Advance care planning for patients with ALS - Making Your Wishes ...

Amyotrophic Lateral Sclerosis, 2011; 12: 172–177

ORIGINAL ARTICLE

Advance care planning for patients with ALS: Feasibility of an interactive computer program

Amyotroph Lateral Scler Downloaded from informahealthcare.com by Dr. Zachary Simmons on 05/06/11 For personal use only.

CARRIE HOSSLER1, BENJAMIN H. LEVI2,3, ZACHARY SIMMONS4 & MICHAEL J. GREEN2,5 Departments of 1Ob/Gyn, 2Humanities, 3Pediatrics, 4Neurology, and 5Medicine, Penn State College of Medicine, Hershey, Pennsylvania, USA

Abstract This pilot study examined whether an interactive, computer based decision aid can help patients with amyotrophic lateral sclerosis (ALS) engage in effective advance care planning. Individuals being treated for ALS (ⱖ18 years old, English speaking, and without dementia) were recruited to use a decision aid and complete pre-/post-intervention measures. Seventeen individuals completed the pre-intervention questionnaires and decision aid; 16/17 (94%) completed the postintervention measures, and none reported any burden from the intervention. ‘Overall satisfaction’ with the decision aid was very high (mean ⫽ 8.5 ⫾ 0.27: 1 ⫽ not at all satisfied, 10 ⫽ extremely satisfied), as was ‘perceived accuracy’ of the computer generated advance directive in reflecting patients’ wishes (mean ⫽ 8.6 ⫾ 0.27: 1 ⫽ not at all accurate, 10 ⫽ extremely accurate). Participants judged the ‘amount of information’ provided by the intervention appropriate (mean ⫽ 6.8 ⫾ 0.38: 1 ⫽ too little, 5 ⫽ about right, 10 ⫽ too much), and on a detailed, 12-item assessment judged the decision aid very positively (mean ⫽ 4.16 ⫾ 0.16: 1 ⫽ very dissatisfied, 5 ⫽ very satisfied). The intervention prompted many participants to discuss advance care planning with loved ones and to share their computer generated advance directive with their physician. This study demonstrates that individuals with ALS can successfully complete a computer based decision aid for advance care planning, and suggests that this intervention can help promote effective advance care planning. Key words: Advance care planning, advance directive, living will, decision aid, amyotrophic lateral sclerosis, surrogate decision making, ethics

Introduction Amyotrophic lateral sclerosis (ALS) usually culminates in death by respiratory failure, with a mean survival of 27–43 months from onset of symptoms (1,2). The inexorable progression and lack of a treatment to alter the fatal outcome underscore the importance to patients and their families of planning for the future. Lack of planning can lead to medical decisions being made on an urgent basis rather than with foresight and planning (3,4), unintended financial burdens to patients, families, and society (5,6), and moral distress for those who must make the healthcare decisions (7–9). Multiple studies have demonstrated that neither families nor physicians accurately predict what life-sustaining treatments patients want (10–14), and this situation cannot be

remedied without explicit discussion and planning in advance. Despite these factors, only 15–35% of American adults have advance directives documenting their wishes (15–18). Low completion rates (27%) persist even among patients who are critically ill with cancer (19), undergoing dialysis (35%) (20), or have ALS (30%) (21). In an effort to improve the process of advance care planning, ‘Making Your Wishes Known: Planning Your Medical Future’ (22,23) was developed. This is an interactive, computer based decision aid for advance care planning that guides people as they make choices, helping users clarify and prioritize their values before translating their wishes and goals into a medical plan. It takes an educational approach, simulating the kind of idealized discussion one might

Correspondence: B. H. Levi, Departments of Humanities and Pediatrics, Penn State College of Medicine, C1743 500 University Drive, Hershey, Pennsylvania 17033, USA. Fax: 717 531 3894. E-mail: [email protected] (Received 2 April 2010 ; accepted 16 July 2010 ) ISSN 1748-2968 print/ISSN 1471-180X online © 2011 Informa Healthcare DOI: 10.3109/17482968.2010.509865


