The Effect of Advance Directives on End-of-Life Cost Experience James Fonk, Donna Davidoff, Thomas Lutzow, Noelle Chesley, Nancy Mathiowetz Journal of Health Care for the Poor and Underserved, Volume 23, Number 3, August 2012, pp. 1137-1156 (Article) Published by Johns Hopkins University Press DOI: https://doi.org/10.1353/hpu.2012.0098

For additional information about this article https://muse.jhu.edu/article/481738

Access provided at 28 Apr 2019 03:49 GMT from Univ of Louisiana @ Lafayette

Original Paper

The Effect of Advance Directives on End-of-Life Cost Experience James Fonk, MD Donna Davidoff, MD Thomas Lutzow, PhD Noelle Chesley, PhD Nancy Mathiowetz, PhD Abstract: Purpose. This study assesses the impact of Advance Directives (ADs) on end-oflife costs, drawing on administrative data from a single health care organization located in Milwaukee, Wisconsin (Independent Care Health Plan, or iCare). Background. As part of ongoing Medicaid and Medicare rate reform efforts, greater use of ADs among plans and providers is being considered to better control costs and enhance health outcomes. Approach. Drawing on decedent-member descriptive and cost data, OLS regression is used to analyze the relationship between AD use and subsequent costs for a single health care plan. Results. The analysis does not provide evidence of a significant relationship between AD use and end-of-life costs when patient health is controlled for the sample. Conclusions. There was no evidence within the iCare data to support a relationship between the presence of ADs and lower end-of-life costs. Key words: Advance directives, end-of-life costs, advance care planning, power of attorney, health care planning, POLST, Do-Not-Resuscitate, living will, advance directive.

I

t is an accepted, even popular, belief that lower end-of-life costs can be obtained through advance care planning.1,2 Indeed, the Health Information Technology for Economic and Clinical Health Act (HITECH, Public Law 101-508, released July 2010) encourages physicians to document the availability of an advance directive in their electronic health record by 2011. Further, the Centers for Medicare and Medicaid Services (CMS), until a January 2011 retraction of a 2010 final rule,3 would have paid physicians to consult with qualified patients regarding end-of-life care plan options. These policy considerations are linked to economic challenges that face the Medicare trust fund. Medicare covers 70% of the decedent events in the United States each year4 and nearly 30% of the Medicare budget is spent on care during the last year of life. Even though this distribution of end-of-life costs to Medicare appears to have James Fonk is the Medical Director, Donna Davidoff is the Associate Medical Director, and Thomas Lutzow is the President/Chief Executive Officer at Independent Care Health Plan. Noelle Chesley is an Associate Professor and Nancy Mathiowetz is a Professor, both of Sociology at the University of Wisconsin–Milwaukee. Please address correspondence to Thomas Lutzow; iCare; 1555 N. River Center Drive; Milwaukee, WI 53212; (414) 225-4777; [email protected]. © Meharry Medical College

Journal of Health Care for the Poor and Underserved  23 (2012): 1137–1156.

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Advance directives and costs of end-of-life care

stabilized (if not decreased) over the years,5 end-of-life care continues to be viewed as a cost-reduction opportunity. Advance care planning has received recent attention in Wisconsin. Varying Medicare costs in regional hospitals during the last six months of life have been noted. The Milwaukee Journal Sentinel, a leading Wisconsin newspaper, reports that Medicare spends roughly $10,000 less at Gundersen-Lutheran during the last six months of life than it spends at Aurora St. Lukes Medical Center and Froedtert Hospital, two hospitals located in Milwaukee County. These lower costs are attributed to advance care planning, specifically to a document, an advance directive (AD): “The low costs incurred by Medicare in La Crosse . . . stem in part from a community-wide initiative, begun in the 1980s, to encourage people to have advance directives—legal documents that state patients’ decisions about end-of-life care should they become incapacitated.”6 The AD use rate in La Crosse County is robust, exceeding the national average by several orders of magnitude, and has improved over time. Hammes, Rooney and Gundrum report in a study of 2007/2008 La Crosse County data that the prevalence of ADs among decedents is significantly higher than indicated in the County’s 1995/1996 data (90% versus 85%, p5.02) and that these ADs were more readily available in the decedent’s medical record at the time and place of death (99.4% versus 95.2%, p.001). Additionally, they report that end-of-life treatment is consistent with AD content in 99.5% of the cases.7 As a result of this performance, the Gundersen-Lutheran plan and the other participating organizations in La Crosse County are recognized nationally as best-practice leaders in advance care planning. It should be noted that the Gundersen-Lutheran system operates in a county with a demographic profile that is noticeably different from the county in which the Milwaukee hospitals operate, a difference that might be important in understanding variations in AD prevalence, content and use. The racial composition for La Crosse County is predominantly White (91% non-Hispanic White, 1.4% African American, 1.5% Hispanic), whereas Milwaukee County is more racially and ethnically diverse (58% non-Hispanic White, 27% African American, and 13% Hispanic). In addition, both Milwaukee hospitals receive tertiary and quaternary care referrals from other hospitals within the state, which may serve to further increase complexity and cost of care. The question addressed in this study is whether the presence of an AD influences end-of-life costs among a health plan membership that is demographically less uniform than the population served by plans and providers in La Crosse County. The environment in Milwaukee County is also without the communal infrastructure supporting advance care planning that seems to be fundamental to the outcomes in La Crosse County. A membership review in this study of a health maintenance organization (HMO) operating in Milwaukee County, Independent Care Health Plan (iCare) provides a direct opportunity to assess the connection between ADs and costs in a more racially/ethnically diverse and economically disadvantaged sample. iCare health plan membership includes beneficiaries who live in the community but who have disabilities or multiple co-morbidities, the majority (87%) receiving Supplemental Security Income (SSI) or Social Security Disability Insurance (SSDI) support. Importantly, 91% of iCare members have incomes 100% or less of the U.S. Federal poverty level (i.e.,  $10,890/ year for an individual, 2011).

