1. The Capture of Morbidity Information in General Practice Douglas Fleming Director, RCGP, Birmingham Research Unit Nottingham: July 20, 2005

2. Content of Presentation  History of morbidity surveys  Purpose of morbidity surveys  THE POTENTIAL OF ROUTINE ELECTRONIC MEDICAL RECORDS FOR EPIDEMIOLOGY IN PRIMARY CARE  The Weekly Returns Service  SELECTED RESULTS FROM MORBIDITY SURVEYS

3. History of morbidity surveys  Deaths by cause 1851 William Farr: the establishment of the ICD-now version 10  1946 the London Sickness Survey  1956 The first national practice based morbidity survey  1971/72 and on to 1976; 1981/82; 1991/92- the 2 nd 3 rd and 4 th surveys  Regular General Household surveys since 1972

4. Purpose of morbidity surveys  To describe disease prevalence  To examine social and regional inequalities  To monitor changes in prevalence and to seek for evidence of trend  To study co-morbidity  To examine GP workload  To provide information for health service planning

5. Electronic Medical Records  Have arrived  Let us ensure we use them to maximum advantage  Remember we will arrive at a time when the record is uniform across primary and secondary care.  Common classification systems and standardises recording protocols are needed

6. What is the practice EMR used for?  Patient Registration  Patient Consultation Record  Complete Prescribing Record  Limited Prescribing Record (e.g. repeat prescriptions)  Research Facilitator – completion of templates  Accessing System for patient lists  Quality Assurance  Epidemiology

7. EMR for epidemiology If you focus on EMR for epidemiology you can achieve all the other functions. Conversely if your primary focus is on any other purpose you may exclude the possibility of use for epidemiological research.

8. The EMR is a filing cabinet containing medical information  Everything put in it can be retrieved  But if we want to retrieve information readily we must put in in an orderly fashion.

9. Example patient record  Abdominal Pain for 3 days, radiation to RIF, Vomiting 24 hours, pain increasing. No diarrhoea and no urinary symptoms.  O/E tender RIF, no guarding, t.38.0 o C  Urine no protein, no sugar, no blood.  Rectal examination not done. Patient told he may have appendicitis and hospital admission (QE) arranged.

10. Structure record for filing and decide what you wish to analyse  Subjective Abdo pain, vomiting  ObjectiveTender RIF t 38.0 o C  Assessment Appendicitis  Plan Admit hospital

11. egative information and qualifying details In structuring for filing, for analytical purposes, you will l lose the free text describing the negative information and qualifying details  S No urinary symptoms, no diarrhoea.  O Rectal examination not done, Urine no sugar.  A May have appendicitis.  P QE hospital

12. All boxes need to be filled in a structured patient electronic record  Essential for an accurate patient record.  Free text is important. Negative and qualifying details need to be stored but not in a way that confuses analysis  Sometimes you can bring data together from different consultations in order to fill every box  Many episodes of illness involve only one consultation, therefore complete the assessment box at each consultation.

13. The meaning of Asthma: an orderly record: information in the right place  Recent hospital admission for asthma  Had asthma as a child.  Never had asthma.  Reversibility test for asthma  Worried about son with serious asthma.  Father died of asthma.  Occupational asthma.  Asthma attack.  Asthma review.

14. Who does the filing? The Classification System, but you must use it properly

15. The Read Thesaurus  Is a medical terminology containing many more codes than ICD.  By using Read codes, you can process the information and analyse by ICD (or ICPC) but you are able to retain a higher level of detail in your patient centred record.  There are separate codes for patient complaints (presenting symptoms) and symptom diagnoses.

16. Consultation/episode type  Used to distinguish incidence from ongoing illness, but not needed for prevalence. The fact of consultation for the specified condition determines prevalence.  A repeat prescription (without consultation) is sometimes an indicator of prevalence (eg. Hay fever, glaucoma)  Intelligent interrogation of database needed

17. Episode typing in use: the example of otitis media Episode typing in use: the example of otitis media  Feb 1 Record= Otitis Media F  Feb 4 Record= Otitis Media O  Oct 10 Record= Otitis Media N  Oct 12 Record= Otitis Media O  Oct19 Record= Otitis Media O 1 person = annual prevalence 2 episodes and when they occurred = incidence 5 consultations = workload

18. The importance of episode type Much epidemiological research is concerned with the timing of events. For this type of research it is important to identify when new episodes of illness occur. For example we may be interested in the factors which precipitate asthma attacks and we need to know when patients consult with new episodes as opposed to consulting simply to renew medication or as part of routine management. The simplest episode typing must distinguish new episodes from ongoing consultations.

19. RCGP Weekly Returns Service  Weekly Returns Service (WRS) established in 1964  Fully computerised data entry and automated data extraction since 1994  Record all new episodes (and consultations) of illness (per 100,000 population)  Report on a twice weekly basis (daily possible)  Monitor at national, regional and practice level  Age and gender specific data  Now also provide annual prevalence data

20. 0-4 years5-14 years WRS Admissions ASTHMA WRS and hospital admissions 1990-97 week

21. Acute Otitis Media & Common Cold (per 100,000 All Ages) 10yr av. incidence in yrs 1991-2000

22. Incidence of influenza-like illness: Virus isolations in sentinel networks 1996/97 England/WalesThe Netherlands 0 Incidence rate Virus isolates Week 37414549159131719 300 250 200 150 100 50 37414549159131719 0 30 25 20 15 10 5 FluA FluB Incidence Baseline Confidence interval From Fleming DM. Zambon M, Bartelds AIM, de Jong JC. The duration and magnitude of influenza epidemics: European Journal of Epidemiology 15: 467-473 1999

23. Episodes, Admissions and Deaths For Respiratory disease (Age 75+)

24. Figure 5: Average excess admissions and excess bed days by age group, 1989/90 to 2000/01

25. Acute bronchitis: weekly incidence in 0-4 and 65+ age groups by winter weeks in alternate years 1995-2002

26. Weekly incidence of acute bronchitis contrasted with RSV reports from the Health Protection Agency: winter weeks from selected years 1996/97 - 1999/00

27. Upper and lower respiratory tract infection (URTI and LRTI): weekly incidence by gender for each quarter over years 1994-2003

28. Mean weekly incidence of acute respiratory infections vs antibiotic prescriptions

29. Respiratory illness and antibiotic prescribing

30. INFECTIONS OF SKIN & SUBCUTANEOUS TISSUE Mean weekly incidence rate by Gender

31. Prostate and Breast Cancer Prevalence per 10,000 by age and gender

32. Benign Prostatic Hypertrophy Prevalence per 10,000 by age and gender

33. WRS; Influenza vaccination uptake 2003 compared with 2002

34. Summary  Computer storage of medical records is replacing paper records.  The computer is a filing cabinet, but you need a good filing system.  Disciplined data capture is at the heart of a good record whether for routine patient management of for epidemiological research.  The classification system does the filing. Select it carefully according to your purpose and collaborators. Be wary of mapping programmes across classifications.  SOAP is a good structure on which to base your recording but if you want to concentrate your analysis on one or two of these boxes you must make appropriate entries in every box at every consultation including home visits.  Episode typing is needed to study seasonality for contemporary surveillance.