PARBx & BPI • forager

PARBx

PARB $x$ , or Percentage of Accounts Receivable Beyond $x$ Days, is exactly what it sounds like: monitoring the percentage of your AR balances as they age, in what are commonly referred to as aging “buckets” or “bins.” This idea, in and of itself, is not revolutionary, other than his suggestion to use PARB $x$ to resolve Days in AR’s inability to highlight the overall behavior of Accounts Receivable. The innovation comes in the form of using the PARB $x$ data to create an index that tracks a payer’s performance month-to-month and annually:

PARB $x$ data can then be used to calculate a BPI, or Billing Performance Index. BPI is a key billing performance characteristic because it’s an indicator of claims that are never paid. Obviously, the lower the index, the better the billing performance. But this statistic is meaningful only when considered in the context of the relative performance of other payers. Lirov (2009)

PARBx resolves the sensitivity issues of the DAR metric. It offers a simple billing process metric that’s not dependent on the charge. Its graphic representation has a skewed bell shape. Its steepness represents billing process quality; a steep curve and thin tail mean a healthy billing process, while a flat bell and fat tail also mean billing problems.

Billing Performance Index (BPI)

Lirov’s Billing Performance Index was inspired by a Wall Street benchmarking technique called a payment performance index. He emphasizes the advantage of a “context-driven, rule-based approach to relative benchmarking”:

The advantage of rule-driven indexing is that participation is dynamically determined at a point in time, reflecting the dynamic nature of the entire market. Today’s top 10 list of index performers may not include the same names next week…A financial instrument’s specific performance is recomputed every time the index itself is computed, reflecting the dynamic nature of performance relative to the market itself. Lirov (2009)

Applying this indexing method to payers allows providers to track the ease/difficulty of the reimbursement process with each payer. Inclusion in the monthly index indicates that the percentage of AR older than 120 days belonging to a payer ranks among the lowest in a provider’s payer mix.

This results in a provider being able to focus his or her AR management resources on more problematic payers. Lirov does suggest several criteria that should be considered before a payer is elligible for inclusion such as a minimum threshold of claims submitted and total gross charges processed.

Monthly BPI Ranking

For this example, I’ve put the mock data provided by Dr. Lirov into a data frame. The data ranks (or indexes) the payers with the top 10 lowest PARBx percentages by the most recent month’s (December) figures, including November’s figures as well. December’s rankings appear alongside a Rank Change column indicating the number of places each payer rose or fell from November to December. Using {reactable} and {reactablefmtr} I can create an interactive table of the data:

parbx_rank <- dplyr::tibble(
  payer = c(
    "Medicare Illinois",
    "BCBS Illinois",
    "Cigna",
    "Horizon BCBS NJ",
    "Aetna",
    "UnitedHealthcare",
    "Medicare NJ",
    "GEICO",
    "BCBS Pennsylvania",
    "BCBS Georgia"
  ),
  parbx_nov = c(5.8, 7.9, 15.7, 20.7, 20, 15, 19.4, 36.2, 30.5, 39.9) / 100,
  parbx_dec = c(6.8, 8.1, 10.7, 13.9, 14.8, 21.2, 18.8, 35.2, 43.4, 43.3) / 100
) |> 
  dplyr::mutate(
    rank_nov = dplyr::min_rank(parbx_nov),
    rank_dec = dplyr::min_rank(parbx_dec),
    rank_change = rank_nov - rank_dec) |> 
  dplyr::arrange(rank_dec)

parbx_rank

#> # A tibble: 10 × 6
#>    payer             parbx_nov parbx_dec rank_nov rank_dec rank_change
#>    <chr>                 <dbl>     <dbl>    <int>    <int>       <int>
#>  1 Medicare Illinois     0.058     0.068        1        1           0
#>  2 BCBS Illinois         0.079     0.081        2        2           0
#>  3 Cigna                 0.157     0.107        4        3           1
#>  4 Horizon BCBS NJ       0.207     0.139        7        4           3
#>  5 Aetna                 0.2       0.148        6        5           1
#>  6 Medicare NJ           0.194     0.188        5        6          -1
#>  7 UnitedHealthcare      0.15      0.212        3        7          -4
#>  8 GEICO                 0.362     0.352        9        8           1
#>  9 BCBS Georgia          0.399     0.433       10        9           1
#> 10 BCBS Pennsylvania     0.305     0.434        8       10          -2

parbx_rank |>
  arrange(rank_dec) |> 
  mutate(dir = case_when(
    rank_change == 0 ~ "code-commit",
    rank_change > 0 ~ "arrow-up",
    rank_change < 0 ~ "arrow-down"
  )
) |> 
  gt(rowname_col = "payer") |>
  cols_add(change_abs = abs(rank_change)) |>
  fmt_icon(
    columns = dir,
    fill_color = c("arrow-up" = "#15607A", "arrow-down" = "#FA8C00", "code-commit" = "grey90")) |> 
  fmt_percent(columns = starts_with("parbx_"),
              drop_trailing_zeros = TRUE) |>
  fmt_integer(columns = ends_with("_change"), force_sign = TRUE) |>
  cols_hide(columns = c(rank_change)) |> 
  cols_move_to_start(columns = c(dir, change_abs, rank_nov, parbx_nov, rank_dec, parbx_dec)) |>
  cols_align(align = "center", columns = c(dir, rank_change, rank_nov, parbx_nov, rank_dec, parbx_dec)) |> 
  # cols_merge(columns = c(change_abs, dir), pattern = "{1} {2}") |> 
  cols_label(
    change_abs = "Change",
    rank_nov = "Rank",
    parbx_nov = md("PARB<b><i><sub>x</sub></i></b>"),
    rank_dec = "Rank",
    parbx_dec = md("PARB<b><i><sub>x</sub></i></b>"),
    dir = ""
  ) |>
  data_color(columns = starts_with("parbx_"),
             palette = c("#15607A", "#FFFFFF", "#FA8C00")) |>
  opt_table_font(font = gt::google_font(name = "Atkinson Hyperlegible")) |> 
  tab_header(title = md("**Billing Performance Index**"),
             subtitle = "Top 10 Payers with the Lowest Percentage of AR Beyond 120 Days") |> 
  tab_spanner(label = md("**November**"), columns = c(rank_nov, parbx_nov)) |> 
  tab_spanner(label = md("**December**"), columns = c(rank_dec, parbx_dec)) |> 
  opt_stylize(color = "cyan", add_row_striping = FALSE) |>
  tab_options(
    quarto.disable_processing = TRUE,
    table.font.size = gt::px(18),
    table.width = gt::pct(100),
    heading.align = "left",
    heading.title.font.size = gt::px(24),
    heading.subtitle.font.size = gt::px(21))