Advance care planning for patients with ALS have with a healthcare professional who is well informed and has ample time. While not intended to take the place of a discussion between a doctor and patient, it can help users make more informed decisions about end-of-life care when creating an advance directive. Using multi-attribute utility theory (MAUT) (24,25), the decision aid helps translate values and goals into a meaningful, usable advance directive that reflects an individual’s healthcare wishes and outlines a plan for how they wish to be treated (see Appendix 1 for a sample advance directive). Previous pilot studies with healthy volunteers have demonstrated high user satisfaction, accuracy in representing individuals’ wishes, and utility in helping physicians make treatment decisions that are consistent with patients’ wishes (26,27). In this paper we describe a pilot study to evaluate the feasibility of ‘Making Your Wishes Known’ for helping patients with ALS engage in advance care planning. Materials and methods

strength and/or coordination communicated their choices to a researcher (CH) or a loved one who operated the computer mouse. Upon completion of the program, each participant received a printed copy of their individualized advance directive. Post-intervention Two post-intervention instruments were administered to each of the first 10 participants: 1. 2.

Pre-intervention Two pre-intervention instruments were administered: 1. 2.

Participant characteristics (22 item – demographics and subjective health assessment) Self-determination (8 item – assesses individuals’ sense of control over future treatments, adapted from Pellino) (28)

Additional data on functional status and quality of life were recorded from patients’ charts, using scores on the ALS-Specific QoL scale (29) and the ALS Functional Rating Scale-Revised ALSFRS-R) (30).

Computer intervention Subjects navigated their own way through the computer program. Those with insufficient upper extremity

Self-determination (same as pre-intervention) Satisfaction with advance care planning (15 item – assesses comprehensibility, length, pace, amount of information, balance, and satisfaction with the program)

Three additional instruments were added for the remaining participants after it was determined that completing the post-intervention questionnaires was feasible for this study population. 3.

Recruitment, screening and eligibility Individuals being treated for amyotrophic lateral sclerosis (ALS) at Penn State Milton S. Hershey Medical Center (PSHMC) were eligible to participate in this study. A recruitment letter from the ALS clinic medical director was sent to all clinic patients with definite, probable, probable laboratory-supported, or possible, ALS, along with an opt-out enclosure that was self-addressed and stamped. Over an eightweek period, all patients deemed by the medical director to be cognitively intact and not too emotionally unstable to discuss the issue of advance care planning were approached to participate. Approval for this study was obtained from the PSHMC Human Subjects Protection Office, and informed consent was elicited from each participant prior to the administration of any study activity.

173

4.

5.

Decisional conflict (16 item – assesses perceptions and feeling of uncertainty about decisions) (31) Satisfaction with decision (6 item – assesses individuals’ satisfaction with their choices) (32) Time and effort (3 item – assesses perceived burden from completing study exercises)

Statistical analysis As a feasibility study, this investigation was not powered to detect statistically significant differences among measured outcomes, but rather was designed to examine whether individuals with ALS could use the computer based decision aid and complete preand post-intervention instruments. As such, data analysis consists of descriptive statistics of all measures, with means and standard errors provided for continuous variables, frequency distributions for categorical variables, and t-test results for pre-/post-intervention measures.

Results Demographics and experience with advance care planning Seventeen subjects were enrolled and completed the study protocol. The majority was white, middle-aged or older, married, and had at least a high school education. The average subject was moderately physically impaired, as measured by the ALSFRS-R (see Table I). Approximately three-quarters of participants reported having read or heard “a lot” (35%) or “a fair amount” (41%) about advance care planning or living wills, while only 24% reported having read or heard “a little” (18%) or “almost nothing” (6%). Almost two-thirds of participants

174 C. Hossler et al. Table I. Participant demographic characteristics (n ⫽ 17).


Characteristic Age in years, mean (range) Gender Female Male Race White Other Duration of disease Mean (months) ALS Functional Rating-Revised* Mean ALS Quality of Life** Mean Physical subscore Highest education Elementary school High school graduate College graduate Postgraduate Religion Catholic Protestant or other Christian Other No formal religion Marital status Married Single Widowed Employment status Employed Unemployed Retired Disabled

Percent (unless otherwise noted)

completed the ‘Time and effort’ instrument (n ⫽ 6) reported that completion of the study activities involved “no burden”.

