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Keywords:

  • deceased donors;
  • donation rates;
  • donor efficiency;
  • hospitals;
  • living donors;
  • mortality statistics;
  • neurosurgery;
  • organ donation;
  • organ procurement

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

The shortage of donor organs calls for a careful examination of all improvement options. In this study, 80 Dutch hospitals were compared. They provided 868 donors in a 5-year period, constituting 91% of all donors in that period in The Netherlands. Multilevel regression analysis was used to explain the differences between hospitals. Potential explanatory variables were hospital-specific mortality statistics, donor policy and structural hospital characteristics. Of all donors, 81% came from one quarter of the hospitals, mainly larger hospitals. A strong relationship was found between the number of donors and hospital-specific mortality statistics. Hospitals with a neurosurgery department had additional donors. Seven hospitals systematically underperformed over a period of 5 years. If these hospitals were to increase their donor efficiency to their expected value, it would lead to an increase of 10% in the number of donors. Most donors are found in large hospitals, implying that resources to improve donor-recruitment should be channelled to larger hospitals. This study presents an efficient strategy toward a benchmark for hospitals of their organ donation rates. Some larger hospitals performed less well than others. This suggests that there is still room for improvement. There is no evidence for large undiscovered and unused pools of donor organs.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

In many countries the demand for donor organs greatly exceeds the supply; there is a considerable shortage of donor organs. Many attempts have been made to increase the number of donor organs. This also applies to the Netherlands, where in 2003 a total of 1411 people were on the waiting list for organ transplantation, with only 202 deceased donors in that year (1). The shortage of donor organs has led to various activities: a campaign among the general public for registration as a consenting donor in the national register (mid-2004 37% of the adult Dutch population had actively registered in the national register, 55% of them consenting to organ donation); introducing support plans for Dutch hospitals and allowing for non-heart-beating organ donation (in 2002 one-third of all deceased donors were derived from a non-heart-beating procedure) (1,2). These activities did not lead to a significant increase in the number of deceased organ donations. Subsequently, a debate followed concerning the consent system for deceased organ donation, as laid down in the Dutch Organ Donation Act of 1998. In the Netherlands, organ donation is allowed only when explicit consent is given, either by a potential donor or relatives. It has been suggested that changing the consent system to a system of presumed consent might increase the number of donors. However, the comparison of donor rates in European countries with an informed consent system to countries with a presumed consent system, while correcting for differences in relevant mortality, shows more than reasonable doubt regarding this assumption (3,4). Since a system change will not solve the shortage of deceased donors, all potential alternatives should be considered. In this article, we will focus on the role of the hospital.

Hospitals play a vital role in the process of organ procurement: potential donors have to be identified, relatives consulted and organs have to be removed. Several initiatives have been employed to help hospitals increase the number of donors. About 50 out of 102 Dutch hospitals with an intensive care unit have a donation officer. Their role is to increase the awareness of the issue of organ donation among hospital staff, so that potential donors are not overlooked and doctors feel supported in their communication with relatives. Also, a donation protocol was developed. Its use is mandatory by law. Specialized teams take on the responsibility of organ removal, so that this does not burden the human resources of busy hospitals. In the year 2002, 1131 possible donors out of 23 953 deaths were identified by doctors in 57 hospitals that provide almost all deceased donors. Of these 264 were reported as donor. Eventually, the number of effective deceased donors was 233. Consent rate for cases not included in the national register was 29% (5).

For the United States, Sheehy et al. (6) showed that potential donors are mainly to be found in larger hospitals: hospitals with 150 or more beds accounted for 80% of all donors. The presence of a neurosurgical service and an emergency department were both correlated to the number of potential donors. The presence of a transplantation program was not related to the number of potential donors, but only to a higher recovery of organs from potential donors. In an earlier study, Christiansen et al. (7) also found that larger hospitals had higher numbers of potential donors than smaller hospitals, just like trauma centers and hospitals with a medical school affiliation. Several authors reported differences in conversion rates from the number of potential donors to the number of effective donors between different organ procurement organizations (OPOs) or hospitals. This suggests a potential for improvement in organizations or hospitals with the lowest conversion rates (6–10).

In this study, we aim at explaining differences in the number of donors between hospitals. Systematic unexplained differences may point to room for improvement among the hospitals that ‘underperform’ as compared to their peers. Explanatory factors will be structural aspects, such as the donor-potential, type of hospital, number of beds and the degree of implementing a donor policy. This study was part of the national evaluation of the Dutch Organ Donation Act (5).

