GPRD 2010

Using electronic patient level data in Primary CareResearch: stories from our General Practice

Research Database experience

Evangelos Kontopantelis1 Tim Doran1 Stephen Campbell1

Jose Valderas2 Martin Roland3 Mark Harrison1 David Reeves1

1National Primary Care Research and Development CentreUniversity of Manchester

2Department of Primary Health Care, University of Oxford

3General Practice and Primary Care Research Unit, University of Cambridge

NPCRDC, 15th June 2010

Kontopantelis (NPCRDC) GPRD & patient level data 15 June 2010 1 / 39

Outline

1 BackgroundElectronic patient records (EPR)Quality and Outcomes FrameworkPrimary Care databases

2 GPRDData detailsExtracting the information

3 Our researchSynopsisDisease prevalencesClinical quality indicator performanceException reportingCo-morbidity and workload

4 Summary


Background Electronic patient records (EPR)

Times are changing!

Tarzan no want computer



Advantages of using EPRs...and disadvantages

They have the potential to bring huge benefits to patients.can speed up clinical communication.reduce the number of errors.assist doctors in diagnosis and treatment

Quality of research can be augmented with the added level of detail.patient level factors can be taken into account.subgroup analyses are made easy.statistically, analyses can be more powerful.

But...(even more) confidentiality issues arise.the structure of the data might require much work and advanced computerskills.



What is happening in the UK...it may take a while though

Implementing EPR systems is one of the main aims of the 10-yearNational Programme for Information Technology (NPfIT), launched in2002.Connecting for Health, the organisation responsible for delivering NPfIT.The main idea is to create a shared patient record divided into two levels:

the Detailed Care Record (DCR) - held locally.the Summary Care Record (SCR) - held nationally. Initially, it will hold onlybasic info (allergies, adverse reactions & prescriptions).

Project core is the development of a national system which will involvereplacing obsolete local IT systems across the NHS and linkingup-to-date systems together.


Background Quality and Outcomes Framework

Computers and GPs DO mix!if lucky you can still get scribbled illegible notes on your prescription

A voluntary pay-for-performance program (QOF) kicked off in 2004 withthe introduction of a new GP contract, which required practices tobecome computerised.A high percentage of practices was already computerised by then(helped by PCTs, own initiative etc).Initial investment £1.8 bn for 3 years (increasing GP income by up to25%) motivated laggard practices.Now over 99.9% of English practices are computerised and participatingin QOF (but using various systems: Emis, Seetec, ViSion etc).READ codes - a coded thesaurus of clinical terms - enable GPs to makeeffective use of the systems and leave freetext behind.



QOF detailsaccording to the rumour mill the scheme that pays GPs to do their job...twice

General practices rewarded for achieving a set of quality targets forpatients with several chronic conditions.Aim was to increase overall quality of care and to reduce variation inquality between practices.146 quality indicators.

Clinical care for 10 chronic diseases (76 indicators).Organisation of care (56 indicators).Additional services (10 indicators).Patient experience (4 indicators).

Into the 7th year now (01Mar10/31Apr11); cost for the first 6 years waswell above the estimate at £5.8 bn approx.QOF is reviewed at least every two years.



Some of the indicators for diabetic patients.Percentage of diabetics...

with a record of HbA1c in previous 15 months (3p).in whom last HbA1c is ≤7.4 in previous 15m (16p).who have a record of BP in the past 15m (3p).in whom the last BP is ≤145/85 (17p).with a rec of serum creatinine testing in previous 15m (3p).who have a record of total cholesterol in previous 15m (3p).whose last measured total cholesterol in previous 15m is ≤5mmol/l (6p).who have had influenza immunisation in the preceding 1Sep-31Mar (3p).


Background Primary Care databases

The General Practice Research DatabaseGPRD - not for profit

Established in 1987, with only a handful of practices.Since 1994 owned by the Secretary of State Health.In April 2010:

545 active practices (ViSion system only).11.20M patients.

Sample of 100k patients can be obtained for ’free’ (MRC funds up to 50approved academic proposals per year).Costs vary for larger samples; our 600k patients sample cost £32,000and is tied to a specific - albeit vague - research proposal (QOF related).Access to the whole database is offered (ability to extract data forapproved projects) and costs £127,000 per annum.


