APPENDIX 2: Strategies for reducing physician-related variability in end-oflife decision-making
1. Guidelines
In many areas of medicine, guidelines have been effective in improving the
process of care [1]. Yet, there are several reasons why guidelines may not be the
answer to variability in ELDM (at least not in isolation). In such contentious areas it is
extremely difficult to reach agreement or consensus [2-4]. Given genuine uncertainty
about the most appropriate course of action, there is a risk that guidelines end up
endorsing rules based on arbitrary thresholds or distinctions [5]. This is one of the
criticisms levelled at gestational-age based guidelines for resuscitation of premature
infants [6], as well as statistical definitions of ‘futility’ [7]. They may enumerate
specific medical or technical criteria, without a clear ethical justification, and at the
cost of individualised treatment [8, 9]. At the other extreme, difficulty in reaching
agreement may lead to guidelines that are unobjectionable, but unhelpfully vague, in
which case they will have little or no impact on variations in practice.
It may be useful to distinguish, though, between two different types of
guideline. Guidelines relating to the content of end-of-life decisions are likely to be
particularly sensitive to the above concerns about arbitrariness, disagreement, or
vagueness. An alternative type of guideline focuses on the process for decisionmaking. For example, recent guidelines and law relating to disputes about ostensibly
“futile” medical treatment have moved away from attempts to define futility, focusing
instead on developing a fair due-process for arbitrating and resolving disputes [10,
11].
2. Advance care planning/Patient decision-aids
If physician-related variability is more likely in the absence of clear
information about patients’ wishes (either for or against life prolonging treatment),
one solution would be to help patients communicate their values and preferences.
Facilitated advance care planning has been shown to improve the chance that patients’
end of life wishes are known and respected [12]. Patient decision-aids increase the
involvement of patients in decisions, and improve knowledge and understanding [13].
A small trial of a video developed to help end-of-life discussions with cancer patients
(compared with verbal description alone) found a substantial reduction in patients
DW
10/2/16
Page 1 of 5
choosing life-prolonging treatment [14, 15], and one that used video of actual patients
with dementia influenced the choices of patients considering end-of-life options [16].
However, one theoretical concern is that decision-aids generated by physicians could
reflect physician values, and hence bias decision-making. There may also be little
time or opportunity for critically ill patients to take advantage of this sort of tool.
3. Awareness/Self-awareness
Another alternative would be to use audit and feedback to improve physician’s
understanding of their own and their peers’ practice. For example, an audit of
involvement in ELDM would potentially make clinicians aware if they were involved
in more or fewer treatment withdrawal decisions than average. This could lead to
reflection on the influence of personal experience and values on decisions, and to a
greater acceptance of patient or surrogate values. In other settings audit and feedback
has been shown to improve professional practice [17], though the effect is modest,
and is most evident when the baseline level of compliance is low, and the feedback
intervention is more intense. Most studies of audit and feedback have taken place in
settings where there is a clear desired practice. It is not known whether this would be
effective in a contested and uncertain area such as ELDM. In one Canadian adult
intensive care unit a review of end-of-life care, which included an audit and feedback
process, reduced variability in the use of medications and led to a reduction in the
number of patients receiving cardio-pulmonary resuscitation [18].
4. Consensus/collaboration
Finally, variability in ELDM might be reduced by a shift from individual to
collective decision-making [19]. Population studies suggest that variations in medical
care are less in regions where more there is more coordinated, or ‘team’-based
practice [20]. In intensive care, greater consistency in ELDM might be expected in
units that have shared management of patients between different consultants, or where
ELDM are taken at a team level. This may also help address differences between
physicians in their assessment of the patient’s prognosis.
However, while the agreement of peers may reduce some variation, it may not
reduce variability that exists between different units. Furthermore, group decisions are
not always better than ones made by individuals [21]. Groups may be particularly
vulnerable to certain types of cognitive error or bias, and may together arrive at
DW
10/2/16
Page 2 of 5
decisions that no individual member would actually endorse [22, 23]. Collective
decisions in intensive care may still fail to respect the wishes of patients and their
families, particularly where their social or cultural background differs from that of a
group of physicians.
One form of collective decision-making that might reduce physician-related
variability is the use of ethics consultation. This is one of the few interventions for
ELDM that has been formally studied in intensive care. Two randomised trials of
routine ethics consultation in the ICU found that this reduced length of stay and the
use of life-sustaining interventions, without increasing overall mortality [24, 25].
Nevertheless, ethics consultation is only likely to be practicable in a subset of cases.
APPENDIX 2 REFERENCES
1.
Grimshaw JM, Russell IT (1993) Effect of clinical guidelines on medical
practice: a systematic review of rigorous evaluations. Lancet 342: 1317-1322.
2.
Batton D (2010) Resuscitation of extremely low gestational age infants: an
advisory committee's dilemmas. Acta Paediatr 99: 810-811. doi:
10.1111/j.1651-2227.2010.01753.x
3.
Brody BA, Halevy A (1995) Is futility a futile concept? J Med Philos 20: 123144.
4.
