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. Author manuscript; available in PMC: 2022 Oct 1.
Published in final edited form as: J Pain Symptom Manage. 2021 Mar 12;62(4):805–812. doi: 10.1016/j.jpainsymman.2021.03.003

Engagement in Non-Medical End-of-Life Planning by Older Adults

Stephanie S Tu 1, John R O’Leary 2,3, Terri R Fried 3,4
PMCID: PMC8435038  NIHMSID: NIHMS1683202  PMID: 33716035

Abstract

Context:

While medical end-of-life planning has been well characterized, less is known about non-medical planning to prepare for the end of life.

Objectives:

To determine the prevalence of engagement in non-medical end-of-life (EOL) planning and its relationship to medical EOL planning.

Methods:

304 persons age 65 and older recruited from physician offices and a senior center were administered an in-person interview asking about participation in the following non-medical EOL planning behaviors: moving to a location with more help, teaching someone to do things around the house, purchasing long-term care insurance, telling someone the location of important documents, preparing a financial will, conveying wishes for funeral arrangements, purchasing a cemetery plot, and prepaying for a funeral.

Results:

Prevalence of participation in the different non-medical EOL planning activities varied widely, from 8% for prepaying for a funeral to 84% for telling someone the location of important documents. There was little overlap in the factors associated with participation in each activity. Conveying wishes for funeral arrangements and completing a financial will were associated with completing a living will (OR 2.69, 95% CI 1.51, 4.78; OR 6.70, 95% CI 3.18, 14.15) and communication about quality versus quantity of life (OR 4.52, 95% CI 2.54, 8.04; OR 2.47, 95% CI 1.25, 4.86).

Conclusion:

There is variability in both the prevalence of and factors associated with engagement in non-medical EOL planning activities. The association of non-medical with medical planning activities supports the utility of programs assisting individuals with broad engagement in EOL planning.

Keywords: advance care planning, patient care planning, end-of-life care

Editor’s Note:

Arif H Kamal MD, MBA, MHS - This survey study is among the first to describe the prevalence of family participation in non-medical end of life planning, and the association with sociodemographic and other factors. This work highlights the need for a greater understanding of non-medical steps in EOL planning, the role of palliative care specialists and other clinicians in assisting with such tasks, and the potential for interventions for stressed patients and their families.

INTRODUCTION

Advance care planning (ACP) is most commonly conceptualized as planning for the kinds of medical care that an individual will receive at the end of life (EOL).1 However, there are additional tasks that individuals need to complete to prepare for the EOL. These fall into three categories, including practical considerations (e.g. living arrangements and telling someone the location of important documents), financial preparation (e.g. preparing a financial will and purchasing long-term care insurance [LTCI]), and funeral arrangements.2–3 Broadly, advance EOL planning can be divided into medical and non-medical planning.

While the prevalence and correlates of medical EOL planning have been well described,4–5 much less is known about non-medical EOL planning. Patients with advanced malignancies in a qualitative study cited a need for both medical and financial planning to be prepared for EOL.6 Most quantitative studies have examined only a single non-medical planning activity.7–9 There is, however, some evidence to support the interrelation of these activities. Several studies have shown that higher education and/or wealth is associated with an increased likelihood of having completed both medical and financial planning10–12 and one that higher wealth is also associated with an increased likelihood of completing both medical and funeral planning.10

The purpose of the current study was to provide a comprehensive description of a full range of non-medical EOL planning activities among community-living older persons and an analysis of the factors associated with these activities. In addition, in order to provide more direct evidence regarding the interrelatedness of non-medical and medical EOL planning, the study examined the associations between these two sets of activities.

METHODS

Participants

Participants aged 65 and older were recruited from two primary care practices and one senior center. These sites were selected because they provided services to a group of older persons with diversity in race, socioeconomic status, and health status reflecting the greater New Haven area. In the primary care practices, letters were sent to sequential persons aged 65 and older whose physicians indicated that they did not have a diagnosis of dementia. Persons who agreed (92% and 88% in the two practices) underwent a telephone screen to determine exclusion criteria: non-English speaker (7% and 2%), hearing loss precluding participation in interview (7% and 1%), nursing home resident (0% and 1%), acute episode of illness (8% and 4%), and cognitive impairment (<2/3 recall on a test of short-term memory; 7% and <1%). Of eligible participants, 83% and 80% completed interviews. In the senior center, volunteers were solicited for participation. Everyone who volunteered at the senior center was eligible for participation and completed interviews.

