Rod Jackson EPIQ group University of Auckland, NZ www.epiq.co.nz GATE: ‘EBP with pictures’ a Graphic Approach to Teaching EBP a Graphic Appraisal Tool for EBP Graphic Architectural Tool for Epidemiology Rod Jackson EPIQ group University of Auckland, NZ www.epiq.co.nz 5/9/05 Oxford ©

What is evidence-based practice (EBP)? Policy ‘ways of knowing” Evidence Ideally evidence based practice (EBP) involves the integration of evidence (and there are many evidence bases), patient preferences, clinical considerations (practitioner defined issues) and policy issues in making decisions about patients. Practitioner Patient

What is evidence-based practice? Policy ‘ways of knowing” Evidence However the term evidence based medicine (aka evidence based practice) was coined by a clinical epidemiologist (Gordon Guyatt from MacMaster University in Canada) who challenged clinicians to use more epidemiological evidence when making clinical decisions Practitioner Patient

What is evidence-based practice? ‘using more evidence from clinical epidemiology (on diagnosis, prognosis & interventions) to inform decisions’ more comprehensively (systematic reviews) more critically (evidence appraisals) more quantitatively (probabilities) Therefore, given its history, the term ebp is more accurately defined as follows.

What is the ‘evidence’ of EBP? ‘clinically relevant evidence, sometimes from basic science, but especially from patient-centred clinical research into the accuracy of diagnostic tests*, the power of prognostic markers*, and the efficacy & safety of interventions*’ Modified from Sackett et al. EBM 2nd Edition 2000 * from clinical epidemiological studies

Epidemiological evidence is the cornerstone of EBP ‘understanding epidemiological study design is the essential skill for teachers of EBP’

The 4 (5) steps of EBP Ask a focussed clinical question Search for appropriate epidemiological evidence to help answer question Appraise (critically) the evidence (validity, impact, precision) Synthesise the evidence with patient, clinical & policy issues; then apply (i.e. answer question) Assess/ evaluate practice (clinical audit). Modified from DS et al

‘a tool for modeling the steps of EBP’ CATs: Critically Appraised Topics: ‘a tool for modeling the steps of EBP’ www.epiq.co.nz

Prognosis/Risk (coming) Systematic Reviews (coming) CAT forms: (in Excel) Intervention Diagnosis Prognosis/Risk (coming) Systematic Reviews (coming) download from: www.epiq.co.nz

The GATE Approach: every epidemiological study hangs on the GATE frame there is only one study design: RCT - interventions Cohort studies - prognosis / interv./ aetiology Cross-sectional studies - diagnosis Case-control studies - interv./aetiol. GATE: Graphic Appraisal Tool for Epidemiology

GATE Frame: PECOT Population Exposure Comparison Outcome Time © GATE: Graphic Appraisal Tool for Epidemiology

GATE: epi study design (P) Population P ©

Source Population: 68,561 women screened from 20 outpatients/community screening centres Eligible Population: Post-menopausal, established CHD, < 80 yrs, no MI in last 6 mths, no HRT last 3 months P Participant Population: all eligibles invited (2763)

Comparison (C) [control] GATE: epi study design (E&C) Population P Exposure (E) [or intervention] Comparison (C) [control] E C ©

Comparison (C) [control] HRT Identical Placebo Exposure (E) [or intervention] Comparison (C) [control] E C

GATE: epi study design (O) Population P Exposure Comparison E C a b yes Outcomes (O) O no c d ©

1º CHD E C yes Outcomes (O) O no

mean HDL cholesterol (mmol/L) HRT Placebo Outcomes (O) 1.4 1.27

GATE: epi study design (T) Population P Comparison Exposure E C T Time (T) Outcomes O ©

E C T Time (T) O CHD measured over 4.1 years (longitudinal)

E C T Time (T) O HDL cholesterol measured at 1 year (cross-sectional)

Multiple Exposure categories Multiple Outcome categories GATE: epi study design Population P Comparison Multiple Exposure categories E1 E2 E3 C Multiple Outcome categories ©

GATE: epi study design Population P E Correlation coefficient O © Continuous measure of Exposure: e.g. body mass index high…med..low Correlation coefficient low Continuous measure of Outcomes e.g. lipids O medium high ©

non- randomised allocation Cohort (Follow-up) study: archetypal epidemiological study Population P cohort non- randomised allocation EG CG Exposure Group Comparison Group Real life time T Time Outcomes O ill-health © “Life” is a cohort study: a “natural experiment”

Cohort of women diagnosed with breast cancer Cohort study (prognosis): Danish Breast Cancer Cooperative Cohort of women diagnosed with breast cancer Population P Non-randomised allocation to prognostic groups No childbirth <2 yrs before diagnosis childbirth <2yrs before diagnosis EG CG T 10 years yes death . no O © Kroman et al. BMJ 1997;315:851-5