YOL  Years of Life MOL  Months of Life

Aurora Sinai Med Cntr Aurora St. Lukes Med Cntr Columbia-St. Mary’s Froedtert Hospital Gundersen-Lutheran Med Cntr St. Joseph’s Hospital National Average

Facility Milwaukee Milwaukee Milwaukee Milwaukee La Crosse Milwaukee NA

County 19.0 24.1 18.4 23.0 12.3 18.7 21.9

Inpatient Days/ Decedent Last 2 YOL 23.2 28.9 22.5 20.5 20.8 23.1 25.4

15.8 11.7 18.2 15.7 9.9 13.8 13.9

25.7% 33.2% 24.7% 31.9% 25.6% 30.2% 25.0%

$34,122 $32,275 $26,389 $37,094 $20,813 $29,852 $30,455

$60,944 $62,671 $53,332 $64,025 $41,325 $56,901 $59,976

Total Medicare SNF Days/ Hospice Days/ % Deaths Inpatient $$/ Medicare $$/ Decedent Decedent Occurring in Decedent Decedent Last Last 2 YOL Last 6 MOL Hospital Last 2 YOL 2 YOL

DARTMOUTH ATLAS OF HEALTH CARE AVERAGES/YR 2003–2007

Table 1.

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Advance directives and costs of end-of-life care

Table 2. DEMOGRAPHIC COMPARISONS AMONG WISCONSIN COUNTIES County Characteristics Population % Age 65a % Femalea % Non-Hispanic Whitea % African Americana % Hispanica % Persons FPLb % HS Grads Age 25b % BA/BS+ Age 25b Median Household $$b % w/ Disability Agec 5

State

La Crosse

Milwaukee

Wisconsin

114,638 13.3% 51.2% 91.1% 1.4% 1.5% 12.8% 92.5% 28.6% $49,505 14.6%

947,735 11.5% 51.7% 54.3% 26.8% 13.3% 20.6% 84.7% 26.8% $42,012 19.7%

5,686,986 13.7% 50.4% 83.3% 6.3% 5.9% 12.4% 89.0% 25.5% $49,994 16.0%

2010 2009 c 2000 a

b

Literature review. AD prevalence. Very few health care regions have AD use rates comparable to those of La Crosse County. In most instances, AD-presence seems to vary with health and treatment state. A random sample survey of all deaths in the United States indicates that approximately 10% of decedents have a living will; 8 when considering only chronically ill individuals residing in nursing homes, Wilkinson, Wenger, and Shugarman report that the ratio of individuals with an AD is one in three.9 Referencing only individuals receiving long-term care services, a January 2011 Data Brief issued by the National Center for Health Statistics reports that the percentage patients with an AD of one sort or another in home health care, nursing home care, and hospice care are 28%, 65%, and 88%, respectively.10 AD impact. Apart from La Crosse County performance, more recent research calls into question the link between AD use and reductions in end-of-life costs. Tan and Jatoi, drawing on a sample of cancer patients, conclude that those with advance directives had no significant difference in cost (p5.30) from those patients without ADs.11 Kelly, Ettner, Morrison, et al. use information from 2,394 Medicare decedents 65 years old and older and are unable to document an association between advance care planning and lower end-of-life expenditures.12 Halpern, Pastores, Chou, et al. report that among intensive care patients, whether an AD was present or not, the level of care was no different.13 Emanuel reports earlier that the few randomized trials conducted show an inconclusive or no relationship between use of ADs and end-of-life costs.14

