Variation across organ procurement organizations in deceased-donor kidney offer notification practices

Abstract

Introduction:

How offer notifications are distributed early in the kidney allocation timeline, including how widely they are offered, is unclear. A better understanding of offer notification practices across organ procurement organizations (OPOs) may identify opportunities for more efficient allocation.

Methods:

We merged the Scientific Registry of Transplant Recipients potential transplant recipient file with additional offer notification time stamps to identify 54,631 deceased-donor kidney match runs from 2017–2023. Offer notifications for a given match run are sent to candidates/centers in “batches”. We quantified the number of offers in the initial batch—which theoretically reflects the OPO’s initial estimate of how widely a kidney should be offered—and compared this metric across OPOs.

Results:

Kidneys were offered to a median of 14 candidates (IQR 9–38) in the first batch of notifications, and this varied across OPOs from 3 to 746 candidates per initial batch. Batch size at the OPO-level did not correlate with rank at kidney placement or OPO nonuse rate. OPOs in the highest quartile of batch size sent more offers (median 100) than presumably necessary to place kidneys (median rank at placement 21), and OPOs in the lowest quartile of batch size sent fewer offers (6) than needed to place kidneys (rank at placement 19).

Conclusions:

Offer notification practices vary widely across OPOs, and many OPOs offer kidneys far more widely than necessary for placement. Optimization of offer notification practices may reduce unnecessary communications. Further research into allocation processes is needed to identify opportunities to improve efficiency of allocation for OPOs and transplant centers.

INTRODUCTION

Allocation of deceased-donor organs is a complex process. In the U.S., this process is carried out by the organ procurement organizations (OPOs) tasked with identifying potential donors within their service areas, procuring organs, and handling the logistics of allocation and transportation to the recipient center. This process has come under greater scrutiny in recent years as the efficiency of allocation has been adversely impacted by recent allocation changes;^1–3 for deceased donor kidneys in particular, rates of organ non-utilization have climbed as high as 25%.^2,4 OPOs face increasing pressure to procure and successfully place organs in the face of new objective performance metrics and the threat of decertification⁵, yet OPO practices remain opaque.⁶ Elucidating the allocation process from the OPOs’ standpoint is necessary to understand how OPOs have responded to regulatory pressures and to identify areas for potential process improvement.

For each deceased donor organ available for transplant, an objective algorithm generates a list of all potential recipients in order of priority called the “match run.” Once a match run is generated, the next step in allocation for OPOs is to send offer notifications to the transplant centers whose candidates are included in the match run. For deceased-donor kidneys, the full match run has thousands of potential recipients per kidney, and each transplant center may have several patients included on the list. Following the order of the match run, the OPOs send offers to transplant centers in one or more sequential “batches” until, ideally, both donor kidneys are placed with an accepting transplant center for a candidate on the waitlist (see schematic in Figure 1). How this process of offer notifications is carried out and varies between OPOs is unclear; the OPTN permits centers to notify all “local” centers in the first batch, and the number of local centers increased³ with the newest kidney allocation policy (“KAS250”). The workload involved in offer-related communication is immense for both OPOs and transplant centers⁷, and this workload has increased since the change to broader distribution of kidneys under KAS.^1,3,7 These communication challenges and inefficiencies in organ allocation are further exacerbated by increasing pressure to avoid kidney nonuse (when a kidney is procured but not ultimately transplanted), which has led to system workarounds and expedited organ placements.^8–10 Therefore, it is timely and critical to examine the current practices of kidney offer communications to better understand this process, identify opportunities for improvement, and identify practices that might be adversely impacting successful organ placement.¹¹

Figure 1: Deceased-donor kidney offer notifications are distributed in batches.

This study only focused on the initial batch of offer notifications. In this schematic of a match run, each circle represents a unique candidate, and each color represents a different center. In this example, the initial batch of offer notifications included 15 candidates from 4 different centers.

To this end, we studied offer notification practices across OPOs using the potential transplant recipient (match run) file from the Scientific Registry of Transplant Recipients linked to a separate file of additional time stamps for each offer notification. We were interested in how widely deceased-donor kidneys were offered early in the allocation process. We focused on the initial “batch” of offers for a given match run and quantified the variation in batch sizes across OPOs. At the OPO level, we compared median batch sizes—how widely a kidney is offered in the first round of notifications—to the median rank at kidney placement—i.e. how widely kidneys theoretically needed to be offered to be placed. We compared variation in these metrics across OPOs and explored how these processes relate to geography, kidney utilization, and CMS-assessed OPO performance.