60.6 (44–86)

Satisfaction with the computer-based decision aid 41 59 94 6 44 ⫾ 4.7 28 ⫾ 1.7 6.0 ⫾ 0.2 6.4 ⫾ 0.5 6 53 29 12 18 59 18 6 82 6 12 6 6 65 24

*ALS

Functional Rating scale ranges from 0 to 48, with higher scores indicating greater function. **ALS-Specific Quality of Life scale ranges from 1 to 10, with higher scores indicating better quality of life, and ‘physical’ being one section of this instrument that uses the same 1–10 scale.

Across the 12 items assessing satisfaction with the computer based decision aid (where 1 ⫽ very dissatisfied, 5 ⫽ very satisfied), the mean rating was 4.2 ⫾ 0.16. The highest rated item was “How satisfied are you with the way the computer program presented information?” (4.4 ⫾ 0.13); the lowest rated item (3.9 ⫾ 0.18) was “How satisfied are you with the way the computer program helped you to choose a spokesperson?” (see Figure 1). Three additional items on the satisfaction instrument also showed very high ratings: 1) ‘Overall satisfaction’ with the computer program (mean ⫽ 8.5 ⫾ 0.27, 1 ⫽ not at all satisfied, 10 ⫽ extremely satisfied); 2) ‘Perceived accuracy’ of the advance directive at reflecting one’s wishes for end-of-life healthcare (mean ⫽ 8.6 ⫾ 0.27, 1 ⫽ not at all accurate, 10 ⫽ extremely accurate); and 3) ‘Amount of information provided’ by the computer program (mean ⫽ 6.8 ⫾ 0.38, 1 ⫽ too little, 5 ⫽ about right, 10 ⫽ too much). Effect of computer intervention on self-determination Participants had a strong sense of self-determination both before and after the intervention. Across the eight items on this scale (where 1 ⫽ lowest level of self-determination, 5 ⫽ highest level of self-determination), there was no significant change pre- versus post-intervention, with a mean score (each time) of 4.3 (see Figure 2). Other results

already had some form of advance directive, and over 80% had formally assigned someone to be their spokesperson. All but three participants reported owning a computer, with an average usage of 12 h per week (range 1–40). Those who did not own a computer reported they did not feel comfortable or confident using a computer. However, no participant reported that using a computer made them nervous.

The six participants who evaluated their ‘Satisfaction with decision’ and ‘Decisional conflict’ reported being very satisfied with the decisions they had made (mean ⫽ 9.7 ⫾ 0.70, where 6 ⫽ greatest satisfaction, 30 ⫽ least satisfaction) and having very little conflict about their decisions (mean ⫽ 1.6 ⫾ 0.11, where 1 ⫽ least conflict, 5 ⫽ greatest conflict).

Discussion Completion rates

Primary goals of study

All 17 participants were able to complete the pre-intervention questionnaires and the computer based decision aid, including creating an advance directive. Due to the emotional distress (of the spouse), one participant did not complete all the post-intervention questionnaires. Participants spent an average of 11 min to complete pre-intervention questionnaires, 68 min (range 45–140 min) to complete the computer intervention, and 13 min for post-intervention questionnaires. All individuals who

This pilot study demonstrates that individuals with ALS can successfully complete a computer based decision aid for advance care planning. It also suggests that it is a useful tool for helping patients with ALS engage in advance care planning, insofar as study participants report being highly satisfied with how the program 1) provides information, 2) helps them clarify their values and wishes for medical treatment, 3) puts these wishes into words in the form of an advance directive, and 4) prepares them to discuss

Advance care planning for patients with ALS

175

Satisfaction with computer based decision aid (n = 16) 4.2

Helped prepare you to discuss your wishes with your family

4.1

Helped prepare you to discuss your wishes with your doctor Helped you put your wishes into words

