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Rationing and triage of scarce, lifesaving therapy in the context of the COVID-19 pandemic: a cross-sectional, social media-driven, scenario-based online query of societal attitudes

Muensterer, Oliver J. MDa,b,c,; Gianicolo, Emilio A. PhDd,e; Paul, Norbert W. MDc

Author Information
International Journal of Surgery: Global Health: January 2021 - Volume 4 - Issue 1 - p e47
doi: 10.1097/GH9.0000000000000047

Abstract

Key points

  • This cross-sectional study generates a comprehensive picture of public opinion regarding criteria and modalities for the allocation of life-saving, limited resources.
  • According to participant’s opinion, prognosis, responsibility towards others, the absence of behavior-induced comorbidities, along with younger age should be criteria for allocation of scarce ventilators.
  • Insurance status, social status, as well as nationality and asylum status should not play a relevant role.
  • Ethics-committees and a point system similar to what is used for organ transplantation were deemed potentially helpful in triage decision making. Distribution by order of presentation (first-come first-serve) or on the basis of legislation was viewed critically.
  • The results of this study may be useful in creating future triage-algorithms and may help expand these by a dimension of societal consensus.

Introduction

Even in highly developed nations, the coronavirus disease 2019 (COVID-19) pandemic has shown how medical resources can become limited when an overwhelming need arises. The discrepancy between supply and demand in southern European medical centers, and later on in some metropolitan areas of the United States, reached dimensions previously unimaginable1. Some of the most strikingly extreme circumstances were the sudden need to ration lifesaving medical therapies, in particular intensive care beds and ventilators, including advanced technology such as extracorporal membrane oxygenation2.

Italy was the first country in which, due to the vast number of affected patients with respiratory distress, medical personnel was required to make ad-hoc decisions regarding which patient would receive a ventilator or not3. This gut-wrenching task mostly fell on physicians working in the forefront, who were already overwhelmed and at their limits. The precarious, highly dynamic situation left them practically no opportunity to prepare emotionally, morally, or functionally for the resulting challenges.

Hence, the discourse focused on triage algorithms to be applied for the distribution of scarce therapeutic resources, mostly in an operational mode. Such practical guidelines have long been established in military and disaster4. Military algorithms, however, focus mainly on maintaining an effective army of soldiers. They do not lend themselves for simple translation into the civilian environment. After the September 11th attacks in 2001, algorithms with an emphasis on patient prognosis as the lead criterion were developed5. In accordance, with the principle of beneficence (acting with the best interest of the other), and with the utilitarian principle of conferring the most benefit to the greatest number of individuals, civilian triage systems correspondingly tend to favor patients with a better prognosis.

At times, triaging purely by prognosis seems inappropriate. Particularly the immanent conflict between urgency and the prospect of successful outcome, along with the need for a timely decision, poses an inextricable dilemma for medical practitioners in the trenches. Moral intuitions that overshadow rational decisions can complicate matters even further. For example, should a 30-year-old mother of 4 with a chronic medical condition receive priority in receiving a scarce, life-saving therapy over an otherwise healthy, single 65-year old? In reality, decisions are based on a multidimensional array of factors. These may include responsibility for others (as in this example), age, expected quality of life after convalescence, or sacrifice for others (eg, in the case of medical personnel). The weighting of these different factors is strongly dependent upon the moral norms that result from the discourse within a particular society. While experts and opinion leaders6 have heavily driven the narrative, for example, labelling triage according to age as “radical-utilitarian discrimination of the elderly”7, there is very little known about the opinions and attitudes of the general public. Cross-sectional studies in this regard are lacking, but would be useful to guide the implementation of acceptable future triage algorithms.

These deficits have been addressed in several recent publications8, particularly in the context of the COVID-19 pandemic9. We were interested in surveying the opinions on concrete criteria that should play a role in the rationing of life-saving measures in a cross-sectional sample of the general public. We hypothesized that the general public would be more inclined to include younger age and better long-term prognosis as a criterion for receiving care, and that most participants would not perceive this as age discrimination. Although the concept of age discrimination in Germany is a politically sensitive topic, we had the impression that most people we discussed the project with, including those of advanced age, would favor giving therapy to the younger patient in order to save more quality-life-years. Also, we hypothesized that drawing lots and triage on a “first come, first serve” basis would be the least popular mechanisms. Although drawing lots gives all participants the same chance, it means an arbitrary distribution that does not take into account individual factors or circumstances. Triage based on time of arrival, on the other hand, is inherently unfair.