METHODS

Data source and study population

This was a retrospective study of U.S. deceased-donor kidney match runs. This study used data from the Scientific Registry of Transplant Recipients (SRTR).¹² The SRTR data system includes data on all donor, wait-listed candidates, and transplant recipients in the U.S., submitted by the members of the Organ Procurement and Transplantation Network (OPTN). The Health Resources and Services Administration (HRSA), U.S. Department of Health and Human Services provides oversight to the activities of the OPTN and SRTR contractors. Donor-level and OPO-level data was obtained from the SRTR Standard Analysis File. Kidney match runs, including data on every offer to every potential recipient, were obtained from the SRTR Potential Transplant Recipient File. An additional file was obtained from the SRTR containing supplemental time stamps related to each match run, including the time each offer notification was sent. This latter file allowed us to identify which offers were grouped together into the same batch (described below). This study was approved by the University of Texas at Austin institutional review board (#00002097). All research activities were consistent with the principles of the Declaration of Istanbul.

Study population, definition of offer notification initial batch size

We included all deceased-donor kidney match runs generated between 12/25/2017–1/06/2023 (the 2018–2022 potential transplant recipient files) for which at least one donor kidney was procured. Because we aimed to study OPO practices, we excluded LifeChoice Donor Services, which merged into New England Donor Services in January 2021, and the timeframe of our data did not capture the most recent merger of Washington Regional Transplantation Community and The Living Legacy Foundation of Maryland. Thus, our study cohort included 57 OPOs whereas there are currently 56 active OPOs at the time of writing. When a match run is generated by an OPO for a kidney donor, the match run includes all potential recipients ordered by their allocation priority. Offer notifications are sent out to transplant centers sequentially in batches (Figure 1). If both donor kidneys are not accepted for a candidate in the first batch of offer notifications, additional batches are sent out as needed until either both kidneys are placed or until the final kidney(s) is(are) declined by enough centers that allocation attempts cease. We chose to study the initial batch of offer notifications because the size of this batch reflects the OPOs initial decision on how widely to offer a kidney. At a maximum, OPOs are allowed to send notifications to all local centers in one batch (all centers within a DSA pre-KAS250, all centers within 250 nautical miles of the donor hospitals post-KAS250). In theory, if a kidney’s quality is perceived as suboptimal, the OPO might plausibly send offer notifications for a larger number of candidates to more centers (a larger batch size). Conversely, for higher-quality kidneys, the OPO might plausibly send fewer offer notifications, expecting the kidney to be accepted earlier in the match run. We quantified the size of this initial batch by summing the number of candidates receiving an offer in this first batch of notifications. As another way of quantifying this, we alternatively defined batch size based on how many distinct centers were included in the initial batch (when multiple candidates receive an offer at a single center, the offer acceptance decision is made by the same clinical team at that center). We excluded bypassed offers from the calculation of batch size since these offers are not sent to the candidate/center. Sometimes a donor/kidney undergoes multiple match runs (1.5% of donors in our sample), and in these instances we limited our analysis to the last/most recent match run from the host OPO.

For each OPO, we also quantified the rank at which the first and second kidneys were ultimately placed, regardless of the batch in which this occurred. To calculate this metric, we included only match runs for which both kidneys were ultimately accepted, and we calculated the position in the match run (Nth candidate, Nth center) at which the first and second kidneys were accepted, excluding automatically bypassed offers. Thus, for match runs with no bypasses, the rank at placement was equal to the sequence number at placement.

Analysis

We aimed to describe the distribution of offer notification batch sizes by kidney quality and within and between OPOs, to compare this to the rank at kidney placement, to identify changes in batch size over time, and to describe the characteristics of OPOs with different batch sizes. We reported median and interquartile range (IQR) as summary statistics. We reported batch sizes stratified by kidney donor profile index (KDPI, a measure of kidney expected longevity). We quantified the change in batch sizes before and after the KAS250 policy change (March 2021) and plotted batch sizes over time by OPO to identify OPOs with the greatest changes in batch size after KAS250.

