Project 1
Jesse Surry, Curtis Baker
4/5/2020
Libraries:
library(tidyverse)## -- Attaching packages -------------------------------------------------------------------------------------- tidyverse 1.3.0 --## v ggplot2 3.2.1 v purrr 0.3.3
## v tibble 2.1.3 v dplyr 0.8.3
## v tidyr 1.0.0 v stringr 1.4.0
## v readr 1.3.1 v forcats 0.4.0## -- Conflicts ----------------------------------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(ggplot2)
library(rattle)## Warning: package 'rattle' was built under R version 3.6.3## Rattle: A free graphical interface for data science with R.
## Version 5.3.0 Copyright (c) 2006-2018 Togaware Pty Ltd.
## Type 'rattle()' to shake, rattle, and roll your data.library(magrittr)## Warning: package 'magrittr' was built under R version 3.6.3##
## Attaching package: 'magrittr'## The following object is masked from 'package:purrr':
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## set_names## The following object is masked from 'package:tidyr':
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## extractTasks:
1.Study how the distributions and means of the number of services, distinct beneficiary per day services, average medicare submitted charged amounts, average medicare paid amount vary as a function of Gender, the Provider Type, and Place of Service, and type of service that is being provided.
2.Study the relationship between average submitted charge amount and average medicare payment amount and analyze how the relationship of these variables varies as a function of the number of services, distinct beneficiary per day services, and Provider Type.
load("/Users/jcsur/Downloads/providerspokane.RDA")
load("providerspokane.RDA")
names(providerspokane)## [1] "National.Provider.Identifier"
## [2] "Last.Name.Organization.Name.of.the.Provider"
## [3] "First.Name.of.the.Provider"
## [4] "Middle.Initial.of.the.Provider"
## [5] "Credentials.of.the.Provider"
## [6] "Gender.of.the.Provider"
## [7] "Entity.Type.of.the.Provider"
## [8] "Street.Address.1.of.the.Provider"
## [9] "Street.Address.2.of.the.Provider"
## [10] "City.of.the.Provider"
## [11] "Zip.Code.of.the.Provider"
## [12] "State.Code.of.the.Provider"
## [13] "Country.Code.of.the.Provider"
## [14] "Provider.Type"
## [15] "Medicare.Participation.Indicator"
## [16] "Place.of.Service"
## [17] "HCPCS.Code"
## [18] "HCPCS.Description"
## [19] "HCPCS.Drug.Indicator"
## [20] "Number.of.Services"
## [21] "Number.of.Medicare.Beneficiaries"
## [22] "Number.of.Distinct.Medicare.Beneficiary.Per.Day.Services"
## [23] "Average.Medicare.Allowed.Amount"
## [24] "Average.Submitted.Charge.Amount"
## [25] "Average.Medicare.Payment.Amount"
## [26] "Average.Medicare.Standardized.Amount"Task 1 Distribution and Means
summary(providerspokane)## National.Provider.Identifier
## Min. :1.003e+09
## 1st Qu.:1.276e+09
## Median :1.509e+09
## Mean :1.516e+09
## 3rd Qu.:1.771e+09
## Max. :1.993e+09
##
## Last.Name.Organization.Name.of.the.Provider
## PATHOLOGY ASSOCIATES MEDICAL LABORATORIES LLC: 491
## MUELLER : 109
## KING : 105
## JOHNSON : 103
## JONES : 99
## LEE : 99
## (Other) :17972
## First.Name.of.the.Provider Middle.Initial.of.the.Provider
## : 964 :3583
## MICHAEL: 630 M :1571
## JOHN : 469 J :1569
## DAVID : 434 A :1506
## ROBERT : 410 L :1299
## WILLIAM: 324 D :1273
## (Other):15747 (Other):8177
## Credentials.of.the.Provider Gender.of.the.Provider Entity.Type.of.the.Provider
## MD :7497 : 964 I:18014
## M.D. :4871 F: 5558 O: 964
## :1322 M:12456
## PA-C : 904
## ARNP : 873
## D.O. : 313
## (Other):3198
## Street.Address.1.of.the.Provider Street.Address.2.of.the.Provider
## 801 S STEVENS ST: 1663 :10058
## 122 W 7TH AVE : 1194 SUITE 200: 538
## 400 E 5TH AVE : 1176 SUITE 310: 421
## 910 W 5TH AVE : 1038 