‘The Quality Outcomes Framework (QOF): Can it be used for more than just paying GPs?’ Ananda Allan Senior Health Intelligence Analyst NHS Dumfries & Galloway Ananda Allan Senior Health Intelligence Analyst Today’s talk will cover… • What is the QOF? • What else can QOF be used for? – Our understanding of patient populations – Comparing disease registers – Geographical distribution of disease – Referral and Admission patterns Ananda Allan Senior Health Intelligence Analyst About the QOF • Started 2004 as part of new GP contract • “A voluntary system of financial incentives… rewarding contractors (GPs) for good practice through participation in an annual quality improvement cycle” • Pays GPs for: – looking after patients with specific chronic illnesses – qualitative practice improvement measures • 134 indicators overall in 2010/11 • 20 conditions across 80+ clinical indicators Ananda Allan Senior Health Intelligence Analyst 1. Patient Populations: accurate count of the full practice lists… • There are different ways of counting D&G patients: – NRS (was GROS) estimate June 2010: 148,190 – CHI residents May 2010: 154,184 – CHP (QOF) headcount July 2010: 155,381 • There may not be much difference between CHI residents and CHP (1,200) but these patients belong to only 3 practices! Ananda Allan Senior Health Intelligence Analyst 700 150 470 N.B. For those of you who are wondering why this doesn’t add up to 1,200… Ananda Allan we have 200 patients living in D&G registered with an English GP in Senior Longtown! Health Intelligence Analyst This is important because: • We can now calculate accurate GP practice activity rates using the CHP headcounts, thanks to the QOF • Prior to the QOF, GP populations were not regularly published • Publishing these figures nationally has forced transparency Ananda Allan Senior Health Intelligence Analyst 2. Disease Registers • Prior to the release of the QOF we had two sources for disease prevalence: – Individual disease registers/audits • Limited number of diseases and focus on acute activity: diabetes, stroke, renal failure, cancer audits – Continuous Morbidity Recording (CMR) • 70 ‘spotter’ practices producing agespecific rates (evolved into PTI) – Or… write out to every practice and ask! Ananda Allan Senior Health Intelligence Analyst Comparing Local Diabetes Register with CMR Estimates… 7000 6141 6000 5834 5000 4000 3000 2788 2000 1000 0 CMR Age-Specific Rates 2002 applied to Board Population 2004 (All ages) Local Diabetic Register (includes under 18s) July 2004 QOF disease register for Diabetes (18+) March 2005 Now SCI-DC Diabetes Register Co-ordinates with EMIS nightly Ananda Allan Senior Health Intelligence Analyst QOF disease prevalence figures are not without problems… Condition Prevalence Condition Prevalence Stroke Palliative Care New Depression 18+ Mental Health Learning Disability 18+ Hypothyroidism High Blood Pressure Heart Failure Epilepsy 18+ Diabetes 17+ 2.3% 0.2% 8.7% 0.8% 0.4% 3.5% 14.8% 0.9% 0.7% 4.7% Dementia CVD Risk COPD Chr Kidney Dis 18+ CHD Cancer Atrial Fibrillation Asthma Obesity 16+ 0.9% 1.0% 2.3% 3.0% 5.1% 1.9% 1.7% 5.8% 7.6% The denominator is still ALL ages; overlap? Ananda Allan Senior Health Intelligence Analyst 3. Mapping the geographical burden of disease • Will QOF disease prevalence follow patterns of area deprivation? • Can we add value to existing GIS analysis? Ananda Allan Senior Health Intelligence Analyst Different in Urban areas? Ananda Allan Senior Health Intelligence Analyst 4. Correlating Disease Prevalence to Acute Activity • Some studies make an a priori assumption that disease prevalence correlates with emergency admissions • It has been shown that recorded prevalence of COPD accounts for 21.9% of admission variance (the APHO estimated prevalence was an even better predictor, accounting for 45.1%) (Calderón-Larrañaga et al, Thorax 2011) • However, local correlations have been disappointingly inconclusive Ananda Allan Senior Health Intelligence Analyst QOF Prevalence New Referral Rates to Cardiology and Diabetes & Endocrinology vs. QOF Prevalence 9% 8% 7% 6% 5% 4% 3% 2% 1% 0% New Referrals ≈ Incidence … ≠ Prevalence? 2 R = 0.0005 2 R = 0.0235 Coronary Heart Disease Diabetes 0 4 8 12 16 20 24 28 Indirectly Standardised Referral Rates per 1,000 Population (Age/Sex/SIMD09v2) Ananda Allan Senior Health Intelligence Analyst QOF Prevalence Emergency Admission Rates for All Heart Disease vs. QOF CHD Prevalence 9% 8% 7% 6% 5% 4% 3% 2% 1% 0% 2 R = 0.0729 Coronary Heart Disease 0 2 4 6 8 10 12 14 Indirectly Standardised Emergency Admission Rates per 1,000 Population (Age/Sex/SIMD09v2) Ananda Allan Senior Health Intelligence Analyst Conclusions from the published papers… 1. Bankart et al, High Emg Adm = closer to hospital, Emerg Med J (2011) small list size, older (removed CHD [2 PCT England] prevalence), white ethnicity, female, deprivation, not seeing own GP 2. Purdy et al, High Emg Adm = deprivation, CHD Public Health prevalence, smoking but not QOF (2011) [All England] quality of care factors for CHD 3. Purdy et al, J High Emg Adm = deprivation, Asthma Health Serv Res and COPD prevalence, smoking, urban, Policy (2011) [All closer to hospital, bed availability England] 4. CalderónLarrañaga et al, Thorax (2011) [All England] High Adm = deprivation, COPD QOF and undiagnosed prevalence, smoking, lower flu jabs, worse GP access/staffing Ananda Allan Senior Health Intelligence Analyst So… • Too many other factors to use prevalence in isolation? • Small rural board = insufficient sample? • Under-diagnosis skewing figures (e.g. COPD)? • Despite the results… Examining outliers has led to new case-finding Ananda Allan Senior Health Intelligence Analyst In conclusion… • QOF has given added value to other health information • What we really need is: – Age/Sex breakdown of QOF prevalence – Knowledge of co-morbidity (overlap) • QOF Calculator not designed to extract this (and does not hold this) • We will continue to explore… Ananda Allan Senior Health Intelligence Analyst Acknowledgments • Dr Andrew Carnon, Consultant in Public Health Medicine • Carolyn Hunter-Rowe, Senior Health Intelligence Analyst Ananda Allan Senior Health Intelligence Analyst