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added CCG level rollup

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fhr committed Dec 3, 2012
1 parent fba7188 commit 91241b88135f032044838e014e37e49464a08023
Showing with 16 additions and 13 deletions.
  1. +16 −13 GP_drugs_analysis.R
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@@ -91,19 +91,6 @@ ggplot(practice.indicator, aes(items.alldrugs,pct.statin.atorva))+
ggplot(practice.indicator, aes(items.alldrugs,pct.statin.rosuva))+
geom_point()+opts(title="Rosuva funnel")
# Roll up to CCG level
ccg.rollup<-read.xls("list-of-proposed-practices-ccg.xls",sheet="Practice list")
spend.ccg.totals<-merge(spend.practice.totals,ccg.rollup,by.x="Practice.code",by.y="Practice.code",all.x=TRUE)
ccg.totals.headings<- list("Drug"=spend.ccg.totals$Drug,
"Proposed.CCG.name"=spend.ccg.totals$Proposed.CCG.name,
"Interim.CCG.code"=spend.ccg.totals$Interim.CCG.code,
"category"=spend.ccg.totals$category)
spend.ccg.totals<-
aggregate(spend.ccg.totals[,c("cost.thisdrug","items.thisdrug",
"amount.wasted")],
by=ccg.totals.headings,
FUN=sum)
## Timeseries plots
t<-subset(spend.practice,Drug %in% c("Atorvastatin","Rosuvastatin Calcium","Simvastatin"))
statin.timeseries<-aggregate(t$cost.thisdrug,by=list(t$Month,t$Drug),FUN=sum)
@@ -139,6 +126,22 @@ pct.totals$pct.problem<-round(pct.totals$pct.problem,3)
pct.totals$total.items.month<-round(pct.totals$total.items.month,0)
write.csv(pct.totals,"pct_statin_totals.csv",row.names=FALSE)
# Roll up to CCG level for mapping
ccg.rollup<-read.xls("list-of-proposed-practices-ccg.xls",sheet="Practice list")
ccg.totals<-merge(spend.practice.totals,ccg.rollup,by.x="Practice.code",by.y="Practice.code",all.x=TRUE)
ccg.totals<-subset(ccg.totals,category=="statin")
ccg.totals$item.bad<-FALSE
ccg.totals[ccg.totals$Drug %in% c("Atorvastatin","Rosuvastatin Calcium"),]$item.bad<-TRUE
ccg.totals<-aggregate(ccg.totals$items.thisdrug,by=list(ccg.totals$item.bad,ccg.totals$Interim.CCG.code),FUN=sum)
ccg.totals<-cast(ccg.totals,Group.2~Group.1)
names(ccg.totals)<-c("CCG.code","ok.drugs","problem.drugs")
ccg.totals$ccg.problem<-ccg.totals$problem.drugs/(ccg.totals$problem.drugs+ccg.totals$ok.drugs)
ccg.totals$total.items.month<-(ccg.totals$ok.drugs+ccg.totals$problem.drugs)/length(file.list)
ccg.totals<-ccg.totals[,c("CCG.code","total.items.month","ccg.problem")]
ccg.totals$ccg.problem<-round(ccg.totals$ccg.problem,3)
ccg.totals$total.items.month<-round(ccg.totals$total.items.month,0)
write.csv(ccg.totals,"ccg_statin_totals.csv",row.names=FALSE)
## Savings figures
median(subset(statin.timeseries,Drug=="Atorvastatin")$Spend)*problem.drugs[problem.drugs$Drug=="Atorvastatin",]$saving
median(subset(statin.timeseries,Drug=="Rosuvastatin Calcium")$Spend)*problem.drugs[problem.drugs$Drug=="Rosuvastatin Calcium",]$saving

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