Re: Dismantling the signposts to public health? NHS data under the Health and Social Care Act 2012
Dismantling the signposts to public health? No, just updating them
Response to: Pollock A, Macfarlane A, Godden S. Dismantling the signposts to public health? NHS data under the Health and Social Care Act 2012. BMJ 2012; 344: e2364 doi: 10.1136/bmj.e2364 (Published 26 April 2012)
In their analysis article on the implications of the Health and Social Care Act 2012 for public health information Pollock et al raise some valid concerns, but also some which are spurious, and others which are inaccurate.1
They compare unfavourably population data derived from general practice registrations with annual population estimates derived from the decennial national Census, and state that practice registrations may be unreliable as denominators because list sizes are often inflated by inclusion of people who have deregistered, moved, or died. However list inflation is decreasing (the England average is 5%),2 and if general practice data is used for public health purposes, only that of active patients is useful anyway. Inter-Censal population estimates are highly dependent on the underlying methods used and are no gold standard. For example, the estimated 2010 resident populations of London Boroughs from two reputable sources, the Office for National Statistics and the Greater London Authority, vary by up to 18%.3
Pollock et al state that it will be more difficult to compile the data needed to monitor health impacts on NHS patients and local populations because denominators will be based on numbers of people registered with general practices rather than numbers of residents in geographical areas. However there is no requirement in the Health and Social Care Act 2012 that registered populations must be used for all epidemiologic analyses. The appropriate population denominator should be used for the type of intervention being studied. The effects of NHS-funded healthcare interventions should be looked for in registered populations, and the effects of resident-based interventions by local authorities or other Government Departments in resident populations. These analyses should include adjustment for population and healthcare confounders respectively.
Converting population data is very easily done using practice to residential area lookup tables. For example, we have converted registered population data on disease prevalence to resident-based populations to incorporate Census-based data,4 and vice versa to adjust for population factors in healthcare evaluations.5 6 As new healthcare and health determinant data sources become available, as is increasingly the case, such translation will be essential to use the data optimally. Estimates suggest that healthcare interventions have contributed around half of recent decreases in cardiovascular mortality.7 8 Ignoring the impact of healthcare on population health is a vestige of the McKeown era.
Pollock et al state that practices collect few socioeconomic data. Practices have never been expected to collect socioeconomic data such as National Statistics Socioeconomic Class, but they should be encouraged to do so to provide more up to date information than decennial Censuses. Ethnicity data is now widely collected by practices at registration and retrospectively (as well as on hospital admission), and is proving to be extremely useful in evaluating health inequalities.9 In some areas ethnicity is recorded in over 70% of the registered population, and ethnicity data collected from healthcare sources can now be used to supplement Census projections.10
Practices can also provide data on the prevalence of smoking, obesity and other risk factors in small populations.11 12 Some public health teams are already making extensive and innovative use of primary care data to shed new light on population health,13 and the new General Practice Extraction Service has the potential to make these data much more accessible.14
The authors’ statement that practice computer systems differ from each other and from hospital episode statistics (HES) in how they code clinical conditions is incorrect. Like HES, Read codes used in practice systems use the International Classification of Diseases version 10, and the transition to the “supercode” SNOMED-CT terminology, now a fundamental NHS Standard, will ensure that all coded primary and secondary healthcare data are fully compatible.
There is an information revolution in progress, but it appears that nostalgia or ignorance of new data sources will prevent Pollock et al from joining it.
1. Pollock AM, Macfarlane A, Godden S. Dismantling the signposts to public health? NHS data under the Health and Social Care Act 2012. BMJ 2012;344. Link: http://www.bmj.com/content/344/bmj.e2364 .
2. Primary Care Commissioning. Tackling list inflation, 2012. Link: www.pcc.nhs.uk/uploads/.../pcc_list_inflation_briefing_feb2012.pdf .
3. Greater London Authority. London Datastore. 2011. Link: http://data.london.gov.uk/datastore/package/office-national-statistics-o... .
4. Soljak M, Samarasundera E, Indulkar T, Walford H, Majeed A. Variations in cardiovascular disease under-diagnosis in England: national cross-sectional spatial analysis. BMC Cardiovasc Disorders 2011;11(1):12. Link: http://www.biomedcentral.com/1471-2261/11/12 .
5. Bang JY, Yadegarfar G, Soljak M, Majeed A. Primary care factors associated with cervical screening coverage in England. J Pub Health 2012. Link: http://jpubhealth.oxfordjournals.org/content/early/2012/03/16/pubmed.fds... .
6. Calderón-Larrañaga A, Carney L, Soljak M, Bottle A, Partridge M, Bell D, Abi-Aad G, Aylin P, Majeed A. Association of population and primary healthcare factors with hospital admission rates for chronic obstructive pulmonary disease in England: national cross-sectional study. Thorax 2011;66(3):191-96. Link: http://thorax.bmj.com/content/66/3/191.abstract .
7. Kottke TE, Faith DA, Jordan CO, Pronk NP, Thomas RJ, Capewell S. The Comparative Effectiveness of Heart Disease Prevention and Treatment Strategies. Am J Prev Med 2009;36(1):82-88.e5. Link: http://www.sciencedirect.com/science/article/pii/S0749379708007691 .
8. Ford ES, Ajani UA, Croft JB, Critchley JA, Labarthe DR, Kottke TE, Giles WH, Capewell S. Explaining the Decrease in U.S. Deaths from Coronary Disease, 1980-2000. N Engl J Med 2007;356(23):2388-98. Link: http://content.nejm.org/cgi/content/abstract/356/23/2388
9. Fischbacher CM, Bhopal R, Steiner M, Morris AD, Chalmers J. Is there equity of service delivery and intermediate outcomes in South Asians with type 2 diabetes? Analysis of DARTS database and summary of UK publications. J Publ Health 2009;31(2):239-49. Link: http://jpubhealth.oxfordjournals.org/content/31/2/239.abstract .
10. Hull SA, Rivas C, Bobby J, Boomla K, Robson J. Hospital data may be more accurate than census data in estimating the ethnic composition of general practice populations. Informatics Primary Care 2009;17:67-78. Link: http://www.ingentaconnect.com/content/rmp/ipc/2009/00000017/00000002/art... .
11. Szatkowski L, Lewis S, McNeill A, Huang Y, Coleman T. Can data from primary care medical records be used to monitor national smoking prevalence? J Epidemiol Comm Health 2011. Link: http://jech.bmj.com/content/early/2011/05/13/jech.2010.120154.abstract .
12. Szatkowski L, McNeill A, Lewis S, Coleman T. A comparison of patient recall of smoking cessation advice with advice recorded in electronic medical records. BMC Public Health 2011;11(1):291. Link: http://www.biomedcentral.com/1471-2458/11/291 .
13. Price S. Annual Public Health Report 2011: extending life in Islington. London: NHS North Central London, 2011. http://www.islington.nhs.uk/About-us/annual-public-health-report-2011.htm .
14. NHS Information Centre for Health & Social Care. General Practice Extraction Service (GPES). Leeds: NHS Information Centre for Health & Social Care, 2012. http://www.ic.nhs.uk/gpes .
Competing interests: No competing interests