SUITE 100: 345
## 101 W 8TH AVE : 820 SUITE 700: 311
## 105 W 8TH AVE : 802 SUITE 400: 306
## (Other) :12285 (Other) : 6999
## City.of.the.Provider Zip.Code.of.the.Provider State.Code.of.the.Provider
## SPOKANE:18978 992042654: 1663 WA:18975
## 992021334: 1176 WI: 2
## 992042349: 1125 WY: 1
## 992042966: 1062
## 992042307: 702
## 992042302: 607
## (Other) :12643
## Country.Code.of.the.Provider Provider.Type
## US:18978 Diagnostic Radiology: 2414
## Internal Medicine : 1809
## Family Practice : 1541
## Physician Assistant : 1240
## Nurse Practitioner : 1214
## Hematology/Oncology : 745
## (Other) :10015
## Medicare.Participation.Indicator Place.of.Service HCPCS.Code
## N: 2 F: 6157 99213 : 820
## Y:18976 O:12821 99214 : 742
## 99204 : 316
## 99203 : 312
## 99232 : 286
## 99212 : 261
## (Other):16241
## HCPCS.Description
## Established patient office or other outpatient visit, typically 15 minutes: 820
## Established patient office or other outpatient, visit typically 25 minutes: 742
## New patient office or other outpatient visit, typically 45 minutes : 316
## New patient office or other outpatient visit, typically 30 minutes : 312
## Subsequent hospital inpatient care, typically 25 minutes per day : 286
## Established patient office or other outpatient visit, typically 10 minutes: 261
## (Other) :16241
## HCPCS.Drug.Indicator Number.of.Services Number.of.Medicare.Beneficiaries
## N:17844 Min. : 11.0 Min. : 11.0
## Y: 1134 1st Qu.: 20.0 1st Qu.: 17.0
## Median : 42.0 Median : 31.0
## Mean : 291.2 Mean : 101.8
## 3rd Qu.: 115.0 3rd Qu.: 71.0
## Max. :155972.0 Max. :70013.0
##
## Number.of.Distinct.Medicare.Beneficiary.Per.Day.Services
## Min. : 11.0
## 1st Qu.: 19.0
## Median : 39.0
## Mean : 154.1
## 3rd Qu.: 101.0
## Max. :155971.0
##
## Average.Medicare.Allowed.Amount Average.Submitted.Charge.Amount
## Min. : 0.019 Min. : 0.23
## 1st Qu.: 19.003 1st Qu.: 48.00
## Median : 56.170 Median : 132.00
## Mean : 104.731 Mean : 295.21
## 3rd Qu.: 107.572 3rd Qu.: 276.00
## Max. :29872.890 Max. :45998.00
##
## Average.Medicare.Payment.Amount Average.Medicare.Standardized.Amount
## Min. : 0.011 Min. : 0.011
## 1st Qu.: 15.498 1st Qu.: 15.990
## Median : 40.720 Median : 43.613
## Mean : 80.178 Mean : 83.320
## 3rd Qu.: 81.984 3rd Qu.: 85.360
## Max. :23420.340 Max. :21855.610
## str(providerspokane$Place.of.Service)## Factor w/ 2 levels "F","O": 1 1 2 2 2 2 2 2 1 2 ...levels(providerspokane$Place.of.Service)=c("Facility","Other")Average number of services at facilities and other centers
place_average_service = providerspokane%>%
group_by(Place.of.Service)%>%
summarise(average_number_of_services = mean(Number.of.Services))
ggplot(place_average_service, mapping = aes(Place.of.Service,average_number_of_services, fill = Place.of.Service )) +geom_bar(stat = "identity")
Average number of beneficiary services at facilities and other centers
place_beneficiacry_service = providerspokane%>%
group_by(Place.of.Service)%>%
summarise(average_number_of_beneficiary_services = mean(Number.of.Distinct.Medicare.Beneficiary.Per.Day.Services))
ggplot(place_beneficiacry_service, mapping = aes(Place.of.Service,average_number_of_beneficiary_services, fill = Place.of.Service )) +geom_bar(stat = "identity")
## Average number of services by provider type
library(rattle)
library(magrittr)
Provider_mean_services=providerspokane%>%
group_by(Provider.Type)%>%
summarise(mean_number_of_services=mean(Number.of.Services))
mean_services_sort <- arrange(Provider_mean_services, desc(mean_number_of_services))
ggplot(data = mean_services_sort, mapping = aes(reorder(Provider.Type, mean_number_of_services), mean_number_of_services)) + geom_bar(stat = 'identity') + ggtitle('Average of Number of Services by Provider Type') + labs(y = 'Average of Number of Services', x = 'Provider Type') + theme(axis.text.y = element_text(size = 5)) + coord_flip()