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

Population

The boards of directors of 102 hospitals with an intensive care unit were approached for this study. From 86 boards, consent was obtained for the use of hospital specific mortality figures. They also provided the name of an intensive care unit doctor involved in organ donation. They were contacted by telephone. It was ascertained that they did indeed work in an intensive care unit and that they considered themselves as a key person involved in the process of organ donation in their hospital. They were invited to participate in this study: 85 of the contacts consented to participate. Subsequently, they were sent a questionnaire assessing the degree of implementation of the donor policy in the year 2002. In total, 80 questionnaires were returned (78% out of 102 hospitals), 76 by medical doctors, 2 by registered nurses, 1 by a transplant coordinator and 1 by a ‘donation officer.’ The data of 80 hospitals were analyzed.

Outcome Measure

The number of effective donors (donors whose organs have not only been presented for transplantation, but have actually been transplanted) for each hospital was obtained from the yearbook of the Dutch transplant foundation (1). The number of donors for 5 consecutive years (1998–2002) was taken in order to test the stability of outcomes through those years.

Explanatory Variables

Structural factors were defined as factors that determine the conditions of a hospital for organ donation; for instance, the number of relevant deaths or the availability of an intensive care unit. Those conditions are not amenable to intervention by hospitals. Hospitals with a similar structural position may be expected to do equally well in the number of effective donors. The number of relevant deaths was based on the routine coding of new hospital patients according to the ICD-9 DE, the Dutch language version of the ICD-9 CM. In the Netherlands, more than 85% of all deceased organ donors died from either a cerebral vascular accident (CVA), a (traffic-) accident or suicide. Furthermore, organ donation is limited to donors under 75 years of age (1). We therefore used the mortality figures for these categories, restricted to the age group of under 75 years for each hospital. Mortality data for 5 consecutive years were used. For our analyses we distinguished two categories: CVA and accidents/suicides. In earlier studies, other relevant structural hospital characteristics were identified: number of hospital beds, presence of a neurosurgical service, trauma center, transplant center or academic educational center (6,7) and having a donation officer (8). These variables were added to the variables in this study. Because of the stability of these characteristics, we restricted these data to the 2002 situation.

The degree of implementation of a donor policy was assessed using a questionnaire. Implementation was characterized by three steps: (1) having a donor policy on paper (2), putting a donor policy into practice and (3) sustaining a donor policy, with two questions for each step (see Table 1). All questions were combined into one variable. Scale analyses showed satisfactory reliability of 0.71, implying that all items refer to one underlying concept: the implementation of a donor policy. Respondents were asked to describe the situation in 2002, thus resulting in one measure for implementation of a donor policy ranging from 0 to 6.

Table 1.  The implementation of a donor policy (n = 80 hospitals)
 Number of hospitals
A policy on paper
 We have a donor protocol65
 We have a registration form73
A policy in practice
 We have a donation committee73
 One person feels extra responsible for organ donation71
Sustaining a policy
 We give regular instructions to new personnel on donor policy61
 We have regular meetings monitoring our donor efficacy56
 We have all six41

Analysis

First, descriptive statistics were used. Subsequently, to predict the number of organ donations in Dutch hospitals from structural factors and donation policy, multiple regression analysis was used within a multilevel model. Two types of explanatory variables should be distinguished. The mortality figures are yearly figures: each hospital provides mortality figures for 5 years. The remaining structural characteristics are restricted to 1 year. Also the implementation of a donor policy and the presence of a donation officer is restricted to a one-time assessment. The dependent variable was the number of donors in each individual hospital, for each of the 5 years in our assessment. A multilevel model was used to tackle these differences, by allowing for an analysis of 5-year data nested within hospitals (11). This analysis enabled us to locate the sources of variance: either between hospitals or between years. Most variance, 86%, was located between hospitals, whereas only 14% of the variance was located within hospitals between years. This means that large differences exist between hospitals and far smaller differences between years within one hospital. A hospital with many donors in 1 year is very likely to have many donors in the following year as well. A regression analysis was used to explain the differences between the hospitals. The focus of the analysis is not only on the explanatory power of this model but also on the unexplained variance. These analyses were repeated on the split half of the hospitals with the highest mortality rates. These hospitals are of special interest, since the larger hospitals are reported to be of most relevance for organ donation (6). In this subset, 85% of all variance was located between hospitals and only 15% within hospitals between years.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

Number of Donors

The participating 80 hospitals provided 868 effective donors in the period 1998–2002 (mean 2.2 per year, maximum 29 per year), accounting for 91% of the total number of donors in that period in the Netherlands (1). The distribution is skewed: the top 25% of the hospitals provide 81% of all donors. In these hospitals the average number of beds was 797 with a minimum of 429.