	Change	November		December
Billing Performance Index
Top 10 Payers with the Lowest Percentage of AR Beyond 120 Days
	Change	Rank	PARB_x	Rank	PARB_x
Medicare Illinois	0	1	5.8%	1	6.8%
BCBS Illinois	0	2	7.9%	2	8.1%
Cigna	1	4	15.7%	3	10.7%
Horizon BCBS NJ	3	7	20.7%	4	13.9%
Aetna	1	6	20%	5	14.8%
Medicare NJ	1	5	19.4%	6	18.8%
UnitedHealthcare	4	3	15%	7	21.2%
GEICO	1	9	36.2%	8	35.2%
BCBS Georgia	1	10	39.9%	9	43.3%
BCBS Pennsylvania	2	8	30.5%	10	43.4%

parbx_rank |> 
  select(payer, parbx_nov, parbx_dec) |> 
  mutate(
    parbx_nov = parbx_nov * wakefield::probs(n()),
    parbx_dec = parbx_dec * wakefield::probs(n()),
    rank_nov = dplyr::min_rank(parbx_nov),
    rank_dec = dplyr::min_rank(parbx_dec),
    rank_change = rank_nov - rank_dec
  ) |>
  arrange(rank_dec) |> 
  gt(rowname_col = "payer") |>
  fmt_percent(columns = starts_with("parbx_"), drop_trailing_zeros = TRUE) |>
  fmt_integer(columns = ends_with("_change"), force_sign = TRUE) |>
  cols_move_to_start(columns = c(rank_change, rank_nov, parbx_nov, rank_dec, parbx_dec)) |>
  cols_align(align = "center", columns = c(rank_change, rank_nov, parbx_nov, rank_dec, parbx_dec)) |> 
  cols_label(
    rank_change = "Change",
    rank_nov = "Rank",
    parbx_nov = md("<sub>wt</sub>PARB<b><i><sub>x</sub></i></b>"),
    rank_dec = "Rank",
    parbx_dec = md("<sub>wt</sub>PARB<b><i><sub>x</sub></i></b>")
  ) |>
  data_color(columns = starts_with("parbx_"),
             palette = c("#15607A", "#FFFFFF", "#FA8C00")) |> 
  opt_table_font(font = gt::google_font(name = "Atkinson Hyperlegible")) |> 
  tab_header(title = md("**Weighted Billing Performance Index**"),
             subtitle = "Top 10 Payers with the Lowest Percentage of AR Beyond 120 Days") |> 
  tab_spanner(label = md("**November**"), columns = c(rank_nov, parbx_nov)) |> 
  tab_spanner(label = md("**December**"), columns = c(rank_dec, parbx_dec)) |> 
  opt_stylize(color = "cyan", add_row_striping = FALSE) |>
  tab_options(
    quarto.disable_processing = TRUE,
    table.font.size = gt::px(18),
    table.width = gt::pct(100),
    heading.align = "left",
    heading.title.font.size = gt::px(24),
    heading.subtitle.font.size = gt::px(21)
              )

	Change	November		December
Weighted Billing Performance Index
Top 10 Payers with the Lowest Percentage of AR Beyond 120 Days
	Change	Rank	_wtPARB_x	Rank	_wtPARB_x
Horizon BCBS NJ	+7	8	3.79%	1	0.06%
Medicare Illinois	−1	1	0.3%	2	0.22%
Aetna	−1	2	0.69%	3	0.34%
BCBS Illinois	+1	5	1.28%	4	0.56%
GEICO	+2	7	2.15%	5	1.23%
Cigna	−3	3	1.01%	6	1.28%
BCBS Pennsylvania	+3	10	5.76%	7	2.32%
UnitedHealthcare	−4	4	1.28%	8	3.97%
Medicare NJ	−3	6	1.29%	9	5.68%
BCBS Georgia	−1	9	4.13%	10	7.52%

Annual BPI Summary

The final destination for all of this data is the annual summary of the monthly Billing Performance Index.

The Annual BPI is simply a list of the payers who participated in the Monthly BPI, ranked by the number of times that they made the top 10 that year. Also included are each payer’s mean, minimum, and maximum BPI for the year. Lirov sums up the importance of the annual summary:

A low percentage of accounts receivable beyond 120 days is critical to being included in the billing index. However, the frequency of inclusion in the index is a more robust performance metric, because it measures billing performance consistency over a longer time period.