For all subsequent analyses in which we described variation across OPOs, we focused only on post-KAS250 match runs to describe current practices. We plotted the variation in batch size across OPOs. To better understand this variation, we grouped OPOs into quartiles of batch size and compared OPO characteristics and performance metrics between OPOs with smaller vs. larger initial batch sizes. We compared batch size (how widely kidneys are offered) to the rank at which kidneys are typically placed (how widely they theoretically need to be offered). To assess how geography may explain variation in batch sizes, we calculated the median number of candidates and centers local to an OPO and correlated this with batch size; we used the OPTN’s allocation categories (ptr_class_alloc_cat in the PTR data) to define “local” (i.e. these centers were within 250 miles of an OPO’s donor hospital). We also assessed how batch size correlated with kidney nonuse within and between OPOs. We compared various descriptive characteristics of OPOs including their volume, characteristics of their donor pool, utilization rates, frequency of out-of-sequence allocation, cold ischemia time, and allocation time (time from first offer to final acceptance [or final offer if one or more kidney was not accepted]) across quartiles of OPO batch size. We quantified the proportion of match runs at a given OPO containing an out-of-sequence allocation using bypass codes 861 (Operational OPO), 862 (donor medical urgency), and 863 (offer not made due to expedited placement attempt).⁸ OPO performance metrics were obtained from the 2023 OPO Annual Public Aggregated Interim Performance Report (based on 2021 data)¹³.

RESULTS

Size of the initial batch of offer notifications, and rank order at which kidneys are placed

A total of 54,631 match runs (N=31,550 pre-KAS250, N=23,081 post-KAS250) and 53,837 unique donors (N=31,008 pre-KAS250, N=22,829 post-KAS250) met inclusion criteria. Most initial batches of offer notifications were sent prior to cross clamp (49,756 [91.1%] pre-cross clamp vs. 4,875 [8.9%] post-cross clamp). Table 1 shows how widely offer notifications were typically sent out (median batch size) by KDPI and pre-/post-KAS250, and for comparison, it shows how far down the list kidneys were placed. When defining batch size by number of candidates notified, median overall batch size was 14 candidates, and this increased with KDPI (11 candidates for KDPI 0–20 kidneys vs. 18 candidates for KDPI >85). The median rank at which the second donor kidney was placed was the 9^th candidate. For KDPI >85 kidneys, median initial batch size (18) was far smaller than the median rank at second kidney placement (73)—suggesting additional batches of offer notifications were typically needed to place high KDPI kidneys. Median batch size, in terms of number of candidates, was similar after KAS250 (15 vs. 15), but kidneys were placed further down the match run after KAS250 (position 18 post-KAS250 vs. 7 pre-KAS250 for the second kidney).

Table 1:

Number of candidates and number of distinct centers per initial batch of offer notifications.

All numbers are median (IQR). i.e. first calculate the median batch size for each OPO, and then take the median of that distribution	Number of candidates notified per match run				Number of centers notified per match run
	Overall	Pre-KAS250	Post-KAS250	Proportional change	Overall	Pre-KAS250	Post-KAS250	Proportional change
Batch size
Initial batch	14 (9–38)	15 (10–45)	15 (7–47)	1.00	4 (3–5)	3 (2–4)	5 (4–9)	1.67
Total match run sizea	193 (102–320)	123 (85–234)	427 (122–670)	3.47	10 (8–14)	6 (5–9)	14 (10–21)	2.33
Batch size by KDPI (initial batch)
KDPI 0–20	11 (8–50)	13 (7–47)	11 (7–35)	0.85	4 (3–5)	3 (2–4)	5 (4–10)	1.67
KDPI 21–34	13 (8–46)	15 (6–55)	13 (7–35)	0.87	4 (3–5)	3 (2–4)	5 (4–10)	1.67
KDPI 35–85	14 (10–40)	17 (10–43)	14 (7–48)	0.79	4 (3–5)	3 (2–4)	5 (4–9)	1.67
KDPI >85	18 (10–39)	18 (10–28)	20 (10–71)	1.11	4 (3–5)	3 (3–4)	5 (4–9)	1.67
Rank at first kidney acceptance
Overall	4 (3–5)	3 (3–4)	7 (5–9)	2.33	3 (2–3)	2 (1–2)	5 (3–6)	2.50
KDPI 0–20	3 (2–3)	2 (2–2)	5 (3–6)	2.50	2 (2–2)	2 (1–2)	3 (2–5)	1.50
KDPI 21–34	3 (3–4)	2.5 (2–3)	6 (4–8)	2.40	2 (2–3)	2 (1–2)	4 (3–6)	2.00
KDPI 35–85	5 (4–6)	4 (3–5)	8 (6–11)	2.00	3 (2–4)	2 (2–3)	5 (4–7)	2.50
KDPI >85	33 (21–43)	23 (15–36)	50 (26–82)	2.15	7 (5–9)	5 (3–7)	10 (6–15)	2.22
Rank at second kidney acceptance
Overall	9 (8–12)	7 (6–10)	18 (10–25)	2.57	4 (3–5)	3 (2–4)	7 (5–11)	2.33
KDPI 0–20	6 (5–8)	4 (4–6)	10 (6–12)	2.50	3 (3–4)	3 (2–3)	5 (4–8)	1.67
KDPI 21–34	8 (6–12)	6 (4.5–8)	15 (11–22)	2.50	4 (3–5)	3 (2–4)	8 (5–11)	2.50
KDPI 35–85	11 (9–17)	8.5 (7–13)	28 (14–40)	3.29	4 (4–6)	3 (2–4)	8 (6–12)	2.67
KDPI >85	73 (37–113)	48 (29–88)	99 (37–195)	2.06	9 (7–11)	8 (6–10)	13 (7–18)	1.58

