Applying meta-analysis to trauma registry

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Applying meta-analysis to trauma registry

• Ammarin Thakkinstian, Ph.D.
• Clinical Epidemiology Unit
• Faculty of Medicine,
• Ramathibodi Hospital
• Tel [phone]
• Fax [phone]
• e-mail raatk_at_mahidol.ac.th

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Meta-analysis

• A tool for pooling results/data of the same
  topics from different sources/centres in order to
  
• estimates treatment/intervention effects
• leading to reduces probability of false negative
  results
• potentially to a more timely introduction of
  effective treatments/intervention/program
• Objective evidence quantitative conclusion

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Type of meta-analysis

• Summary data
• Unit of analysis is study
• Mean (SD)
• Count/frequency data by intervention outcome
• Person-time data

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Summary-data

• Continuous data

Studyi N Mean SD Rx/Exp N1 Mean1 SD1 Cont/Exp-
N2 Mean2 SD2
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Summary-data

• Categorical data

Studyi Case Control
Rx/Exp Cont/Exp- a c b d
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Type of meta-data

• Individual patient data (IPD)
• Raw databases
• Unit of analysis is patient
• Analogous to multi-centre trials
• More retrospective than prospective
• Data registry

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IPD

• Carry out data checking (data validation)
• Better standardization of information
• Categorization of eligible participants
• Definition of Outcomes
• Variables Classification
• ICD-10
• Type of trauma
• AIS

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IPD

• Flexible to apply statistic modeling
• Better adjust for confounders adjust for the
  same confounders simultaneously
• More flexible to assess interaction effects
• More flexible and capable in assessing cause of
  heterogeneity
• Allow to assess which subgroup of patients
  (centre) that intervention/program may/may not
  work
• Establishment of international networks of
  collaborating investigators

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IPD

• Disadvantage
• Data quality
• Missing data
• Data validation
• More cost time consuming
• Substantial effort and infrastructure require to
• Develop administer a standardized protocol
• Collect, manage, data management
• Communicate with collaborators

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• Data collection management
• Data Registry

Hospitals
Databases
Data coding
Data manager
QC
Data entry
Cleaning Checking Validate data
Validated Data
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Retrieve databases
Combine data
Statistician
Re-check data
Analyse data
Report results
Writing report (manuscript)
Publish (annual, twice/year)
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Data analysis

• Heterogeneity test
• Different source data are homogeneous?
• Homogeneity

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Analysis

• Heterogeneity

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Outcomes

• Death/alive
• Disability/Non-disability
• Complications
• Infection
• Fracture
• Hospitalization
• Hospital days
• QoL
• Cost

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Count (discrete) outcome

• Poisson regression
• Number of death
• Number of infection
• Number of disability
• Number of fracture

Intervention Period Pop No. of death Death /1000 RR
Audited 2001-2005 87870 3926 45 0.65 (0.62, 0.67)
Non-audited 1999-2003 228243 13120 57 1
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Hospital standardised mortality ratio
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HSMR

• Definition
• The ratio of actual number of deaths to expected
  number of deaths in the hospital

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Expected number of deaths
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• Original HSMR
• X
• Age in year
• Sex
• Admission category
• Emergency versus elective
• Length of stay
• Diagnosis group
• Account for 80 of death
• Co-morbidity
• Chalsons index
• Might be able to use AIS scores
• Transfer
• Patient was transferred from acute care

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Step of analysis

• Fit logistic regression with death as the outcome
  
• Estimate probability of death from the logit
  model
• E sum(p)

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Modified HSMR

• age in year
• sex
• Length of stay
• Admission category
• Emergency vs elective
• Transfers
• Acute care
• Diagnosis group
• Account for 80 of death
• Co-morbidity
• Chalsons index

• age in year
• sex
• Length of stay
• Patient transferring
• Ambulance
• Non-ambulance
• AIS scores
• Add
• Risk behavior
• Alcohol
• Transquilizer/sedation
• Type of trauma

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Problem

• Missing
• Diagnosis
• Co-morbid
• Length o stay
• Data validation??