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1141

AD application. Implementation factors may interfere with the potential effectiveness of ADs in reducing costs. Hoffman, Zimmerman and Tompkins report that 41% of their subjects expressed end-of-life treatment preferences verbally that were not consistent with preferences contained in the AD form.15 Another report finds that nearly half (p.001) of a group (60 years of age or older) studied over two years (n5189) changed their end-of-life treatment preferences over time.16 Among patients with written ADs, 91% state a desire that surrogates have at least some leeway to override their written directives at end-of-life.17 Surrogates with Power-of-Attorney designation, on the other hand, may not be as reliable as one would like and tend to be uncertain about the patients’ end-of-life wishes, even when an AD is present.18 Research finds that both family surrogates and more formally appointed agents are 32% inaccurate in predicting member end-of-life wishes in hypothetical testing,19 pointing again to the need for recurrent communication, adjusting to the patient’s changing preferences.20 Advance directive documents by themselves are not without ambiguity.21 Even where a surrogate or designated agent is available, the end-of-life process is approached with caution as proxy decision makers have difficulty converting a patient’s written treatment preferences into clinical decisions.22 Implementation problems can occur when physicians are not aware of ADs at the moment of care. A report from the Agency for Healthcare Research and Quality records that up to 76% of physicians whose patients have an AD are unaware of its existence.23 Access to the advance care plan by health care professionals exactly when it is needed continues to frustrate. Taken as a whole, this body of research suggests that use of ADs as a tool guiding (and perhaps conserving) end-of-life care may not be as effective as one would like, perhaps pointing to the importance of an embedded communal practice over an AD document in delivering valued advance care outcomes. AD preferences. Racial/ethnic differences in preferences, adoption, and construction of ADs have been observed. Minority groups appear to prefer more aggressive end-oflife care,24,25 even when Physician Orders for Life-Sustaining Treatment (POLST) is the AD form used.26 The origin of such preferences is not clear. There is some speculation ranging from lack of trust in the health care system,27 different belief-sets,28 low health literacy29 or an ethno-cultural view that regards the dying process as a family affair and not an individual matter to be discussed with a clinician.30–32 Minority groups are reported to have less knowledge about ADs than non-minority groups and, therefore, less likely to support their use.33 This disparity may be aggravated by differences in relationships between providers and minority patients. One report finds among nursing home patients that health care providers engage in fewer discussions (p.001) about end-of-life treatment options with minority residents and their family members than with non-Hispanic White residents.34 These end-of-life discussions may be key. Zhang, Wright, Huskamp, et al. find that recurrent patient-physician discussions about endof-life care are associated with lower rates of ventilation (1.6% vs. 11%), resuscitation (0.8% vs. 6.7%, ICU admission (4.1% vs. 12.4%), and earlier hospice referral (65.6% vs. 44.5%), i.e., less aggressive care (less costly care) during final moments, without regard to an AD.35 Even when the pattern of patient-provider communication is the same, however, another study finds that non-Hispanic Whites receive lower levels (p5.04) of life-prolonging care immediately prior to death than their non-White counterparts.36

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Advance directives and costs of end-of-life care

There may then be deeper systemic variations within and across health systems that explain a greater use of life-sustaining care with minority patients. The Dartmouth Institute reports that the known differences in racial and ethnic preferences for aggressive treatment at the end of life are not large enough to explain the regional differences in the use of hospital care for end-of-life patients.37 Regional provider practice patterns and service capacities may explain much of the remaining variation.12