Data Collection

Trained research assistants interviewed participants in person. Participants were asked if they had completed the following non-medical EOL planning activities: making plans or moving somewhere to get more help with daily activities, teaching someone how to do things around the house, purchasing LTCI, telling someone where the participant keeps important papers, completion of a financial will, conveying wishes about funeral arrangements, pre-paying for the funeral, and purchasing a cemetery plot or making arrangements for cremation. Participants were also asked if they had completed each of the four following medical EOL planning activities: completing a living will, naming a healthcare proxy, communication with loved ones about the use of life support, and communication with loved ones about quality versus quantity of life. The interview also included measures of sociodemographic status (age, ethnicity, race, education, sufficiency of monthly income, marital status, and employment status). Health status measures included self-rated health, assessed using the single-item measure: “In general, would you say your health is…” with response categories of excellent, very good, good, fair, and poor. As in prior studies, we compared those who rated their health as fair or poor with those who rated their health as good or better.13 Also included was global quality of life, assessed using the single-item measure: “How would you rate your overall quality of life?” with response categories of best possible, good, fair, poor, or worst possible. We compared those who rated their quality of life as fair, poor, or worst possible with those who rated their quality of life as good or best possible. Function was assessed using the instrumental activities of daily living scale.14 Depression was assessed using the PHQ-2 with a cut off of ≥ 2 used to identify depression.15 Executive function was measured using 3 items from the EXIT interview (number-letter task, word fluency, and memory/distraction task), in which higher scores indicate greater dysfunction,16 and health literacy was assessed using the REALM, using the established scoring to compare those with at least a high-school level of health literacy to those with lower literacy levels.17 In order to assess participants’ experiences with end-of-life decision-making, they were asked whether they had ever made a medical decision for someone who was dying.

Analysis

Univariate statistics were used to describe the study population and the prevalence of non-medical EOL planning. We examined the association between the sociodemographic, health, cognitive, and experience variables with each of the non-medical EOL planning activities in bivariate analysis using the chi-square test. Variables associated with P<.20 were entered into a logistic regression analysis with backward elimination. We did not examine those non-medical planning activities for which the vast majority of participants had either performed the activity (>80%) or had not performed the activity (<20%). We examined the association between non-medical and medical EOL planning activities in logistic regression analysis adjusting for factors known to be associated with ACP from prior studies4, 18–19 and/or associated with multiple non-medical planning activities in the current analysis: age, gender, education, employment status, finances, and self-rated health. We created a separate logistic regression mode for each of the medical EOL planning activities, entering the non-medical EOL planning activities and covariates into each model.

RESULTS

A description of the sociodemographic and health status of the participants in provided in Table 1. There was wide variability in the proportions of participants who completed each of the non-medical EOL planning activities (Table 1). Whereas fewer than 10% had pre-paid for a funeral, 70% had prepared a financial will and over 80% had told somewhere where they keep important papers. About a one-fourth had made plans or moved somewhere to get more help with daily activities, purchased LTCI, and taught someone to do things around the house. Nearly half had conveyed wishes for funeral arrangements and prepaid for a funeral by purchasing a cemetery plot or making arrangements for cremation.

Table 1:

Description of Participants (N=304) and their Participation in Medical and Non-Medical EOL Planning Activities

Characteristic Value
Age, mean ± SD 75 ± 7.1
Female, % 73
Nonwhite, % 26
>High school education, % 62
Married, % 46
Living alone, % 43
Number of chronic diseases, mean ± SD 3.8 ± 2.2
>1 instrumental activity of daily living disability, % 20
Self-rated health fair or poor, % 22
Quality of life fair or poor, % 17
Medical EOL planning activities, %
 Completed a living will 51
 Named a healthcare proxy 34
 Communicated with loved ones about the use of life support 59
 Communicated with loved ones about quality versus quantity of life 47
Non-medical EOL planning activities, %
 Pre-paid for funeral 8
 Made plans or moved somewhere to get more help with daily activities 23
 Long-term care insurance 24
 Taught someone how to do things around the house 26
 Conveyed wishes for funeral arrangements 48
 Purchased cemetery plot/made arrangements for cremation 49
 Financial will 70
 Told someone where you keep your papers about money matters or other important things 84
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SD=standard deviation

