Detecting referral and selection bias by the anonymous linkage of practice, hospital and clinic data using Secure and Private Record Linkage (SAPREL): case study from the evaluation of the Improved Access to Psychological Therapy (IAPT) service

Background: The evaluation of demonstration sites set up to provide improved access to psychological therapies (IAPT) comprised the study of all people identified as having common mental health problems (CMHP), those referred to the IAPT service, and a sample of attenders studied in-depth. Information technology makes it feasible to link practice, hospital and IAPT clinic data to evaluate the representativeness of these samples. However, researchers do not have permission to browse and link these data without the patients’ consent. Objective: To demonstrate the use of a mixed deterministic-probabilistic method of secure and private record linkage (SAPREL) - to describe selection bias in subjects chosen for in-depth evaluation. Method: We extracted, pseudonymised and used fuzzy logic to link multiple health records without the researcher knowing the patient’s identity. The method can be characterised as a three party protocol mainly using deterministic algorithms with dynamic linking strategies; though incorporating some elements of probabilistic linkage. Within the data providers’ safe haven we extracted: Demographic data, hospital utilisation and IAPT clinic data; converted post code to index of multiple deprivation (IMD); and identified people with CMHP. We contrasted the age, gender, ethnicity and IMD for the in-depth evaluation sample with people referred to IAPT, use hospital services, and the population as a whole. Results: The in IAPT-in-depth group had a mean age of 43.1 years; CI: 41.0 - 45.2 (n = 166); the IAPT-referred 40.2 years; CI: 39.4 - 40.9 (n = 1118); and those with CMHP 43.6 years SEM 0.15. (n = 12210). Whilst around 67% of those with a CMHP were women, compared to 70% of those referred to IAPT, and 75% of those subject to indepth evaluation (Chi square p< 0.001). The mean IMD score for the in-depth evaluation group was 36.6; CI: 34.2 - 38.9; (n = 166); of those referred to IAPT 38.7; CI: 37.9 - 39.6; (n = 1117); and of people with CMHP 37.6; CI 37.3- 37.9; (n = 12143). Conclusions: The sample studied in-depth were older, more likely female, and less deprived than people with CMHP, and fewer had recorded ethnic minority status. Anonymous linkage using SAPREL provides insight into the representativeness of a study population and possible adjustment for selection bias

Predictors of patient non-attendance at Improving Access to Psychological Therapy services demonstration sites

© 2014 The Authors. Published by Elsevier B.V. Background Improving Access to Psychological Therapy (IAPT) services have increased the number of people with common mental health disorders receiving psychological therapy in England, but concerns remain about how equitably these services are accessed.Method Using cohort patient data (N=363) collected as part of the independent evaluation of the two demonstration sites, logistic regression was utilised to identify socio-demographic, clinical and service factors predictive of IAPT non-attendance.Results Significant predictors of IAPT first session non-attendance by patients were: lower non-risk score on the Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM); more frequent thoughts of "being better off dead" (derived from the CORE-OM); either a very recent onset of common mental health disorder (1 month or less) or a long term condition (more than 2 years); and site.Limitations The small sample and low response rate are limitations, as the sample may not be representative of all those referred to IAPT services. The predictive power of the logistic regression model is limited and suggests other variables not available in the dataset may also be important predictors.Conclusions The clinical characteristics of risk to self, severity of emotional distress, and illness duration, along with site, were more predictive of IAPT non-attendance than socio-demographic characteristics. Further testing of the relationship between these variables and IAPT non-attendance is recommended. Clinicians should monitor IAPT uptake in those they refer and implement strategies to increase their engagement with services, particularly when referring people presenting with suicidal ideation or more chronic illness

Variations in GP decision making in the diagnosis of lung cancer

BACKGROUND The United Kingdom's lung cancer patients have lower survival than patients in comparable countries. Delays in diagnosis may contribute to this. There are significant socio-demographic variations in the interval between cancer patients first presenting to their general practitioner (GP) and referral, but it is unclear why these exist. AIM To examine patient and GP characteristics associated with GPs' referral decisions, focusing on patients with symptoms indicative of lung cancer. METHODS Study 1: Systematic literature review considering non-clinical patient, GP and practice characteristics associated with variations in GPs' referral of patients for investigations or to secondary care. Study 2: GP decision making study: a factorial experiment using interactive multimedia vignettes to examine GPs' decisions to refer patients with symptoms indicative of lung cancer, and a survey to examine factors influencing decision making. RESULTS Study 1: 11,791 titles were screened; 47 were of sufficient quality and relevance for inclusion. There was strong evidence that patients over 75 were less likely to be investigated or referred, and of variations by patient gender. However few higher quality studies examined associations with patient ethnicity and GP or practice characteristics, or considered why socio-demographic variations occurred. Study 2: 227 GPs completed the study. GPs were less likely to investigate older than younger patients, and black patients than white. The survey identified several factors that GPs believe affect their referral decisions (such as patients' lifestyles), some of which may explain the observed differences in GPs' referral decisions. CONCLUSIONS My thesis identified socio-demographic variations in GP decision making that are independent of clinical characteristics (for lung cancer and more widely) and factors that may underlie these. Further research addressing the extent to which these factors contribute to socio-demographic variations, and the development of primary care interventions which address these findings, could reduce delays in lung cancer diagnosis

