daySupply (version 0.1.0)

REWarDS: REWarDS

Description

Estimates patients' individualized average daily dose and subsequently, days' supply, by fitting a random effects linear regression model to patients' cumulative dose over time. Model parameters include a minimal universally-available set of variables from prescription records.

Usage

REWarDS(
  data,
  dspd_qty,
  strength,
  id,
  gap_handling = "none",
  permissible_gap = NULL,
  serv_date,
  tot_dose_disp = NULL,
  Pt_level = TRUE
)

Arguments

data

Sample simulated data. Data may have multiple rows per person (one row per prescription fill). Required columns include: 1. ID: Patient's unique identification number 2. ServDate: Date on which each prescription was filled. 3. DSPD_QTY: Dispensed quantity: Number of tablets dispensed to patient at each prescription fill. 4. strength: Strength of the tablets dispensed.

dspd_qty

Dispensed quantity: Number of tablets dispensed to the patient in at each prescription fill.

strength

Strength of the dispensed tablets in milligrams.

id

Unique patient identification number.

gap_handling

Method to handle gaps between prescription fills that are more than the permissible gap. Currently, gaps can be handled in three ways: 1) The <U+201C>None<U+201D> method: This is the default and it ignores gaps 2)The <U+201C>Initial consecutive Rx<U+201D> method: Starting from the first prescription fill, patients' prescription refills are considered until the permissible gap is exceeded. REWarDS uses these initial prescription refills to estimates patient's individualized daily dose. If the permissible gap is exceeded after the first fill, there will only be one prescription for REWaRDS to use, and as of now, REWarDS is unable to provide estimates of daily dose based on a single prescription. 3) The <U+201C>Longest consecutive Rx<U+201D> method: Looks at all periods with consecutive. prescription refills with gaps between them that do not exceed the permissible gap) during the follow up, it then counts the number of prescription fills in each period, and picks the period with the highest number of prescription fills and estimates the patient's average daily dose during that period.

permissible_gap

Gap (in days) allowed between prescription fills.

serv_date

Date of the prescription fill.

tot_dose_disp

Total dose dispensed: dispensed quantity x strength of the tablets dispensed for each prescription fill.

Pt_level

When TRUE, the estimated dose and days' supply are averaged for the patient.

Value

REWarDS returns a dataset called "REWarDS_result". This data set includes all the variables originally in the data, plus the following:

tot_dose_disp: Total dose dispensed at prescription fill: dispensed quantity x strength of the tablet dispensed.

REWarDS_avg_daily_dose: Patient's individualized average daily dose.

REWarDS_Rx_DS: Days' supply for prescription.

REWarDS_Pt_DS: Average days' supply for patient.

Details

REWarDS (Random Effects Warfarin Days' Supply) has been validated for warfarin. It demonstrated excellent performance that was superior to all current alternative methods for estimating days' supply of warfarin. REWarDS could potentially be used for other medications with variable dosing regimens (e.g. tacrolimus), or in populations with high inter-individual variability in drug clearance (e.g. elderly patients). Validation with cohorts of such patients, or medications other than warfarin, has yet to be done.

Examples

# NOT RUN {
#Patient collects 100 tablets of 5 mg warfarin  on January 3rd,
#and 100 tablets of 7 mg warfarin on February 1st.

#' #Generate a simulated dataset

library(dplyr)
n_patients <- 10
n_records <- 80
data <- data.frame(ID = rep(c(1 : n_patients), each = n_records))
data %>%
  group_by(ID) %>%
  mutate(ServDate = as.Date('2020/01/01') + abs(round(rnorm(n = 80, 700, 330))),
         DSPD_QTY = abs(round(rnorm(n = 80, 43, 28))),
         strength = abs(round(rnorm(n = 80, 4, 1))))  -> data
data <- as.data.frame(data)


data_new <- REWarDS(data, id = "ID", dspd_qty = "DSPD_QTY",
                    strength = "strength", serv_date = "ServDate",
                    tot_dose_disp =  NULL, Pt_level = FALSE,
                    gap_handling = "none", permissible_gap = NULL)

#tot_dose_disp: 500mg on January 3rd and 700mg for February 1st.
#REWarDS_avg_daily_dose: patient's individualized average daily dose obtained
#                        from regression analysis
#REWarDS_Rx_DS: 500mg/ patient's individualized average daily dose, for Jan 3rd
#               700mg/patient's individualized average daily dose , for Feb 1st

#Pt_level can be set as TRUE to get mean values for each patient
#REWarDS_Pt_DS: average of days' supply on Jan 3rd and Feb 1st

#Gap handling method can be specified
data_new <- REWarDS(data, id = "ID", dspd_qty = "DSPD_QTY",
                    strength = "strength", serv_date = "ServDate",
                    tot_dose_disp =  NULL, Pt_level = TRUE,
                    gap_handling = "Longest consecutive Rx", permissible_gap = 30)
#gap: Gap in number of days between each prescription and the prescription preceding it
#Rx_count: Number of prescriptions in each period of consecutive prescriptions until
#          the permissible gap is exceeded.
# }