Complete results of bivariate analysis of factors associated with each of the non-medical EOL planning activities is provided in Table 2. Different combinations of factors were associated with each of the activities. Older age was associated with multiple activities, including moving or making plans to move, conveying wishes for funeral arrangements, and prepaying for a funeral. White race was associated with a different group of activities, including purchasing LTCI, prepaying for a funeral, and completing a financial will. Home ownership, higher education, employment, and better finances were all associated with completing a financial will; one or more of these factors were also associated with purchasing LTCI and prepaying for a funeral. Poorer self-rated health and quality of life were associated with teaching someone how to do practical things around the house. Higher health literacy and better executive function were associated with purchasing LTCI and completing a financial will.

Table 2:

Bivariate Associations Between Sociodemographic Status, Health, and Life Experience with Non-Medical EOL Planning Activities

FACTOR NON-MEDICAL EOL PLANNING ACTIVITY
Move or plans to move for more help Long-term care insurance Taught someone practical things Conveyed funeral arrangement wishes Purchased cemetery plot Completed a financial will
% P-value % P-value % P-value % P-value % P-value % P-value
Age
 60–69 15 .03 21 .57 18 .08 37 .04 31 <.001 67 .37
 70–79 22 24 27 52 48 75
 80+ 32 28 33 53 68 68
Race
 White 23 1.0 28 .006 24 .18 48 .90 55 <.001 83 <.001
 Non- White 23 13 33 49 31 36
Gender
 Male 25 .76 30 .17 16 .02 46 .70 49 77
 Female 22 22 30 49 48 .90 68 .20
Marital status
 Married 23 1.0 28 .10 25 .60 40 .008 48 .90 84 <.001
 Other 23 20 28 55 49 59
Homeownership
 Own home 16 <.001 28 .007 25 .31 46 .37 53 .03 84 <.001
 Other 42 13 31 52 38 36
Living situation
 Alone 27 21 .41 27 .70 55 .04 48 .90 61 .002
 With others 20 .21 26 25 43 48 77
Education
 ≤ 12th grade 22 .67 10 <.001 34 .03 47 .90 52 .41 55 <.001
 > 12th grade 24 32 22 48 47 80
Employment
 Full/part time 15 .03 27 .46 18 .05 47 .80 38 .02 80 .03
 Unemployed 26 23 30 49 53 67
Finances at end of month
 Not/just enough 26 .34 16 .004 31 .11 45 .35 48 1.0 58 <.001
 Some left over 21 30 23 51 49 80
Self-rated health
 E/G/VG 22 .50 24 .87 23 .007 46 .32 47 .40 73 .05
 Fair/poor 26 25 40 54 54 60
Quality of life
 Best/good 21 .06 25 .59 23 .003 42 .36 49 .76 72 .18
 Fair/poor/worst 34 20 44 49 46 62
Depressed
 Yes 39 .002 25 .87 36 .10 49 .89 73 .75
 No 19 24 24 48 70
Health literacy
 ≤ 8th grade 29 .34 9 .008 40 .03 56 .33 38 .15 42 <.001
 ≥ 9th grade 22 27 24 47 51 75
EXIT score
 0 23 .62 32 <.001 26 .53 45 .29 44 .31 81 <.001
 1 19 30 21 44 48 73
 2+ 26 12 29 54 54 56
Made a decision for someone who died
 Yes 21 .57 30 .07 30 .28 55 .09 57 .05 76 .11
 No 24 21 24 44 44 67
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E=Excellent G=Good VG=Very good

Table 3 lists the factors significantly associated with non-medical EOL planning activities in multivariable analysis. There was little overlap in the factors associated with each of these activities. Overall, the activities of purchasing LTCI, completing a financial will, and pre-paying for a funeral were associated with a number of different sociodemographic characteristics indicating higher socioeconomic status. For example, higher education was associated with purchasing LCTI (OR 3.31, 95% CI 1.66, 6.62), whereas home-ownership was associated with completing a financial will (OR 4.72, 95% CI 2.42, 9.21) and prepaying for a funeral (OR 2.04, CI 1.04, 3.98). Poorer quality of life was associated with teaching someone how to do things around the house (OR 2.38, CI 1.23 4.55). Having made a decision for someone who died was associated with both conveying wishes for funeral arrangements (OR 1.68, 95% CI 1.03, 2.75) and prepaying for a funeral (OR 1.93, 95% CI 1.13, 3.29).

