randomising every patient you see: software for clinic seat research

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Randomising every patient you see: Software for clinic seat research Bruce Arroll Douglas Kingsford Antonio Fernando III 2010 Department of General Practice & Primary Health Care Faculty of Medical & Health Science University of Auckland, Auckland, New Zealand

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Randomising every patient you see: Software for clinic seat research. Bruce Arroll Douglas Kingsford Antonio Fernando III 2010 Department of General Practice & Primary Health Care Faculty of Medical & Health Science University of Auckland, Auckland, New Zealand. The problem with RCTs. - PowerPoint PPT Presentation

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Page 1: Randomising every patient you see: Software for clinic seat research

Randomising every patient you see:Software for clinic seat research

Bruce Arroll

Douglas Kingsford

Antonio Fernando III

2010

Department of General Practice & Primary Health Care

Faculty of Medical & Health Science

University of Auckland, Auckland, New Zealand

Page 2: Randomising every patient you see: Software for clinic seat research

The problem with RCTs

Expensive Exclude many of the patients we see

May not be the patients we usually see-restrictive Expensive Time consuming Huge amount of paperwork If paper based need data entry

How generalisable are they How to get a cheap computer generated randomisation

code to ensure concealed allocation.

Page 3: Randomising every patient you see: Software for clinic seat research

McVickers paper

– Vickers AJ, Scardino PT. The clinically integrated randomised trial proposed novel method for conducting large trials at low cost. Trials (Biomed Central 5/3/2009)

Integrate RCT in to clinical practice Randomise every eligible patient Eligible if clinician uncertain-broad-crucial point Adverse effects, me too drugs; lifestyle Patients could enter own data eg adverse effects

Page 4: Randomising every patient you see: Software for clinic seat research

Randomisation “daily”

20 starter packs of Varenicline (Champix)

Give them out haphazardly or systematically

“Pressured” my colleagues to be systematic Mailed a letter to 40 Maori smokers offering 4 free visits

with or without a starter pack of Champix 4/20 with starter pack replied and 0/20 in control Conclusion “don’t send out letters to Maori patients”

Without a starter pack

Better way would be phone call or face to face

Page 5: Randomising every patient you see: Software for clinic seat research

Pediatric Oncology-the challenge

Every child with a malignancy in the (developed

world) is in a randomised controlled trial

Contributed to increase in survival for leukemia from about 30% to 90%

Page 6: Randomising every patient you see: Software for clinic seat research

Generalisability RCT

300 patients from 250 GPs

300 consecutive patients from 3 GPs

Which has the most generalisability?

Page 7: Randomising every patient you see: Software for clinic seat research

Office RCT

Internet based software

Make RCTs from office chair simple

Answer simple research questions as part of every day clinical work

Page 8: Randomising every patient you see: Software for clinic seat research

Ideas for RCT

Gratitude diaries

Telephone call from practice nurse

Page 9: Randomising every patient you see: Software for clinic seat research

Gratitude diaries 3 things grateful for and what did to cause them daily for

one week. Control group writes down early life memories. ? Then once per week

RCT done with internet sample had an effect up to 6 months later. CES-D 13 vs 10.5 Seligman ME, American psychologist 2005;60;5:410-21

Once per week enough Lyubomirsky S.The How of Happiness: Penguin

No trials in primary care Anecdote 90%+ patients happy to do them.

Page 10: Randomising every patient you see: Software for clinic seat research

Research Question Does giving depressed patients a gratitude diary vs

control writing improve their PHQ outcomes at 4 (?) months

Inclusion criteria broad Any one with PHQ ≥ 10 (600 pts in 4000 patients) Excl Bipolar; severe drug/alcohol;dementia; personality

disorder; eating disorder; persisting psychotic illness; life expectancy < 2 years; patient unreliable at attending appointments

Page 11: Randomising every patient you see: Software for clinic seat research

Research Issues ? Follow up as they come in versus attempt a formal

follow up

A sample size of 98 patients in each arm will be required to demonstrate a 2 point reduction on the PHQ from 13 to 11 with a standard deviation of 5

Page 12: Randomising every patient you see: Software for clinic seat research

Issues Follow up and analysis

Stop trial at 4 months and do last value carried forward

Or

Stop trial at 4 months and take data as found (akin to Kaplan Meir)

– Analyse using random coefficients which would compare the gradient of the intervention group and the control group

Page 13: Randomising every patient you see: Software for clinic seat research

Develop office based software Able to get randomisation code from clinic computer

Data gets stored on web No extra data entry required

Multiple doctors/nurses can submit data from different clinics-international collaboration possible

Privacy assured as each clinic uses own patient file identifier Simple entry criteria and simple outcome criteria Eg 600 patients with PHQ ≥ 10

Page 14: Randomising every patient you see: Software for clinic seat research

Doug Kingsford-sleep deprived

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Validated in primary care In NZ Arroll et al 2010 (not published)

Short Gives a “diagnosis” categorical Also continuous score to monitor improvement Free from June 2010 Currently been used in decision support in our district

health board therefore familiar and used

Why PHQ-9 and GAD-7

Page 21: Randomising every patient you see: Software for clinic seat research

Data collected after randomisation-next slide

Previous psych contact and admissions asked after

randomisation

Done to simplify recruiting

Not part of primary outcome

Used for exploring for future studies

? Cause any bias

Page 22: Randomising every patient you see: Software for clinic seat research

Spectrum

No gold standard ie post mortem won’t tell you if the

person is depressed.

Sadness →→→→→→→→→→Depression

Consider Treatment if severe or

persistent

Page 23: Randomising every patient you see: Software for clinic seat research

DSM IVDiagnostic and statistical manual of mental disorders

Page 24: Randomising every patient you see: Software for clinic seat research
Page 25: Randomising every patient you see: Software for clinic seat research

What is in paper form?

Consent form –need to be kept/scanned

Information sheet

Intervention instructions

Page 26: Randomising every patient you see: Software for clinic seat research

Follow up data entry

Less than 1 minute

Page 27: Randomising every patient you see: Software for clinic seat research

PHQ

9 questions over past month

Score 10-14 mild major depression

Score 15-19 moderate major depression

Score 20+ severe major depression

Advantage a dichotomous score and a continuous scale

to monitor improvement

Page 28: Randomising every patient you see: Software for clinic seat research

PHQ 2009

Total = 19 Below 10 = 16 people 10-14 = 1 person 15-19 = 2 person 20+ nil

Page 29: Randomising every patient you see: Software for clinic seat research

GAD

Below 8 =14 persons 8 or more = 5 persons

Page 30: Randomising every patient you see: Software for clinic seat research

Missed consent tick

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Analysis

Both ways i.e. all at 4 months –send out/phone for follow up At 4 months according how they have come in

– Using random coefficients analysis of slopes

Analyse all Analyse by PHQ 10-14 and >14

>14 more difficulty with functioning and may be less able to do Gratitude diaries

Page 36: Randomising every patient you see: Software for clinic seat research

Start testing July 2010

Ethics underway

Beta test in own clinic

Page 37: Randomising every patient you see: Software for clinic seat research

Advice

Control activity ? 3 memories of past

Ok to collect data over randomisation

Follow all at 4 months or as they have come in