tibble(
  rank = 1:15,
  n_months = c(
    12, 11, 11, 10, 10,
    7, 7, 7, 5, 4, 3,
    3, 3, 2, 2
  ),
  payer = c(
    "BCBS Illinois", "Cigna",
    "Medicare New Jersey",
    "Aetna", "UnitedHealthcare",
    "Medicare Illinois", "Horizon BCBS New Jersey",
    "BCBS Pennsylvania", "BCBS Georgia",
    "Anthem BCBS Colorado",
    "BCBS Michigan", "BCBS Texas", "GEICO",
    "Anthem BCBS Colorado", "Humana"
  ),
  min = c(
    7.1, 8.9, 7.5, 8.8, 11.3,
    5.8, 13.9, 12.4, 22.9, 12.4,
    3.2, 10.3, 33.4, 6.8, 7.9
  ) / 100,
  mean = c(
    10.9, 13.4, 15.7, 16.6, 17.2,
    14, 18, 23.5, 34.1, 19.1, 6.8,
    15.2, 34.9, 9.6, 9.9
  ) / 100,
  max = c(
    16, 24.1, 20.5, 22.1, 23.2,
    30.4, 24.3, 43.4, 43.3, 34.1,
    13.6, 20, 36.2, 12.3, 11.8
  ) / 100
) |> 
  gt(rowname_col = "rank", groupname_col = "payer", row_group_as_column = TRUE) |>
  fmt_percent(columns = c(min, mean, max), drop_trailing_zeros = TRUE) |>
  cols_align(align = "center", columns = c(rank, n_months, min, mean, max)) |> 
  cols_label(
    rank = "Rank",
    n_months = "Months",
    min = "Minimum",
    mean = "Average",
    max = "Maximum"
  ) |>
  data_color(columns = c(min, mean, max),
             palette = c("#15607A", "#FFFFFF", "#FA8C00")) |> 
  opt_table_font(font = gt::google_font(name = "Atkinson Hyperlegible")) |> 
  tab_header(title = md("**Annual Billing Performance Index**"),
             subtitle = "Top 15 Payers Ranked by Months Included on BPI.") |> 
  tab_spanner(label = md("**Percentage of AR Beyond 120 Days**"), columns = c(min, mean, max)) |> 
  opt_stylize(color = "cyan", add_row_striping = FALSE) |>
  tab_options(
    quarto.disable_processing = TRUE,
    table.font.size = gt::px(18),
    table.width = gt::pct(100),
    heading.align = "left",
    heading.title.font.size = gt::px(24),
    heading.subtitle.font.size = gt::px(21))

		Months	Percentage of AR Beyond 120 Days
Annual Billing Performance Index
Top 15 Payers Ranked by Months Included on BPI.
		Months	Minimum	Average	Maximum
BCBS Illinois	1	12	7.1%	10.9%	16%
Cigna	2	11	8.9%	13.4%	24.1%
Medicare New Jersey	3	11	7.5%	15.7%	20.5%
Aetna	4	10	8.8%	16.6%	22.1%
UnitedHealthcare	5	10	11.3%	17.2%	23.2%
Medicare Illinois	6	7	5.8%	14%	30.4%
Horizon BCBS New Jersey	7	7	13.9%	18%	24.3%
BCBS Pennsylvania	8	7	12.4%	23.5%	43.4%
BCBS Georgia	9	5	22.9%	34.1%	43.3%
Anthem BCBS Colorado	10	4	12.4%	19.1%	34.1%
Anthem BCBS Colorado	14	2	6.8%	9.6%	12.3%
BCBS Michigan	11	3	3.2%	6.8%	13.6%
BCBS Texas	12	3	10.3%	15.2%	20%
GEICO	13	3	33.4%	34.9%	36.2%
Humana	15	2	7.9%	9.9%	11.8%

Mock PARBx

mock_parbx()

#> # A tibble: 1,620 × 5
#>    date       month    payer    aging_bin aging_prop
#>    <date>     <ord>    <chr>    <ord>          <dbl>
#>  1 2024-01-01 January  Medicare 0-30          0.31  
#>  2 2024-01-01 January  Medicare 31-60         0.37  
#>  3 2024-01-01 January  Medicare 61-90         0.17  
#>  4 2024-01-01 January  Medicare 91-120        0.0097
#>  5 2024-01-01 January  Medicare 121+          0.15  
#>  6 2024-02-01 February Medicare 0-30          0.22  
#>  7 2024-02-01 February Medicare 31-60         0.24  
#>  8 2024-02-01 February Medicare 61-90         0.077 
#>  9 2024-02-01 February Medicare 91-120        0.32  
#> 10 2024-02-01 February Medicare 121+          0.15  
#> # ℹ 1,610 more rows

mock_parbx() |>
  mutate(aging_prop = fuimus::roundup(aging_prop * 100)) |> 
  pivot_wider(names_from = "aging_bin", 
              values_from = "aging_prop") |> 
  arrange(month) |> 
  select(-date) |> 
  gt(rowname_col = "payer", 
     groupname_col = "month", 
     row_group_as_column = TRUE) |> 
  fmt_number(decimals = 1) |> 
  opt_table_font(font = google_font(name = "Atkinson Hyperlegible")) |> 
  tab_options(
    column_labels.font.weight = "bold",
    column_labels.font.size = px(16),
    column_labels.border.bottom.width = px(3),
    quarto.disable_processing = TRUE,
    table.font.size = px(18),
    table.width = pct(75),
    heading.align = "left",
    heading.title.font.size = px(24),
    heading.subtitle.font.size = px(21),
    # table_body.hlines.style = "none",
    column_labels.border.top.color = "darkgreen",
    column_labels.border.bottom.color = "darkgreen",
    table_body.border.bottom.color = "darkgreen",
    stub.border.style = "none",
    stub.background.color = "darkgreen",
    # stub.font.weight = "bold",
    row_group.font.weight = "bold"
    )