Methods Source of data. The iCare health plan was initially formed as a research and demonstration program by the CMS (the Center for Medicare and Medicaid Services, then the Health Care Financing Administration) through the State of Wisconsin Department of Health Services. iCare is jointly owned by a Milwaukee non-profit organization (the Milwaukee Center for Independence, Inc.) and Humana, Inc. (Louisville, Kentucky). iCare has provided services under contracts with the State of Wisconsin and the Federal governments since 1992. The original purpose of the CMS demonstration was to assess the value of managed care with participants in SSI/SSDI programs. The data for this study (N5858) come from iCare’s administrative records and are limited to iCare members who died during the period January 1, 2005–August 31, 2010. These data include information about age at death, gender, race/ethnicity, annual income, English proficiency, whether or not iCare is the primary insurer, years on SSI/SSDI support, household composition, and health status. Nearly all of iCare’s 15,133 members are eligible for Medicaid due to poverty and disability: 13,164 of these members are SSI/ SSDI recipients and a large number (3,980) are also eligible for Medicare covered benefits and are enrolled in iCare’s Special Needs Plan (SNP). Some of these members are eligible for Medicaid long-term care due to risk of nursing home placement and are enrolled in iCare’s Fully Integrated Special Needs Plan (FIDESNP). Information (e.g. name, address) that might identify decedents was eliminated prior to this analysis. All iCare members are assigned to a care coordinator who is responsible for outreach, assessment, care planning, resource connections, monitoring, and follow-up for both medical and social needs. iCare members tend to remain enrolled in the iCare plan for extended periods (years), permitting plan-member relationships to thrive. Care coordinators, as instructed by U.S. Patient Self-Determination Act of 1990, alert members at the time of enrollment, and then annually during review, of their right to an advance care plan. Standard AD templates are available on the Wisconsin Department of Health Services website. While members are informed of their rights to have an AD, they are encouraged to conduct advance care planning with their primary providers and family members. iCare staff may not (by policy) arrange for the member to sign an AD during the enrollment or review encounters with the plan only. iCare care coordinators note in the member’s case record whether an AD exists or not. A copy of the AD is requested, but not required, and 8.2% of iCare members have an AD. As Table 3 indicates, the presence of ADs among iCare’s membership increases with age, a pattern consistent with other reports.38,39 End-of-life costs. The dependent variable for this study is total costs in the last month of life. For the purposes of this analysis, the term total costs refers to the total costs

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Table 3. PRESENCE OF ADS AMONG ACTIVE iCARE MEMBERS BY AGE Age Range (yrs)

Member Count

Yes

No

% Yes

,20 20–39 40–59 601

921 3,873 7,022 3,317

3 182 560 491

918 3,691 6,462 2,826

0.3% 4.7% 8.0% 14.8%

Total

15,133

1,236

13,897

8.2%

incurred by iCare and thus may not reflect other member costs that may be assigned elsewhere. To the extent that some costs are not submitted to iCare, the costs presented here may differ from the total costs sometimes reported in the scholarly or policy literature. Total costs in the last month of life range from $0 (41 of 858 members had no end-of-life costs) to $279,000 (see Table 4). No expenditures ($0) for end-of-life costs may indicate that iCare is not the primary insurer, among other possible explanations (e.g., sudden natural or accidental death). Independent variable. The key independent variable is whether or not a decedent has an advanced directive in place (measured as a binary variable where 1 5 has AD; 0 5 otherwise). The State of Wisconsin, like many other states, offers two forms for advance care planning. One is a Power of Attorney–Health (POA-H) and the other a living will.40 These two types of advance planning structures work differently. A living will records the member’s instructions for care during his or her end-of-life experience. A POA-H document transfers end-of-life treatment decisions to another party who presumably knows the wishes of the member and will make treatment decisions on behalf of the member, if the member is incapacitated. The State of Wisconsin also has a Do Not Resuscitate Order (DNRO) program.41 The DNRO program requires the patient to wear a bracelet that can be seen by Emergency Medical Service (EMS) responders; unless the bracelet is present, the EMS responder(s) will resuscitate. Additionally, there is a growing interest in POLST as a statewide standard in Wisconsin, noted for its use in the State of Oregon and preferred currently for use in La Crosse County.42 One of the more appealing features of the POLST initiative is that it is a medical order, rather than a legal document. As a medical order it is signed by a physician and usually contained in the patient’s medical record. All ADs held by iCare decedents in this study are POA-H forms. Other variables. To minimize concerns about spuriousness, these analyses include a number of other variables to serve as statistical controls. These include age at death (measured in years), gender (1 5 female; 0 5 male), race/ethnicity (African American, Other, Non-Hispanic White), household income (measured in dollars), an indicator variable that tracks English as the primary language (1 5 English is Primary; 0  5 otherwise), an indicator variable tracking iCare as the primary insurer (1 5 Primary Insurer; 0 5 otherwise), number of years on SSI, and household composition (member

Yes (or by legal guardian or health care agent)

POAHb

POLSTd (Physician Order for Life Sustaining Treatment)

(Do Not Resuscitate Order)

DcROc

No (in La Crosse), Yes (in some other States)

Yes (or by legal guardian or appointed agent)

Yes

Living Willa

(Power of Attorney– Health)

Signed by Member

Form

Yes

Yes

No

No

Signed by Physician

Medical order where member states preferences for life-sustaining treatment.