Background Primary Care databases

The Health Improvement Network databaseTHIN - commercial

A collaboration between In Practice Systems Ltd (INPS) and EPIC.In April 2010:

428 active practices (ViSion system only, 50-60% overlap with GPRD).8.70M patients.

Usually offered under a 4-year licence which costs £119,000.Similar to GPRD (judging by a very small sample) and they promise tooffer more patient characteristics (using the patient’s home postcode).


GPRD Data details

The single source of truth......not

Sorry, you are not in the database


GPRD Data details

Why we needed GPRD

Interested in longitudinal data from 1999 to 2007: 270 active practiceswith GPRD in the whole period.We set out to measure the effect of QOF on incentivised andnon-incentivised aspects of clinical quality of primary care.We needed GPRD since there are considerable advantages over theNHS published QOF data (QMAS):

data availability prior to the introduction of QOFability to construct non-incentivised indicators of qualityability to focus on a gender or specific age groups.

Sampled 1,000 patients from each of 100 ’representative’ UK practices.


GPRD Data details

The 100,000 patients ’free’ sample

Database broken down to numerous tables, because of the volume of thedata (4GB).Text files need to be imported into powerful analysis/databasemanagement software.Some of the information available:

Patient birthyear, sex, marital status, smoking/drinking status, height, weightand BMI.Clinical, referral, therapy, test, immunisation and consultation events.

All events are entered in codes (lookup tables available).Everything (likely to be recorded by a GP) can be identified; provided oneknows which codes to look for and in which tables!BUT a manual search on all the codes is not possible (the READ codesalone are 98,031) and automated processes are required.


GPRD Data details

The main GPRD tablesand relationships between them

Event files.Clinical: all medical history data (symptoms, signs and diagnoses).Referral: information on patient referrals to external care centres.Immunisation: data on immunisation records.Therapy: data relating to all prescriptions issued by a GP.Test: data on test records.

Lookup files.Medical codes: READ codes, 98,031 available.Product codes: 77,198 available.Test codes: 304 available.


GPRD Extracting the information

Our approach

Size of the tables prohibits looking at codes one by one.Instead we use search terms to identify potentially relevant codes in thelookup tables and create draft lists.

Example (Search terms for diabetes)

String search in Medical codes: ’diab’ ’mell’ ’iddm’ ’niddm’.READ code search in Medical codes file: ’C10’ ’XaFsp’.String search in Product codes file: ’insulin’ ’sulphonylurea’’chlorpropamide’ ’glibenclamide’.



Our approach...continued

Clinicians go through the draft lists and select the relevant codes.Three sets of codes are created, corresponding to:

QOF criteria.Conservative criteria.Speculative criteria.

Using the finalised code lists we search for events in the Clinical,Referral, Immunisation, Therapy and Test files.The whole process involves much work in code writing, therefore usageof an appropriate statistical package like STATA or SAS is essential.

Diabetes code example



Moving on to the bigger sample

Once all the processes were inplace and we were ’confident’about our estimates......code lists werecommunicated to GPRD andthey extracted a snapsot of thedatabase using the specificcodes.Final GPRD sample holds dataon 660,565 patients, from 150’representative’ UK practices.Power analyses on the originalsample informed our decisionon the numbers of practicesand patients required.


Our research Synopsis

It all starts with a grant...

They're harmless when they're alone but get a bunch of them together with a research grant and watch out


Our research Synopsis

What GPRD has done for usafter some convincing...

Estimated year on year prevalence scores for various conditions.Generated trends for practice performance on clinical quality indicators.Examined the effect of QOF on incentivised and non-incentivised aspectsof quality of primary care.Investigated the reasons of exception reporting in QOF (and their timing).Created co-morbidity mappings of the available patients.Measured the workload associated with each condition (includingco-morbidities).


Our research Disease prevalences

PrevalenceBased on conservative criteria

0.00%

2.00%

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18.00%

1999/00 2000/01 2001/02 2002/03 2003/04 2004/05 2005/06 2006/07

Percentage

Prevalence

Asthma

CHD

COPD

Depression

Diabetes

Hypertension

Hypothyroidism

Osteoarthritis

Osteoporosis

Stroke


Our research Clinical quality indicator performance

QOF measurement/recording indicator exampleDM11: % who have a record of BP in the previous 15 months (3p).