Numbers represent median (IQR). Results are shown stratified by kidney donor profile index (KDPI) and by pre-/post-KAS250 (March 2021).

^aNumber of candidates or number of centers receiving notifications on the entire match run, regardless of which batch (1^st, 2^nd, N^th) those offer notifications were sent.

When defining batch size by number of centers notified in the initial batch of offer notifications (Table 1), median overall batch size was 4 centers, and this was consistent across KDPI groups. The median rank at which the second donor kidney was placed was the 4^th center offered. For KDPI >85 kidneys, median batch size (4 centers) was smaller than the median number of centers offered prior to second kidney placement (9 centers)—suggesting additional batches of offer notifications, doubling the number of centers initially contacted, was typically needed to place high KDPI kidneys. After KAS250, median initial batch size, in terms of number of centers, was 67% higher, and this increase was consistent across KDPI groups.

Changes in offer notification batch sizes over time pre-/post-KAS250

Figures 2a and 2b show offer notification initial batch sizes (number of candidates and centers, respectively) by OPO and over time relative to KAS250. Batch size (candidates per batch) increased for 45.6% of OPOs after KAS250, with the largest being a 4,175% increase. Batch size (centers per batch) increased for 82.4% of OPOs after KAS250, with the largest being a 500% increase.

Figure 2a: Number of candidates per initial batch of offer notifications, over time, by organ procurement organization.

Each line represents one OPO. The 5 OPOs with the largest increase in batch size after KAS250 (March 2021) are highlighted in red. The bold black line indicates the median batch size (of all OPOs) over time.

Figure 2b: Number of centers per initial batch of offer notifications, over time, by organ procurement organization.

Each line represents one OPO. The 5 OPOs with the largest increase in batch size after KAS250 (March 2021) are highlighted in red. The bold black line indicates the median batch size (of all OPOs) over time.

Variation in offer notification batch sizes across OPOs

Given the large changes after KAS250, to focus on current practices, all subsequent analyses were limited to post-KAS250 match runs. Figure 3 shows the distribution of initial batch sizes (in terms of number of candidates per initial batch) for each of the 57 OPOs. Median batch size varied across OPOs from 3 to 746 candidates per initial batch of notifications. Figure 3 also indicates, with blue and red markers, the median rank at which the first and second kidneys, respectively, are placed by each OPO. For OPOs on the left of the figure with the smallest initial batch sizes, the median number of candidates receiving offer notifications in the initial batch is smaller than the median number of candidates ultimately offered by the time both donor kidneys are placed. For OPOs on the right of the figure with the largest initial batch sizes, the median number of candidates receiving offer notifications in the initial batch is much larger than the number typically needed to place both donor kidneys. eFigure 1 shows similarly wide variation across OPOs in initial batch size, defined here as number of centers per initial batch, which ranged from 1 to 21.

Figure 3: Variation in offer notification batch sizes across organ procurement organizations – post-KAS250.

Batch size here is defined as the number of candidates per initial batch of offer notifications. Only post-KAS250 (after March 2021) match runs are included here. The boxes for each OPO represent the median (line), 25^th/75^th percentiles (boundaries of box), and 5^th/95^th percentiles (boundaries of whiskers). Boxes are sorted by OPO median batch size. Darker gray boxes represent OPOs with greater (above 50^th percentile) number of local candidates. For reference, the blue and red markers indicate, respectively, the median rank at which the first and second kidneys are placed among all match runs at each OPO. The y-axis is in the log scale.