		0-30	31-60	61-90	91-120	121+
January	Medicare	35.7	14.4	5.6	20.8	23.5
	Medicaid	9.0	36.1	22.1	3.5	29.3
	Kaiser Permanente	23.5	21.1	17.4	31.2	6.9
	Elevance (Anthem)	21.9	16.8	25.4	16.7	19.2
	HCSC	30.6	55.4	2.1	0.9	10.9
	UnitedHealth	12.1	20.8	29.2	11.4	26.4
	Centene	19.8	26.2	19.1	16.9	18.1
	CVS Aetna	3.1	14.3	21.4	38.0	23.1
	Humana	29.5	2.7	29.5	26.6	11.7
	Cigna	7.4	14.9	23.5	28.7	25.5
	Molina	2.6	25.1	37.4	10.0	24.9
	GuideWell	39.6	0.6	26.8	12.2	20.8
	Highmark	32.1	25.5	6.0	19.7	16.7
	BCBS MI	2.0	12.7	22.7	28.6	34.0
	Univ. Healthcare	10.4	18.1	7.2	55.8	8.5
	BCBS WY	3.7	35.1	26.4	16.1	18.7
	Bright	12.4	1.3	23.5	35.5	27.3
	Oscar	35.2	12.2	18.4	8.5	25.7
	Wellcare	18.0	27.0	24.6	12.6	17.9
	Omaha	21.6	26.0	18.7	29.4	4.4
	Athene	66.7	16.5	5.0	0.9	10.9
	American	23.1	34.8	1.6	6.6	33.9
	Mass Mutual	18.6	8.2	18.7	48.6	5.9
	New York Life	0.2	5.7	36.9	28.1	29.1
	Lincoln Nat'l	22.0	22.1	16.9	23.9	15.0
	Equitable	9.2	10.8	2.0	37.3	40.6
	Allianz	20.6	20.3	30.6	19.2	9.3
February	Medicare	28.6	16.8	16.1	33.2	5.4
	Medicaid	29.1	12.1	19.2	16.1	23.4
	Kaiser Permanente	23.1	8.1	23.8	31.7	13.3
	Elevance (Anthem)	11.7	17.8	33.2	35.7	1.6
	HCSC	0.5	25.7	19.8	17.3	36.7
	UnitedHealth	24.9	34.5	3.9	14.5	22.2
	Centene	6.1	33.9	24.9	8.8	26.2
	CVS Aetna	13.5	32.7	23.1	7.5	23.1
	Humana	35.2	23.9	9.9	8.5	22.5
	Cigna	35.0	19.2	15.0	24.2	6.6
	Molina	8.8	12.5	33.7	32.9	12.1
	GuideWell	17.7	10.5	8.7	49.6	13.5
	Highmark	10.7	19.6	25.0	25.5	19.2
	BCBS MI	28.5	22.3	14.9	18.8	15.5
	Univ. Healthcare	24.1	27.1	29.6	9.6	9.7
	BCBS WY	29.8	4.2	13.4	28.2	24.4
	Bright	4.8	42.8	0.2	44.9	7.3
	Oscar	9.3	4.9	1.3	46.8	37.7
	Wellcare	34.7	4.0	15.7	11.9	33.6
	Omaha	33.5	23.6	1.2	9.9	31.7
	Athene	8.6	37.6	11.4	10.7	31.7
	American	32.5	8.5	12.9	25.8	20.3
	Mass Mutual	30.3	1.3	7.4	29.7	31.3
	New York Life	6.7	14.9	35.5	26.7	16.2
	Lincoln Nat'l	38.8	12.5	15.0	28.1	5.5
	Equitable	4.2	4.0	30.1	30.0	31.7
	Allianz	23.8	6.2	18.3	26.4	25.3
March	Medicare	24.8	24.4	25.9	7.6	17.3
	Medicaid	5.6	31.0	24.3	19.7	19.4
	Kaiser Permanente	35.8	2.9	26.2	18.5	16.7
	Elevance (Anthem)	41.7	36.3	10.8	6.0	5.2
	HCSC	5.0	35.0	13.1	42.8	4.1
	UnitedHealth	2.7	21.2	19.2	16.2	40.6
	Centene	37.0	5.8	1.1	11.8	44.3
	CVS Aetna	27.5	11.5	17.7	13.4	29.9
	Humana	26.1	26.9	30.6	0.1	16.3
	Cigna	28.0	34.4	1.2	31.9	4.5
	Molina	23.1	36.7	2.0	21.6	16.4
	GuideWell	6.0	11.3	2.3	55.8	24.5
	Highmark	29.2	25.5	15.6	9.0	20.6
	BCBS MI	13.5	23.0	21.8	10.5	31.2
	Univ. Healthcare	38.0	9.9	10.9	13.3	27.9
	BCBS WY	36.3	13.0	26.9	0.4	23.4
	Bright	11.4	6.8	30.1	36.8	14.9
	Oscar	16.0	15.2	28.8	9.2	30.7
	Wellcare	17.2	32.1	22.5	19.7	8.5
	Omaha	10.6	26.6	13.5	26.7	22.6
	Athene	8.6	34.5	12.7	36.4	7.7
	American	23.1	11.0	31.8	9.8	24.3
	Mass Mutual	46.0	0.7	12.8	5.5	35.0
	New York Life	33.0	10.5	26.8	10.8	18.8
	Lincoln Nat'l	19.2	22.5	15.5	22.7	20.1
	Equitable	33.1	19.2	15.2	14.7	17.7