Structural factors

In the participating hospitals, 14 804 patients died with a diagnosis of accident, suicide or CVA in the period 1998–2002; in the age category 20–75 years (CVA n = 11 016 (mean 28 deaths per hospital per year), (accidents/suicide: n = 3788 (mean 10 deaths per hospital per year)). The mean number of beds in the hospitals was 536 (ranging from 140 to 1368). Nineteen hospitals had a neurosurgery department, 7 had a transplant center, 10 had a trauma center and 8 had an academic training center. These hospital characteristics were highly related: all transplant centers were academic training centers and all but one were trauma centers.

Implementation of donor policy

The degree of implementation of donor policy is shown in Table 1. Most frequently cited—by 73% of all hospitals—are the donor registration form and the donation committee. About half of all hospitals (41) said they had a fully implemented donor policy. Larger hospitals more often report a fully implemented donor policy than smaller hospitals. In 44 of the hospitals donation officers were present.

The relationship between structural factors, donor policy and the number of donors

In the regression analysis mortality rates were entered first. These explained 80.5% of the variance between hospitals (not in table). Entering the remaining structural factors increased the explanatory power by 0.7% to 81.2% (not in table). Only one of these variables contributed significantly to the model: having a neurosurgery department (Table 2). Entering the implementation of a donor policy and the donation officer did not change the explanatory power of the model. Table 2 shows the full model. It shows that 17 out of 100 dead (0.17) from accidents or suicides became donors, whereas 4.9 out of 100 (0.049) dead from a CVA became a donor. The presence of a neurosurgery department adds 1.84 donors per hospital.

Table 2.  Regression analyses explaining the number of donors in hospitals in the Netherlands (1998–2002)
Explanatory variablesN = 80 hospitalsN = 40 hospitals with highest mortality
B95% CIb95% CI
Constant2.150.95–3.352.410.33–4.49
Implementation of donor policy0.04–0.26–0.34–0.10–1.26–1.07
Having a donation officer0.15–0.90–1.200.46–2.04–2.96
Number of beds0.000.000.000.00–0.01
With a neurosurgery department (yes = 1, n = 0)1.840.62–3.052.210.09–4.34
Trauma center (yes = 1, n = 0)0.25−1.32–1.820.17–1.92–2.26
Academic educational center (yes = 1, n = 0)1.18−2.26–4.620.99–3.59–5.57
Transplant center (yes = 1, n = 0)–1.43–4.76–1.91–1.20–5.62–3.23
Number of dead diagnosed as accident or suicide0.170.13–0.210.160.10–0.21
Number of dead diagnosed as CVA0.050.03–0.070.02–0.01–0.05

These analyses were repeated on the split half of the hospitals with the highest mortality rates. In these hospitals the number of dead diagnosed as accident/suicide explained 70.7% of the variance between hospitals (not in table). Table 2 shows that the number of dead from a CVA no longer adds significantly to the model. The variance in the number of deaths from accidents and suicides explains 70.7% of the variance between hospitals. Entering the remaining structural factors increased the explanatory power by 1.1% to 71.8% (not in table). In these hospitals the presence of a neurosurgery department provides an extra of 2.2 donors each year. The implementation of donor policy and the donation officer again failed to reach significance.

Figure 1 demonstrates the strong linear correlation between total relevant mortality (CVA, accidents and suicide) and the number of donors (0.80; p < 0.001). However, the differences between hospitals remain. In particular, the right-hand side of the graph shows hospitals with mortality figures in the same range (e.g. between 100 and 150) but with a far wider range of number of donors, namely between 6 and 28. In the subset of 40 hospitals with higher mortality rates, we found 7 hospitals that performed systematically worse than average: every year their number of donors was below the expected value based on the regression analysis, taking into account the mortality figures and neurosurgery. The mean difference was –2.8 donors per hospital per year. On the other hand, there were six hospitals that always scored above their expected value, with a mean difference of +3.3 donors per hospital per year.

image

Figure 1. Scatterplot of the yearly number of relevant death by number of donors in 80 Dutch hospitals in the period 1998–2002 (each dot represents one hospital in 1 year, thus hospitals appear five times).

Download figure to PowerPoint

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

In this study, we aimed at explaining the differences in the number of organ donors between hospitals and at identifying hospitals with potential to improve. The strongest predictor of the number of donors is mortality—from accidents, suicide and CVA. The number of traumatic deaths is correlated to more donors as compared to deaths from a CVA, as was also found by Frezza et al. (12). In addition to this, the presence of a neurosurgical department increases the number of donors. The degree of donor policy implementation nor having a donation officer did add to this explanation. Finally, we found seven hospitals that performed systematically worse than average over a 5-year period.