4.2

Helped you make end-of-life healthcare decisions

4.1 3.9

Helped you choose a spokesperson

4.3

Helped you feel greater control over future health

4.3

Helped clarify you wishes regarding helathcare


Helped clarify your values

4.1

Provided information about medical treatment

4.1

Provided information about medical conditions

4.1

Increased knowledge about ACP

4.3

Presented information

4.4 0

1

2

3

4

5

Satisfaction Rating (1 = low, 5 = high) Figure 1. Satisfaction with computer based decision aid.

their wishes with others. That most participants reported some prior experience with advance care planning further suggests that standard, existing strategies for advance care planning may not meet patients’ needs. Although most of the 17 participants had clinically significant physical limitations, all were able to complete the computer program and none perceived the intervention or questionnaires as burdensome, including the six who completed the expanded set of questionnaires. Because the age and functional status of our participants were similar to

those of a large, multicenter study (33), this is encouraging for the clinical prospects of using this computer based decision aid with ALS patients, as well as for the research implications for similar computer based interventions. It was not uncommon for participants and loved ones to become emotional while completing the advance directive. Nonetheless, these preliminary data suggest that individuals with ALS who completed this computer based decision aid had little conflict regarding the decisions made in the course of the computer program and were very satisfied with those decisions.

Pre-intervention

Self Determination (Pre-intervention, n = 17; Post-intervention, n = 16)

Post-intervention 4.5 4.5

I can make my wishes known. I can plan for my future medical needs.

4.3 4.3

I can effectively communicate my wishes to my doctors

4.4 4.3 4.5 4.6

I can effectively communicate my wishes to my loved ones. I have control over what medical treatments I receive.

4.4 4.4

I believe my wishes will influence my medical care even in I am unable to...

4.3 4.4

I can influence the medical decisions that my doctors make for me.

4.0 4.3 3.8 4.1

I have the power to affect what heppens to me in the future. 0

1

2

3

4

5

Self Determination (1 = Low, 5 = High) Figure 2. Self-Determination.

176 C. Hossler et al.


A stimulus for conversation Prior research on advance care planning and ALS has found that both clinicians and patients delay engaging in advance care planning discussions, despite the value of addressing these issues (34). It should be reassuring to clinicians that participants in this study often expressed to the research team their appreciation for the opportunity to complete an advance directive, and commented that completing the decision aid left them more informed about advance care planning and clearer about their own wishes for end-of-life care. Many participants completed the computer based decision aid in the presence of a spouse or loved one, which frequently led to detailed discussions about what was most important to them as they approached death. These conversations often went far beyond the questions presented in the computer program, demonstrating that participants were thinking seriously about their medical futures, and not simply ‘completing an advance directive’. For some individuals, these discussions seemed to be a more refined version of a familiar conversation. For others, it appeared to be the first time they had found a way to have this important conversation. Relatedly, some participants chose to provide copies of their new advance directive to their physicians, often commenting how they hoped to discuss their decisions with their physicians. This suggests that this computer based advance care planning program has the potential to be a springboard for meaningful dialogue with family, friends, healthcare providers, and others about values and goals, not just specific treatments (35–37). In ongoing research, we are examining whether this intervention 1) improves knowledge and decisionmaking among patients with ALS, 2) increases the ALS medical team’s awareness of their patients’ healthcare wishes, and 3) has any effect on patient anxiety, decisional conflict, or sense of self-determination. There are several features of this study that limit its generalizability. First, there were only 17 participants from a single university center. Although the average age and the gender distribution of our patients are similar to those of the ALS patient population overall, there may be other ways in which our participants are not representative of the broader population of individuals with ALS. Secondly, though most patients we approached agreed to participate, some declined and there are no data comparing participants with non-participants. Nonetheless, as a pilot study the primary aim was to determine the feasibility of using a computer based intervention for advance care planning with patients with ALS, and this was accomplished successfully.