	Allianz	23.0	18.2	30.5	15.9	12.3
April	Medicare	8.3	24.1	24.5	22.1	20.9
	Medicaid	41.4	0.2	24.4	26.6	7.4
	Kaiser Permanente	23.9	6.0	27.0	24.7	18.4
	Elevance (Anthem)	11.6	21.6	26.3	19.9	20.6
	HCSC	19.2	19.3	10.5	29.9	21.1
	UnitedHealth	25.4	22.4	9.4	25.3	17.5
	Centene	6.0	12.5	28.2	24.0	29.3
	CVS Aetna	4.8	27.9	23.2	27.7	16.4
	Humana	19.6	24.6	24.0	20.4	11.4
	Cigna	21.3	9.8	14.3	13.9	40.6
	Molina	25.2	4.2	15.4	27.0	28.2
	GuideWell	30.4	30.5	19.0	0.1	20.1
	Highmark	42.3	15.7	22.1	19.7	0.3
	BCBS MI	0.9	28.9	31.9	21.8	16.5
	Univ. Healthcare	12.9	26.4	17.4	33.6	9.8
	BCBS WY	28.7	32.0	15.4	12.8	11.1
	Bright	23.6	18.5	16.5	27.1	14.3
	Oscar	21.6	21.2	22.5	20.4	14.4
	Wellcare	32.2	8.2	26.5	3.2	29.9
	Omaha	3.8	19.0	26.3	9.3	41.6
	Athene	4.8	10.4	29.3	1.4	54.1
	American	0.9	17.7	21.4	30.4	29.5
	Mass Mutual	30.6	30.7	11.5	2.5	24.8
	New York Life	3.1	7.0	39.7	20.5	29.7
	Lincoln Nat'l	22.9	22.8	8.7	18.4	27.2
	Equitable	16.9	17.6	35.7	22.9	6.9
	Allianz	30.8	24.8	33.8	0.1	10.6
May	Medicare	29.3	10.4	29.1	5.1	26.0
	Medicaid	21.8	4.4	11.0	55.3	7.5
	Kaiser Permanente	22.4	9.8	10.1	3.3	54.3
	Elevance (Anthem)	26.5	23.5	8.3	14.5	27.1
	HCSC	19.6	26.5	35.7	12.7	5.5
	UnitedHealth	13.0	23.2	29.6	12.1	22.2
	Centene	25.3	3.9	23.0	23.9	23.9
	CVS Aetna	42.6	1.2	16.5	31.6	8.1
	Humana	28.9	14.0	27.8	10.4	18.9
	Cigna	14.6	32.0	43.2	8.5	1.7
	Molina	7.7	18.4	35.0	25.6	13.3
	GuideWell	3.0	24.3	4.7	36.8	31.2
	Highmark	19.1	26.2	13.3	30.6	10.8
	BCBS MI	25.1	0.5	18.3	38.3	17.7
	Univ. Healthcare	4.1	40.4	41.1	12.3	2.1
	BCBS WY	22.7	15.8	28.2	15.3	18.0
	Bright	15.4	26.2	18.8	13.2	26.4
	Oscar	11.3	49.8	16.6	2.8	19.5
	Wellcare	6.3	14.8	10.4	36.4	32.1
	Omaha	31.4	21.8	11.8	25.0	10.1
	Athene	18.8	5.6	24.6	29.8	21.2
	American	4.3	25.4	21.5	8.2	40.6
	Mass Mutual	13.8	30.4	20.8	11.2	23.8
	New York Life	28.3	25.8	8.9	2.2	34.8
	Lincoln Nat'l	14.1	2.5	7.8	31.3	44.4
	Equitable	30.2	31.3	6.6	14.6	17.3
	Allianz	22.2	17.0	9.7	22.9	28.2
June	Medicare	9.5	36.5	6.3	15.7	32.0
	Medicaid	30.2	37.7	7.6	13.1	11.5
	Kaiser Permanente	13.1	16.1	35.1	20.2	15.5
	Elevance (Anthem)	2.5	3.9	17.0	22.5	54.2
	HCSC	11.8	31.0	3.9	39.3	13.9
	UnitedHealth	15.2	12.8	21.1	27.1	23.9
	Centene	10.3	15.9	19.0	26.7	28.1
	CVS Aetna	18.4	20.2	23.3	21.9	16.1
	Humana	4.5	11.4	37.1	26.4	20.5
	Cigna	30.3	13.7	30.7	15.0	10.3
	Molina	53.3	21.9	2.3	0.4	22.0
	GuideWell	31.2	2.7	20.8	4.4	40.8
	Highmark	0.9	43.6	20.4	2.2	32.8
	BCBS MI	16.3	27.6	6.4	12.2	37.5
	Univ. Healthcare	4.4	31.1	14.6	22.7	27.1
	BCBS WY	10.9	9.2	0.1	39.4	40.4
	Bright	12.3	18.1	18.9	24.7	26.0
	Oscar	22.3	25.8	12.1	16.9	23.0
	Wellcare	17.6	28.3	1.3	39.9	12.9
	Omaha	1.2	11.0	30.9	40.4	16.4
	Athene	27.6	15.9	10.2	20.8	25.5
	American	15.4	21.8	31.1	15.6	16.2
	Mass Mutual	25.1	5.6	7.0	39.9	22.4
	New York Life	31.2	23.6	4.2	6.4	34.6
	Lincoln Nat'l	31.1	16.2	17.2	12.5	22.9
	Equitable	29.0	33.9	0.8	7.3	29.0
	Allianz	28.5	6.8	44.1	13.1	7.5