Medical order instructing responders to not resuscitate.

Legal document where member entrusts another to make life-sustaining care decisions on member’s behalf.

Legal document where member states preferences for end-of-life medical treatment.

Function

Sometimes not accessible unless attached to the patient record or in a public registry.

Presumes intimate Medical Home relationship with patient and family (covers DNRO and other providers).

(Continued on p. 1145)

Physician directed medical order that does NOT require cosigning by member, a witness or notary.

Order can be nullified and revoked verbally by member or by appointed agent.

Written changes must be witnessed, but revocable verbally to witnesses, in writing or by destruction.

Appointed agent may not reflect final wishes of the member.

Must be presented by signer to physician. May also be registered in probate. Sometimes not available.

Does not cover services beyond applied CPR by responders.

Written changes must be witnessed, but revocable verbally to physician, in writing or by destruction.

May not anticipate latest treatments or technologies and may not be followed.

Must be presented by signer to physician. May also be registered in probate. Sometimes not available.

Member compliance required as member must wear approved alert bracelet.

Flexible

Reliable

Accessible

ADVANCE CARE PLANNING OPTIONS IN WISCONSIN

Box 1.

Not necessary (but preferred)

Member Instrectionse Not necessary

NA (or No)

Signed by Physician

b

a

Wisconsin Statutes §§ 154.01–154.15 Wisconsin Statutes §§ 155 c Wisconsin Statutes §§ 154.17–154.29 d www.ohsu.edu/polst/programs/state+programs.htm e L.W., 167 Wis. 2d 53, 67, 482 N.W. 2d 60, 65 (1992)

NA (or No)

Signed by Member

Recognized Surrogate

Form

Box 1. (continued)

Directly conveys (verbally or in writing) member preferences at the moment of end-oflife treatment.

Allows recognized surrogate (relative, friend) to make end-of-life decisions.

Function Recognized surrogate may not reflect final wishes of the member or family. Recognized only if member is of “sound mind” (i.e., capable) in the opinion of end-oflife caregiver(s).

Available directly from the member at time of end-of-life treatment.

Reliable

Sometimes not accessible . . . if a suitable surrogate is not available.

Accessible

Instructions, if written, are included in the medical record. Over-ride other forms.

Non-written, but may over-ride other forms except member’s direct instructions, living will or POA-H.

Flexible

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Advance directives and costs of end-of-life care

lives alone, member lives with spouse, member lives with family, member lives with non-family). In addition to these variables, we also account for member health status by tracking key diagnoses, including diagnosis of: 1) diabetes/endocrine disorder, 2)  coronary artery disease-hypertension, 3) chronic lower respiratory condition, 4) cancer, 5)  mental health condition, 6) substance use/abuse, 7) gastrointestinal (GI) conditions, 8) neurological conditions, 9) renal disease, 10) musculoskeletal conditions, and 11) HIV/AIDS/STDs. Having organized the data in this manner, the analytic plan includes examining the data set’s descriptive statistics, multiple linear regression models assessing relationships to end of life costs, and logistic regression predicting the likelihood of having an advance directive.

Results Descriptive statistics. Table 4 reports descriptive statistics for the full sample (N5858) of iCare decedents. On average, total costs in the last month of life were approximately $17,000 and 16% of the membership had an AD in place during this time. In terms of medical diagnoses, the most common health conditions include musculoskeletal conditions (57% of deceased members show this condition) and diabetes (54% of deceased members show this condition), while members with HIV/AIDS/STDs are much less common (4% of deceased members show these conditions). The mean age at death is 55 and 53% of decedents are women. The vast majority (98%) of iCare decedents lived in Milwaukee County at the time of death and the racial/ethnic makeup of the sample differs from the larger demographic makeup of the county; iCare members skew toward minority status. While 60% of iCare decedents are African American, 30% are non-Hispanic White, and 11% are of other races/ethnicities (proportions round to 101), the latest census figures indicate almost the opposite profile for Milwaukee County as a whole: 27% of Milwaukee County residents are African American and 54% are non-Hispanic White. Noting the structure of the iCare profile may be important, again, because minority status is associated with higher end-of-life costs in national studies43 and also appears linked generally to non-use of ADs as well as to preferences for more intensive life-sustaining treatments.9 Because iCare serves an economically disadvantaged group, household income is low and restricted in its range. Almost all (93%) of decedents speak English, and iCare is the primary insurer for 71% of deceased members. On average, iCare decedents had been receiving SSI or SSDI benefits for four years. Around 38% of decedents report living alone, while the remaining 62% (61% without ADs, 66% with ADs) report living with a spouse, family, or others. Table 4 also documents that three variables—race/ethnicity, an indicator for English speakers, and household composition (e.g., % lives alone, % lives with spouse, and so on)—have missing information for some cases. The analyses that follow eliminate cases with missing information on these three variables, resulting in an analytic sample of 713 deceased members who have complete information. Regression analysis. Table 5 presents the results of the regression analysis. Two statistical models using Ordinary Least Squares (OLS) regression are estimated to examine iCare’s end-of-life costs for the last month of life. The first model assesses the influence of ADs on iCare’s total costs in the last one month of life, controlling