QOF treatment indicator exampleDM18: % who have had influenza immunisation in the preceding 1 Sep-31 Mar (3p).



QOF outcome indicator exampleDM6: % in whom last HbA1C is ≤7.4 in the previous 15 months (16p).



Inc vs non-inc clinical aspects of primary care

Two aspects to clinical indicators:a disease condition (e.g. diabetes, CHD).a care activity (e.g. influenza vaccination, BP control).

Three indicator classes, in terms of incentivisation:(A) Condition & process incentivised within QOF (28 ind)(B) Condition or process incentivised (13 ind)(C) Neither condition nor process incentivised (7 ind)

Three different types of activities:clinical processes related to measurement (PM/R).e.g. blood pressure measurementclinical processes related to treatment (PT).e.g. influenza immunisationintermediate outcome measures (I).e.g. control of HbA1c to 7.4 or below

We end up with 48 indicators in six indicator groups.




A-PM/R: fully inc recordingprocess.Hypertension & BPA-PT: fully inc treatment process.COPD & influenza immunisationA-I: fully incentivisedindermediate outcome.DM & BP of 145/85 or lessB-PM/R: partially inc recordingprocess.PAD & total cholesterolB-PT: partially inc treatmentprocess.CRD & influenza immunisationC-PT: non-inc treatment process.back pain & strong analgesics

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2000/01 2001/02 2002/03 2003/04 2004/05 2005/06 2006/07Year

A−PM/R (17) A−PT (6) A−I (5)

B−PM/R (9) B−PT (4) C−PT (7)

using group means of indicator means (by practice)in brackets, the number of indicators in each group

Percentage scores

Indicator group performance




Short term (2004/05):Overall, all three groups of fully incentivised indicators exhibitedperformance above the pre-QOF expectation.(from 1.1% to 38.2% with 4 smoking indicators having uplifts of over 30%).Partially incentivised Measurement/Recording indicators demonstratedsignificantly lower than expected gains, on average.

Long term (2006/07):Overall, the three fully incentivised groups continued to perform above theexpectation, although none exceeded 4%.The three partially incentivised and non-incentivised groups displayedsignificantly negative uplifts, on average.


Our research Exception reporting

Exceptionstiming

Exception reportingis considered asafeguard againstpatientdiscrimination.There is interest in...

the patients whoare excepted fromQOF.whether practicesuse ER as a’gaming’ tool(timing/reason).’met exceptions’.

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requ

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first record of exception reporting in year, for each patient

using GPRDExceptions over time, ages 60+



Exceptionstiming

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Date

Reported achievement, excluding all exceptions IQR

Total exception reporting rate IQR

% of unmet exceptions in exception total

Excluding all exceptions

RA & ER for STROKE8

STROKE8: % of stroke patients with last chol meas ≤5mmol/l



ExceptionsQOF conditions multimorbidity

Multimorbidity count No Yes Total % ER No Yes Total % ER No Yes Total % ER0 0 934 934 ‐ 0 624 624 ‐ 0 1,085 1,085 ‐1 70,177 1,843 72,020 2.6% 72,411 2,216 74,627 3.0% 71,278 2,889 74,167 3.9%2 22,910 1,330 24,240 5.5% 24,239 1,558 25,797 6.0% 25,896 1,815 27,711 6.5%3 10,003 765 10,768 7.1% 10,514 892 11,406 7.8% 11,987 1,049 13,036 8.0%4 4,084 448 4,532 9.9% 4,345 487 4,832 10.1% 5,491 627 6,118 10.2%5 1,421 232 1,653 14.0% 1,581 223 1,804 12.4% 2,204 296 2,500 11.8%6 450 82 532 15.4% 498 100 598 16.7% 845 144 989 14.6%7 103 27 130 20.8% 155 28 183 15.3% 298 69 367 18.8%8 28 6 34 17.6% 31 9 40 22.5% 75 13 88 14.8%9 3 1 4 25.0% 4 2 6 33.3% 20 5 25 20.0%

10 ‐ 2 0 2 0.0% 5 1 6 16.7%Total 109,179 5,668 114,847 4.9% 113,780 6,139 119,919 5.1% 118,099 7,993 126,092 6.3%

2006/072004/05 2005/06Exception reported



Exceptionsreasons and ’met exceptions’

