondary data sources and median regression modelling was used. Data from the year 2011 for 7711 of the GP practices in England (92.7%). Associations of dementia diagnosis rates (%) per practice, calculated using National Health Service England's 'Dementia Prevalence Calculator' and various practice characteristics were explored using a regression model. RESULTS: The median dementia diagnosis rate was 41.6% and the interquartile range was 31.2-53.9%. Multivariable regression analysis demonstrated positive associations between dementia diagnosis rates and deprivation of the population, overall Quality and Outcomes Framework performance, type of primary care contract and size of practice list. Negative associations were found between dementia diagnosis rates and average experience of GPs in the practice and the proportion of the practice caseload over 65 years old. CONCLUSION: Dementia diagnosis rates vary greatly across GP practices in England. This study has found independent associations between dementia diagnosis rates and a number of patient and practice characteristics. Consideration of these factors locally may provide targets for case-finding interventions and so facilitate timely diagnosis.

Optimizing primary care research participation: a comparison of three recruitment methods in data-sharing studies.

BACKGROUND: Recruitment of representative samples in primary care research is essential to ensure high-quality, generalizable results. This is particularly important for research using routinely recorded patient data to examine the delivery of care. Yet little is known about how different recruitment strategies influence the characteristics of the practices included in research. OBJECTIVE: We describe three approaches for recruiting practices to data-sharing studies, examining differences in recruitment levels and practice representativeness. METHODS: We examined three studies that included varying populations of practices from West Yorkshire, UK. All used anonymized patient data to explore aspects of clinical practice. Recruitment strategies were 'opt-in', 'mixed opt-in and opt-out' and 'opt-out'. We compared aggregated practice data between recruited and not-recruited practices for practice list size, deprivation, chronic disease management, patient experience and rates of unplanned hospital admission. RESULTS: The opt-out strategy had the highest recruitment (80%), followed by mixed (70%) and opt-in (58%). Practices opting-in were larger (median 7153 versus 4722 patients, P = 0.03) than practices that declined to opt-in. Practices recruited by mixed approach were larger (median 7091 versus 5857 patients, P = 0.04) and had differences in the clinical quality measure (58.4% versus 53.9% of diabetic patients with HbA1c ≤ 59 mmol/mol, P < 0.01). We found no differences between practices recruited and not recruited using the opt-out strategy for any demographic or quality of care measures. CONCLUSION: Opt-out recruitment appears to be a relatively efficient approach to ensuring participation of typical general practices. Researchers should, with appropriate ethical safeguards, consider opt-out recruitment of practices for studies involving anonymized patient data sharing.

Predictors of response to anti-TNF therapy in ankylosing spondylitis: results from the British Society for Rheumatology Biologics Register.

OBJECTIVE: Few data exist on the use of anti-TNF drugs for AS during routine clinical use in the UK. This report describes an improvement in Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and Bath Ankylosing Spondylitis Functional Index (BASFI) after 6 months of therapy in 261 patients enrolled in a national prospective observational register. METHODS: The British Society for Rheumatology Biologics Register (BSRBR) recruited patients starting anti-TNF therapy for AS between 2002 and 2006. Multivariable linear regression models were used to estimate the predictors of absolute improvement in BASDAI and BASFI at 6 months. Covariates included age, gender, disease duration, baseline BASDAI and BASFI, presence of raised inflammatory markers (defined as twice the upper limit of normal) and DMARD therapy. RESULTS: The cohort was young (median age 43 years) and 82% were males. Median baseline BASDAI was 7.6 and BASFI 7.9. At 6 months, the mean improvements in BASDAI and BASFI were 3.6 and 2.6 U, respectively; 52% reached a BASDAI50. Patients with raised inflammatory markers at the start of therapy had a 0.9-U (95% CI 0.2, 1.5) better improvement in BASDAI compared with those without. Lesser responses were seen in those with higher baseline BASFI scores. Women had a 1.1-U (95% CI 0.3, 2.0) greater improvement in BASFI at 6 months, as did those who were receiving concurrent DMARD therapy [0.9 U (95% CI 0.2, 1.7)]. CONCLUSIONS: The majority of patients receiving anti-TNF therapy for AS during routine care demonstrated an improvement in disease activity. Raised inflammatory markers at the start of therapy predicted a greater improvement in BASDAI, identifying a group of patients who may be more responsive to anti-TNF therapies, although the results were not confined to this group.