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Table 4. DESCRIPTIVE STATISTICS OF STUDY VARIABLES FOR 858 DECEASED iCARE MEMBERS Variable Total Costs in Last Month of Life % with Advance Directive % Diagnosed with:  Diabetes-Endocrine   Coronary Artery Disease-CHF  Hypertension   Chronic Lower Respiratory   Disease  Cancer   Mental Health Conditions   Substance Use/Abuse   GI Conditions   Neurological Conditions   Renal Disease   Musculoskeletal Conditions  HIV-AIDS-STDs Control Variables   Age at Death   % Female   % African American   % Non-Hispanic White   % Other   Household Income   % English Speakers   % iCare is Primary Insurer   # of years on SSI   % Lives Alone   % Lives w/ Spouse   % Lives w/Family   % Lives w/ Non-Family

N

Mean

Std. Dev.

Min

Max

858 858

$16,920 0.16

$23,873 0.37

$0 0

$278,878 1

858 858 858

0.54 0.25 0.31

0.50 0.43 0.46

0 0 0

1 1 1

858 858 858 858 858 858 858 858 858

0.38 0.28 0.46 0.25 0.43 0.27 0.16 0.57 0.04

0.49 0.45 0.50 0.43 0.50 0.45 0.37 0.50 0.20

0 0 0 0 0 0 0 0 0

1 1 1 1 1 1 1 1 1

858 858 771 771 771 858 834 858 858 748 748 748 748

55.22 0.53 0.60 0.30 0.11 $3,193 0.93 0.71 4.13 0.38 0.08 0.34 0.19

12.43 0.50 0.49 0.46 0.31 $4,127 0.26 0.46 3.65 0.49 0.28 0.48 0.40

20 0 0 0 0 $0 0 0 0 0 0 0 0

95 1 1 1 1 $20,988 1 1 16 1 1 1 1

for a series of demographic (e.g., age, gender) and other (e.g., primary insurer, years on SSI/SSDI) factors. This model indicates that costs incurred by decedents with ADs were, on average, about $5,000 higher than costs incurred by decedents without ADs, controlling for all other variables in the model. This finding is statistically significant at conventional levels (p.05). Model Two on Table 6 adds some additional information to the analysis, namely the health of the decedents. What is observed in this second model is that several serious

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Advance directives and costs of end-of-life care

Table 5. INFLUENCE OF ADS ON COSTS IN LAST MONTH OF LIFE, CONTROLLING FOR OTHER FACTORS Variable Age at death Female Race/Ethnicity (Comparison is Non-Hispanic Whites)   African Americans  Other Current Annual Income English Speaker iCare is Primary Insurer Years on SSI Household Composition (Comparison is Lives) Alone)   Lives with Spouse   Lives with Other Family   Lives with Non-Family Has Advance Directive Add Health Conditions:  Diabetes   Coronary Artery Disease  Hypertension   Chronic Lower Respiratory Disease  Cancer

Model One

Model Two

b (SE) 234.92 (78.26) 3,404.89 (1,795.90)

b (SE) 282.08 (81.74) 2,502.10 (1,842.71)

21,683.73 (2,043.71) 1,710.98 (4,427.21) 0.28 (0.21) 26,058.15 (5,098.67) 12,116.31*** (1,983.18) 1,497.42*** (250.65)

21,942.78 (2,106.82) 736.04 (4,390.40) 0.17 (0.21) 27,403.45 (5,072.39) 12,249.16*** (2,012.57) 1,295.86*** (256.73)

10,093.15** (3,536.57) 1,590.96 (2,153.20) 2,975.46 (2,506.70) 4,813.83* (2,388.70)

