This function calculates estimates of healthcare resource utilization (HCRU) from electronic health record data across various care settings (e.g., IP, OP, ED/ER). It provides descriptive summaries of patient counts, encounters, costs, length of stay, and readmission rates for pre- and post-index periods.
Usage
estimate_hcru(
data,
cohort_col = "cohort",
patient_id_col = "patient_id",
admit_col = "admission_date",
discharge_col = "discharge_date",
index_col = "index_date",
visit_col = "visit_date",
encounter_id_col = "encounter_id",
setting_col = "care_setting",
cost_col = "cost_usd",
readmission_col = "readmission",
time_window_col = "period",
los_col = "length_of_stay",
custom_var_list = NULL,
pre_days = 180,
post_days = 365,
readmission_days_rule = 30,
group_var_main = "cohort",
group_var_by = "care_setting",
test = NULL,
timeline = "Pre",
gt_output = TRUE
)Arguments
- data
A dataframe specifying the health care details.
- cohort_col
A character specifying the name of the cohort column.
- patient_id_col
A character specifying the name of the patient identifier column.
- admit_col
A character specifying the name of the date of admission column.
- discharge_col
A character specifying the name of the date of discharge column.
- index_col
A character specifying the name of the index date or diagnosis column.
- visit_col
A character specifying the name of the date of visit/claim column.
- encounter_id_col
A character specifying the name of the encounter/claim column.
- setting_col
A character specifying the name of the HCRU setting column e.g. IP, ED, OP, etc.
- cost_col
A character specifying the name of cost column.
- readmission_col
A character specifying the name of readmission column.
- time_window_col
A character specifying the name of time window column.
- los_col
A character specifying the name of length of stay column.
- custom_var_list
A character vector providing the list of additional columns.
- pre_days
Number of days before index (default 180 days).
- post_days
Number of days after index (default 365 days).
- readmission_days_rule
Rule for how many days can be permissible to define readmission criteria in AP setting (default 30 days).
- group_var_main
A character specifying the name of the main grouping column.
- group_var_by
A character specifying the name of the secondary grouping column.
- test
An optional named list of statistical tests (e.g.,
list(age = "wilcox.test")).- timeline
A character specifying the timeline window (default "Pre").
- gt_output
Logical; if
TRUE, also returns output formatted using gtsummary (default isTRUE).
Value
A list containing one or two summary data frames:
- Summary by settings using dplyr
A descriptive summary of HCRU metrics by cohort, setting, and time window.
- Summary by settings using gtsummary (optional)
Formatted summary statistics using gtsummary, if
gt_output = TRUE.
Examples
# \donttest{
df <- hcru_sample_data[sample(nrow(hcru_sample_data), 10), ]
estimate_hcru(data = df)
#> Warning: The `update` argument of `modify_header()` is deprecated as of gtsummary 2.0.0.
#> ℹ Use `modify_header(...)` input instead. Dynamic dots allow for syntax like
#> `modify_header(!!!list(...))`.
#> ℹ The deprecated feature was likely used in the gtsummary package.
#> Please report the issue at <https://github.com/ddsjoberg/gtsummary/issues>.
#> $`Summary by settings using dplyr`
#> # A tibble: 9 × 15
#> patient_id cohort care_setting time_window Days Month Year Visits Cost
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 P_1015 control OP Pre 14 0.460 0.0383 1 587.
#> 2 P_1038 control OP Pre 82 2.70 0.224 1 175.
#> 3 P_1085 control ED Post 87 2.86 0.238 1 4572.
#> 4 P_1090 treatment ED Pre 5 0.164 0.0137 1 4885.
#> 5 P_1096 treatment OP Post 8 0.263 0.0219 1 775.
#> 6 P_1100 treatment OP Post 80 2.63 0.219 1 1882.
#> 7 P_1105 treatment ED Pre 32 1.05 0.0876 1 1312.
#> 8 P_1164 treatment IP Post 85 2.79 0.233 1 16170.
#> 9 P_1170 treatment IP Post 155 5.10 0.424 1 7040.
#> # ℹ 6 more variables: LOS <dbl>, Readmission <dbl>, Visit_PPPM <dbl>,
#> # Visit_PPPY <dbl>, Cost_PPPM <dbl>, Cost_PPPY <dbl>
#>
#> $`Summary by settings using gtsummary`
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#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 1</td>
#> <td headers="stat_1_1" class="gt_row gt_center">2 (100%)</td>
#> <td headers="stat_1_2" class="gt_row gt_center">2 (100%)</td></tr>
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#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 175.25</td>
#> <td headers="stat_1_1" class="gt_row gt_center">1 (50%)</td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 586.6</td>
#> <td headers="stat_1_1" class="gt_row gt_center">1 (50%)</td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
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#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 0.370939024390244</td>
#> <td headers="stat_1_1" class="gt_row gt_center">1 (50%)</td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 2.17264285714286</td>
#> <td headers="stat_1_1" class="gt_row gt_center">1 (50%)</td>
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#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 4.45731707317073</td>
#> <td headers="stat_1_1" class="gt_row gt_center">1 (50%)</td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 26.1071428571429</td>
#> <td headers="stat_1_1" class="gt_row gt_center">1 (50%)</td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left" style="font-weight: bold;">Cost_PPPM</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 65.0070640243902</td>
#> <td headers="stat_1_1" class="gt_row gt_center">1 (50%)</td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 1274.4723</td>
#> <td headers="stat_1_1" class="gt_row gt_center">1 (50%)</td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left" style="font-weight: bold;">Cost_PPPY</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 781.144817073171</td>
#> <td headers="stat_1_1" class="gt_row gt_center">1 (50%)</td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 15314.45</td>
#> <td headers="stat_1_1" class="gt_row gt_center">1 (50%)</td>
#> <td headers="stat_1_2" class="gt_row gt_center"><br /></td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 1312.47</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center">1 (50%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 4885.25</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center">1 (50%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 0.95053125</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center">1 (50%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 6.0834</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center">1 (50%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 11.421875</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center">1 (50%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 73.1</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center">1 (50%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 1247.5437496875</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center">1 (50%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 29718.92985</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center">1 (50%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 14990.86828125</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center">1 (50%)</td></tr>
#> <tr><td headers="label" class="gt_row gt_left"> 357111.775</td>
#> <td headers="stat_1_1" class="gt_row gt_center"><br /></td>
#> <td headers="stat_1_2" class="gt_row gt_center">1 (50%)</td></tr>
#> </tbody>
#>
#> <tfoot class="gt_footnotes">
#> <tr>
#> <td class="gt_footnote" colspan="3"><span class="gt_footnote_marks" style="white-space:nowrap;font-style:italic;font-weight:normal;line-height:0;"><sup>1</sup></span> <span class='gt_from_md'>n (%)</span></td>
#> </tr>
#> </tfoot>
#> </table>
#> </div>
#>
# }