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Percentages of 'met exceptions' in total / by reason of exception

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Percentages of 'met exceptions' in total / by reason of exception

no consent/refusal unsuitable/contraindicated


Our research Co-morbidity and workload

Co-morbidityco-morbidites Thursday October 1 12:14:12 2009 Page 1

___ ____ ____ ____ ____tm /__ / ____/ / ____/ ___/ / /___/ / /___/ Statistics/Data Analysis

User: Evan Project: GPRD conservative estimates (where applicable) and QOF year 2006/07 CHD DM Strk 45+ HRT Lith Dem Depr Asth COPD PADHT 17.6 17.2 8.4 94.2 3.1 0.2 1.2 22.8 9.0 4.4 2.4 56.2 56.4 59.0 29.3 19.9 20.6 40.0 19.8 17.7 40.1 58.2CHD 20.3 12.4 98.1 1.9 0.1 1.7 24.9 10.5 7.5 4.6 20.8 27.4 9.5 3.7 5.3 17.5 6.8 6.5 21.3 35.1DM 8.5 88.6 1.7 0.3 1.2 24.0 9.4 4.4 3.1 18.2 8.4 3.4 9.7 12.3 6.3 5.6 12.1 23.4Stroke 97.5 1.3 0.1 4.9 27.6 9.0 7.1 4.7 4.3 1.2 2.0 22.6 3.4 2.5 9.1 16.345orover 4.4 0.2 0.9 21.5 7.5 3.4 1.2 91.3 78.5 99.7 59.8 47.3 97.9 96.7HRT 0.3 0.1 38.7 11.2 2.0 0.5 4.9 0.5 5.2 3.4 2.8 1.8Lithium_therapy 2.4 76.9 9.7 2.2 0.8 0.6 0.5 0.2 0.2 0.2Dementia 32.0 5.2 4.7 2.9 0.8 0.3 1.3 2.2Depression 9.9 2.9 1.0 22.6 30.7 28.3Asthma 9.3 0.8 42.8 10.2COPD 4.4 12.0

first row for each condition/activity: denominator indicated by rowsecond row for each condition/activity: denominator indicated by columni.e. first observation indicates the % of patients with HyperTension, who also have CHD



Workload - consultation typenumber of appointments

Freq. Percent Freq. Percent Freq. PercentAcute visit 1,955 0.35 1,889 0.31 1,771 0.27Administration 88,119 15.97 102,014 16.69 119,900 18.24Casualty Attendance 1,021 0.19 985 0.16 897 0.14Clinic 22,694 4.11 23,901 3.91 24,506 3.73Discharge details 1,614 0.29 1,476 0.24 1,580 0.24Emergency Consultation 940 0.17 759 0.12 731 0.11Follow‐up/routine visit 1,226 0.22 864 0.14 746 0.11Letter from Outpatients 31,075 5.63 37,500 6.14 39,482 6.01Mail from patient 482 0.09 954 0.16 953 0.14Mail to patient 477 0.09 757 0.12 711 0.11Night visit, Deputising service 18 0 15 0 12 0Night visit, Local rota 17 0 4 0 2 0Other 89,128 16.15 103,406 16.92 112,331 17.09Out of hours, Non Practice 854 0.15 994 0.16 1,289 0.2Out of hours, Practice 58 0.01 58 0.01 115 0.02Repeat Issue 109,711 19.88 110,196 18.03 107,029 16.28Results recording 66,433 12.04 78,722 12.88 88,764 13.51Surgery consultation 122,964 22.29 131,625 21.54 136,425 20.76Telephone call from a patient 6,664 1.21 7,552 1.24 8,026 1.22Telephone call to a patient 3,443 0.62 3,977 0.65 4,130 0.63Third Party Consultation 2,841 0.51 3,456 0.57 7,861 1.2Total 551,734 100 611,104 100 657,261 100

