Calculate the Care Density for all Patients

This function calculates the classic Care Density Index as defined by Pollack et al. (2013) for each patient in the supplied dataset. Works well with large patient-sharing networks.

Usage

care_density(data, pat_col=1, data_frame=TRUE)

Arguments

data: A data.frame like object containing exactly two columns. One should include only patient IDs and the other one only provider IDs. Each row should denote one patient-provider contact. Multiple contacts (same rows) are allowed but have no effect on the outcome. Both patient and provider IDs should be unique, which means that one ID may not be in both rows.
pat_col: Specifies which column of data includes the patient IDs. If the first column contains the patient IDs this should be kept at 1, if the second column contains the patient IDs it should be set to 2.
data_frame: Set this argument to TRUE to return a data.frame instead of the data.table format that is used under the hood.

Details

The Care Density ($C_p$) is "a patient-level measure that quantifies the amount of patient-sharing among his or her providers" (DuGoff et al. 2018). Higher care densities have been posited to reflect greater connections among a patients "care team". Formally, it is defined as:

$$C_p = \frac{\sum_{i = 1}^m w_{p, j}}{n_p (n_p - 1)/2}$$

with $n_p$ being the number of providers a patient has visited, $m$ defined as the number of all possible combinations of length two and $w_{p, j}$ being the number of patients that a pair of provider is sharing. An example is given below and explained more thoroughly in the vignette of this package.

Under the hood, this function uses the igraph package to construct a patient-sharing network from the provided data to calculate the weights. It then uses the data.table package to efficiently calculate the care densities from a resulting edge list with weights.

Value

Returns a single data.frame (or data.table) containing the sum of all weights ("sum_weights"), the number of providers seen by each patient ("n") and the calculated Care Density ("care_density").

References

Pollack, Craig Evan, Gary E. Weissman, Klaus W. Lemke, Peter S. Hussey, and Jonathan P. Weiner. (2013). "Patient Sharing Among Physicians and Costs of Care: A Network Analytic Approach to Care Coordination Using Claims Data". Journal of General Internal Medicine 28 (3), pp. 459-465.

DuGoff, Eva H., Sara Fernandes-Taylor, Gary E. Weissman, Joseph H. Huntley, and Craig Evan Pollack. (2018). "A Scoping Review of Patient-Sharing Network Studies Using Administrative Data". Translational Behavioral Medicine 8 (4), pp. 598-625.

Author

Robin Denz

Examples

library(CareDensity)
library(data.table)
library(igraph)
#> 
#> Attaching package: ‘igraph’
#> The following objects are masked from ‘package:stats’:
#> 
#>     decompose, spectrum
#> The following object is masked from ‘package:base’:
#> 
#>     union

# some arbitrary patient-provider contact data
data <- data.frame(PatID=c("1", "1", "1", "2", "2", "3", "3", "4", "5"),
                   ArztID=c("A", "C", "D", "A", "D", "A", "D", "D", "C"))
                   
# calculate the care densities
care_density(data)
#>   PatID sum_weights n care_density
#> 1     1           5 3     1.666667
#> 2     2           3 2     3.000000
#> 3     3           3 2     3.000000
#> 4     4          NA 1           NA
#> 5     5          NA 1           NA