Conclusions By guiding users through a step-by-step reflective and educational process, a computer based program can help individuals with ALS create an advance

directive that is medically informed, consistent with their underlying values and preferences, and easy to update. Results of this pilot study suggest that this program can serve as an effective and rewarding method for engaging individuals with ALS in advance care planning. Additional research is needed to determine whether such advance care planning actually leads to better communication with others and to end-of-life medical decision-making that is more respectful of patient autonomy by being more consistent with patients’ values and goals.

Acknowledgements This research was supported by grants from the Penn State University Social Science Research Institute. Benjamin Levi and Michael Green have intellectual property and copyright interests for the decision aid used for this study, and anticipate making the decision aid available through Penn State University as a marketed product.

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

References 1. Ganzini L, Johnston WS, Silveira MJ. The final month of life in patients with ALS. Neurology. 2002;59:428–31. 2. Lechtzin N, Wiener CM, Clawson L, Chaudhry V, Diette GB. Hospitalization in amyotrophic lateral sclerosis: causes, costs, and outcomes. Neurology. 2001;56:753–7. 3. Chochinov HM, Tataryn D, Clinch JJ, Dudgeon D. Will to live in the terminally ill. Lancet. 1999;354:816–9. 4. Upadya A, Muralidharan V, Thorevska N, AmoatengAdjepong Y, Manthous CA. Patient, physician, and family member understanding of living wills. Am J Respir Crit Care Med. 2002;166:1430–5. 5. Emanuel EJ, Emanuel LL. The economics of dying: the illusion of cost savings at the end of life. N Engl J Med. 1994;330:540–4. 6. Teno J Lynn J Phillips R Younger S Connors A Oye B Desbiens N et al. Do advance directives save resources? Clin Res. 1993;41:551. 7. Curtis JR, Patrick DL, Caldwell ES, Collier AC. Why don’t patients and physicians talk about end-of-life care? Barriers to communication for patients with acquired immunodeficiency syndrome and their primary care clinicians. Arch Intern Med. 2000;160:1690–6. 8. Hawkins NA, Ditto PH, Danks JH, Smucker WD. Micromanaging death: process preferences, values, and goals in end-of-life medical decision making. Gerontologist. 2005; 45:107–17. 9. Steinhauser KE, Christakis NA, Clipp EC, McNeilly M, Grambow S, Parker J, et al. Preparing for the end of life: preferences of patients, families, physicians, and other care providers. J Pain Symptom Manage. 2001;22:727–37. 10. Coppola KM, Ditto PH, Danks JH, Smucker WD. Accuracy of primary care and hospital based physicians’ predictions of elderly outpatients’ treatment preferences with and without advance directives. Arch Intern Med. 2001;161:431–40. 11. Miura Y, Asai A, Matsushima M, Nagata S, Onishi M, Shimbo T, et al. Families’ and physicians’ predictions of

Advance care planning for patients with ALS

12.

13.

14.