Table 3:

Factors Significantly Associated with Non-medical EOL Planning Activities

Made plans or moved somewhere to get more help with daily activities
Factor Odds Ratio 95% Confidence Interval P-value
Owns own home/condo 0.28 0.16, 0.50 <0.0001
Depressed 2.39 1.26, 4.52 0.008
 
Long-term care insurance
Factor Odds Ratio 95% Confidence Interval P-value
>12th grade education 3.31 1.66, 6.62 0.0007
EXIT score 2+1 0.44 0.22, 0.91 0.03
 
Taught someone practical things/ how to do things around the house
Factor Odds Ratio 95% Confidence Interval P-value
Male 0.47 0.24, 0.91 0.03
QOL good/best 2.38 1.23, 4.55 0.01
 
Conveyed wishes for funeral arrangements
Factor Odds Ratio 95% Confidence Interval P-value
Age 70–79 years 2 1.96 1.11, 3.47 0.02
Married 0.55 0.34, 0.89 0.01
Made a decision for someone who died 1.68 1.03, 2.75 0.04
 
Purchased cemetery plot/made arrangements for cremation
Factor Odds Ratio 95% Confidence Interval P-value
Age 70–79 years2 2.35 1.25, 4.39 0.008
Age 80+ years2 6.51 2.98, 14.21 <0.0001
White 2.58 1.35, 4.94 0.004
Owns own home/condo 2.04 1.04, 3.98 0.04
Made a decision for someone who died 1.93 1.13, 3.29 0.02
 
Completed a financial will
Factor Odds Ratio 95% Confidence Interval P-value
White 3.73 1.86, 7.49 0.0002
Owns own home/condo 4.72 2.42, 9.21 <0.0001
Money left over at end of month 2.04 1.10, 3.79 0.02
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1

Reference is EXIT score of 0

2

Reference is age 60–69 years.

QOL=quality of life

Figure 1 shows the non-medical EOL planning activities that were significantly associated with medical EOL planning activities, adjusting for age, gender, education, employment status, finances, and self-rated health. Purchasing LTCI was associated with completing a living will and naming a healthcare proxy. Preparing a financial will was associated with completing a living will, naming a healthcare proxy, and discussing quality vs. quantity of life. Conveying wishes for funeral arrangements was significantly associated with all four medical EOL planning activities—completing a living will, naming a healthcare proxy, discussing life-sustaining therapy, and discussing quality vs. quantity of life.

Figure 1:

Figure 1:

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Non-medical EOL planning activities significantly associated with medical EOL planning activities. The odds ratios are derived from models adjusting for participation in the other non-medical activities, age, gender, education, employment status, finances, and self-rated health.

DISCUSSION

This observational cohort study of older community dwelling adults examined the frequency which these participants completed non-medical EOL planning activities, the factors associated with completing these activities, and relationships between non-medical and medical EOL planning. The frequency with which participants completed non-medical EOL planning activities ranged from 8% prepaying for funeral to 70% preparing a financial will and 84% telling someone where they kept important papers. Approximately one-quarter had made plans to or had moved to obtain additional help, purchased LTCI, and taught someone how to do things around the house. Approximately one-half had prepaid for a funeral and conveyed their wishes regarding their funeral arrangements. Each non-medical EOL planning activity was associated with a different set of factors. There were multiple associations between non-medical and medical EOL planning.

This study adds to the small body of literature on non-medical EOL planning by examining a broad array of planning activities. Of these activities, two have been examined using national datasets of older persons, with findings remarkably similar to the current study regarding prevalence of engagement but with some differences regarding the factors associated with engagement. One study utilizing data from the National Health and Aging Trends Study (NHATS), found the 18.4% of NHATS participants had purchased LTCI, compared to 24% in the current study.8 Similar to the current study, the NHATS data demonstrated an association between purchase of LTCI and education, but also found associations not seen in the current study with race, older age, higher income, and better self-rated health. A second study utilizing data from the Health and Retirement Survey (HRS) found that 69% of HRS participants had completed a will or trust, compared to 70% in the current study. Both studies found associations among white race, income, and home ownership with completion of a will, with the HRS data also demonstrating associations with female gender, older age, and higher education.9 The similarities in prevalence suggest that the findings of the current study are more broadly generalizable. The larger number of factors found to be associated with these activities in the national datasets may be a reflection of the much larger sample sizes in those datasets. Many of these factors are related to one another, and the larger sample size may have provided the ability to detect the independent contributions of a larger number of inter-related variables.