8,111.05* (3,522.60) 887.69 (2,151.48) 2,720.76 (2,502.32) 2,993.56 (2,413.32)

2579.64 (1,949.64) 1,814.42 (2,090.81) 5,129.13** (1,964.15) 3,847.04* (1,846.00) 3,242.46 (1,975.94) (Continued on p. 1149)

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Table 5. (continued) Variable

Model One

Model Two

6,328.23 (7,569.99) 13.00 713

21,512.44 (1,886.92) 2663.86 (2,056.90) 4,259.34* (1,845.01) 588.35 (1,933.44) 1,449.78 (2,382.07) 4,520.37* (1,899.49) 1,605.97 (4,272.40) 3,986.79 (7,817.60) 13.54 713

Add Health Conditions: (continued)   Mental Health Conditions   Substance Use/Abuse   GI Conditions   Neurological Conditions   Renal Disease   Musculoskeletal Conditions  HIV-AIDS-STDs Constant Adjusted R2 N   *p.05 **p.01 ***p.001

health conditions help predict iCare’s total costs in the last month of life. For example, decedents with a hypertension diagnosis have total costs that are about $5,100 higher (p.01), on average, than decedents without that diagnosis, controlling for other factors in the model. Similarly, decedents with a chronic lower respiratory disease have end-of-life costs that are $3,847 higher (p.05), on average, than those without such a diagnosis. Not surprisingly, then, serious health problems are linked to higher end-oflife costs. Estimating a model that simply accounts for the total number of diagnoses yields similar results. Notably, the positive and statistically significant relationship observed between presence of an AD and total iCare costs in the last month of life (present in the first model) disappears in the second model. This pattern is normally interpreted as evidence that the new information in the second model explains the relationship observed in the first model (i.e., mediation). More specifically, once differences in health conditions across decedents are considered, the influence of ADs on iCare’s total costs disappears. Thus, the differences in health conditions largely explain differences in iCare’s end-of-life costs among this sample of decedents, rather than the use of ADs. To examine the latter result more carefully, a statistical model designed to examine

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what characteristics of decedents are predictive of having an AD in place is estimated. A logistic regression is used to assess the odds that decedents with particular characteristics have an AD. The Odds Ratios in Table 7 (standard errors associated are in parentheses) can be interpreted in the following way: odds ratios that are greater than 1.0 and statistically significant (marked with one or more asterisks) indicate that a particular characteristic increased the likelihood that an iCare decedent has an AD in place. For example, for each one-year increase in the age at death, the odds of having an AD in place increase by 4%. This result is consistent with the descriptive trends observed over iCare’s full membership (Table 3). Logistic regression. Odds ratios that are significant and less than 1.0 denote that a characteristic reduces the odds that a decedent has an AD in place. The iCare data show that both African American decedents and decedents of other races/ethnicities are less likely than non-Hispanic White decedents to have an AD; this tendency is consistent with other reviews of AD use9 and with descriptive trends among the full iCare membership (not shown). More specifically, African Americans are 48% less likely than non-Hispanic Whites to have an AD while decedents of other races/ethnicities are 76% less likely than non-Hispanic Whites to have an AD. Additional analyses were conducted to determine if the findings were robust. Specifically, because the term total costs is defined for this study as costs incurred by

Table 6. MEMBER CHARACTERISTICS THAT INFLUENCE THE ODDS OF HAVING AN ADVANCE DIRECTIVE Factor Age at death Female Race/Ethnicity (Comparison is Non-Hispanic Whites)   African Americans  Other Current Annual Income English Speaker iCare is Primary Insurer Years on SSI

Odds Ratio (SE) 1.04*** (0.01) 1.39 (0.32) 0.52** (0.13) 0.24* (0.15) 1.00 0.00 0.86 (0.61) 1.31 (0.33) 0.97 (0.03) (Continued on p. 1151)

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Table 6. (continued) Factor

Odds Ratio (SE)

Household Composition (Comparison is Lives Alone)   Lives with Spouse   Lives with Other Family   Lives with Non-Family Health Conditions:  Diabetes   Coronary Artery Disease  Hypertension   Chronic Lower Respiratory Disease  Cancer   Mental Health Conditions   Substance Use/Abuse   GI Conditions   Neurological Conditions   Renal Disease   Musculoskeletal Conditions  HIV-AIDS-STDs Constant Log-Likelihood N *p.05 **p.01 ***p.001

 