Relationship between geography (number of local centers) and batch size

We calculated the number of candidates and centers considered “local” to each OPO after KAS250 (all centers within 250 nautical miles of an OPO’s donor hospitals). Number of candidates per initial batch was moderately correlated with number of local candidates (r=0.39, P=0.003; eFigure 2), and number of centers per initial batch was more strongly correlated with number of local centers (r=0.61, P<0.001; eFigure 3). Darker gray boxes in Figure 3 and eFigure 1 represent OPOs with larger numbers of local candidates/centers. The proportion of match runs in which all local candidates were notified in the initial batch ranged from 1% to 87% across OPOs (median 13%).

Batch size is weakly correlated with rank and placement and OPO out-of-sequence allocation practices

At the OPO level, number of candidates per initial batch was not correlated with the median rank at which the second kidney was placed (r=0.06, P=0.674, eFigure 4)—meaning, how widely OPOs offer kidneys in the initial batch of offer notifications is not related to how difficult it is to place kidneys (i.e. how many candidates are offered before the second donor kidney is placed). Finally, we quantified for each OPO, how often out-of-sequence allocation is used anywhere in a match run. At the OPO level, batch size was not correlated with how frequently out of sequence allocation is used (eFigure 5). When an out-of-sequence allocation occurred, it rarely occurred during the initial batch of offer notifications (694 match runs [1.3%]).

Batch size and kidney nonuse

Between OPOs, batch size was weakly correlated with OPO kidney nonuse rate (r=0.268, P=0.044, eFigure 6). Across all OPOs, median batch size was 18 candidates for match runs in which both kidneys were used, 17 candidates in match runs where only one kidney was used, and 20 candidates in match runs where no kidneys were used. Considering OPO-specific changes after KAS250, the proportional change in batch size was not correlated with the proportional change in nonuse rate (r=0.049, P=0.720). As a sensitivity analysis, we created versions of Figure 3 for two subsets of match runs: both kidneys transplanted (eFigure 7A) and one or more kidney transplanted (eFigure 7B), and results were similar to Figure 3.

Characteristics of OPOs by quartile of initial batch size

To compare OPO characteristics, we grouped OPOs into quartiles based on their median initial batch size. Table 2 shows batch sizes by KDPI, and rank at which kidneys are typically placed, stratified by batch size quartile. For the 15 OPOs with the smallest initial batch size, median batch size was 6 (IQR 4–7) candidates offered per batch, yet the median rank at which the second kidney was placed was 19. For the 14 OPOs with the largest initial batch size, median batch size was 100 (IQR 80–100) candidates, whereas the median rank at which the second kidney was placed was 21. eTable 1 presents the data with batches and quartile groupings defined instead by number of centers per initial batch.

Table 2:

Offer notification batch size and rank at kidney placement, by KDPI and by quartile of OPO batch size (post-KAS250 only).

	OPO batch size (no. candidates per initial batch of offer notifications, quartiles)
	Quartile 1 (smallest batches)	Quartile 2	Quartile 3	Quartile 4 (largest batches)
No. OPOs in each group	15	14	14	14
Range of batch size (no. candidates)	3 – 7	8 – 15	17 – 47	50 – 746
Batch size by KDPI (initial batch)
Overall	6 (4–7)	10 (10–12)	20 (19–33)	100 (80–100)
KDPI 0–20	6 (4–7)	10 (8–10)	19 (17–31)	79 (50–100)
KDPI 21–34	6 (4–6)	10 (8–12)	20 (19–34)	100 (80–100)
KDPI 35–85	5 (4–6)	11 (9–12)	20 (18–22)	100 (80–140)
KDPI >85	7 (5–9)	17 (10–20)	26 (20–38)	100 (80–312)
Rank at first kidney acceptance
Overall	7 (6–9)	7 (5–9)	6 (3–10)	8 (5–9)
KDPI 0–20	5 (4–6)	4 (3–5)	5 (2–6)	4 (3–6)
KDPI 21–34	7 (4–9)	5 (5–8)	5 (3–8)	7 (4–9)
KDPI 35–85	8 (6–11)	9 (6–13)	8 (5–11)	9 (5–15)
KDPI >85	42 (27–58)	54 (26–82)	53 (22–159)	48 (26–85)
Rank at second kidney acceptance
Overall	19 (13–25)	17 (12–30)	10 (8–20)	21 (12–26)
KDPI 0–20	10 (8–13)	8 (6–11)	10 (5–12)	9 (7–13)
KDPI 21–34	19 (12–24)	14 (11–17)	12 (8–19)	15 (11–23)
KDPI 35–85	30 (18–40)	23 (15–47)	15 (10–38)	31 (15–48)
KDPI >85	103 (60–196)	132 (37–228)	120 (37–360)	70 (35–127)