Equity of utilisation of cardiovascular care and mental health services in England: a cohort-based cross-sectional study using small-area estimation

Background: A strong policy emphasis on the need to reduce both health inequalities and unmet need in deprived areas has resulted in the substantial redistribution of English NHS funding towards deprived areas. This raises the question of whether or not socioeconomically disadvantaged people continue to be disadvantaged in their access to and utilisation of health care.Objectives: To generate estimates of the prevalence of cardiovascular disease (CVD) and common mental health disorders (CMHDs) at a variety of scales, and to make these available for public use via Public Health England (PHE). To compare these estimates with utilisation of NHS services in England to establish whether inequalities of use relative to need at various stages on the health-care pathway are associated with particular sociodemographic or other factors.Design: Cross-sectional analysis of practice-, primary care trust- and Clinical Commissioning Group-level variations in diagnosis, prescribing and specialist management of CVD and CMHDs relative to the estimated prevalence of those conditions (calculated using small-area estimation).Results: The utilisation of CVD care appears more equitable than the utilisation of care for CMHDs. In contrast to the reviewed literature, we found little evidence of underutilisation of services by older populations. Indeed, younger populations appear to be less likely to access care for some CVD conditions. Nor did deprivation emerge as a consistent predictor of lower use relative to need for either CVD or CMHDs. Ethnicity is a consistent predictor of variations in use relative to need. Rates of primarymanagement are lower than expected in areas with higher percentages of black populations for diabetes, stroke and CMHDs. Areas with higher Asian populations have higher-than-expected rates of diabetes presentation and prescribing and lower-than-expected rates of secondary care for diabetes. For both sets of conditions, there are pronounced geographical variations in use relative to need. For instance, the North East has relatively high levels of use of cardiac care services and rural (shire) areas have low levels of use relative to need. For CMHDs, there appears to be a pronounced ‘London effect’, with the number of people registered by general practitioners as having depression, or being prescribed antidepressants, being much lower in London than expected. A total of 24 CVD and 41 CMHD prevalence estimates have been provided to PHE and will be publicly available at a range of scales, from lower- and middle-layer super output areas through to Clinical Commissioning Groups and local authorities.Conclusions: We found little evidence of socioeconomic inequality in use for CVD and CMHDs relative to underlying need, which suggests that the strong targeting of NHS resources to deprived areas may well have addressed longstanding concerns about unmet need. However, ethnicity has emerged as a significant predictor of inequality, and there are large and unexplained geographical variations in use relative to need for both conditions which undermine the principle of equal access to health care for equal needs. The persistence of ethnic variations and the role of systematic factors (such as rurality) in shaping patterns ofutilisation deserve further investigation, as does the fact that the models were far better at explaining variation in use of CVD than mental health services.Funding: The National Institute for Health Research Health Services and Delivery Research programme

Detecting referral and selection bias by the anonymous linkage of practice, hospital and clinic data using Secure and Private Record Linkage (SAPREL): Case study from the evaluation of the Improved Access to Psychological Therapy (IAPT) service

Background: The evaluation of demonstration sites set up to provide improved access to psychological therapies (IAPT) comprised the study of all people identified as having common mental health problems (CMHP), those referred to the IAPT service, and a sample of attenders studied in-depth. Information technology makes it feasible to link practice, hospital and IAPT clinic data to evaluate the representativeness of these samples. However, researchers do not have permission to browse and link these data without the patients’ consent. Objective: To demonstrate the use of a mixed deterministic-probabilistic method of secure and private record linkage (SAPREL) - to describe selection bias in subjects chosen for in-depth evaluation. Method: We extracted, pseudonymised and used fuzzy logic to link multiple health records without the researcher knowing the patient’s identity. The method can be characterised as a three party protocol mainly using deterministic algorithms with dynamic linking strategies; though incorporating some elements of probabilistic linkage. Within the data providers’ safe haven we extracted: Demographic data, hospital utilisation and IAPT clinic data; converted post code to index of multiple deprivation (IMD); and identified people with CMHP. We contrasted the age, gender, ethnicity and IMD for the in-depth evaluation sample with people referred to IAPT, use hospital services, and the population as a whole. Results: The in IAPT-in-depth group had a mean age of 43.1 years; CI: 41.0 - 45.2 (n = 166); the IAPT-referred 40.2 years; CI: 39.4 - 40.9 (n = 1118); and those with CMHP 43.6 years SEM 0.15. (n = 12210). Whilst around 67% of those with a CMHP were women, compared to 70% of those referred to IAPT, and 75% of those subject to indepth evaluation (Chi square p< 0.001). The mean IMD score for the in-depth evaluation group was 36.6; CI: 34.2 - 38.9; (n = 166); of those referred to IAPT 38.7; CI: 37.9 - 39.6; (n = 1117); and of people with CMHP 37.6; CI 37.3- 37.9; (n = 12143). Conclusions: The sample studied in-depth were older, more likely female, and less deprived than people with CMHP, and fewer had recorded ethnic minority status. Anonymous linkage using SAPREL provides insight into the representativeness of a study population and possible adjustment for selection bias