Unlocking a national adult cardiac surgery audit registry with The R - - PowerPoint PPT Presentation
Unlocking a national adult cardiac surgery audit registry with The R User Conference 2013 University of Castilla-La Mancha, Albacete, Spain GL Hickey 1,2,3 , SW Grant 2,3 & B Bridgewater 1,2,3 1 Northwest Institute of BioHealth Informatics,
GL Hickey1,2,3, SW Grant2,3 & B Bridgewater1,2,3
1Northwest Institute of BioHealth Informatics, University of Manchester 2University Hospital of South Manchester 3National Institute of Cardiovascular Outcomes Research, UCL
The R User Conference 2013 University of Castilla-La Mancha, Albacete, Spain
NICOR NIBHI
HOSPITALS
DATABASE CLEANING ANALYSES
AUDIT & GOVERNANCE TOOLS
CLINICAL RESEARCHERS
NATIONAL DEATH REGISTER*
* Ability to link with many
RESEARCH
MESSY DATA
DATA EXTRACT VARIABLE 1 VARIABLE 2 VARIABLE 3 ………… EXCLUDE RECORDS ADD VALUE CLEANE D DATA Scripts to add:
variables
E.g. duplicates Rapidly reproducible
> with(SCTS, table(X4.04.Discharge.Destination, X4.05.Status.at.Discharge)) X4.05.Status.at.Discharge X4.04.Discharge.Destination 0. Alive 1. Dead 828 48296 2453 . Another dept within the trust 0 57 0 0 1 1 0
1 Home 0 4104 0
2 Convalescence 0 63 0
3 Other hospital 0 1 0 3 Other Hospital 0 151 0 3 Other Hospital - wd 6 0 1 0 3 Other Hospital wd 2 0 1 0 3 Other ward 0 1 0
4 Patient deceased 0 0 173
5 0 7 0
7 0 2 0 8 0 38 4 9 114 3820 518 Second op 0 2 6
Illegal options Transcriptional discrepancies Missing data Conflicts
* Applies to analysing healthcare data also
DATA
MONITORING
5% 10% 15%
Mortality rate
200 400 600 800
f procedures
Healthcare provider
2503756 3166114 3207776 3226274 3286898 3451180 3631845 4445638 4473204 4683551
subset
RISK ADJUSTMENT
glm, glmer {lme4}, mfp {mfp}, predict, auc {pROC},
CLASSIFICATION & PRESENTATION
ggplot {ggplot2}, write.csv
AGGREGATION
summaryBy {doBy}, merge, arrange {plyr}
summaryBy {doBy} + gvisMotionChart {googleVis}
RESEARCH
0.0 0.2 0.4 0.6 0.8 1.0 1 2 3 4 5 6 7 8 9 10 Time from procedure (years) Survival probability
1415 991 779 559 398 276 180 114 64 23 6
All octogenarians having MV surgery
Octogenarians having Mitral Valve Surgery ± CABG ± TV repair
survfit + Surv {survival} kmplot {by Tatsuki Koyama} Mean 4 patients per unit / year
Unmatched Unmatched
3 2 1 1 2 0.0 0.2 0.3 0.5 0.6 0.8 0.9 Mechanical Biological Propensity score
Matched Matched
3 2 1 1 2 3 0.0 0.2 0.3 0.5 0.6 0.8 0.9 Mechanical Biological
matchit {MatchIt}
Probability of receiving a mechanical valve Mechanical valve Biological valve Mechanical valve Biological valve
2002 2004 2006 2008 2010 0.02 0.04 0.06 0.08 0.10 Time Observed Expected Actual Overall average Trend
Mortality proportion Ratio = 0.37 Ratio = 0.73 2% 4% 6% 8% 10% Mortality Date of surgery
Intercept −6.00 −5.75 −5.50 −5.25 2002 2004 2006 2008 2010
Time Coefficient
Estimate 95% CI No update Rolling 24−month window (12−months) Rolling 24−month window (1−month) Piecewise recalibration (12−months) Piecewise recalibration (24−months) Dynamic logistic regression
logistic.dma {dma}