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National Register for Quality Improvement in Primary Care

National Register for Quality Improvement in Primary Care. Andy Maun University of Gothenburg, Sweden. Declaration of conflicts of interest or relationship. Speaker Name: Andy Maun GP Trainee, PhD student Member of the Swedish Quality Council

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National Register for Quality Improvement in Primary Care

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  1. National Register for Quality Improvement in Primary Care Andy Maun University of Gothenburg, Sweden

  2. Declaration of conflicts of interest or relationship • Speaker Name: Andy Maun • GP Trainee, PhD student • Member of the Swedish Quality Council • Member of the Development Team of a National Register for Quality Improvement in Primary Care • I have no conflicts of interest to disclose with regard to the subject matter of this presentation

  3. Healthcare systems in Sweden In health care and certainly primary healthcare: 21 counties and regions differing in: payment systems IT – systems follow–up of quality

  4. Reform on Choice of Care 2008 Aim: Increase the number of healthcare centres • Patients can choose a centre but not personal GP - centres compete! • Resulted in a lot of new centres mostly run by great companies owned by risk capitalists.

  5. Trends in most Counties • Payment by individual capitation based on • age • socio-economy • morbidity burden (ACG - adjusted clinical groups) • The centre pays all costs for laboratory services, x-ray and drugs

  6. Quality surveillance Existing quality registers • mandatory to report to the National Diabetes Register • often also mandatory to report to other registers (heart failure, asthma, COPD, etc.) • Problem: most existing registers are constructed by and for hospital clinicians

  7. Public debate

  8. National Register for Quality Improvement in Primary Care? • The Swedish Association of Local Authorities and Regions (SALAR) stimulates the development of a national register (550.000 Euro 2012) • 3 initiativesmergedto 1 national group: • SFAM – Swedish Association of General Practice (Vision of a database for research) • QualityConsil / pvkvalitet.se feedback and benchmarking • Register for Quality Improvement of the Western Region VGR

  9. National development team for the register National database • MalinAndré (chairperson), GP, docent, chairperson SFAM research council • Jörgen Månsson, GP, docent, CMO Carema Register of the Western Region VGR • Claes Hegen GP, chairpersonof the VGR register • Fredrik Bååthe, senior projectleaderRC VGR pvkvalitet.se • Sven Engström, GP, PhD, chairperson SFAM quality council • Andy Maun, GP-Trainee, PhD student

  10. Assignment • Define relevant variables from daily practice that can be collected automated from regional databases • in a legally applicable system • Target groups: • Healthcare centres - internal improvements • Academy - scientific research • Other Registers - delivery and sharing of data • Political management - results, follow-up • Patient – empowerment

  11. National coordination!

  12. Relevant variables from daily practice? • Ryggvärk M54* • Myalgier M790, M791 M797 • Arthros M16, M17 • Ledvärk M254, M255, M256 M250 • Tendinit/bur. M70*, M75*, M766, M771 M770 • Osteoporos M80*-M828 • Diabetes E10* - E14* • AngP/Isch/AF I20*-I25* • Astma/KOL J45*, J44* J46* • Stroke I64*, I67P*. I69* I65-68* • Luftvägsinf. B27, B34*, J01*-J06*, J18*, J22, R05* J00*, J12*-18*, J20*-21* (finns gen. viros) • UVI N30* N39.0 • Hudinf. L01*, L02*, L03*, L08*, A46, A692 • Depression F32*, F33*, F39* F34*, F38* • Ångest F410, F41* • Sömnstörn. F51* • Demens G30*, F01*, F03 F00*, F02* • Stressreaktion F43* -F43.2 Experiences from earlier projects Experiences from other countries medical outcomes, structural / process measures? How to avoid silos?

  13. Feasibility? Legally applicable? IT?

  14. Pvkvalitet.se - Philosophy • Quality indicators developed by clinical active GPs • We GPs think that we follow guideline to much greater extent than we actually do! • We have to study how we do in practice to understand that we need to work differently!

