Routinely-collected data from GPs’ EPR and GP active electronic questioning method:

a comparative studyACHIL research laboratory

Etienne De Clercq (UCL-IRSS), V. Van Casteren, S. Moreels, N. Bossuyt, Katrien Vanthomme (ISP), G. Goderis, (KUL)

(Etienne.DeClercq@UCLouvain.be)

MEDINFO 2013 CongressCopenhagen 20/08/13 – 23/08/13

Etienne De Clercq: Clos Chapelle aux Champs 30 Bte B1.30.13 | 1200 Brussels | Belgium | T +32 2 764.32.62 | email: etienne.declercq@UClouvain.be

UCLouvainKULeuven

Ambulatory Care Health Information Laboratory

ACHIL

ACHIL is funded by the National Institute for Health and Disability Insurance

2ACHIL, funded by the National Institute for Health and Disability Insurance

UCLouvainTheoretical framework

Patients healthcare

status (PHS)GP’s Thoughts EPR

Research DBQ

Questionnaire

Research DBAE

PHS as perceived by the GP

DocumentedPHS

Proxy

Proxy

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UCLouvainResearch questions

• Is there any agreement between both research DB?

• Could “PHS as perceived by the GPs” be deduced from the “documented PHS” (aggregated data)?

• Is it useful to perform both data collection methods at the same time?

4ACHIL, funded by the National Institute for Health and Disability Insurance

UCLouvainResoPrim data collection

GPs’ consultation

EPR

Research DB AE

Research DB Q

Que

stio

nnai

re

Source validation

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UCLouvainClinical automatic extracted data New coded and active diagnosis (ICPC2, ICD10, Belgian

Thesaurus)(hypertension, diabetes type 2, cardiovascular past event)

New coded and active drug prescription (ATC code)(anti-diabetic drugs, anti-hypertension drugs, aspirin, statin)

Clinical Parameters (2 most recent values extracted): height, weight, syst. & diast. Blood pressure

Biological Parameters (2 most recent values extracted): Total & LDL cholesterol

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UCLouvain

• Is the patient suffering from hypertension?

• Does the patient currently take any antihypertensive drugs?

• Is the patient suffering from type 2 diabetes?

• Does the patient currently take any antidiabetic drugs?

• Does the patient have a history of cardiovascular event(s)?

• Does the patient currently take low-dose aspirin?

• Is the patient’s blood pressure currently higher than 140/90?

• Does the patient currently take a statin?

• Is the patient overweight (BMI > 25)?

• Patient known to have a history of hypercholesterolemia? (total cholesterol > 190 mg/dl and/or LDL cholesterol > 115 mg/dl)

Electronic questionnaire

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UCLouvainAgreement between research DB (1)

Kappa(AE vs Questions)

Healthcare conditions

Extracted data Missing excluded Missing AE = “-”

Hypercholes-terolemia

Cholesterol -0,12 -0,06

Cholest. < 4 months

-0,06 0,05

Blood Pressure > 140/90

Blood Pressure 0,42 0,40

BP < 4 months 0,47 0,44

Overweight(BMI > 25)

BMI 0,44 0,33

BMI < 4 months 0,48 0,20

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UCLouvainAgreement between research DB (2)

Kappa(AE vs Questions)

Healthcare conditions

Extracted data Missing excluded Missing AE = “-”

Hypertension HT Diag. code N/A 0,47

Diabetes Diab. Diag. code N/A 0,55

PCVE PCVE Diag. code N/A 0,36

HT Drugs HT Drug code N/A 0,24

Diab. Drugs Diab. Drug code N/A 0,75

Aspirin Aspirin Drug code N/A 0,44

Statin Statin Drug code N/A 0,54

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UCLouvainAggregated Patient Healthcare Status proxies – Prevalences (1)

Observed AE Prevalence Q Prevalence

Healthcare conditions

Extracted data

Missing excluded

Missing AE = “-”

Hypercholes-terolemia

Cholesterol 65,17% 52,4%45,5%Cholest.

< 4 months60,91% 20,5%

Blood Pressure > 140/90

Blood Pressure

48,5% 45,6%28

BP < 4 months

49,2% 39,6%

Overweight(BMI > 25)

BMI 75,35% 47,5% 56,4%

BMI < 4 months

78,88% 22,1%

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UCLouvainAggregated Patient Healthcare Status proxies – Prevalences (2)

Observed AE Prevalence

Q Prevalence

Healthcare conditions

Extracted dataMissing

excludedMissing AE = “-”

Hypertension HT Diag. code N/A 17,4% 30,6%

Diabetes Diab. Diag. code N/A 5,3% 7,5%

PCVE PCVE Diag. code N/A 4,7% 8,6%

HT Drugs HT Drug code N/A 68,1% 91,9%

Diab. Drugs Diab. Drug code N/A 14,0% 26,7%

Aspirin Aspirin Drug code N/A 20,6% 42,8%

Statin Statin Drug code N/A 22,4% 38,3%

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From documented care to a better proxy

ySensitivitPPVevAEevQEstimated .Pr_.Pr__

e.g. PPV: proportion of drug codes (extracted from EPR) confirmed by the GPs’ answers to the questionnaire?

e.g. Sensitivity: Proportion of patients with drug prescription (according to the GPs’ answers to the questionnaire) identified by a drug code extracted from EPR?

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UCLouvainEstimated Q prevalence (1)

Healthcare conditions

Extracted data

Observed AE Prevalence

QPrevalence

Estimated Q Prevalence

Hypercholes-terolemia

Cholesterol 52,4% 45,5% 45,1%

Cholest. < 4 months

20,5% 45,5% 44,8%

Blood Pressure > 140/90

Blood Pressure

45,6% 28,0% 27,8%

BP < 4 months

39,6% 28,0% 27,7%

Overweight(BMI > 25)

BMI 47,5% 56,4% 56,1%

BMI < 4 months

22,1% 56,4% 56,2%

14ACHIL, funded by the National Institute for Health and Disability Insurance

UCLouvainEstimated Q prevalence (2)

Healthcare conditions

Extracted dataObserved

AE Prevalence

QPrevalence

Estimated Q

Prevalence

Hypertension HT Diag. code 17,4% 30,6% 31,5%

Diabetes Diab. Diag. code 5,3% 7,5% 8,0%

PCVE PCVE Diag. code 4,7% 8,6% 9,1%

HT Drugs HT Drug code 68,1% 91,9% 90,5%

Diab. Drugs Diab. Drug code 14,0% 26,7% 19,5%

Aspirin Aspirin Drug code 20,6% 42,8% 42,6%

Statin Statin Drug code 22,4% 38,3% 38,3%

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UCLouvainDocumentation impact

Prevalence Statin

PPV Sens. AE Q Estimated

Year 1 90.4% 52.9% 22.39% 37.84% 38.26%

PEst. = PAE * PPV / Sens.

Year 2 35.00% ???90.4% 84.3% 37.53%

Year 2bis 28.00% ???90.4% 52.9% 47.85%

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UCLouvainBenefits of the approach

• Documentation process impact

• “Triangulation” benefits

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UCLouvain“Triangulation” Benefits

3261 patients Relevant question

Extracted parameters + - missing

Cholesterol< 4 months

+ 316 303 51

- 218 165 47

missing 815 1148 198

Identifying potential tracks to improve the quality of care or the quality of the documentation of care

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UCLouvainOne message …

If we were to use routinely collected data from primary care EPR for secondary usage, such as assessment of quality of care, we strongly advise

• To try, as far as possible, to identify the impact of the documentation system,

• or at least to compare with one another data collection process to identify potential ways to improve both care quality and information system.

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UCLouvain