1. How to use HES database as a public health tool Dr Richard Wilson Senior Public Health Information Specialist South Birmingham PCT

2. “Statistics are like a lamp post to a drunk man, more for support than illumination” David Brent

3. HES as a public health tool HES and public health analysis – a different way of thinking Examples –Incidence model –Population study –Equity –Geography analysis

4. HES and Public Health: A different way of thinking Consider the database as a record of acute morbidity in our population rather than a record of commissioning decisions –First episodes become incidents –Unique NHSNo become patients –Length of stay and deaths become outcomes –Admissions over years become a longitudinal study Consider it as the largest survey of the health of the population –“Have you had a major accident in the last year?” Consider it as the largest health survey of your local population –Where were the highest accident rates in our PCT? –What is the variation in admission rates for CHD in our ethnic populations?

5. Deaths Teritary care Primary care, prescribing, NHS Direct, screening Acute secondary care A&E, Ambulance pick up, secondary care interface (waiting lists and outpatients HES HES and the health pyramid

6. HES - the data hub Cancer registrations HES Census Mortality Births PCT registered populations Hospital code Postcode or ward code Probabilistic and ecological linkage GP Code The Environment Postcode Adminstrative areas Prescribed codes Accounting data: HRGs Programme budgets Local Surveys Resident populations

7. How does this work? DsPH “I saw on the news that there are more people are becoming allergic to nuts, is this true and should I be worried about it?” –What is the incidence of anaphylaxia? –Has it changed over time? No national record of those suffering shock A widely held belief that allergies on the rise If the shock is severe enough it will result in admission to hospital or death

8. Constructing the investigation 1.Conditions and procedures must be described by: ICD, OPCS4, HRG –T78.0 - Anaphylactic shock due to adverse food reaction (not specifically Nuts!) –T78.2 - Anaphylactic shock, unspecified –T80.5 - Anaphylactic shock due to serum –T88.6 – Anaph’c shock due adv effect correct drug or med prop admin 2.How would people be admitted? Admission method – all/elective/emergency transfers? 3.Time period – Introduction of ICD10 in 1995/6 4.Geography – PCT/Region/England?

9. Considerations Appropriateness – is HES the right tool? –Is the event likely to turn up in HES ? Looking at emergency events requiring hospital stay is the condition clearly recorded? –Are all hospitals likely to have similar treatment regimes? Medical Assessment Units? Consultants with an interest? –Will there be sufficient events to be meaningful ? –Missing events - will all those who die be included ? Could always check versus public health mortality files –Primary care/alternative provision? Would an acute shock be treated in a primary care setting? –Private provision ? Emergencies rather than elective care so should not impact on this study

10. Impact of ICD10 Introduction of ICD10

11. Anaphylactic shock 1995/6 to 2000/1 England

12. Retrospective population studies HES provides over 13 years of continuous data collection This allows for the development of very detailed investigations of specific patient groups. Example: Femural fracture in children 1991/2 to 2001/2 across West Midlands –Constructing the investigation Codes ICD9 and ICD10

13. Creating the population For each year extract all FCEs where diagnosis in list Sort FCEs by NHSNo, Date of Birth, sex, postcode Visually compare adjacent records for FCEs from same spell and for same patient Select the fracture admission and update treatment and outcome from subsequent FCEs Include secondary fractures if they occur over 12months later Population of 3,288 fractures in 3,203 children

14. Temporal trend

15. Seasonal variation

16. Demography

17. External cause

18. Cause by age

19. Equity Is the provision of CHD operations equitable? Method 1.Linkage between patient and deprivation based on postcode of residence 2.Using NHS postcode lookup to link patient postcode to ward 3.Link ward to deprivation score 4.Allocate deprivation score to patient

20. Equity  Deaths  Admissions

21. Equity  Deaths  Admissions

22. Geographical studies Increasing interest to spatially relate data –Be it for presentational purposes to highlight geographical variation –To investigate access issues –To investigate environmental exposure HES is well suited to these types of analyses as it is specified both temporally and geographically

23. Geography - presentational Variations across health area

24. Geography - equity

25. Challenge to investigate whether there is evidence of a relationship between an environmental exposure (foundry chimney) and health Question raised by local community Can we use HES? –What health outcomes and would be the casual pathways? Respiration and contact through deposits on skin –Respiratory disease –Lung Cancer –Skin conditions… Exposure –Long term –Acute events –Aim therefore to examine asthma admissions across time, by age for case and control areas. Limitations –Primary care/alternative provision? Study assumes same level of asthma management in the population Would an acute asthma attack be treated in a primary care setting? Geography – environmental exposure

26. Size of dot relates to number of admissions Circles of increasing radii Red area plume dispersion model Analyses –compared quadrants for increased incidence –plume area (cases) vs non- plume area (controls) Results demonstrated no association between exposure and asthma incidence

27. Other examples of similar questions This type of analysis can be applied to many conditions and events. –Medical: Encephalitis –Surgical: Appendicitis, Pneumothorax –Poisonings: Carbon monoxide –Injuries: Falls, Burns, Assaults –Nutritional conditions: Vitamin D deficiency –Rare conditions: Lupus, Congenital heart conditions –Temporal: Myocardial infarction and football, air pollution episodes Form part of a multiple index methodology for describing hard to reach populations –For example Drug misuse –HES reporting on those admitted for intentional or non intentional poisoning alongside data on deaths, treatment, and arrests

28. Limitations No patient names - NHSno Only postcodes of residence not occurence Restricted access to certain sensitive fields –GP code (only available for local region) Data Quality –What you see is what you get –No opportunity to correct errors Annual updates rather than monthly –Historical not contemporary –Always 8-12 months behind –2002/3 most recent cleaned data

29. Strengths Probably the second largest 'medical' database in the world after medicare/mediaid (USA) Uninterrupted period covering 13 years from 1990/1 to 2002/3 and still being collected for the foreseeable future Resident and registered populations A standardised measure of –Events: the episode –Diagnosis and external cause – ICD –Operations and procedures – OPCS4 Geographically and temporally referenced Over 120,000,000 episodes Over 10,000 conditions Covering a population of 48,000,000 Covers all NHS hospitals ~ 90-95% of all inpatient care

30. A different way of thinking A health survey that is updated annually A health survey with 90% coverage of all elective procedures A health survey with 98% coverage of all severe injuries A health survey that covers a population of 48,000,000 that can be broken down by postcode and re-aggregated into alternative boundaries A health survey that can be linked to other sources of population data A health survey that can be used both cross- sectionally and longitudinally