One quarter of the hospitals accounted for 81% of all donors, confirming earlier findings (6) that the highest proportion of donors is to be found in the larger hospitals. However, in our study the larger hospitals had at least 429 beds as compared to 150 in the Sheehy et al. study (6). Nevertheless, we agree that extra efforts to increase the number of donors should focus on relatively larger hospitals, without neglecting the smaller hospitals; additional resources should be spent where most donors are.

Several studies have focused on the issue of defining a reliable denominator for comparing hospitals or OPOs for their donor efficiency. Ojo et al. (13) state that population size is not a good indicator for donor potential, because of the apparent differences between populations. They suggest using ‘notifiable’ deaths instead. Notifiable deaths are defined in terms of age (70 years or below), place of death (in hospital) and relevant ICD codes. ICD-9 codes of in-hospital deaths have been used to identify the donor pool and to compare the performance of OPOs (7,14). Stogis et al. (10) calculated an expected number of donors based on the link between national donation rates and deaths in 24 population-subgroups. A more labor intensive approach was used by Sheehy et al. (6), who extracted exact data from the death records of individual hospitals to identify actual potential donors. This methodology provides precise data for each hospital, but also is very labor intensive (9,10). In our study, we used routinely registered mortality figures per hospital as a predictor for the number of donors in each hospital. They serve as a better denominator than population size. We found a strong relationship between mortality figures and the number of donors (R2= 0.80). This correlation exceeded the correlation between the expected number of donors and the real number of donors as found by Stogis et al. (10), suggesting hospital-specific mortality figures to be a more precise predictor for the number of donors than the expected number of donors as calculated by Stogis et al. (10). The use of hospital specific mortality figures will offer certain advantages to chart review. First, the use of such data is less time-consuming than chart reviews, as was also noted by Tuppin and Pessione (15). Second, such data are routinely collected with a standardized procedure and therefore less prone to influence for strategic reasons or coding errors. The difficulty in standardizing chart reviews nationally was mentioned earlier by Stogis et al. (10). It is also less likely that hospitals will be lost for analysis because of nonresponse. Third, the use of mortality data enables hospital comparison over a period of more years. Differences between years explained 15% of the variance in the number of donors. These differences could not be attributed to the differences in mortality. This means that a benchmark of hospitals based on 1 year can lead to misclassifications. Stogis et al. also demonstrated that random variation may cause some misclassification (10). Even if these advantages are not fully convincing, the use of mortality figures can introduce a vital element of efficiency by using the donor/mortality ratio as a preselection for chart review. The more time-consuming and costly method of chart review could subsequently be administered to those hospitals that seem to underperform based on their donor/mortality ratio. This would reduce the burden dramatically. All in all, we think that the use of mortality figures for assessing the performance of hospitals on donor recruitment should not be discarded with the argument that these figures can never be the gold standard. Either as a screening instrument, but also on their own, mortality figures can serve as a cost effective and reliable instrument for assessing the potential number of donors in individual hospitals. Stogis et al. report formal hindrances to accessing OPOs specific information (10). We were in a fortunate situation to be able to get hospital-specific data on both mortality figures combined with diagnoses and donation figures. However, we restricted our analysis to only three relevant diagnoses, covering at least 85% of all causes of death for donors in the Netherlands (1). Others included many more diagnoses (10,13). Another limitation of our study is that ICD-code is based on the diagnoses given to a patient when entering the hospital. This is not necessarily in all cases the cause of death. From this point of view our analyses may seem crude. Nonetheless, these data, whether crude or not, proved to be a strong predictor for the number of donors in each hospital.

The ultimate goal of this study was to identify hospitals with improvement potential. This is important, since many other strategies have already been employed and we seem to be running out of options as far as cadaveric organ donation is concerned (14,16,17). Not much gain is to be expected from a general measure aiming at improving the implementation of a donor policy. As our data show, more than half of the hospitals state that they implemented their donor policy fully. We also found a strong relationship between mortality and number of donors. This implies that hospitals with many potential donors also use this potential: no large undiscovered and unused pools of donor organs were found. In spite of this we found some hospitals that appear to underperform. For 5 consecutive years these hospitals provided less donors than might be expected from their mortality figures and the availability of a department with neurosurgery. These differences are not spectacular, but can amount to several donors per hospital per year. It would require a more in-depth analysis in these seven hospitals on the relevance of inhibiting or promoting factors for organ donation. If these hospitals could improve their performance toward their expected value, this would mean an increase of 20 donors, which is an increase of 10% in the annual number of donors in the Netherlands: a worthwhile quest.

Acknowledgment

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References

We would like to thank Dr. J.J. Kerssens for his advice on the multilevel analysis.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgment
  8. References
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