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Randomised C ontrolled Trials: a workshop

Randomised C ontrolled Trials: a workshop. Ngaire Kerse Professor and General Practitioner and asker of questions. . Key issues - randomised trials. There must be uncertainty The question m ust be answerable and feasible Outcome reasonably common Examples of randomised trials in GP

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Randomised C ontrolled Trials: a workshop

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  1. Randomised Controlled Trials: a workshop NgaireKerse Professor and General Practitioner and asker of questions.

  2. Key issues - randomised trials • There must be uncertainty • The question must be answerable and feasible • Outcome reasonably common • Examples of randomised trials in GP • Green Script, Health promotion • Is it ethical to continue non-randomised studies that are evaluating interventions where there is uncertainty about effectiveness?

  3. The beginning • Uncontrolled trials • 18th century • Oranges and lemons, sailors and scurvy • Smallpox, Queen Caroline, Newgate Prison and ‘charity children’ • Controlled trials • Agricultural trials (1920’s) • Archie Cochrane - Salonica (1941) Vit C vs yeast for oedema • Streptomycin for TB (1946)

  4. Who’s afraid of the randomised trial and why? • Unethical • Explanatory (efficacy) vspragmatic trials (effectiveness) • Reluctance to pay – do it anyway

  5. Stepping into the unknown • Common sense interventions still need to be tested • Kerse caused Falls JAGS 2004. • Social work interventions • 1930s Cambridge-Somerville Youth Study • 1971 Blenker, 164 older persons

  6. Why randomise? • To decide whether an observed event is attributable to the meaningless play of chance or to causation (Silverman, 1980) • Reduces bias • researchers unable to consciously/unconsciously load the intervention group with ‘good’ GPs, good communicators, high SES patient groups • Evenly distribute known/unknown factors associated with certain outcomes

  7. Where to randomise? • Patient vs GP • Individual GP vs Practice? • Practice vsPHO? • DHB vs Local Government area?

  8. Analysis of findings • Analysis should occur at the level of randomisation • Are traditional analysis techniques appropriate? • Randomisation by cluster accompanied by an analysis appropriate to randomisation by individual is and exercise in self-deception (Cornfield, 1978) • Adjust for the design effect, increase sample size

  9. Where to randomise? Inflation Factor 2.5 Individual 2.0 1.5 Cluster 1.0 0 0.2 0.3 Total contamination

  10. Measuring - more than numbers? • Use of validated instruments - SIP, EPNDS, SF36 • Use of specific questions • open-ended, likert scales, categorical • Self-report vs observed practice • Observed practice - patient outcomes, simulated patient

  11. Intervention Group • Lo intensity intervention • Manual, risk assessment and suggestions. • Control Group • usual care Falls and injury Prevention pilot – FIPPS Randomly selected: 8 rest-homes, 4 private hospitals, 2 large complexes All residents 560 mean age 85 years Randomisation • Process Evaluation • focus groups with staff • Outcome Evaluation • >2,000 falls

  12. Promoting Independence in Residential Care • Social Group • 2 visits 41 Rest-homes in Christchurch and Auckland Falls, function, QOL, 682, mean age 87 years. Randomisation (no stratification) • Activity Group • PIRC, goal set, functional assessment, PIP to caregiver • falls surveillance Outcome evaluation No Impr QOL Function (on average, signif subgroup) No increase in falls

  13. Thinking differently • RCT design does not preclude ‘evaluation’ • process and impact • ‘Qualitative’ methods can be incorporated into trials • trial development - getting the intervention right • making sure the intervention is working • measuring the outcomes of the intervention

  14. The big question….. • Is it ethical to continue non-randomised studies in the general practice setting that are testing/evaluating interventions where there is a genuine uncertainty about the effectiveness?

  15. PICOT BMC Med Res Methodol. 2010; 10: 11. Population, Intervention, Comparator, Outcome, Time-frame • Everyone in the trial gets the same research process except for the intervention • Is the research process greater than the intervention

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