I want to compare costs of CPT codes from two different claims payers. Both have par and non par priced providers. I am using dplyr
and modeest::mlv
, but its not working out as anticipated. Heres some sample data;
source CPTCode ParNonPar Key net_paid PaidFreq seq
ABC 100 Y ABC100Y -341.00 6 1
ABC 100 Y ABC100Y 0.00 2 2
ABC 100 Y ABC100Y 341.00 6 3
XYZ 103 Y XYZ103Y 740.28 1 1
XYZ 104 N XYZ104N 0.00 2 1
XYZ 104 N XYZ104N 401.82 1 2
XYZ 104 N XYZ104N 726.18 1 3
XYZ 104 N XYZ104N 893.00 1 4
XYZ 104 N XYZ104N 928.20 2 5
XYZ 104 N XYZ104N 940.00 2 6
and the code
str(data)
View(data)
## Expand frequency count to individual observations
n.times <- data$PaidAmounts
dataObs <- data[rep(seq_len(nrow(data)), n.times),]
## Calculate mean for each CPTCode (for mode use modeest library)
library(dplyr)
library(modeest)
dataSummary <- dataObs %>%
group_by(ParNonPar, CPTCode) %>%
summarise(mean = mean(net_paid),
median=median(net_paid),
mode = mlv(net_paid, method=mfv),
total = sum(net_paid))
str(dataSummary)
I thought I could load modeest in the summarize function with the mean and median, but this formulation errors out with Error in as.character(x) : cannot coerce type 'closure' to vector of type 'character' Without mlv I am getting a df like this, but what I want is to get all the stats for a payer cpt on one line. I envision graphing it in boxplots by limiting the x and y segments, once I get what I need on a row
the inadequate answer is this ( I forgot to get the payer name in here!)
ParNonPar CPTCode mean median(net_paid) total
N 0513F 0.000000 0.000 0.00
N 0518F 0.000000 0.000 0.00
N 10022 0.000000 0.000 0.00
N 10060 73.660000 90.120 294.64
N 10061 324.575000 340.500 1298.30
N 10081 312.000000 312.000 312.00
thanks very much for your time and effort.