Taken together, these studies highlight the importance of socioeconomic status and race in engagement in estate planning. Both the HRS and the current study found strong associations between completion of a will and completion of advance directive documents (living wills and assignment of healthcare agents), with odds ratios of 5 or higher. It has been proposed that this association is explained by individuals seeking out legal assistance for estate planning and then being prompted by the legal professional to complete medical planning.12 While this explanation suggests that legal professionals may be an important component of efforts to promote medical EOL planning, it also illustrates a troubling pathway by which racial and sociodemographic status leads to disparities in health outcomes.

In contrast to purchasing LTCI and completing a financial will, conveying wishes for funeral arrangements and purchasing a cemetery plot were not associated with measures of wealth, but instead with age and experience making a decision for someone who died. Conveying wishes about funeral arrangements was more strongly associated with communication about quality versus quantity of life than was completion of a financial will, and it was the only non-medical EOL planning activity that was associated with communication about the use of life-sustaining treatment. The association of these activities may be explained by the shared need for a readiness to confront the end of life and desire to have a say in how EOL events will unfold. This finding suggests that asking about whether a patient has talked with loved ones about their funeral arrangements may be one strategy clinicians can use in engaging patients in conversations about medical EOL planning. Patients who have discussed their funerals with loved ones but who have not done medical EOL planning have overcome what can be the formidable barrier of wanting to avoid considering the EOL, but may need education to understand that there are choices they may need to make about their healthcare during a final illness.

A shared readiness for engagement in both medical and non-medical activities highlights the potential advantages of bringing these activities together to reach a larger number of individuals who come to EOL planning from different places. There has been a rapid rise and increasing interest in the work of end-of-life doulas and in “death cafes,” which are small gatherings encouraging strangers to come together to talk about issues related to death and dying.20,21 These innovations respond to the desire to “demedicalize” death and dying. Analogous to the work of birth doulas, end-of-life doulas attend to individuals’ non-medical needs and assist with the practical aspects of end of life. In the same way that birth doulas help expectant mothers to understand the medical issues she could face, these EOL supports may play a role in helping individuals learn about and prepare for the types of medical decisions they may face at the end of life. Conversely, clinicians who complete medical EOL planning with their patients should be aware of the additional resources available to support patients in broader planning.

The study has several limitations. Although the similarity between several of the findings and the results of studies using national datasets supports the generalizability of the study results, the study population was recruited from a single geographic region. Moreover, the high educational attainment and financial status of participants in the study cohort is not representative of the older US population. Additional work is needed among more diverse communities and to explore whether there are non-medical end of life planning activities that are particular to specific populations. While the participation rate among eligible persons from the practices was high, we do not have information about how many persons in the community center were eligible for but chose not to participate in the study.

In conclusion, this paper demonstrates the variability in prevalence of engagement in non-medical EOL planning activities and in the factors associated with this engagement. The association between engagement in non-medical and medical planning supports the notion that individuals who have overcome barriers to planning for the EOL are ready to engage in a broad set of activities and highlights the potential for innovations that encompass the full range of EOL planning.

Key message:

This article describes the prevalence of engagement in non-medical end-of-life planning activities by older adults. The results indicate highly variable engagement in different activities, with little overlap in the characteristics associated with engagement. Association with medical planning activities supports the use of programs aimed at assisting with broad planning.

ACKNOWLEDGEMENTS

We acknowledge the work of Lynne Iannone, M.S. in recruiting participants and conducting interviews.

FUNDING

This work was supported by the National Institute of Nursing Research (R01NR016007) and National Institute on Aging (P30AG21342). This work was supported with resources and the use of facilities at the VA Connecticut Healthcare System. The contents do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.

The funding sources had no role in the study design; collection, analysis, and interpretation of data; writing of the report; or the decision to submit the article for publication.

Footnotes

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DISCLOSURE/CONFLICT OF INTEREST

Dr. Terri Fried received support by the NIH. Ms. Tu and Mr. O’Leary have no disclosures.

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