Since contemporary public opinion has been shaped increasingly by social media, we decided to launch this empiric study of the societal attitudes through social media channels. After the COVID-19-pandemic had hit some European countries so heavily, conducting this study during the ongoing crisis was embedded in the ethically founded overall concept of preparedness, which might have contributed to the relatively controlled course of the pandemic in Germany with relatively low mortality rates. To our knowledge, a similarly-designed study has so far not been performed or published.

Methods

In April, 2020, an online survey (LimeSurvey GmbH, Hamburg) was generated in German language and propagated broadly via different social media channels (Internet webpages of our institution, medical ethics listserver, pediatric surgery forum, institutional Facebook account, Instagram account, SurveyCircle website, private contacts). In order to snowball the distributive effects, participants were expressively asked to resend the link to their friends and contacts.

Regarding content, the online survey (Appendix A, Supplemental Digital Content 1, http://links.lww.com/IJSGH/A9) included 10 imaginary scenarios, in which 2 critically ill patients required mechanical ventilation, but only one ventilator was available. The fictitious patient pairs differed in one principal characteristic [(1) age, (2) insurance status, (3) fateful, non–behavior-associated comorbidities (such as other preexisting conditions), (4) behavior-associated comorbidities (resulting from behavior, such as smoking or drinking alcohol), (5) working in a health care profession, (6) asylum status/nationality, (7) social status, (8) prognosis/chance of therapeutic success, (9) explicit consent for the intensive therapy, and (10) responsibility for others]. The participants were asked who they would provide the ventilator to (patient A or patient B). Another option was to draw lots for an equal chance to receive the therapy. Subsequently, participants were asked to mark how sure they were of their decision on a scale from 0 to 100. They were also asked to mark how important in their opinion the particular criterion should be for the distribution of lifesaving therapies on a scale from 0 to 100.

After the imaginary case-vignettes, the participants were asked about their opinion on the modalities that should be employed to make triage decisions [(a) drawing lots (randomization), (b) chronologic distribution (“first come, first serve”), (c) legal criteria (laws that specify how a physician should decide in a particular circumstance), (d) ethics committees (on-site counselling of the physicians by an interdisciplinary team), (e) decision committees (the decision is made by an independent team remote from the treatment location), (f) a point-system similar to what is used for organ transplantation]. Finally, the participants were queried on their age, sex, religious beliefs, and whether they were working in a medical profession.

Data were stored anonymously. The characteristics of our sample such as mean age, sex, religion and proportion of health care professional were compared with those of the general population (Statistisches Bundesamt10). Results of the scale values from 0 to 100 were presented as mean and 95% confidence interval (CI). In order to compare characteristics of the groups of participants according to the decisions met (patient A, patient B, or draw lot) we employed an analysis of variance for comparing the mean age of participants and a binomial test for categorical variables such as sex, religion and health care profession.

According to the laws and decision of the ethics board of the state of Rhineland-Palatinate, this study is exempt from formal ethics board review. All respondents consented to participation in the survey. Participation in the online study was voluntary and anonymous. No identifiable information was collected or stored. The manuscript was drafted in accordance to the STROCSS guideline11.

Results

Recall and demographic data

The social media campaign was launched on March 30, 2020. From April 1 to 12, 2020, the online survey was clicked a total of 3438 times. Overall, 1626 participants completed the entire survey (47%). Only complete surveys were included in this analysis.

Mean age of the participants was 40 years (SD 14 y, median 39 y, range 12–80 y; Table 1). Most participants were female (n=984, 61%), 623 were male and 4 considered themselves diverse, while 15 elected not to reveal their sex. A total of 645 (40%) worked in a medical or health profession.