OPOs were grouped into quartiles by their median initial batch size. The values shown are median (IQR) for the OPOs in each quartile. The rank at placement represents the median position on the match run (the Nth center) at which the first and second kidney are placed for a given OPO. KDPI = kidney donor profile index. OPO=organ procurement organization.

Using the same groupings of OPOs by quartile of batch size, Table 3 describes characteristics of OPOs in terms of their volume, donor characteristics, and performance metrics. Compared to OPOs with the smallest initial batch sizes, OPOs with the largest batch sizes had higher procurement and transplant volume and more local candidates, but these were not stepwise trends across quartiles. OPOs with larger batch sizes had slightly higher median KDPI of their procured kidneys. Cold ischemia time was similar across quartiles, but the time spent allocating kidneys was shortest among OPOs with the smallest batch sizes. There was not a clear trend in frequency of out-of-sequence allocation across quartiles of batch size; this practice was least common (2.3% of match runs) among OPOs with the largest batch sizes. Kidney utilization rates did not vary substantially across quartiles. In terms of the CMS metrics by which OPOs are judged, compared to OPOs with moderate batch sizes (second and third quartile), OPOs with the smallest batch sizes (first quartile) and largest batch sizes (fourth quartile) had slightly lower transplant rates (Q1 34.1 and Q4 33.0 vs. Q2 37.8 and Q3 35.8) and were more likely (though not statistically significantly) to be in the lowest tier (Tier 3) of ranking (Q1 53.3% of OPOs and Q4 57.1% vs. Q2 21.4% and Q3 35.7%; P=0.305). eTable 2 presents the data with quartile groupings defined instead by number of centers per initial batch.

Table 3:

Characteristics of organ procurement organizations by quartile of initial offer notification batch size (post-KAS250 only).

	OPO batch size (no. candidates per initial batch of offer notifications, quartiles)
	Quartile 1 (smallest batches)	Quartile 2	Quartile 3	Quartile 4 (largest batches)
No. OPOs in each group	15	14	14	14
Range of batch size (no. candidates)	3 – 7	8 – 15	17 – 47	50 – 746
OPO Characteristics
Volume and characteristics of kidneys procured or transplanted
No. centers receiving a kidney from each OPO	49 (38–62)	40.5 (35–49)	41 (21–60)	39.5 (31–48)
Median no. local candidates per match run	374 (64–527)	158 (80–306)	123 (73–282)	439 (307–828)
Median no. local centers per match run	16 (7–21)	9 (7–16)	8 (3–18)	12 (8–23)
No. kidneys procured annually	278 (178–527)	390 (244–487)	384 (147–772)	376 (298–560)
No. kidneys transplanted annually	198 (148–420)	259.5 (180–357)	299 (108–572)	280.5 (206–438)
Donor age	43 (41–45)	43 (42–44)	42.75 (41–45)	42 (41–46)
Proportion of donation after circulatory death donors	0.33 (0.26–0.36)	0.33 (0.28–0.40)	0.33 (0.26–0.35)	0.33 (0.30–0.40)
KDPI of all kidneys procured	50 (47–53)	49 (47–52)	52 (45–55)	51.5 (45–57)
Proportion of match runs with expedited allocation	6.9% (5.1% - 10.1%)	5.6% (3.7% - 8.1%)	8.7% (4.8% - 17.0%)	2.3% (0.8% - 11.4%)
Metrics related to allocation timing
Cold ischemia time of all kidneys procured (hrs.)a	20.2 (19.5–20.9)	19.3 (17.8–20.9)	18.5 (17.1–20.3)	20.3 (19–21.1)
Total allocation time of all kidneys procured (hrs.)b	29.4 (25.6–30.7)	31.5 (28.1–35.0)	33.3 (29.9–39.3)	31.3 (28.0–33.5)
OPO performance metrics
Proportion of procured kidneys transplanted	0.74 (0.71–0.81)	0.74 (0.73–0.79)	0.76 (0.74–0.79)	0.76 (0.70–0.79)
Proportion of procured kidneys nonutilized	0.26 (0.19–0.29)	0.26 (0.21–0.27)	0.26 (0.21–0.26)	0.24 (0.21–0.30)
CMS metrics (2021 performance, 2023 report)c
Donation rate	11.0 (9.3–12.8)	11.7 (10.2–14.6)	11.1 (9.6–13.5)	10.7 (9.7–13.4)
Transplant rate	34.1 (29.9–41.1)	37.8 (36.2–43.9)	35.8 (31.6–39.3)	33.0 (29.2–43.5)
Tier ranking (N, %)
1 (highest)	4 (26.7%)	4 (28.6%)	3 (21.4%)	4 (28.6%)
2	3 (20.0%)	7 (50.0%)	6 (42.9%)	2 (14.3%)
3 (lowest)	8 (53.3%)	3 (21.4%)	5 (35.7%)	8 (57.1%)