McCormick RA (1974) To save or let die. The dilemma of modern medicine.
JAMA 229: 172-176.
5.
Anderson-Shaw L, Meadow W, Leeds HS, Lantos JJ (2005) The fiction of
futility: what to do with policy? HEC Forum 17: 294-307.
6.
Wilkinson D (2012) Gestational ageism. Arch Pediatr Adolesc Med 166: 567572. doi: doi:10.1001/archpediatrics.2011.1262
7.
Pope TM (2007) Medical futility statutes: no safe harbor to unilaterally refuse
life-sustaining treatment. Tennessee Law Review 75: 1-81.
8.
Veatch RM (1977) The technical criteria fallacy. Hastings Cent Rep 7: 15-16.
9.
Woolf SH, Grol R, Hutchinson A, Eccles M, Grimshaw J (1999) Clinical
guidelines: potential benefits, limitations, and harms of clinical guidelines.
BMJ (Clinical research ed) 318: 527-530.
10.
Burns JP, Truog RD (2007) Futility: A Concept in Evolution. Chest 132:
1987-1993. doi: 10.1378/chest.07-1441
DW
10/2/16
Page 3 of 5
11.
Stewart C (2011) Futility Determination as a Process: Problems with Medical
Sovereignty, Legal Issues and the Strengths and Weakness of the Procedural
Approach. Journal of Bioethical Inquiry 8: 155-163. doi: 10.1007/s11673-0119297-z
12.
Detering KM, Hancock AD, Reade MC, Silvester W (2010) The impact of
advance care planning on end of life care in elderly patients: randomised
controlled trial. BMJ 340: c1345. doi: 10.1136/bmj.c1345
13.
Stacey D, Bennett CL, Barry MJ, Col NF, Eden KB, Holmes-Rovner M,
Llewellyn-Thomas H, Lyddiatt A, Legare F, Thomson R (2011) Decision aids
for people facing health treatment or screening decisions. Cochrane Database
of Systematic Reviews: -. doi: 10.1002/14651858.CD001431.pub3
14.
El-Jawahri A, Podgurski LM, Eichler AF, Plotkin SR, Temel JS, Mitchell SL,
Chang Y, Barry MJ, Volandes AE (2010) Use of video to facilitate end-of-life
discussions with patients with cancer: a randomized controlled trial. J Clin
Oncol 28: 305-310. doi: 10.1200/JCO.2009.24.7502
15.
Volandes AE, Barry MJ, Chang Y, Paasche-Orlow MK (2010) Improving
decision making at the end of life with video images. Med Decis Making 30:
29-34. doi: 10.1177/0272989X09341587
16.
Volandes AE, Paasche-Orlow MK, Barry MJ, Gillick MR, Minaker KL,
Chang Y, Cook EF, Abbo ED, El-Jawahri A, Mitchell SL (2009) Video
decision support tool for advance care planning in dementia: randomised
controlled trial. BMJ 338: b2159. doi: 10.1136/bmj.b2159
17.
Jamtvedt G, Young JM, Kristoffersen DT, O'Brien MA, Oxman AD
(2006) Audit and feedback: effects on professional practice and health care
outcomes. Cochrane database of systematic reviews (Online): CD000259. doi:
10.1002/14651858.CD000259.pub2
18.
Hall RI, Rocker GM, Murray D (2004) Simple changes can improve conduct
of end-of-life care in the intensive care unit. Can J Anaesth 51: 631-636. doi:
10.1007/BF03018408
19.
Azoulay E, Pochard F, Garrouste-Orgeas M, Moreau D, Montesino L, Adrie
C, de Lassence A, Cohen Y, Timsit J-F, Group OS (2003) Decisions to forgo
life-sustaining therapy in ICU patients independently predict hospital death.
Intensive Care Med 29: 1895-1901. doi: 10.1007/s00134-003-1989-3
20.
Wennberg JE (2011) Time to tackle unwarranted variations in practice. BMJ
342: 687-690. doi: 10.1136/bmj.d1513
21.
Spielman B (1994) Collective decisions about medical futility. J Law Med
Ethics 22: 152-160, discussion 161-152.
22.
Janis IL (1982) Groupthink : psychological studies of policy decisions and
fiascoes. Houghton Mifflin, Boston
23.
Sunstein CR (2007) Deliberating Groups vs. Prediction Markets (or Hayek's
Challenge to Habermas). Episteme 3: 192-213.
24.
Schneiderman LJ, Gilmer T, Teetzel HD, Dugan DO, Blustein J, Cranford R,
Briggs KB, Komatsu GI, Goodman-Crews P, Cohn F, Young EW (2003)
DW
10/2/16
Page 4 of 5
Effect of ethics consultations on nonbeneficial life-sustaining treatments in the
intensive care setting: a randomized controlled trial. JAMA 290: 1166-1172.
25.
Schneiderman LJ, Gilmer T, Teetzel HD (2000) Impact of ethics consultations
in the intensive care setting: a randomized, controlled trial. Crit Care Med 28:
3920-3924.
DW
10/2/16
Page 5 of 5