adding time‐dependent effects to the evaluation of geographic variation. enrique bernal-delgado-...
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Adding time‐dependent effects to the evaluation of geographic variation. Enrique Bernal-Delgado, Julian Librero‐López on behalf of Atlas VPM group. The Wennberg International Collaborative, London 2014TRANSCRIPT
Adding 'me-‐dependent effects to the evalua'on of geographic
varia'on
Enrique Bernal-‐Delgado, Julian Librero-‐López on behalf of Atlas VPM group
WIC, London 2014
FIS Grant PI10494
Time 1
Time 3
Time 2
Risks across spaQal units are considered Qme-‐independent
Risks across spaQal units are considered Qme-‐dependent Following a pre-‐defined, parametric shape – lineal, quadraQc (leV) Following a structured trend although without a pre-‐defined shape
t is linear or quadra'c including (or not) a space-‐'me interac'on term where δj is the difference between the area specific trend and the mean trend
Different intercepts for each 'me period including or not an Interac'on term: δj the difference between the area specific effect and the Qme effect
Time as random effects: accounQng for the 'me trend (βt) and as the interac'on (ϕjt)
CASE STUDY -‐ COPD
Study characteris'cs
– PopulaQon and se^ng • ≅ 110,000 hospitalizaQons per year, produced in the 203 healthcare areas composing SHCS, from 2002 to 2012
– Main endpoint • COPD Standardized HospitalizaQon RaQo • Interpret: the higher the raQo, the worse the performance
– Analyses
– Sources: AdministraQve data
Descrip've sta's'cs
Standardised Hospitaliza'on Risk SpaQal only (2008)
Standardised Hospitaliza'on Risk SpaQal-‐temporal (2008)
2002
Posterior probability
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Spatial'structured' 0.043'Spatial'unstructured' 0.111'Time'' 0.006'S*t'Interaction' 0.028'' 'Spatial'fraction'' 0.822'''''Structured(( 0.282'Time'fraction' 0.031'Interaction'' 0.147'
Variance fracQons
Specific evoluQon along the period
Discussion – Standardized uQlizaQon raQos are subject to large variaQon when studying small populaQons or rare events
– Frequently, informaQon is scarce or inexistent – latent phenomena can be explored
– FracQons of variance discriminates the relaQve importance of Qme-‐dependent phenomena (early adopQon, guidelines uptake) in the spaQal context (providers influence)
– Quasi-‐experiments
SUR: effect of random noise in the estimation England: knee replacement and prostatectomy
20.6 10.5 5.01 9.3
0.5
11.5
2
SUR EBPGrr EBLNrr EBMarshall
0.5
11.5
2
SUR EBPGrr EBLNrr EBMarshall
16.3 12.2 4.5 9.9
Discussion – Standardized uQlizaQon raQos are subject to large variaQon when studying small populaQons or rare events
– Frequently, informaQon is scarce or inexistent – latent phenomena can be explored
– FracQons of variance discriminates the relaQve importance of Qme-‐dependent phenomena (adopQon, guidelines uptake, policies implementaQon) in a spaQal context (insQtuQonal factors at area level)
– Quasi-‐experiments
Caveats – Classical 0.80 thresholds might not be valid for ST models • Different cut-‐off points might be needed depending on the period of study (higher values) and math models.
– In highly heterogeneous contexts (concentraQon of high risks in the larger units of analysis) keeping 1 as the null value increases the number of false posiQve areas.
Adding 'me-‐dependent effects to the evalua'on of geographic
varia'on
Enrique Bernal-‐Delgado, Julian Librero-‐López on behalf of Atlas VPM group
WIC, London 2014
FIS Grant PI10494
Posterior mean deviance (DIC)
2002
Standardised hospitalisa'on risk Average and evoluQon (2002 to 2008 )
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
M. D. Ugarte1, T. Goicoa, B. Ibáñez and A. F. Mili=no. Evalua=ng the performance of spa=o-‐temporal Bayesian models in disease mapping. Environmetrics 2009; 20: 647–665