Why on earth would I want data: the use & misuse of health informatics

1. Why on earth would I want data: the use & misuse of health informatics Dr Fawzia Rahman First BACCH trainees’ day, RCPCH, 19th April 2013

2. Learning aims • Why you might want data • what sort of data • how to get it • how to make sense of it • how to use it.

3. Whyon earth do you want data? • For yourself? • For someone else? Who might that be?

4. Whyon earth do you want data? • To show what you have been doing ( quantity) • To show you have done it well ( quality) • To see if you can do it better ( quality improvement) ( you= person/ service/ manager)

5. So, Doctor, do tell me,what have you been doing? • If you were a trainee surgeon, what would you show? • You are a BACCH trainee: what can you show? • Can you keep a basic record of the cases you see? (hands up anyone who does!) • If yes, how? • If no, why not?

6. The top 30 diagnoses that cover 90% of cases seen • eating disorder • Conduct disorder • tic disorder • behavioural & emotional disorder unspecified • sleep disorder • self harm • Autistic spectrum disorder • Attention deficit hyperactivity disorder • behaviour problems related to learning disability • moderate mental retardation • severe mental retardation • Disorder of speech and language development • Specific developmental disorder of motor function • Constipation • Metabolic disorders • Congenital malformation • Chromosomal abnormality • Down syndrome • Epilepsy • primary disorders of muscle • Cerebral palsy • congenital malformation of brain • neurological problem NOS • Low vision, both eyes • Conductive hearing loss • Sensory neural hearing loss, bilateral • Neglect • Non accidental injury • Child sexual abuse • Emotional abuse • 1-8 mental health (behaviour) • 9-13 learning (development) • 14-26 physical • 27-30 child protection

7. So you have the data • It is now time for your next training assessment at the end of this posting • You have a graph from the list of main diagnoses of the cases you have seen over the last 6 months • Would you use it? • How?

8. Your activity data after 6 months any specific diagnoses codes also available

9. So far so good, but.. • So you know how many cases you have seen , with main diagnosis. • That is your case load ( numbers of children, and contacts) & case mix ( diagnoses) • Now tell me , Doctor, • How would you go about demonstrating the quality of your work?

10. Using data to demonstrate qualityFour domains of quality 2 matter to individuals 2 matter to populations Equity is care fairly distributed? Efficiency could the resource used be more productive? ( more bang for your bucks?) • Access can you get health care? • Effectiveness do you like it? (interpersonal) does it work? ( technical)

11. Quality domain 1: Access • In time: waiting times for contact & treatment i.e. was treatment initiated within 18 weeks of referral? • in space: what was your DNA rate for new and for follow ups? Hands up if Your service has this data Your service can get some of this data

12. Some suggestions to measure timely access( treatment within 18 weeks is a right under the NHS constitution) • Monitor RTT for 3 or 4 basic conditions e.g. • ADHD: treatment with medication/access to formal behavioural management • Constipation: treatment with laxatives • Epilepsy: time to treatment with drugs • Cerebral palsy: access to physiotherapy • ASD: time to diagnosis or formulation

13. Did Not Attend ( was not brought) • Is your personal rate better or worse than the service average? • Hands up if you know • If your follow up DNA rate is worse than your new DNA rate, what might it mean?

17. Quality domain 2 :Effectiveness • Interpersonal: did the patient like the care? • Hands up if you have examples in your service • Technical: did the care work i.e. make the patient better in some way? • Hands up if you have examples in your service

18. Interpersonal effectivenessthe human dimension of outcomes • Parent/ carer surveys • child satisfaction surveys • surveys of children ,carers ,& social workers after CSA & NAI examinations • surveys of CYPs after LAC assessments • SAIL audit of clinic letters by peers, GPS and CYP/ carers.

19. Examples with data • 90% of children aged 8 years and above felt the doctor had listened to them • 95% of social workers attending NAI examinations felt the doctors’ attitude was professional • 85% of of parents of CYP undergoing CSA examinations felt their child had been treated sensitively • Only 70% of clinic letters were felt by the GP auditor to be well structured

20. Technical effectiveness: the elusive Holy Grail of medicine • We must look & strive for it • Name one condition each • in which to expect an improvement • In which to expect stability • In which to expect worsening • Could the service record this?

22. Some suggestions for outcomes( measure only what you can influence) • Improved/ worse/ stable/ unchanged are very basic but valid patient/ clinician reported outcomes • For specific conditions purpose specific scales can and should be used • Conners/ SDQs/ Honoscas for mental health • Paediatric QL/ CPQL for physical/ complex cases • Family stress Questionnaires • Report % with improved scores • Work is underway to define better measures

23. Quality domain 3: EquityThe uniqueness of community based paediatrics( our unique selling point) • Reducing heath inequalities • More care for the less equal • Reversing the inverse care Law • Hands up if you think your service can show it does this

24. Suggestions to evidence a search for equity • Ethnicity monitoring (ask) • Deprivation quintile monitoring ( postcode) • Disability status monitoring ( record) • other vulnerability factors • For referrals, activity ( e.g. DNA rates) & all outcomes

25. Are all referrals treated equally regardless of source?( excluding section 47 , LAC & SEN)

26. Do you record vulnerability factors? SPECIAL CATEGORIESupto 4 entries SPECIAL CATEGORIES

27. 50% of the total caseload of about 4000 nhs numbers has at least ONE vulnerability factor/ special category ( 11/12 data)

28. Does your service record ethnicity? if yes,Does the case load reflects the ethnicity of the background population

29. Breakdown of black & ethnic minority groups

30. Vulnerability factors due to parental problems

31. Deprivation & caseload: Quintile breakdown of caseload by NHS numbers quintile 1 most deprived, IMD 20072012 caseload figures

32. Deprivation & diagnoses:Quintile spread of ADHD on medication & definite ASDvz Downs 2012caseload

35. Quality domain 4 Efficiency: getting there faster and probably cheaper • what % of referrals are accepted? • If less than 90% , do you know why? • Is information at the time of referral complete enough to accept? • If no, why not? • How much time before the information is obtained? • Did you really need to accept the referral?

40. Was this appointment needed? • Children seen once & discharged • exclude statutory work • exclude ASD tier 3 clinic • 20% of new cases • increasing waiting times • supposedly complex caseload • ? Deprivation profile?

41. Seen once & discharged • Analysed for referral source • Analysed for reason • analysed per doctor • analysed per quintile • ( 50%more disabled children in deprived quintiles) • More deprived children were discharged

42. Reducing seen once & discharged( why were we discharging twice as many deprived children as affluent ones?)

43. Efficiency: some suggestions in getting there faster and probably cheaper • Number of appointments to diagnosis of ASD • Rate limiting step? • Reducing the DNA rates while “minding the quintile gap” • Reducing inappropriate follow up e.g. ASD or LD with no medically treatable comorbidity • Reducing inappropriate seen once & discharged

44. Understanding numbers children vz contacts hands up if you can tell me • How many contacts did you have last year? • Split new: follow up? • How many individual children did you see? • split new: follow up?

45. New and follow up successful activityover the last 4 years

46. NEW children by main pathway

47. Follow up children ( not contacts) by main pathway

48. follow up Contacts for behaviour

49. Increase in adhd on medication from229 children in 08/09 to 502 in 11/12mostly in deprived quintiles

50. Increase in asd caseload from402 children in 08/09 to 742 children in 11/12. also skewed towards deprived quintiles