Table 1 - Demographics of the respondents compared with the German general population10.
Religion, n [%]
Collective (n) Sex (n [%]) Age (y) Protestant Catholic Atheist Health Care Profession (%)
Respondents study (1626) Female 984 [61] Mean 40 446 [29] 432 [28] 318 [21] 645 [40]
Male 623 [38] Median 39
Diverse 4 [<1] Range 12–80
General population (83.2 m) Female 42.1 m [51] Mean 44 21.1 m [25] 23.0 m [28] 34–40 m 5.7 m [13]
Male 41.0 m [49] Median 47 41%–49%12 Of 44.8 m employed
Diverse 150 [<1%]13 Range 0–113
Respondends tended to be more females and slightly younger than the general population. Also, health care professionals were overrepresented in our collective.
m indicates million.

The distribution of religious beliefs is also depicted in Table 1. Most commonly participants were of protestant Christian faith [n=446 (29.2%)], and catholic Christian faith [n=432 (28.3%)], followed by atheists-agnostics [n=318 (20.8%)], and those that elected not to give any specifics regarding their religious denomination [n=247 (16.2%)]. Less commonly represented were other Christian faith [n=67 (4.4%)], Islam [n=13 (0.9%)], Judaism [n=4 (0.3%)], and 1 Hindu person.

Rationing decisions according to patient characteristics

Figure 1 illustrates the triage decisions. A majority of participants decided to provide the ventilator to the younger patient, the patient without comorbidities, the patient with explicit consent, and the mother taking care of 4 children. The majority of participants elected to draw lots when insurance status, asylum status/nationality, and social status was in question. Nearly equal distribution for patient A, patient B and drawing lots was found for the criteria chance of treatment success/prognosis.

Figure 1
Figure 1:
Participants’ decisions on the case scenarios. The paired characteristics of the imaginary patients A versus B comprise (1) young/old, (2) public/private insurance, (3) with or without fateful comorbidities, (4) with or without behavior-associated comorbidities, (5) working or not working/working in health care, (6) local nationality/asylum seeker, (7) high/low social status, (8) unfavorable/favorable prognosis, (9) consent given/lacking, (10) single household/mother of 4 children.

Opinions on triage criteria

The relative weighting of the respective concrete triage criteria are found in Figure 2. The participants scored chance of treatment success/prognosis as the most important criterion for rationing life-saving resources [mean score 77.8 (95% CI, 76.7–78.8)]. According to the participants’ opinions, behavior-associated comorbidities [62.1 (95% CI, 60.7–63.5)] should be as much of a criterion against receiving a scarce lifesaving therapy as responsibility for others should be a criterion in favor of receiving the therapy [62.1 (95% CI, 60.8–63.6)]. Also, participants generally favored younger over older patients [59.8 (95% CI, 58.7–60.9)]. On the other hand, according to the participants, insurance status [5.9 (95% CI, 5.2–6.7)], asylum status/nationality [19.1 (95% CI, 17.8–20.4)], as well as social status [24.8 (95% CI, 23.4–26.2)] should not play a major role. Fateful comorbidities [49.1 (95% CI, 47.7–50.6)], health care profession [43.6 (95% CI, 42.1–45.1)] and explicit consent for intensive care [52.6 (95% CI, 51.1–54.1)] scored somewhat in the middle.

Figure 2
Figure 2:
Opinions of the participants regarding the weighting of the respective triage criteria (A) and triage modalities (B). Participants regarded triage by prognosis as the most appropriate criterion, followed by behavior-associated comorbidities and responsibility for others, as well as age (A). Most participants determined ethics committees and a point-system similar to that used in organ transplantation to be the most appropriate triage modalities (B) (ns: nonsignificant, *P<0.05).

Opinions on decision modalities

The participants viewed ethics committees that provide on-site interdisciplinary guidance to practicing physicians as the most helpful modality to make triage decisions [75.5 (95% CI, 74.3–76.7)], followed by point systems similar to what is established for the distribution process in organ transplantation [68.5 (95% CI, 67.3–69.7)]. Triaging according to temporal sequence of presentation [27.3 (95% CI, 26.1–28.5)] and laws [34.4 (95% CI, 33.1–35.7)] were viewed as less helpful (Fig. 2). The scores regarding drawing lots [41.4 (95% CI, 40.2–42.6)] and decision committees [50.5 (95% CI, 49.0–52.0)] were scored in the neutral middle.