July	Medicare	26.6	8.0	3.0	31.8	30.6
	Medicaid	31.1	1.4	25.7	22.9	18.8
	Kaiser Permanente	33.5	28.6	11.4	10.0	16.6
	Elevance (Anthem)	24.2	30.0	14.2	23.6	8.0
	HCSC	4.1	25.1	32.1	22.7	16.1
	UnitedHealth	1.6	40.9	8.2	40.9	8.4
	Centene	30.4	11.4	28.1	2.2	27.9
	CVS Aetna	2.3	23.9	13.6	35.1	25.1
	Humana	39.4	25.6	23.9	4.5	6.7
	Cigna	8.4	21.8	9.3	44.2	16.3
	Molina	25.5	18.8	0.3	37.6	17.9
	GuideWell	5.1	24.4	8.8	29.4	32.3
	Highmark	26.4	20.3	37.5	10.6	5.2
	BCBS MI	36.3	13.4	16.6	9.9	23.9
	Univ. Healthcare	14.4	30.9	17.7	8.4	28.6
	BCBS WY	2.7	25.4	1.8	33.0	37.1
	Bright	1.4	20.0	31.0	19.9	27.7
	Oscar	22.9	4.8	35.6	1.5	35.2
	Wellcare	3.8	21.1	21.7	20.4	33.0
	Omaha	17.9	19.8	24.9	16.1	21.3
	Athene	16.0	34.2	19.5	8.5	21.8
	American	31.6	39.3	19.5	8.6	1.1
	Mass Mutual	9.7	18.8	13.0	30.6	27.9
	New York Life	12.3	17.7	9.0	5.8	55.2
	Lincoln Nat'l	23.5	15.3	22.3	20.3	18.6
	Equitable	23.3	6.0	30.3	14.6	25.8
	Allianz	2.4	31.8	17.4	27.6	20.8
August	Medicare	34.2	18.5	14.8	2.7	29.8
	Medicaid	2.3	26.9	16.7	19.2	35.0
	Kaiser Permanente	47.5	5.5	19.9	8.0	19.0
	Elevance (Anthem)	23.1	23.3	13.4	26.5	13.7
	HCSC	22.4	17.8	22.7	18.9	18.2
	UnitedHealth	16.1	24.5	20.5	13.8	25.0
	Centene	13.0	24.1	54.1	7.6	1.2
	CVS Aetna	28.1	13.7	30.1	22.9	5.2
	Humana	55.2	21.7	12.2	6.0	4.9
	Cigna	18.4	8.8	11.1	40.5	21.2
	Molina	2.2	32.0	3.4	39.3	23.0
	GuideWell	21.7	24.1	4.4	34.6	15.2
	Highmark	21.0	24.9	26.5	4.1	23.6
	BCBS MI	8.5	26.7	18.7	5.8	40.4
	Univ. Healthcare	19.5	12.3	10.9	38.5	18.7
	BCBS WY	1.5	24.1	21.4	32.2	20.9
	Bright	27.2	5.7	17.0	12.5	37.6
	Oscar	4.0	32.9	31.5	28.0	3.6
	Wellcare	31.2	20.1	18.9	9.2	20.6
	Omaha	8.9	23.6	16.2	28.4	23.0
	Athene	18.9	15.4	30.5	12.2	23.0
	American	9.2	33.3	11.0	32.1	14.4
	Mass Mutual	8.0	35.3	28.4	17.0	11.4
	New York Life	13.7	30.4	20.4	20.3	15.2
	Lincoln Nat'l	8.5	8.4	23.2	28.7	31.1
	Equitable	0.4	40.1	14.5	27.3	17.7
	Allianz	7.4	23.9	6.2	25.1	37.4
September	Medicare	4.1	17.7	29.9	11.3	36.9
	Medicaid	31.5	4.1	22.7	28.1	13.6
	Kaiser Permanente	4.6	24.8	24.0	23.0	23.6
	Elevance (Anthem)	3.6	32.5	30.3	19.4	14.2
	HCSC	19.0	32.7	12.1	29.2	7.0
	UnitedHealth	9.3	22.7	10.7	20.2	37.1
	Centene	25.0	21.3	14.1	10.6	28.9
	CVS Aetna	1.4	26.6	14.6	26.7	30.8
	Humana	38.2	16.3	26.4	1.8	17.3
	Cigna	5.5	31.5	4.2	28.3	30.5
	Molina	17.3	20.8	17.5	12.7	31.7
	GuideWell	10.9	14.0	21.5	29.8	23.8
	Highmark	28.2	15.9	0.1	24.0	31.9
	BCBS MI	29.8	4.9	10.7	42.3	12.3
	Univ. Healthcare	26.2	2.3	21.3	26.2	24.0
	BCBS WY	17.0	6.1	39.6	2.6	34.7
	Bright	29.3	15.1	10.4	21.7	23.5
	Oscar	20.4	29.1	9.3	18.0	23.2
	Wellcare	25.5	6.9	32.4	8.5	26.7
	Omaha	16.3	17.6	22.7	21.2	22.1
	Athene	53.5	6.9	18.0	6.7	14.8
	American	21.9	5.6	30.8	19.5	22.1
	Mass Mutual	2.8	18.5	8.4	53.5	16.8
	New York Life	12.6	18.4	25.0	27.7	16.4
	Lincoln Nat'l	30.0	26.9	2.4	7.2	33.6
	Equitable	30.5	25.2	9.3	30.0	4.9
	Allianz	42.5	7.7	12.3	6.3	31.1