## Average number of beneficiary services by provider type
Provider_mean_bservices=providerspokane%>%
group_by(Provider.Type)%>%
summarise(mean_distinct_beneficiaries=mean(Number.of.Distinct.Medicare.Beneficiary.Per.Day.Services))
mean_bservices_sort <- arrange(Provider_mean_bservices, desc(mean_distinct_beneficiaries))
ggplot(data = mean_bservices_sort, mapping = aes(reorder(Provider.Type, mean_distinct_beneficiaries), mean_distinct_beneficiaries)) + geom_bar(stat = 'identity') + ggtitle('Average of Number of Distinct Beneficiary Services by Provider') + labs(y = 'Average of Number of Distinct Beneficiary per Day Services', x = 'Provider Type') + theme(axis.text.y = element_text(size = 5)) + coord_flip()
## Average number beneficiary services by gender
providerspokane%>%group_by(Gender.of.the.Provider)%>%summarise(Mean_Number.of.Distinct.Medicare.Beneficiary.Per.Day.Services=mean(Number.of.Distinct.Medicare.Beneficiary.Per.Day.Services))%>%filter(Gender.of.the.Provider!="")%>%ggplot(.,aes(Gender.of.the.Provider,Mean_Number.of.Distinct.Medicare.Beneficiary.Per.Day.Services))+geom_bar(stat="identity")
Average Medicare submitted charge amounts by gender
providerspokane%>%group_by(Gender.of.the.Provider)%>%summarise(Mean_submitted_charge_amount=mean(Average.Submitted.Charge.Amount))%>%filter(Gender.of.the.Provider!="")%>%ggplot(.,aes(Gender.of.the.Provider,Mean_submitted_charge_amount))+geom_bar(stat="identity")
Average Medicare submitted charge amount by place
Place_charge = providerspokane%>%
group_by(Place.of.Service)%>%
summarise(mean_submitted_charge_amount = mean(Average.Submitted.Charge.Amount))
ggplot(Place_charge, mapping = aes(Place.of.Service, mean_submitted_charge_amount, fill = Place.of.Service)) +geom_bar(stat = "identity")
## Average medicare subimtted charge by provider type
Provider_charge=providerspokane%>%
group_by(Provider.Type)%>%
summarise(mean_submitted_charge_amount=mean(Average.Submitted.Charge.Amount))
charge_sort <- arrange(Provider_charge, desc(mean_submitted_charge_amount))
ggplot(data = charge_sort, mapping = aes(reorder(Provider.Type, mean_submitted_charge_amount), mean_submitted_charge_amount)) + geom_bar(stat = 'identity') + ggtitle('Average of the Submitted Charge Amount by Provider Type') + labs(y = 'Average of the Submitted Charge Amount ($)', x = 'Provider Type') + theme(axis.text.y = element_text(size = 5)) + coord_flip()
## Average Medicare paid amount by Gender
providerspokane%>%group_by(Gender.of.the.Provider)%>%summarise(Mean_Average.Medicare.Payment.Amount=mean(Average.Medicare.Payment.Amount))%>%filter(Gender.of.the.Provider!="")%>%ggplot(.,aes(Gender.of.the.Provider,Mean_Average.Medicare.Payment.Amount))+geom_bar(stat="identity")
Average Medicare parment at facilities and other centers
Place_payment = providerspokane%>%
group_by(Place.of.Service)%>%
summarise(mean_medicare_paid = mean(Average.Medicare.Payment.Amount))
ggplot(Place_payment, mapping = aes(Place.of.Service, mean_medicare_paid, fill = Place.of.Service)) +geom_bar(stat = "identity")
## Average medicaer paid by provider type
Provider_payment=providerspokane%>%
group_by(Provider.Type)%>%
summarise(mean_medicare_paid=mean(Average.Medicare.Payment.Amount))
payment_sort <- arrange(Provider_payment, desc(mean_medicare_paid))
ggplot(data = payment_sort, mapping = aes(reorder(Provider.Type, mean_medicare_paid), mean_medicare_paid)) + geom_bar(stat = 'identity') + ggtitle('Average of Amount Medicare Paid by Provider Type') + labs(y = 'Average of the Amount Medicare Paid ($)', x = 'Provider Type') + theme(axis.text.y = element_text(size = 5)) + coord_flip()