Demographics

Table 2 shows the associations of demographic factors with the responses. Older participants preferred drawing lots when the triage was based on age. Women preferred drawing lots for fateful comorbidities, health care profession, as well as for asylum status/nationality and social status. Atheists-agnostics less often chose treating the patient with an unfavorable prognosis than participants of religious faiths. Working in health care almost always influenced the decision, except for the criteria social status and health care profession.

Table 2 - Overview of the responses according to age, sex, religious denomination, and working in a health care profession.
Religion
Age Decision n [%] Mean Age (y), [95% CI] Female Sex, n [%] Protestant, n [%] Catholic, n [%] Atheist, n [%] Health Care Profession: No, n [%]
1. Patient A 1500 [92] 40 [39–40] 911 [56] 416 [35] 402 [33] 299 [25] 872 [54]
Patient B 37 [2] 38 [34–43] 23 [1] 9 [1] 7 [1] 8 [1] 27 [2]
Draw lots 88 [5] 46 [44–49] 50 [3] 21 [2] 23 [2] 18 [2] 67 [4]
2. Patient A 259 [16] 40 [38–41] 153 [9] 58 [5] 71 [6] 49 [4] 161 [10]
Patient B 135 [8] 37 [35–39] 65 [4] 37 [3] 31 [3] 34 [3] 93 [6]
Draw lots 1231 [76] 40 [40–41] 767 [47] 351 [29] 330 [27] 242 [20] 712 [44]
3. Patient A 183 [11] 40 [38–42] 106 [7] 51 [4] 39 [3] 35 [3] 127 [8]
Patient B 1044 [64] 40 [39–41] 622 [38] 280 [23] 282 [23] 217 [18] 554 [14]
Draw lots 398 [24] 40 [39–42] 256 [16] 115 [10] 111 [9] 73 [6] 285 [18]
4. Patient A 1427 [88] 40 [39–41] 860 [53] 394 [33] 375 [31] 290 [24] 820 [51]
Patient B 31 [2] 42 [37–48] 13 [1] 9 [1] 8 [1] 4 [0] 19 [1]
Draw lots 167 [10] 39 [37–41] 111 [7] 43 [4] 49 [4] 31 [3] 127 [8]
5. Patient A 54 [3] 41 [37–45] 21 [1] 13 [1] 14 [1] 13 [1] 33 [2]
Patient B 754 [46] 39 [38–40] 425 [26] 193 [16] 206 [17] 166 [14] 454 [28]
Draw lots 817 [50] 41 [40–42] 538 [33] 240 [20] 212 [18] 146 [12] 279 [30]
6. Patient A 514 [32] 41 [39–42] 296 [18] 135 [11] 132 [11] 87 [7] 340 [21]
Patient B 108 [7] 37 [34–40] 55 [3] 26 [2] 26 [2] 32 [3] 55 [3]
Draw lots 1003 [62] 40 [39–41] 633 [39] 285 [24] 274 [23] 206 [17] 571 [35]
7. Patient A 501 [31] 40 [39–42] 265 [16] 138 [11] 132 [11] 104 [9] 279 [17]
Patient B 131 [8] 42 [39–44] 77 [5] 30 [2] 29 [2] 21 [2] 88 [5]
Draw lots 993 [61] 39 [39–40] 642 [40] 278 [23] 271 [23] 200 [17] 599 [37]
8. Patient A 476 [29] 39 [38–41] 279 [17] 126 [10] 150 [12] 76 [6] 277 [17]
Patient B 606 [37] 39 [38–40] 361 [22] 167 [14] 154 [13] 143 [12] 343 [21]
Draw lots 543 [33] 41 [40–43] 344 [21] 153 [13] 128 [11] 106 [9] 346 [21]
9. Patient A 24 [1] 39 [33–45] 12 [1] 6 [1] 8 [1] 9 [1] 17 [1]
Patient B 989 [61] 41 [40–42] 568 [35] 277 [23] 254 [21] 189 [16] 619 [38]
Draw lots 612 [38] 39 [38–40] 404 [25] 163 [14] 170 [14] 127 [11] 330 [20]
10. Patient A 26 [2] 41 [34–47] 9 [1] 4 [0] 8 [1] 8 [1] 16 [1]
Patient B 1202 [74] 40 [40–41] 706 [43] 344 [29] 326 [27] 225 [19] 743 [46]
Draw lots 397 [24] 39 [38–40] 269 [17] 98 [8] 98 [8] 92 [8] 207 [13]
Discrepancies to 100 are due to rounding.
Significant differences are italicized (regarding health care profession, italic values marks difference to those not working versus working in health care).