October	Medicare	1.7	48.5	8.0	7.6	34.3
	Medicaid	29.5	15.9	11.9	21.1	21.6
	Kaiser Permanente	8.3	32.9	15.0	18.5	25.2
	Elevance (Anthem)	15.2	15.3	44.1	6.9	18.5
	HCSC	25.6	22.9	7.2	30.5	13.8
	UnitedHealth	20.3	25.6	15.1	17.8	21.3
	Centene	27.6	24.7	10.4	3.3	34.0
	CVS Aetna	18.8	17.1	26.0	10.8	27.2
	Humana	12.3	22.6	22.8	28.1	14.1
	Cigna	28.8	28.7	8.0	18.2	16.4
	Molina	22.4	21.5	25.2	22.1	8.7
	GuideWell	34.9	3.2	9.4	46.1	6.4
	Highmark	21.6	9.1	18.1	30.9	20.3
	BCBS MI	10.3	4.9	2.7	53.1	29.0
	Univ. Healthcare	17.9	17.1	25.1	12.3	27.5
	BCBS WY	38.1	22.7	0.3	36.0	3.0
	Bright	19.5	11.5	29.0	32.8	7.3
	Oscar	26.3	1.2	6.5	29.5	36.5
	Wellcare	15.8	21.7	28.6	26.8	7.1
	Omaha	42.5	21.3	0.4	22.8	13.0
	Athene	15.3	25.9	5.6	3.3	49.8
	American	22.1	24.0	21.2	29.0	3.8
	Mass Mutual	24.8	10.4	26.4	30.0	8.4
	New York Life	5.7	27.5	37.2	9.1	20.4
	Lincoln Nat'l	41.3	5.9	33.9	6.8	12.0
	Equitable	28.6	14.2	25.4	17.8	14.1
	Allianz	24.1	53.5	1.9	4.2	16.3
November	Medicare	17.4	34.6	28.8	9.2	10.0
	Medicaid	24.2	27.1	34.0	9.9	4.7
	Kaiser Permanente	18.9	34.0	32.9	1.6	12.7
	Elevance (Anthem)	9.4	13.1	18.7	15.8	43.0
	HCSC	3.5	27.2	16.2	26.9	26.1
	UnitedHealth	24.6	36.0	0.3	2.7	36.3
	Centene	13.6	10.1	12.9	16.1	47.3
	CVS Aetna	7.2	12.2	20.4	36.4	23.8
	Humana	35.6	8.9	30.5	1.3	23.6
	Cigna	24.4	11.4	23.9	6.5	33.9
	Molina	11.6	25.7	32.6	28.6	1.5
	GuideWell	8.0	10.8	43.4	18.0	19.9
	Highmark	0.6	27.4	28.1	14.9	29.0
	BCBS MI	28.4	27.7	34.0	0.9	8.9
	Univ. Healthcare	10.5	32.7	14.3	31.6	10.8
	BCBS WY	4.7	34.7	41.6	18.6	0.3
	Bright	18.7	15.5	30.6	30.6	4.5
	Oscar	15.5	13.8	52.0	13.8	5.0
	Wellcare	50.6	21.1	7.4	13.5	7.5
	Omaha	11.6	24.7	27.5	35.5	0.8
	Athene	10.1	26.7	25.7	17.4	20.0
	American	29.1	24.1	37.0	9.2	0.7
	Mass Mutual	17.7	16.4	15.0	30.2	20.7
	New York Life	27.3	26.8	6.3	34.3	5.3
	Lincoln Nat'l	27.1	8.6	30.9	15.7	17.8
	Equitable	8.3	11.7	27.7	27.2	25.1
	Allianz	25.6	23.9	7.5	30.9	12.1
December	Medicare	32.9	0.1	29.7	17.9	19.4
	Medicaid	32.8	18.7	15.0	15.8	17.7
	Kaiser Permanente	12.9	24.1	32.7	29.5	0.8
	Elevance (Anthem)	15.6	39.1	7.1	23.3	14.9
	HCSC	1.8	49.1	19.1	12.4	17.6
	UnitedHealth	15.9	24.5	29.7	27.3	2.6
	Centene	7.7	40.5	30.6	2.0	19.1
	CVS Aetna	30.6	27.7	15.9	15.2	10.6
	Humana	17.9	10.9	25.2	41.3	4.8
	Cigna	33.4	21.3	4.4	17.9	23.1
	Molina	24.7	32.5	2.9	10.1	29.9
	GuideWell	19.6	12.0	19.2	15.5	33.8
	Highmark	24.2	1.2	30.4	31.2	12.9
	BCBS MI	3.9	37.0	26.0	18.2	14.9
	Univ. Healthcare	5.1	7.9	11.6	38.5	36.8
	BCBS WY	9.2	17.7	22.8	16.5	33.8
	Bright	41.1	7.6	7.9	25.3	18.1
	Oscar	24.8	3.3	26.3	17.3	28.4
	Wellcare	26.3	16.7	22.8	8.6	25.6
	Omaha	20.9	17.7	21.4	21.1	18.8
	Athene	54.9	16.9	10.4	16.1	1.7
	American	16.6	7.6	32.7	28.9	14.2
	Mass Mutual	25.7	31.5	11.8	9.5	21.5
	New York Life	30.0	7.3	21.2	8.0	33.4
	Lincoln Nat'l	24.2	18.1	4.7	31.1	21.8
	Equitable	17.3	26.2	2.0	31.1	23.4
	Allianz	15.4	17.9	31.1	22.9	12.7

