Family Practice 2013; 30:613–614

doi:10.1093/fampra/cmt071

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Tackling health inequalities: socio-demographic data could play a bigger role Carolyn Tarrant*, Fatimah Wobi and Emma Angell SAPPHIRE, Department of Health Sciences, University of Leicester, Leicester LE1 6TP, UK. *Correspondence to Carolyn Tarrant; SAPPHIRE, Department of Health Sciences, University of Leicester, 22–28 Princess Road West, Leicester LE1 6TP, UK; E-mail: [email protected]

Despite long-standing arguments for the importance of systematic recording of socio-demographic data as part of a strategy for tackling inequalities,4 the reality is that few socio-demographic indicators are routinely and systematically collected in primary care. Gender and age are routinely recorded in patient records, but the recording of other information on ethnicity, language, disability and socio-economic status of individual patients is highly variable. In the UK, financial incentives provided via the Quality and Outcome Framework have been successful at promoting the recording of ethnicity for newly-registered patients, and more recently, carer status, but the collection of information on other socio-demographic indicators remains patchy. Primary care commissioners have expressed concerns about the lack of availability of goodquality data to underpin commissioning decisions related to reducing inequalities.5

Socio-demographic data and the fight to tackle health inequalities Health inequalities are a cause for significant concern across the globe; in the UK, the gap in disability-free life expectancy between the richest and poorest is around 17 years.1 General practitioners (GPs) have an important role to play in tackling inequalities, through delivering services that meet the needs of their local population, and engaging in preventative work, not just with patients who regularly consult but also with harder to reach groups. If GPs are to be able to play this role to the full, they need to understand the characteristics and needs of their local populations. The recent King’s Fund report on tackling inequalities in general practice argues that ‘Good clinical practice involves GPs being aware of key demographic data pertinent to health inequalities and actively seeking to address these when opportunities arise’.2 Electronic patient records held by practices are potentially a valuable source of socio-demographic data about patient populations. With a growing recognition of the importance of data to drive improvement, there have been a number of systems developed in the UK that collate and display these data alongside other indicators, such as patient experience and clinical outcomes, in ways that are easy to access and use. The National General Practice Profiles (NGPPs), compiled by the Public Health Observatories are a good example of this, enabling data to be viewed at individual practice or clinical commissioning group level.3

Challenges to recording socio-demographic data So why is the collection and recording of socio-demographic data in primary care problematic, and how might these problems be overcome? A recent review by the Race Equality Foundation identified some key challenges in routinely collecting ethnicity data. Alongside the challenge posed by the time and resources involved,6 additional barriers included: staff reluctance to request data for fear of giving offence, reluctance on the part of service users to supply data, inability of patients to supply data owing to language barriers, difficulties in obtaining an accurate classification of ethnic group, the lack of meaningful incentives to collect or provide data and a lack of understanding as to how data can or will be used.7 Although much of the research in this area is primarily concerned with ethnicity, it is likely that the collection of other data relevant to inequalities, particularly socio-economic status, disability, sexuality and religion, is subject to similar challenges.

Quality and comprehensiveness of socio-demographic data in primary care The value of routine primary care data for mapping diversity and informing efforts to reduce inequalities is limited, however, by the data’s lack of comprehensiveness and variable quality. Within the NGPP displays, for example, many practices do not have ethnicity profiles due to insufficient data. 613