Decision certainty

All participants together were more insecure about their decisions regarding age and behavior-associated comorbidities in comparison to other factors (Table 3). Female participants were generally more secure about their decisions than males. Atheists/agnostics were generally less secure about their decisions than protestant or catholic Christians.

Table 3 - Feeling of security about the decision according to participant characteristics (scale from 0 to 100).
Case Mean 95% CI
1. Age 38 36–39
2. Insurance status 46 44–48
3. Fateful comorbidities 45 44–46
4. Behavior-associated comorbidities 37 35–38
5. Health care profession 48 46–49
6. Asylum status—nationality 45 43–46
7. Social status 45 44–47
8. Chance of treatment success—prognosis 42 41–44
9. Consent 46 45–48
10. Responsibility for others 41 40–43
11. Male 41 40–43
12. Female 45 44–46
13. Diverse 54 12–97
14. Health care profession: yes 44 42–45
15. Health care profession: no 43 42–44
16. Protestant Christian 45 43–47
17. Catholic Christian 45 44–47
18. Atheist-agnostic 40 38–42
19. Other 41 39–43
Statistical significant values are italicized.
CI indicates confidence interval.

Discussion

To our knowledge, this is the first empirical survey study on triage attitudes of a cross-sectional population sample using social media distribution. This study shows that using this methodology, a relatively large sample of participants can be recruited in a short amount of time, thus promoting participatory processes so essential in democratic societies, particularly in the context of an ongoing crisis. This study gives insight into opinions and attitudes of a select sample of the German population on rationing life-saving therapies during the European peak of the corona-pandemic. It seems noteworthy, that during this peek, the rationing of scarce resources and triage was highly present in German (mass-) media, particularly with reference to the devastating situation in Northern Italy, parts of France, Spain, and most currently, hot-spots in the United States, where physicians were suddenly put in charge of what figuratively could be described as a Titanic with not enough life-boats. This led to a situation in which most Germans were at least confronted with—if not interested in—the concept of triage which they may have never heard of before. This was also one of the reasons for addressing the issue at the first European peak of the pandemic and sending out the questionnaire in a timely manner, using the window of opportunity to generate knowledge about values and beliefs in the general population to avoid the implementation of morally counterintuitive or socially inacceptable procedures in the process of preparing for the impact of the COVID-19 pandemic.

The word triage etymologically stems from the French verb trier, which means to sort or select. The principle of categorizing injured soldiers on the battleground according to their treatability was developed by the Napoleonic military physician Baron Dominique-Jean Larrey (1766–1842)14. Larrey also invented the so-called ambulances volantes, with which injured soldiers could be transported rapidly to the field lazaret. Once there, they were triaged according to acuity and prognosis, and received tailored treatment. The COVID-19 crisis has brought the concept of triaging scarce health care resources into the public discourse15.

