1 / 37

What’s new in Q new tools for commissioning & early diagnosis

What’s new in Q new tools for commissioning & early diagnosis. Professor Julia Hippisley-Cox EMIS NUG, Warwick 2011. Acknowledgements. Contributing practices EMIS NUG (Chris, Charlie + others) EMIS (Sean, David, Andy, Shaun+ others) University of Nottingham QResearch Advisory Board

Download Presentation

What’s new in Q new tools for commissioning & early diagnosis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. What’s new in Qnew tools for commissioning & early diagnosis Professor Julia Hippisley-Cox EMIS NUG, Warwick 2011

  2. Acknowledgements • Contributing practices • EMIS NUG (Chris, Charlie + others) • EMIS (Sean, David, Andy, Shaun+ others) • University of Nottingham • QResearch Advisory Board • ClinRisk (software) • Co-authors/researchers

  3. Overview • QFeedback • QData Linkage Project • Risk stratification tools for commissioning • QCancer – assess risk of existing cancer • Questions/Discussion/Suggestions

  4. See the invitation in your delegate bag ideally all practices to contribute to both QResearch & QSurveillance Email julia.hippisley-cox@nottingham.ac.uk Get switched on

  5. QFeedback

  6. QFeedback: update • Interactive tool based on QSurveillance • Allows practices to view own data compared • PCT, SHA, UK • Similar practices • Graphs, Maps, Export data to excel • Deployed to 3,400 EMIS LV in early 2011 • Uptake 2885 practices in 1st 6 months • Final of E Heath innovation awards

  7. QFeedback in LV

  8. QFeedback dashboard

  9. Example maps

  10. QResearch Data Linkage Project

  11. QResearch Data Linkage Project • QResearch database already linked to • deprivation data • cause of death data • Very useful for research • better definition & capture of outcomes • Health inequality analysis • Improved performance of QRISK and similar scores

  12. QResearch Linkage Project Data source Content Inpatient, outpatient, A&E, maternity Cancer type, grade stage Heart attack type and treatment • Hospital Episode Statistics • Cancer registry • MINAP ‘Myocardial Infarction National Audit Project’

  13. New approach pseudonymisation • Need approach which doesn’t extract identifiable data but still allows linkage • Legal, ethical and NIGB approvals • Secure, Scalable • Reliable, Affordable • Generates ID which are Unique to Project • Applied within the heart of the clinical system • Minimise disclosure

  14. Pseudonymisation: method • Scrambles NHS number BEFORE extraction from clinical system • Takes NHS number + project specific encrypted ‘salt code’ • One way hashing algorithm (SHA2-256) • Cant be reversed engineered • Applied twice in to separate locations before data leaves EMIS • Apply identical software to external dataset • Allows two pseudonymised datasets to be linked

  15. QScores – risk prediction tools

  16. QScores – family of Risk prediction tools • Population level • Risk stratification • Identification of rank ordered list of patients for recall or reassurance • Individual assessment • Who is most at risk of preventable disease? • Who is likely to benefit from interventions? • What is the balance of risks and benefits for my patient? • Enable informed consent and shared decisions

  17. Criteria for chosing clinical outcomes • Major cause morbidity & mortality • Represents real clinical need • Related intervention which can be targeted • Related to national priorities (ideally) • Necessary data in clinical record • All then available as Open Source software

  18. Population risk stratification for PCTs/CG • Possible to apply all algorithms at PCT level • view the risk profile of population, • estimate the likely burden of disease • model the costs and benefits of interventions at different thresholds of risk • set local targets • determine search strategies which the practice or community staff can use for call/recall • evaluate outcomes & reset priorities.

  19. Risk Stratification: questions • QRISK & QDScore now being used at PCT level for recall • How useful has QRISK been for PCTs/practices • Useful to do this for other existing QScores? • Suggestions for new outcomes which would be useful • at PCT level? • at patient level?

  20. Risk of Hospital Admission • Requests from PCTs/CG to develop new tool identify patients • At risk of hospital admission • At risk of re-admission • Problems with PARR ++ and the Combined Tool • Never properly validated • Difficult to implement • Not been updated

  21. QAdmission (QA) Scoreshall we do it? • Utility • To identify patients high risk (re) admission • Intervention • Virtual wards • Community matrons • Implementation • Needs to be simpler to implement • Integrated into any clinical system • Regularly updated coefficients

  22. QCancer Tools to help earlier diagnosis www.qcancer.org Username: nuguser Password: ATouchOfSpice

  23. Cancer: The problem of diagnosis • Some cancers diagnosed very late when curative Rx not possible • Symptoms very common in general practice • Single symptoms not very specific • Earlier diagnosis improves options & outcome • NICE guidelines • Complicated • Miss patients & false positive • No indication of risk of patient having cancer

  24. Key predictive symptoms & factors • Loss weight/appetite • Rectal bleeding • Haematemesis • Dysphagia • Haemoptysis • Haematuria • PMB • Abdominal pain • Constipation/diarrhoea • Cough • Age, sex, ethnicity • deprivation • Smoking • Alcohol • Family history • Chronic diseases • Prior cancers • Anaemia (Hb<11)

  25. Six common cancers so far • Lung cancer • Colorectal cancer • Gastro-oesophageal cancer • Pancreatic cancer • Ovarian cancer • Renal cancer

  26. New approach needed • Need information based on patients record • combines symptoms + patient characteristics (age, sex, deprivation, PMH, FH) • Absolute risk of different type of cancer • Needs to be available WITHIN the consultation to guide management • Also as batch processing to identify patients with alarm symptoms/high risk but no investigations or outcome BEFORE or AFTER consultation

  27. QCancer methods • Used 2/3 sample of QResearch database • Identified all patients with new onset alarm symptoms in last 10 years • Followed up over 2 yr for diagnoses of cancer • Developed set of models which incorporates symptoms and profile to give risk calculation • Tested performance of models on rest of QResearch database & THIN database (INPS) • External validation by Oxford academics • Publication due Winter 2011/12

  28. Using QCancer in practicesdemo • www.qcancer.org • Either use as standalone or integrated • Template to help better recording positive and negative symptoms triggered by code for alarm symptom? • system calculates background risk before consultation and alerts to high risk of undiagnosed alarm symptoms? • Run in batch mode to pick up those with high risk and/or undiagnosed alarm symptoms

  29. Discussion/questions • QFeedback • QLinkage project/pseudonymiation • Risk stratification tools • QAdmission Score – shall we do it • QCancer tools • Suggestions for future work.

  30. Questions on pseudonymisation • Pseudonymisation needed for QResearch • Do we need it for other purposes in clinical system? • Eg generating list of patients for recruitment to studies • Any more examples? • Any questions?

  31. See the invitation in your delegate bag Get switched on

  32. General application

More Related