OPOs were grouped into quartiles by their median initial batch size. The values shown are median (IQR) for the OPOs in each quartile. KDPI = kidney donor profile index. OPO=organ procurement organization.

^aCold ischemia time is calculated only for transplanted kidneys.

^bTotal allocation time is calculated as the time from first organ offer notification to final offer acceptance; for match runs in which one or both kidneys was not accepted, allocation time was calculated as time from first to last organ offer notification.

^cOPO performance metrics were obtained from the 2023 OPO Annual Public Aggregated Interim Performance Report (based on 2021 data).¹³

DISCUSSION

In this descriptive analysis of U.S. deceased-donor kidney match runs, we show wide variation in offer notification practices across OPOs. Since KAS250’s implementation, the same number of candidates are included in the initial batch of offer notifications, but the number of centers included in the initial batch is now higher, and the rank at kidney placement more than doubled—even for high quality kidneys. Some OPOs had dramatic increases in their batch sizes after KAS250. Median initial batch size varied across OPOs from 3 to 746 candidates offered per initial batch, and batch size did not correlate with how far down the match run allocation typically proceeds (rank at placement) for a given OPO. Variation in batch size was explained in part by geographic factors, as OPOs with more local centers (post-KAS250) tended to offer more centers per initial batch. For OPOs with the smallest batch sizes, too few offer notifications are sent in the initial batch relative to the rank at which kidneys are typically placed by those OPOs. For OPOs with the largest batch sizes, four times as many offers are sent in the initial batch compared to the rank at which kidneys are typically placed by those OPOs. Batch size was not clearly related to characteristics of an OPO’s donor pool and was not correlated with kidney nonuse rates or with the frequency of out-of-sequence allocation. The wide variation in offer notification practices highlights an aspect of the allocation process that may be a suitable target for optimization to offer kidneys more discriminately and in a more data-driven manner.

A focus on offer notification practices is timely and necessary under the current allocation framework of broader organ sharing. Since KAS250, the volume of organ offers received by transplant centers has increased dramatically, adding workload and logistical burden for transplant centers, without a clear link to increased transplant volume.^1,7 An increase in the number of offers that a transplant center receives was expected under broader distribution, and with the rising nonuse rate^2,4 and new OPO performance metrics⁵, it is not surprising that some OPOs are casting a wider net to identify a transplant center willing to accept an organ early in the allocation process. Correspondingly, we show that some OPOs increased the number of offer notifications per initial batch by as much as 4,175%; for such OPOs, this results in many “excess offers.” For the OPO with the largest batch size, a median of 746 candidates received offer notifications for a given match run even though kidneys from that OPO were typically placed at sequence number 24. Excess offer-related communication places unnecessary strain on centers⁷, who must dedicate additional resources to deal with this surge in offers, and OPOs are likely burdened by inefficient communication as well. OPOs are permitted to notify all local centers within the same batch, but this is not happening across the board, as the median OPO notified all local candidates in the initial batch only 13% of the time. However, we did see a strong correlation between number of local centers and number of centers notified in the initial batch; thus, it seems at least some OPOs are compelled to offer a majority of their local centers even if this results in many more offer notifications than needed to place the kidneys. Casting a wide net with offer notifications does not clearly increase OPO efficiency, as neither time spent on allocation nor cold ischemia time were lower among the OPOs with the largest batch sizes (Table 3). On the other side of the spectrum, some OPOs do not offer kidneys widely enough in the first batch of notifications (though, it is unclear if this would delay the allocation process, as allocation time was lowest in this group of OPOs). Ultimately, a more tailored approach to offer communications—informed by organ quality and offer acceptance patterns of centers—might facilitate a more efficient allocation system.