Triage decisions are usually made according to utilitarian principles, so according to how the scarce resources must be distributed to afford most beneficence for the greatest number of patients. Superficially, this translates into the goal of simply saving the highest number of lives. However, upon closer examination, it becomes more complex. Should a young person be treated the same as a 93-year old? From a utilitarian perspective, one could argue that by favoring the younger patient, more life-years are saved. Should a patient in a vegetative state without a prospect of improvement receive the same chance of survival as a healthy individual who is mentally normal? With other words, in a difficult triage situation, should really every human life be valued and treated equally? The German ethics council demands that egalitarian principles should be followed, based on the dignity of every human person16. What appears obvious on first glance becomes challenging and counterintuitive in reality. Consequently, one can hardly blame physicians working in SARS-CoV-2 hotspots for including expected life-years and quality of life in their ad-hoc decisions of distributing lifesaving resources. Some authorities actually explicitly demand taking these factors into account17. From a socioeconomic standpoint, it may also be desirable for a society to prefer younger, more active and fertile individuals in the triage of lifesaving measures. In this sense, the call for “women and children first” may as well be regarded as a—possibly cynical—neoliberal attempt of pushing an otherwise unacceptable construct of human economic value.

On engaging deeper with this subject, one inevitably encounters John Rawls’ contractual approach18, in which the members of a society agree upon fair, universal rules behind an imaginary veil of ignorance. In our case, these rules pertain to the criteria which should be applied for triage in the event of a disaster such as the COVID-19 pandemic. The model is based on the premise that nobody knows which position one would occupy in such a situation. One could be anybody, the infant or the elderly individual, the rich or the poor, the smoker or the health fanatic. This study tries to emulate such a paradigm by presenting the different scenarios and allowing the participant to decide from an outside, noninvolved standpoint.

Nonetheless, it needs to be stressed that triage criteria should not be considered universal in the way it is usually understood in ethics, but varying according to the moral principles and priorities of a given society. While they must be adapted to a certain situation, this should not lead to complete moral relativism that is a fully fledged particularism, which may also be found as an argumentative position in ethical debates, particularly in very diverse societies. To facilitate a more pragmatic decision-making in the realm of clinical ethics, the results of this study must be viewed in light of basic, universal, and associative norms embedded in a larger framework of ethical principles, human dignity, and human rights in the sense of integrative particularisms.

Another aspect is how the triage should be conducted, what modality should be used. In the acute phase of a disaster, patients are often treated by chronologic sequence. Patients who arrive to the hospital earlier are treated first. As long as resources are available for all, this approach is fair. Once the available capacity is surpassed, however, this distribution becomes arbitrary and inherently unfair. Drawing lots provides every patient with the same chance of receiving therapy, however, this approach is only legitimate in patients presenting under the same circumstances and with the same prognosis, a prerequisite that is hardly imaginable in clinical practice. Acting upon set laws predetermined by the legislative alone would provide legal security, but strongly encroach on individual and situational treatment decisions. Expert panels that decide upon treatment allocation remotely have been criticized polemically as “death panels” in the context of the implementation of the Affordable Care Act in the United States19. In most western countries, ethics committees in the form of interdisciplinary advisory teams are available to consult on and solve complex triage dilemmas, while preserving autonomy of the patient and treating physicians.

The participants of this study most vehemently based their triage decisions on prognosis, age, and responsibility for others. They also regarded behavior-associated comorbidities as a negative criterion for receiving therapy. On the other hand, an overwhelming majority rejected insurance, social, and asylum status as factors in the triage process.

Concerning the triage modality, most were in favor of ethics committees and a point system. These are already commonplace in modern health care culture, as well as organ transplant systems. Since health care professionals were relatively overrepresented in the study sample, the responses can be interpreted as an affirmation of the existing triage mechanisms.

An additional interesting finding of our study is the influence of demographics. Older participants did not universally favor the older imaginary patients, but were more likely to draw lots. Women tended to employ randomization in questions of status more frequently, and overall seemed surer about their decision than men. Christians also expressed more certainty about their decisions than atheists/agnostics. This may be the result of an internalized religious moral framework that could help making triage decisions. The sample size of the other religions was too small to draw conclusions.