Cohort of British Doctors established in 1951 Cohort study (aetiology): British Doctors Study Cohort of British Doctors established in 1951 Population P Non-randomised allocation (self-reported smoking) EG CG Non-smokers Smokers T 50 years yes Lung Cancer . no O © Doll et al. BMJ 2004;328:1519

Non-randomised allocation (self-reported use) Cohort study (intervention): Nurses Health Study Cohort of US Nurses Population P Non-randomised allocation (self-reported use) EG CG No HRT HRT T 10 years yes CHD . no O © Stampfer et al. NEJM 1991;325:756-62

Randomised Controlled Trial (RCT): HERS Population P Randomised allocation Exposure (intervention): HRT Comparison (control): Placebo EG CG T Time Outcomes: CHD O © Hulley et al. JAMA1998;280:605-13

No one allocated to Comparison Group Case series Population P Exposure Grp EG C No one allocated to Comparison Group T Time Outcomes O ©

Allocation: randomised or non-randomised Before-After Study (& cross-over study) Population P CG Comparison Grp Allocation: randomised or non-randomised EG Exposure Grp T Time Outcomes O ©

Cross-sectional (prevalence) study/survey: PECO Population P Real life time O  LTPA  angina EG CG  angina  LTPA Time ? O EG CG © E/C assignment & Outcomes assessed in cohort at same Time

Allocation by measurement Diagnostic Test Accuracy Study (cross-sectional) Population P Allocation by measurement EG: Gold Standard +ve CG: Gold Standard -ve EG CG Time GS+ GS- + Test Outcomes . - a b O c d ©

Allocation by measurement Diagnostic Test Study Application (cross-sectional) Population P Allocation by measurement EG: Test +ve CG: Test -ve EG CG Time T+ T- +ve predictive value. a b O c d -ve predictive value. ©

GATE: the NUMBERS Population P= EG= CG= T= a= b= c= d= © Exposure Group EG= CG= Comparison Group Time T= a= b= Outcomes c= d= ©

GATE: the numbers = HERS P= 2763 Population EG= 1380 CG= 1383 Exposure Group Comparison Group Time a= 172 b= 176 T= 4.1 yrs Outcomes ©

Denominators = EG x T and CG x T Numerators = a or c and b or d Occurrence = outcome / population P= Population Denominators = EG x T and CG x T sub-populations EG= CG= T + a= b= Numerators = a or c and b or d outcomes - c= d= © Epidemiology = numerator / denominator (E=N/D)

GATE: occurrence = numerator / denominator P= EG= CG= T= Exp. Group Occurrence EGO = a / EG x T Comp. Group Occurrence CGO = b / CG x T a= b= c= d= EGO = c / EG x T EGO = d / EG x T ©

GATE: occurrence HERS P= 2763 T= 4.1 yrs EG= 1380 CG= 1383 Exp. Group Occurrence EGO = A / EGxT = 172/1380 x 4.1 = 30.40/1000/yr A= 172 B= 176 Comp. Group Occurrence CGO = B / CGxT = 176/1383 x 4.1 = 31.04/1000/yr

Occurrence = 30.40 / 1000 persons / year = 30.40 / 1000 persons / year EGO = Exposure Group Occurrence (A/[EGxT]) CGO = Comparison Group Occurrence (B/[CGxT] = 30.40 / 1000 persons / year = 30.40 / 1000 persons / year

Effects: comparing occurrences Relative Effect/Risk (RR) = EGO CGO e.g. relative risk, risk ratio, prevalence ratio, incidence ratio Absolute Effect/Risk Difference (RD) = EGO - CGO e.g. risk difference, absolute risk Number Needed to Treat (NNT) to prevent/cause 1 event = 1/RD

Using GATE to frame all the steps of EBP www.epiq.co.nz

STEP 1: Ask focussed 5-part questions: 1. Participants (patient/population group) 2. Exposure (intervention if about therapy) 3. Comparison (there is always an alternative!) 4. Outcome 5. Timeframe

STEP 2: Search for best evidence using 3/4-part search terms: 1. Participants (patient/population group) 2. Exposure (intervention if about therapy) 3. Comparison (e.g placebo) 4. Outcome

Step 3a: appraise the evidence - hang the study & numbers on the GATE frame: PECOT Population P Exposure Comparison E C T Outcome O Time ©

Step 3b:appraise the evidence: ‘did the right people get in the right places? RAMM Representative of who? P Allocated appropriately? Measured well? -blinded or objective -complete E C T Measured well? -blinded or objective -complete O ©

R A M M

EBCP Step 4: applying the evidence - the X-factor ©

X-factor: making evidence-based decisions Epidemiologic evidence Patient preferences Policy issues clinical considerations ‘clinical expertise: other ways of knowing’ X-factor: integrating everything

Step 4

the evidence based practitioner RAM

a tool for life long learning the CAT: a tool for life long learning