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Improving data quality How can the comprehensiveness and quality of primary care data be improved, to maximize their value in informing and developing practice, and their utility for research? Technological developments mean that it is becoming easier to compile data from different sources. This provides a potentially valuable route for improving the completeness of data in primary care, for example, by linking with secondary care. The fact remains, however, that the data need to be collected and recorded in the first place. Most work to tackle the problem of data quality and comprehensiveness has tended to focus on providing guidance and standard questions that can be used routinely to elicit information from patients. This has the potential to help improve standardization and comparability across primary care providers, but other problems, including those of staff resistance to requesting information and patients’ reluctance to disclose, are more challenging to overcome. Recent work in Scotland has attempted to address these issues, with the production of an excellent suite of materials, entitled ‘Happy to ask, happy to tell’,8 which is aimed at engaging staff and helping them work with patients to facilitate the process of collecting personal information. Perhaps more important is a need to acknowledge that systematically collecting socio-demographic data within primary care organizations requires significant time and resources. Data collection, particularly when targeted at understanding and proactively addressing health inequalities, may not be seen as a priority in the context of a system that is increasingly pressed for resources and under high levels of demand. Improvements in recording will only happen if primary care providers and commissioners appreciate the value of such data, have a clear vision about how they can be used and have tools, skills and support to make optimum use of them. Innovative projects, such as the ‘GPs at the deep end’ work in Glasgow, provide good examples of how the existing data within primary care records systems, along with local knowledge, can be used to improve the efficiency of local services and to identify appropriate and feasible solutions to reducing health inequalities in local populations.9 A further challenge, yet to be addressed, is that of ensuring that the data are of high quality. Recent work to develop a concept map for the quality of GP registrations provides a starting point in thinking about methodologies for assessing quality.10

Conclusion In conclusion, interventions to reduce health inequalities are dependent on providers and commissioners understanding the demographic make-up of their local populations and identifying those who are

under-served or at risk. The collection of good-quality socio-demographic data in primary care will make this possible, but the potential of this resource will only be unlocked if staff in primary care understand why such data are valuable, have resources available to support data collection activities and have the tools and knowledge needed to use the data effectively.

Declaration Funding: University of Leicester intern scheme to F.W. This work was informed by research conducted as part of a study funded by the National Institute for Health Research Health Services and Delivery Research Programme (09/1801/1029). The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Health Services and Delivery Programme, National Institute for Health Research, National Health Service or the Department of Health. Ethical approval: none. Conflict of interest: none.

References 1 Marmot M, Atkinson T, Bell J et  al. Fair Society, Healthy Lives. The Marmot Review. Strategic Review of Health Inequalities in England post-2010. London, UK: University College London, 2010. http://www.instituteofhealthequity.org/projects/fair-society-healthy-lives-the-marmot-review (accessed on 1 November 2013). 2 Hutt P, Gilmour S. Tackling inequalities in general practice. Research Paper. London, UK: The Kings Fund, 2010. http:// www.kingsfund.org.uk/projects/gp-inquiry/health-inequalities (accessed on 1 November 2013). 3 Association of Public Health Observatories. User Guide for the National General Practice Profiles (version 7). http://www. apho.org.uk/resource/item.aspx?RID=96894 (accessed on 10 October 2013). 4 Smeeth L, Heath I. Tackling health inequalities in primary care. BMJ 1999; 318: 1020–1. 5 Turner D, Salway S, Mir G et al. Prospects for progress on health inequalities in England in the post-primary care trust era: professional views on challenges, risks and opportunities. BMC Public Health 2013; 13: 274. 6 Jones M, Kai J. Capturing ethnicity data in primary care: challenges and feasibility in a diverse metropolitan population. Diversity in Health and Social Care 2007; 4: 211–20. 7 Fulton R. Ethnic monitoring: is health equality possible without it? Briefing Paper. London, UK: Race Equality Foundation, 2010. http://www.raceequalityfoundation.org.uk/publications/ downloads/ethnic-monitoring-health-equality-possible-without-it (accessed on 1 November 2013). 8 NHS Health Scotland. Happy to Ask, Happy to Tell. Handbook for Trainees (Revised 2012). http://www.healthscotland.com/documents/3715.aspx (accessed 10 October 2013). 9 Watt G. GPs at the Deep End—Connecting with General Practice to Improve Public Health. http://www.gcph.co.uk/publi cations/277_gps_at_the_deep_end (accessed 10 October 2013). 10 van den Dungen C, Hoeymans N, Schellevis FG, van Oers HJ. Quality aspects of Dutch general practice-based data: a conceptual approach. Fam Pract 2013; 30: 355–61.

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