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Using MIQUEST Rebecca Wilkinson, NHS Southampton Jenny Bowers, NHS Hampshire.

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Presentation on theme: "Using MIQUEST Rebecca Wilkinson, NHS Southampton Jenny Bowers, NHS Hampshire."— Presentation transcript:

1 Using MIQUEST Rebecca Wilkinson, NHS Southampton Jenny Bowers, NHS Hampshire

2 "The most valuable repository about the current health of the population may well be GP records and it is ironic that these are virtually unused for local health surveillance and service audit." ( Information for Health, NHS Executive, 1998)

3 MIQUEST is … A method of extracting data from GP clinical systems Available on all GP systems - same data searches used by all practices In case you’ve been wondering … MorbIdity QUery information Export SynTax

4 MIQUEST used for (some examples)… National data collection - Seasonal influenza vaccination uptake - National Diabetes Audit - Pneumococcal (PPV) vaccine uptake National toolkits -GRASP-AF : Guidance on Risk Assessment and Stroke Prevention for Atrial Fibrillation Local enhanced services (SHIP) - NHS Health Checks / Phlebotomy / Minor Surgery / HPV / Learning disabilities / Disease Modifying Anti-rheumatic Drugs (MARDS)

5 MIQUEST searches typically look for … Patient demographics Name / date of birth / age, address / ethnicity / Patient identifiable / pseudonymised / anonymous Clinical codes (Read / CTV-3) Diagnoses / Drugs / Immunisations / Referrals / Advice Date

6 3 types of MIQUEST query: 1.Subset – patients who meet a certain criteria 2.Analyse – counts patients that meet the criteria of specified group 3.Report – several pieces of info from selected patient records

7 MIQUEST combined with Excel workbooks … -MIQUEST extracts the data -EXCEL workbook processes it Example toolkits: -Diabetic retinopathy : compare GP and screening service data sets -Minor surgery LES : payment rules (codes and counts) -Child Immunisations : HPA cover and LC50 reports / compare datasets -Health check LES : invitation/exclusion list

8 Example MIQUEST Query *QRY_WDATE, ,13/01/2012 *QRY_SDATE, ,13/01/2012 *QRY_TITLE,SHPHPV3,Report of 1st HPV vaccinations *QRY_ORDER,003 *QRY_AGREE,LOCAL, *QRY_SETID,SHPHPV,HPV VACCINATIONS *ENQ_IDENT,LOCAL,Local enquirer *QRY_MEDIA,D,DISK *ENQ_RSPID,M12345, *QRY_CODES,0,9999R2,Read version 2 # # 65FS First human papillomavirus vaccination # FOR SHPHPV2 REPORT FIXED PRINT NHS_NUMBER,DATE,CODE FROM JOURNALS (LATEST FOR PATIENT) WHERE CODE IN ("65FS%") TRUD for Read codes https://www.uktcregistration.nss.cfh.nhs.uk/trud3/user/guest/group/0/home

9 Example of using MIQUEST NHS Hampshire Health Checks

10 Risk assessment and management Local additions: alcohol screen and pulse check

11 Approval Process Necessary to obtain IG clearance -Operational agreement for data sharing between agencies Local Medical Committee (LMC) Approval

12 Agree MIQUEST specification – Query name – Data – Clinical Codes - different queries for clinical systems using 5-byte version 2 Read codes (including variants for BNF) and those using CTV- 3. – Data selection criteria – e.g. within the last 60 days Data outputs – Multiple.csv files – one for each practice – Header rows missing – Unique reference – starts with 1 for each.csv file – Dates not formatted Smoking status CVD risk score 137S Ex smokerEx Smoker38DF QRisk cardiovascular disease score 23 % Light smoker cigs/day Current smoker38DF QRisk cardiovascular disease score 11 % Moderate smoker cigs/d Current smoker38DF QRisk cardiovascular disease score 11 %11 137S Used to smoke 20 /dayEx Smoker38DP Qrisk 2 10yr 20.1 % Never smoked tobaccoNever smoked38DP Qrisk 2 10yr 3.9 % P Cigarette smoker Current smoker38DR Framingham 1991 cardiovascular disease 10 year risk score Never smoked tobaccoNever smoked38DR Framingham 1991 cardiovascular disease 10 year risk score CVD Risk Score Rubric CVD Risk Score

13 Hampshire NHS Health Checks Performance summary Between 01/04/2012 and 30/09/2012 a total of 14,242 health checks were undertaken across 120 GP practices (84%) in Hampshire. 23 practices (16%) did not return data, PPSA data suggest that 5,793 invitations for a health check were sent out collectively for these practices. Uptake rate was 46.8% (Practice uptake rates ranged from 5.3% to 122.1%)

14 Health inequalities: Practice deprivation summary NumberPercentage IMD National Quintile Number of practices Number of invitations April to September 2012 Total Number of health checks UptakeFemaleMale FemaleMale Quintile % %41.70% Quintile % %29.30% Quintile 3112,7031, % %31.70% Quintile 4286,9462, %1,8091, %37.40% Quintile 57620,51110, %6,3223, %37.90% Hampshire11941,17114, %9,0455, %37.30%

15 Diagnosis Summary Treatment Summary 688 patients (from 107 practices) were newly prescribed lipid modification medication within 180 days of the health check. Overall Hampshire prescribing rate of 4.8%. Practice prescribing ranged from 0% to 21.5% Referral/Advice Summary Overall 16.7% of people across Hampshire were recorded as obese, compared to 23.7% adult smokers in Hampshire reported in the Health profiles. 18 patients (0.7%) with a BMI of 30 or more were referred to weight management services within 60 days of the health check Overall 8.1% of people across Hampshire were current smokers, compared to 17.2% adult smokers in Hampshire reported in the Health profiles 892 patients (76.2%) who currently smoke were given smoking cessation advice during their health check. Condition Number of patients diagnosed (within 180 days of health check) Hampshire Diagnosis Rate Hypertension2731.9% Chronic Kidney Disorder (Stage 3, 4 or 5)110.1% Type II diabetes mellitus600.4% Non diabetic hyperglycaemia710.5% CHD230.2% Hypercholesterolemia1340.9% Atrial fibrillation140.1%

16 CVD Risk Score Summary – % risk of developing CVD in the next 10 years 52.5% were assessed as being low risk 36.1% as medium risk, 9.1% of patients as high 2.3% of patients as very high risk The data does not suggest that there is a positive correlation between the most deprived practices and CVD risk, with 5.5% of patients in quintile one and 11.4% of patients in quintile five assessed as high or very high risk.

17 Limitations Time intensive Need to develop Quality Assurance process Provides a snap shot of the peoples health not a complete picture – potential to develop MIQUEST query Data will only ever be as good as that recorded on the GP systems!

18 Other uses of MIQUEST Let’s Get Moving pilot Smoking Quitters Learning Disability Needs Assessment

19 Learning Disability MIQUEST query in Southampton ConditionCrude rate per 1000 population LD patientsAll patients CHD Epilepsy Obesity Severe mental illness Hypertension Asthma

20 Acknowledgements: Steve McGuire Primary Care Information Support and Training Commissioning Support South / Contacts: Rebecca Wilkinson Head of Public Health Intelligence NHS Southampton Jenny Bowers Senior Public Health Intelligence Analyst Hampshire Public Health Intelligence Team


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