  15. Asthma Registration form Health centre GP Period Emergency/unplanned visits last year Have inhaled cortico-steroids Spirometry last 2 years Smoking registred Notes Yes No Yes No Yes No Yes No • Note indicators in the form for each sample patient • Summarize the results Sum

  16. Proportion who had emergency/ unplannedvisitfor asthma last year Proportion who had a check up including spirometry last 2 years

  17. common conditions and chronicdiseases • Tonsillitis • Cystitis in women • Asthma • COPD • Heart failure • Leg ulcer • Pneumonia • Atrial fibrillation • Urinary incontinence • Otitis media

  18. Qualityimprovement • Review onesownwork, myown “exceptions” • Discusstogether: Whatcouldwe do better? • Read patientsrecords • Sample small but enoughtoseetrends • Possibleto find thingslikeunplanned/emergencyvisitsforasthma • qualityofpatientrecords, diagnosis

  19. Pvkvalitet.se • 261 Health Centres participating • 37 000 patients reviewed = 950 localimprovementprojectssupported!

  20. Results Areas with systematic use • Antibiotics • Quinolones for cystitis in women 6%  1% (2006 - 2007) • Asthma • Patients with spirometrylast 2 years 38%  62% (2006 - 09) • Heart failure • Proportion investigated with UCG 65%  81% (2006-2009)(p < 0.05) • Patients treated with ACE / AII 71%  83%(2006 - 2007) (p = 0.002)

  21. Development of a register for Quality Improvement of the Western Region • Aim: regional primary healthcare register with the potential for a national register • Target group: • Healthcare centres - internal improvements • Academy - scientific research • Political management - results, payment • Patient – choice of healthcare centre

  22. Get a new… …perspective

  23. Indicators • Five chronic diseases: (< age 75) • Diabetes (National Diabetes Register) • Ischemic heart disease • Hypertension • Asthma • COPD

  24. Medical variabels • Diagnosis • Smoking • Weight • Length • Waistlines • Age / Gender • Spirometry • HbA1c • Blood lipids • Blood pressure • Results can be linked to • other registers e.g. stroke register • prescription register • socioeconomic data

  25. Effects? Before/after ACG (Payment for morbidity burden) 70 000 60 000 50 000 40 000 Number of individuals Diabetes diagnosis Primary Healthcare, Western Region 30 000 20 000 10 000 0 2005 2006 2007 2008 2009 2010 Staffan Björck, Analysis Unit Western Region

  26. Co-morbidity

  27. Identifying high-risk groups Percentageofindividualswithhigh blod pressure, high LDL cholesteroland smoking.

  28. Effects? Difficulities for centres in poor districts? Relation between socioeconomic index and percentage of patients with HbA1c < 52 Preliminary data Staffan Björck, Analysis Unit Western Region

  29. Percentage of patients with atrial fibrillation that receive Warfarin in different healthcare centres Preliminary data StaffanBjörck, Analysis Unit Western Region

  30. Percentage of patients atrial fibrillation and Warfarin Different parts of the Western Region Preliminary data StaffanBjörck, Analysis Unit Western Region

  31. Percentage of patients atrial fibrillation and Warfarin by Sex Female Male Preliminary data StaffanBjörck, Analysis Unit Western Region

  32. Percentage of patients atrial fibrillation and Warfarin by Age Preliminary data StaffanBjörck, Analysis Unit Western Region

  33. Percentage of patients atrial fibrillation and Warfarin by Age and Sex Preliminary data StaffanBjörck, Analysis Unit Western Region

  34. Pilot study - continuity continuity® • Aim: to examine the feasibility of a larger study, where the correlation between provider continuity and health outcomes is to be explored • Method: • retrospective study (Oct 2009-Febr 2012) • four primary care centres (33485 individuals) • health outcomes (blood pressure, HbA1c) • usual provider continuity (UPC) and continuity of care index (COC) for physician/nurse

  35. Results – No distinct correlations • No distinct correlations could be found between interpersonal continuity with physician/nurse and blood pressure and HbA1c values • A timeline-study on the whole population of the region (1,5 million inhabitants) is feasible and necessary to gain more knowledge

  36. Benefit? • See the whole population / ”your own” population • new thoughts and discussions • Knowledge on effects of treatments in “real populations” vs study populations • Primary Care influence strengthened • on guidelines • on development of healthcare system

  37. The challenge remains • systems that measure quality and stimulate improvement • validity / complexity / interpretation of data • no evidence of benefit of P4P but some evidence of harm • the hard part is to ensure the change and stimulate improvement

  38. Thank you for your attention!

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