Since the beginning of the COVID-19 spread, several associations have published guidelines on triage. One of these was the German Interdisciplinary Association for Intensive Care and Emergency Medicine (Deutschen Interdisziplinären Vereinigung für Intensiv- und Notfallmedizin, DIVI)20. In these guidelines, the authors focus on the role of prognosis and consent of the patient and postulate that triage decisions should be made in consensus by the individuals involved in care. Aborting treatment of one patient in the interest of another is not admissible because of the German constitution, which highlights the dignity of every individual as equal. Also, prioritizing solely by age is also unacceptable. Other concrete criteria are not mentioned in this publication. As the COVID-19 pandemic progresses, a vast number of other professional organizations and associations have produced a myriad of guidelines and position papers, which can overwhelm the medical practitioner. Recently, Huxtable published a practical approach to determine the utility of these publications on the basis of source, applicability, and methodology21.

Our study provides an initial impulse to substantiate triage criteria in the context of the COVID-19 pandemic. By using case-based scenarios, we tried to include an emotional component in the decision process, beyond the participants’ abstract views on triage criteria.

However, it also has several limitations. The most obvious one is the fact that an online survey based on recruitment through social media does not necessarily confer a representative sample of society in general. In addition, those working in health care seemed over-represented. We cannot make any statements regarding recall, since the denominator of how many people actually were reached is lacking. What we have shown, however, is that a large group of people can be recruited through an online survey in a very short time, and that the interest was high enough so that almost half of those that clicked the link also completed the survey in whole. We interpret this finding as a general interest in the subject of triage, and a willingness to participate in the public discourse around the factors that should play a role. In the future, more precise and representative measurements may be obtained by using more elaborate distribution channels, focus groups, and more detailed demographic information.

Also, one may question whether the general public should be included in the discussion about triage criteria or not. While some may argue that categorical principles interpreted by experts in the relevant fields should receive priority, we strongly believe that it is appropriate and necessary in a democratic society to develop such criteria in a societal discourse and to facilitate participatory processes. In this regard, this study is also a small pilot test case for the implementation of such participation. Since a large part of this public exchange currently takes place on social media, we found it reasonable to evaluate whether these new technologies can be harnessed to foster a culture of participation and inclusion, even when the subject matter are complex ethical decisions. This study also shows that something as abstract as moral attitudes involved in medical triage can be quantified in an empirical study.

We suggest that the findings of this study are used as a backdrop for a broader public debriefing on triage criteria after the COVID-19 pandemic subsides. This should include a push to establish morally acceptable triage criteria and algorithms for future disasters and pandemics.

In conclusion, this study generated a snapshot of the attitudes of a sample of German-speaking participants regarding criteria and modalities for the allocation of life-saving, limited resources during the height of the COVID-19 pandemic. According to the participants, prognosis, responsibility toward others, the absence of behavior-associated comorbidities, along with younger age should be criteria for allocation of scarce ventilators. Insurance status, social status, as well as nationality and asylum status should not play a relevant role. Ethics-committees and a point system similar to what is used for organ transplantation were deemed potentially helpful in triage decision making. The findings and results of this study may be useful in creating future surveys addressed at a broader public. Similar but refined methods may be useful to expand future triage-algorithms by a dimension of societal consensus.

Presentation

This work has not been presented at a scientific meeting yet.

Provenance and peer review

Not commissioned, externally peer-reviewed.

Ethical approval

According to local laws, this study was deemed except from formal ethics board review.

Sources of funding

The work of NWP regarding concepts of rationing was partly funded through the DFG-grant “Graduiertenkolleg 2015/2,” Research Training Group “Life Sciences—Life Writing.” Other work is based on intramural funding.

Author contribution

O.J.M.: conception of this study, study design, creation of the online survey, data collection and processing, creating figures and tables, drafting and editing of the manuscript. E.A.G.: data processing, statistical analysis, editing tables, review and editing of manuscript. N.W.P.: mentoring and overseeing the master thesis, conception of the study, study design, co-drafting, review and editing manuscript.

Conflict of interest disclosures

The authors declare that they have no financial conflict of interest with regard to the content of this report.

Research registration unique identifying number (UIN)

The study was registered at http://www.researchregistry.com (Research Registry UIN 6207).

Guarantor

None.

Acknowledgments

The authors thank Grigorios Pilidis and Diana Walz for helping with the online survey on Lime. Thanks to the many participants in the survey that made this study possible.

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      Keywords:

      COVID-19; Intensive care; Survey; Triage; Medical ethics

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