Chestpain in primary care: a systematic research programme to support guideline development

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1 allgemeinmedizin Chestpain in primary care: a systematic research programme to support guideline development Norbert Donner-Banzhoff Jörg Haasenritter Stefan Bösner Department of General Practice University of Marburg/Germany German Society of General Practice (DEGAM)

2 Just ask the patient, she will tell you the diagnosis.

3 The history: a neglected topic Researcher nothing new, negative results: disimplementation Manufacturer complete lack of interest Payer seemingly cheap, not contentious Clinician autopilot, but: uncertainty allgemeinmedizin

4 The hydraulic model of guideline development motivation technologies - cost Clinical application guideline clinicians needs Clinical application

5 What can be learnt? What kind of evidence is needed to inform recommendations regarding the clinical history? How should we disseminate the evidence? How can we measure the successful implementation of guideline recommendations? allgemeinmedizin

6 Chest Pain: Research Programme at Dept. of General Practice U of Marburg/Germany Exploratory Interviews Systematic Review Symptom&signs: validity MHS: Derivation CMAJ 2010;182:1295 Br J Gen Pract 2010;60:e246 Br J Gen Pract 2012;62:e415 INTERCHEST Indiv Px Data National Guideline (DEGAM) MHS: MHS: Validation - II (D) Validation - I (CH) Fam Pract 2007;24:622 Arch Intern Med 2010;170:251 Eur J Gen Pract 2009;15:141

7 Age Known vascular disease exertion Patient assumes cardiac cause Not reproducible by palpation 0-2: low risk The Marburg Heart-Score YES IHD (any) 5 4 NO 3 29 Se 86% Sp 75% +PV 35% -PV 97% OR 19.3 Prev 15% positive Test negative CMAJ 2010;182:

8 Chest Pain: Research Programme at Dept. of General Practice U of Marburg/Germany Exploratory Interviews Systematic Review Symptom&signs: validity MHS: Derivation CMAJ 2010;182:1295 Br J Gen Pract 2010;60:e246 Br J Gen Pract 2012;62:e415 INTERCHEST Indiv Px Data National Guideline (DEGAM) MHS: MHS: Validation - II (D) Validation - I (CH) Fam Pract 2007;24:622 Arch Intern Med 2010;170:251 Eur J Gen Pract 2009;15:141

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10 What can be learnt? What kind of evidence is needed to inform recommendations regarding the clinical history? How should we disseminate the evidence? Input from clinicians: intuition, rules of How can measure the implementation of guideline thumb recommendations? Comprehensive diagnostic studies Large samples, external validation (money & patience) Primary care researchers with special interest allgemeinmedizin

11 What can be learnt? What kind of evidence is needed to inform recommendations regarding the clinical history? How should we disseminate the evidence? How can measure the implementation of guideline recommendations? Simple clinical prediction rules Internet download Pocket version Teaching materials allgemeinmedizin

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14 What can be learnt? What kind of evidence is needed to inform recommendations regarding the clinical history? How should we disseminate the evidence? How can we measure the implementation of guideline recommendations???? allgemeinmedizin

15 What can be learnt? What kind of evidence is needed to inform recommendations regarding the clinical history? How should we disseminate the evidence? How can we measure the implementation of guideline recommendations? Danke - thank you allgemeinmedizin

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17 Results: The MHS in clinical decision making Negative predictive value Positive predictive value GPs judgment GPs + MHS MHS Triage I MHS Triage II %

18 Results: The MHS in clinical decision making Negative predictive value Positive predictive value GPs judgment MHS GPs + MHS MHS Triage I Se maximal + - History MHS Triage II % + -

19 Results: The MHS in clinical decision making Negative predictive value Positive predictive value GPs judgment MHS GPs + MHS MHS Triage I MHS Triage II 0 Sp maximal % + - History + -

20 Results: Diagnostic Efficacy Measures Sensitivity 89.1% (95% CI: %) Specifity 63.5% (95% CI: %) Positive likelihood ratio 2.44 (95% CI: ) Negative likelihood ratio 0.17 (95% CI: ) Positive predictive value 23.3% (95% CI: %) Negative predictive value 97.9% (95% CI: %) allgemeinmedizin

21 Results: Calibration Score Any CHD (%) ACS (%) n (0.6) 1 (0.6) (3) 3 (1) (12) 6 (3) (28) 3 (3) (52) 8 (14) 56 Σ allgemeinmedizin

22 Patienten Flow Einschluss Kriterien erfüllt (n=939) Marburger Herz-Score n=853 Ausgeschlossen: Verweigerer n=59 Trauma Fälle n=15 Loss to follow-up n=12 < 3 n=483 3 n=361 missing n=9 Beurteilung Expertenpanel Beurteilung Expertenpanel Beurteilung Expertenpanel Inkonkl. Diagnose n=3 Inkonklusive Diagnose n=9 Inkonklusive Diagnose n=0 KHK n=10 Keine KHK n=470 KHK n=82 Keine KHK n=270 KHK n=1 Keine KHK n=8 allgemeinmedizin

23 Ergebnisse der Sensitivitätsanalyse allgemeinmedizin

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25 Alternative Einsatzmöglichkeiten des MHS Existierender Test Replacement Spezifität Triage Sensitivität BS-Patient BS-Patient BS-Patient BS-Patient A & B A & B & MHS MHS MHS A & B A & B + - Referenzstrategie Vergleichs strategie I Vergleichs strategie II Vergleichs strategie III A & B: Anamnese und Befund MHS: Marburger Herz-Score allgemeinmedizin

26 Der bessere Test? Sensitivität und Spezifität als Auswahlkriterien Sensitivität: Wahrscheinlichkeit, dass der Test positiv ist, wenn der Patient krank ist. Spezifität: Wahrscheinlichkeit, dass der Test negativ ist, wenn der Patient gesund ist. Diagnostische Strategie Sensitivität (%) Spezifität (%) klinische Einschätzung A&B klinische Einschätzung A&B&MHS integriert klinische Einschätzung A&B + MHS-sequentiell hoch sensitiv klinische Einschätzung A&B + MHS-sequentiell hoch spezifisch 0% 50% 100% allgemeinmedizin

27 Der bessere Test? Sensitivität und Spezifität als Auswahlkriterien Sensitivität: Wahrscheinlichkeit, dass der Test positiv ist, wenn der Patient krank ist. Spezifität: Wahrscheinlichkeit, dass der Test negativ ist, wenn der Patient gesund ist. Referenz (klinische Einschätzung auf Grundlage von A&B) Sensitivität (%) Spezifität (%) Vergleichstrategie I (Integration von MHS in A&B) Vergleichstrategie II (Triage, Sensitivität hoch) Vergleichstrategie III (Triage, Spezifität hoch) 0 % 50 % 100 % allgemeinmedizin