care_density {CareDensity} | R Documentation |
Calculate the Care Density for all Patients
Description
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 |
pat_col |
Specifies which column of |
data_frame |
Set this argument to |
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"
).
Author(s)
Robin Denz
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.
See Also
Examples
library(CareDensity)
library(data.table)
library(igraph)
# 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)