15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

dialysis patients’ preferences regarding life-sustaining treatments in Japan. American Journal of Kidney Diseases. 2006;47:122–30. Pruchno RA, Lemay EP Jr, Feild L, Levinsky NG. Predictors of patient treatment preferences and spouse substituted judgments: the case of dialysis continuation. Med Decis Making. 2006;26:112–21. Shalowitz DI, Garrett-Mayer E, Wendler D. The accuracy of surrogate decision makers: a systematic review. Arch Intern Med. 2006;166:493–7. Zettel-Watson L, Ditto PH, Danks JH, Smucker WD. Actual and perceived gender differences in the accuracy of surrogate decisions about life-sustaining medical treatment among older spouses. Death Studies. 2008;32:273–90. Salmond SW, David E. Attitudes toward advance directives and advance directive completion rates. Orthopaedic Nursing. 2005;24:117–27. Sessanna L, Jezewski MA. Advance directive decision making among independent community-dwelling older adults: a systematic review of health science literature. Journal of Applied Gerontology. 2008;27:486–510. Jezewski MA, Meeker MA, Sessanna L, Finnell DS. The effectiveness of interventions to increase advance directive completion rates. Journal of Aging and Health. 2007;19:519–36. McAuley WJ, Buchanan RJ, Travis SS, Wang S, Kim M. Recent trends in advance directives at nursing home admission and one year after admission. Gerontologist. 2006;46:377–81. Kish SK, Martin CG, Price KJ. Advance directives in critically ill cancer patients. Crit Care Nurs Clin North Am. 2000;12:373–83. Holley JL, Stackiewicz L, Dacko C, Rault R. Factors influencing dialysis patients’ completion of advance directives. Am J Kidney Dis. 1997;30:356–60. Borasio GD, Shaw PJ, Hardiman O, Ludolph AC, Luis MLS, Silani V, et al. Standards of palliative care for patients with amyotrophic lateral sclerosis: results of a European survey. Amyotroph Lateral Scler Other Motor Neuron Disord. 2001;2:159–64. Green MJ, Levi BH. Development of an interactive computer program for advance care planning. Health Expectations. 2009;12:60–9. Levi BH, Green MJ. Too Soon to Give Up? Re-examining the value of advance directives. American Journal of Bioethics. 2010;10:1–14. Jain NL, Kahn MG. Using knowledge maintenance for preference assessment. Proc Annu Symp Comput Appl Med Care. 1995:263–9.

Supplementary material available online Supplementary Appendix is only available in the online version of the journal. Please find this material with the following direct link to the article: http://www.infor mahealthcare.com/doi/suppl/ 10.3109/17482968.2010.509865

177

25. Torrance GW, Feeny DH, Furlong WJ, Barr RD, Zhang Y, Wang Q. Multi-attribute utility function for a comprehensive health status classification system. Health Utilities Index Mark 2. Med Care. 1996;34:702–22. 26. Green MJ, Levi BH, Farace E. Acceptability and accuracy of a computer-generated advance directive. Society for Medical Decision Making, 29th National Meeting; October 23; Pittsburgh, PA 2007. 27. Levi BH, Green MJ, Heverley SR. Accuracy of a decision aid for advance care planning. Association for Bioethics & Humanities National Meeting; October 15; Washington, D.C. 2009. 28. Pellino T, Tluczek A, Collins M, Trimborn S, Norwick H, Engelke ZK, et al. Increasing self-efficacy through empowerment: preoperative education for orthopedic patients. Orthop Nurs. 1998;17:48–51, 4–9. 29. Simmons Z, Felgoise SH, Bremer BA, Walsh SM, Hufford DJ, Bromberg MB, et al. The ALSSQoL: balancing physical and non-physical factors in assessing quality of life in ALS. Neurology. 2006;67:1659–64. 30. Cedarbaum JM, Stambler N, Malta E, Fuller C, Hilt D, Thurmond B, et al. The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function. Journal of the Neurological Sciences. 1999;169:13–21. 31. O’Connor AM. Validation of a decisional conflict scale. Med Decis Making. 1995;15:25–30. 32. Holmes-Rovner M, Kroll J, Schmitt N, Rovner DR, Breer ML, Rothert ML, et al. Patient satisfaction with health care decisions: the satisfaction with decision scale. Med Decis Making. 1996;16:58–64. 33. Felgoise SH, Stewart JL, Bremer BA, Walsh SM, Bromberg MB, Simmons Z. The SEIQoL-DW for assessing quality of life in ALS: strengths and limitations. Amyotroph Lateral Scler. 2008;10(5–6):456–62. 34. Burchardi N, Rauprich O, Hecht M, Beck M, Vollmann J. Discussing living wills: a qualitative study of a German sample of neurologists and ALS patients. Journal of the Neurological Sciences. 2005;237:67–74. 35. Martin DK, Emanuel LL, Singer PA. Planning for the end of life. Lancet. 2000;356:1672–6. 36. Tulsky JA. Beyond advance directives: importance of communication skills at the end of life. JAMA. 2005;294: 359–65. 37. Fins JJ. Commentary: from contract to covenant in advance care planning. Journal of Law Medicine & Ethics. 1999; 27:46–51.