The current regulatory environment is increasingly scrutinizing OPO practices and performance. CMS is charged with certifying OPOs, and in December 2020, the OPO conditions for coverage were revised such that OPOs face decertification if their donation and/or transplantation rates are significantly below the national median.⁵ It is unclear how this regulatory pressure might directly affect how OPOs approach their offer communication practices. We found that the “outlier” OPOs—those with the smallest or largest initial batch sizes—were more frequently in the lowest performance Tier, but this was not a statistically significant finding. Whether outlier offer notification batch sizes are reflective of lower OPO performance, or whether OPOs might change their batch sizes in response to lower performance, remains unclear. Expedited allocation—offering an organ out of sequence when it would otherwise be at risk of nonuse, is a practice increasingly used by OPOs in response to regulatory pressures⁸; we found no relationship between expedited allocation and offer notification practices at the OPO level.

Examining the various steps of the allocation process is critically important to identify opportunities for a more efficient system, and understanding how OPO practices have changed and how notification practices function under broader distribution is a prerequisite to informed implementation of the upcoming allocation policy changes with continuous distribution. We introduce here a novel linkage of additional offer notification time stamps to the SRTR Potential Transplant Recipient file, and we chose to focus first on the initial step of the offer notification process: the initial batch size. Additional work will need to characterize the subsequent steps of the offer notification process to identify inefficiencies and areas for workflow optimization. This work should be considered by the OPTN’s Expeditious Task Force¹⁴ which seeks to improve allocation efficiency and transparency and to minimize organ nonuse. Although we did not see a strong link between offer notification batch size and kidney nonuse rates at the OPO level, the wide variation in batch sizes and mismatch between batch size and rank at placement is evidence of need for a more data-driven approach to the offer process. Predictive analytics can be used to guide how widely a given kidney should be offered¹⁵, and this could minimize unnecessary offer burden while potentially facilitating kidney placement for OPOs.

This study has limitations. As with any analyses of OPOs and transplant practices in recent years, multiple competing policy and regulatory changes must be acknowledged, including the KAS250 allocation policy, changes to the OPO conditions for coverage by CMS, and the COVID-19 pandemic. Though we show changes in offer notification batch sizes after KAS250, these other changes to the transplant landscape played a role as well. With the current analysis, we focused on describing the current state of offer notification practices, and this is the first time these novel data have been examined in this way, to our knowledge. We chose to focus only on the initial batch of offer notifications, and thus this paper does not describe or account for the entire timeline of allocation (including subsequent batches of additional notifications). We were limited to analyzing the data captured by the SRTR, and thus, understanding the exact drivers of these differing offer notification practices across OPOs will require additional primary data collection. Finally, our use of statistical inference was intentionally limited, and thus our findings should be taken as a large descriptive account of an understudied topic using novel data, and differences shown here should be interpreted with caution, and causality should not be inferred.

In conclusion, we used a novel linkage of offer notification time stamps to the SRTR Potential Transplant Recipient file to examine differences in offer communication practices across OPOs. The size of the initial batch of offer notifications in a deceased-donor kidney match run varied widely across OPOs. Many OPOs offer kidneys to more candidates than presumably necessary to find an accepting center, while many other OPOs seem to offer kidneys too narrowly in the first round of notifications, especially for higher KDPI kidneys. More efficient offer notification practices would likely benefit OPOs, transplant centers, and candidates alike. Further examining the current organ allocation process may help identify additional areas for process improvement to ultimately improve organ utilization and efficiency of the allocation system.

Abbreviations:

OPOs

Organ Procurement Organizations

SRTR

Scientific Registry of Transplant Recipients

KAS250; circle-based kidney allcoation

Kidney allocation system 250

IQR

interquartile range

OPTN

Organ Procurement and Transplantation Network

HRSA

Health Resources and Services Administration

KDPI

kidney donor profile index

Data statement:

The data that support the findings of this study are available from the corresponding author upon reasonable request.