ex_prop <- mock_parbx() |> 
  pivot_wider(names_from = "aging_bin", 
              values_from = "aging_prop") |> 
  select(month, payer, `121+`) |> 
  pivot_wider(names_from = month, values_from = `121+`) |> 
  rlang::set_names(c("payer", month.abb))

ex_prop_payer <- mock_parbx() |> 
  pivot_wider(names_from = "aging_bin", 
              values_from = "aging_prop") |> 
  select(month, payer, `121+`) |> 
  pivot_wider(names_from = payer, values_from = `121+`)

ex_prop |> 
  gt(rowname_col = "payer") |> 
  fmt_percent(decimals = 0) |>
  cols_align(align = "center") |> 
  data_color(
    columns = !payer,
    palette = "ggsci::red_material",
    apply_to = "text"
    ) |> 
  opt_table_font(font = google_font(name = "Fira Code")) |> 
  tab_options(
    column_labels.font.weight = "bold",
    quarto.disable_processing = TRUE,
    # table.background.color = "grey50",
    table.font.size = gt::px(18),
    table.width = gt::pct(100),
    heading.align = "left",
    heading.title.font.size = gt::px(24),
    heading.subtitle.font.size = gt::px(21))

	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
Medicare	13%	37%	39%	9%	35%	21%	20%	17%	31%	16%	39%	29%
Medicaid	12%	29%	23%	28%	8%	18%	0%	43%	28%	25%	20%	3%
Kaiser Permanente	26%	16%	18%	1%	36%	11%	5%	3%	27%	22%	16%	28%
Elevance (Anthem)	23%	9%	9%	24%	36%	26%	26%	29%	28%	0%	28%	19%
HCSC	38%	38%	17%	31%	32%	22%	14%	2%	9%	9%	10%	24%
UnitedHealth	26%	22%	29%	26%	7%	9%	45%	16%	7%	18%	9%	6%
Centene	0%	23%	20%	26%	5%	8%	0%	13%	8%	27%	15%	28%
CVS Aetna	15%	36%	38%	20%	20%	27%	26%	24%	24%	25%	29%	20%
Humana	6%	9%	8%	26%	10%	20%	0%	7%	3%	24%	23%	2%
Cigna	1%	2%	27%	16%	26%	3%	16%	41%	15%	15%	26%	14%
Molina	9%	11%	27%	27%	8%	7%	22%	41%	25%	37%	21%	15%
GuideWell	17%	2%	16%	23%	18%	25%	5%	32%	19%	31%	11%	16%
Highmark	13%	37%	34%	23%	18%	27%	17%	24%	17%	38%	1%	25%
BCBS MI	46%	4%	28%	7%	27%	25%	15%	44%	8%	10%	3%	30%
Univ. Healthcare	25%	25%	33%	9%	23%	24%	7%	32%	12%	22%	23%	25%
BCBS WY	30%	30%	9%	16%	25%	35%	0%	32%	6%	7%	26%	24%
Bright	4%	26%	27%	20%	28%	30%	25%	28%	4%	1%	27%	36%
Oscar	1%	32%	19%	30%	12%	1%	36%	12%	11%	12%	18%	2%
Wellcare	25%	21%	4%	41%	23%	29%	8%	7%	25%	12%	8%	17%
Omaha	5%	13%	2%	36%	29%	38%	6%	2%	4%	21%	18%	25%
Athene	22%	36%	8%	7%	4%	30%	28%	15%	9%	28%	5%	29%
American	25%	7%	17%	14%	28%	17%	30%	21%	35%	30%	20%	12%
Mass Mutual	14%	42%	13%	3%	21%	26%	20%	13%	32%	34%	32%	32%
New York Life	36%	33%	14%	2%	14%	24%	22%	25%	28%	17%	18%	12%
Lincoln Nat'l	28%	17%	21%	3%	28%	3%	6%	23%	38%	24%	27%	4%
Equitable	37%	16%	23%	32%	3%	24%	35%	28%	17%	22%	29%	10%
Allianz	26%	28%	12%	2%	32%	13%	6%	34%	4%	38%	31%	2%

ex_prop |> 
  reframe(
    payer,
    Jan = min_rank(Jan),
    Feb = min_rank(Feb),
    Mar = min_rank(Mar),
    Apr = min_rank(Apr),
    May = min_rank(May),
    Jun = min_rank(Jun),
    Jul = min_rank(Jul),
    Aug = min_rank(Aug),
    Sep = min_rank(Sep),
    Oct = min_rank(Oct),
    Nov = min_rank(Nov),
    Dec = min_rank(Dec)) |> 
  gt(rowname_col = "payer") |> 
  opt_table_font(font = google_font(name = "JetBrains Mono")) |> 
  data_color(
    columns = !payer,
    palette = "Greens",
    apply_to = "text",
    reverse = TRUE
    ) |> 
  cols_align(align = "center") |> 
  tab_options(
    column_labels.font.weight = "bold",
    column_labels.font.size = px(16),
    column_labels.border.bottom.width = px(3),
    quarto.disable_processing = TRUE,
    table.font.size = px(18),
    table.width = pct(75),
    heading.align = "left",
    heading.title.font.size = px(24),
    heading.subtitle.font.size = px(21),
    table_body.hlines.style = "none",
    column_labels.border.top.color = "darkgreen",
    column_labels.border.bottom.color = "darkgreen",
    table_body.border.bottom.color = "darkgreen",
    stub.border.style = "none",
    stub.background.color = "darkgreen"
    )

	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
Medicare	10	24	27	9	25	12	17	11	24	9	27	24
Medicaid	8	18	17	22	6	10	1	26	22	18	13	4
Kaiser Permanente	19	9	13	1	27	7	6	3	20	15	9	21
Elevance (Anthem)	15	5	6	17	26	20	21	19	21	1	22	14
HCSC	26	26	11	24	23	13	12	2	9	4	6	16
UnitedHealth	21	13	23	19	4	6	27	10	6	11	5	6
Centene	1	14	15	20	3	5	3	8	7	20	8	22
CVS Aetna	12	23	26	14	12	21	22	14	17	19	23	15
Humana	6	6	4	18	7	11	2	5	1	16	16	1
Cigna	2	1	19	11	17	2	14	24	13	8	19	10
Molina	7	7	20	21	5	4	18	25	19	25	15	11
GuideWell	13	2	10	16	11	17	5	20	16	23	7	12
Highmark	9	25	25	15	10	22	15	15	14	27	1	20
BCBS MI	27	3	22	7	18	18	13	27	8	5	2	25
Univ. Healthcare	18	15	24	8	15	15	10	21	12	14	17	19
BCBS WY	23	19	5	12	16	26	4	22	5	3	18	17
Bright	4	16	21	13	21	25	20	17	4	2	20	27
Oscar	3	20	14	23	8	1	26	6	11	6	12	2
Wellcare	17	12	2	27	14	23	11	4	18	7	4	13
Omaha	5	8	1	26	22	27	8	1	3	12	11	18
Athene	14	22	3	6	2	24	23	9	10	21	3	23
American	16	4	12	10	19	9	24	12	26	22	14	8
Mass Mutual	11	27	8	5	13	19	16	7	25	24	26	26
New York Life	24	21	9	3	9	16	19	16	23	10	10	9
Lincoln Nat'l	22	11	16	4	20	3	7	13	27	17	21	5
Equitable	25	10	18	25	1	14	25	18	15	13	24	7
Allianz	20	17	7	2	24	8	9	23	2	26	25	3