Freq. Percent Freq. Percent Freq. PercentAcupuncturist 0 0 359 0.06 467 0.08Administrator 39,242 7.71 49,713 8.71 53,876 8.71Assistant 6,614 1.3 7,754 1.36 8,779 1.42Associate 4,026 0.79 5,127 0.9 3,652 0.59Business Manager 923 0.18 1,020 0.18 1,417 0.23Chiropodist 189 0.04 92 0.02 59 0.01Commercial Deputising service 22 0 18 0 35 0.01Community Nurse 1,651 0.32 1,930 0.34 2,569 0.42Community Psychiatric Nurse 209 0.04 133 0.02 133 0.02Computer Manager 3,125 0.61 3,964 0.69 4,933 0.8Consultant 414 0.08 342 0.06 444 0.07Counsellor 833 0.16 779 0.14 765 0.12Dietician 263 0.05 291 0.05 277 0.04Dispenser 12,444 2.45 15,482 2.71 15,779 2.55Fund Manager 695 0.14 189 0.03 58 0.01GP Registrar 8,116 1.6 10,374 1.82 12,385 2Health Education Officer 34 0.01 26 0 49 0.01Health Visitor 176 0.03 221 0.04 204 0.03Hospital Nurse 22 0 29 0.01 21 0Interpreter/Link Worker 7 0 7 0 20 0

2006/07

2006/07

2005/06

2005/06

2004/05

2004/05



Workload - health workernumber of appointments

Freq. Percent Freq. Percent Freq. Percent Freq. Percent Freq. Percent Freq. PercentAcupuncturist 0 0 359 0.06 467 0.08 Hospital Nurse 22 0 29 0.01 21 0Administrator 39,242 7.71 49,713 8.71 53,876 8.71 Interpreter/Link Worker 7 0 7 0 20 0Assistant 6,614 1.3 7,754 1.36 8,779 1.42 Locum 10,816 2.13 10,310 1.81 10,550 1.71Associate 4,026 0.79 5,127 0.9 3,652 0.59 Maintenance staff 55 0.01 8 0 15 0Business Manager 923 0.18 1,020 0.18 1,417 0.23 Midwife 167 0.03 282 0.05 349 0.06Chiropodist 189 0.04 92 0.02 59 0.01 Other Health Care Professional 24,900 4.9 31,283 5.48 36,573 5.91Commercial Deputising service 22 0 18 0 35 0.01 Partner 93,973 18.47 104,501 18.32 115,918 18.74Community Nurse 1,651 0.32 1,930 0.34 2,569 0.42 Pharmacist 2,157 0.42 2,195 0.38 2,040 0.33Community Psychiatric Nurse 209 0.04 133 0.02 133 0.02 Physiotherapist 299 0.06 349 0.06 240 0.04Computer Manager 3,125 0.61 3,964 0.69 4,933 0.8 Practice Manager 20,396 4.01 21,616 3.79 21,337 3.45Consultant 414 0.08 342 0.06 444 0.07 Practice Nurse 54,697 10.75 60,036 10.52 61,118 9.88Counsellor 833 0.16 779 0.14 765 0.12 Receptionist 150,926 29.67 165,525 29.02 187,014 30.23Dietician 263 0.05 291 0.05 277 0.04 School Nurse 166 0.03 136 0.02 150 0.02Dispenser 12,444 2.45 15,482 2.71 15,779 2.55 Secretary 31,762 6.24 31,376 5.5 30,654 4.96Fund Manager 695 0.14 189 0.03 58 0.01 Senior Partner 37,152 7.3 42,289 7.41 43,544 7.04GP Registrar 8,116 1.6 10,374 1.82 12,385 2 Social Worker 2 0 0 0 3 0Health Education Officer 34 0.01 26 0 49 0.01 Sole Practitioner 2,208 0.43 2,716 0.48 3,131 0.51Health Visitor 176 0.03 221 0.04 204 0.03 Total 508,681 100 570,472 100 618,558 100

2004/05 2005/06 2006/07 2004/05 2005/06 2006/07


Summary

OverviewSo, GPRD then?

Advantages...Patient level data; breakdown by age, sex, year of diagnosis etcData on many time points are available.We are able to extract/create data not available anywhere else.Available now (with trustworthy data for a few years back).

Disadvantages...Too much work!Not cheap.Only a sample of all English practices participates.Practices are anonymised and controlling analyses for practicecharacteristics can be a struggle.Absolute reliance on codes and GPs getting them right...Quality of data before the introduction of QOF is questionable.Too much work! (but you become everyone’s new best friend...)


Summary

Still a long way to go!

Something goes around something but that's as far as I've got...

Comments: [email protected]


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GPRD 2010

Health & Medicine