1.23 (0.51) 0.87 (0.24) 1.35 (0.40) 0.79 (0.19) 2.18*** (0.51) 0.94 (0.23) 1.55* (0.34) 1.50 (0.34) 0.86 (0.20) 0.77 (0.20) 1.60* (0.36) 1.46 (0.34) 1.30 (0.36) 0.89 (0.21) 2.01 (0.97) 0.02*** (0.02) 2291.56 713

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iCare decedents for whom iCare is not the only or primary insurer, some deceased members may have additional end-of-life costs not calculated in the study’s total cost per decedent. The analyses were repeated, restricting the sample to just those decedents for whom iCare was the primary insurer. The findings reported above were unchanged when using this more restricted sample. In addition, because the iCare sample differs so markedly from other samples in terms of race/ethnicity, models drawing just on subsamples of African American and non-Hispanic White decedents were also estimated. Analyses restricted in this way do not reveal anything additional to or different from what is already described.

Discussion Overall, this study indicates that older, non-Hispanic White iCare decedents with worse health (i.e., coronary artery disease, chronic lower respiratory disease, or gastrointestinal conditions) are more likely to have ADs in place than decedents without these health conditions or demographic characteristics. Further, it is worth noting that many of the same health conditions that drive use of an AD also drive iCare’s total costs in the last month of life. Taken as a whole, then, the statistical results suggest that sicker people are both more likely to have an AD and to have higher end-of-life costs. When the analysis does not account for decedent health (see Model One on Table 6), the presence of an AD may be acting as a proxy for worse health, rather than having an independent influence on processes that change iCare’s end-of-life costs. Thus, these results, in concert with other recent studies,11–14 call into question whether an AD by itself can be viewed as a reliable cost-differentiating element at end-of-life. Advance directive use is more prevalent among non-Hispanic Whites than minorities.44,45 Among iCare members, 17.8% of non-Hispanic Whites have an AD in place, compared with 11.0% of Hispanics (z53.86; p.001) and 9.7% of African Americans (z59.66; p.001). Poverty among iCare members itself may be a factor. Previous studies find that Medicare spending for minority decedents is 28% higher than for other beneficiaries and 43% higher among decedents from highest-poverty ZIP codes compared with lowest-poverty ZIP codes.46 Given the demographic make-up of urban areas relative to other geographic distributions, expectations for these areas may need to be adjusted in light of variations in end-of-life treatment preferences and socio-economic status. The very different profile of La Crosse County from Milwaukee County may account for some of the success of AD use in La Crosse County. Because all decedents in the iCare study were SSI/SSDI-supported, there may be additional reasons to approach ADs with caution. Advance care planning with members who have cognitive impairments, mental illness, dementia or similar incapacitating conditions has inherent ethical risks. Certainly there is evidence that advance planning occurs among challenged patients,47,48 but less frequently compared with the other populations.49 While people with cognitive impairments are able to participate in end-of-life planning, the validity of these plans can be questioned (e.g., by the courts within States and between States50), both in preparing and then in modifying the plan over time. The member’s understanding of advance care planning and its future con-

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sequences may not be complete or adequate—clinically or legally. Decision-making capacity and informed consent are states often assessed informally or inconsistently across clinicians.51 Members with mental illness have varying degrees of lucidity, often changing across variations in medicated states. Decisions made at one moment are not uncommonly reversed moments later. One study concludes that severely depressed patients, for instance, should be encouraged to defer decisions about life-sustaining treatment and care planning until after treatment for depression.52 If soundness-of-mind is required for future changes in ADs, there is some question whether patient-requested changes in preference (e.g., among patients with cerebral palsy, mental retardation, etc.) will be recognized by a future provider who may have no prior relationship with the patient. With special needs members, changes in preference may require interpreters who are familiar with the member (e.g., family members) or special efforts by professionally-trained caregivers,53 as the member’s ability to communicate may be limited. In many instances, this intimate understanding of a patient’s communication patterns is held by individuals who may not be available during the patient’s end-of-life experience. Finally, quality-of-life is a questioned measure among advocates when considering end-of-life treatment decisions for persons with special needs. Loss of activities of daily living (ADL) may not be just an end-of-life state for these patients, but describes their every-day life experience since birth. Future providers who fail to value this way of life, it is feared, may not work hard to save it.54 One study finds that advocates are concerned that ADs may provide a foundation for the professional health care community to hasten death because the lives of people with disabilities are not considered valuable.55 Future providers, it is thought, may have a biased view of the quality of life of a person with disabilities and abusively withdraw life-sustaining treatment prematurely.56 This study of the iCare data does have limitations, which should be considered when interpreting its findings. The data are observational and taken from a single health care organization. The observational nature of the data limits the ability to make any causal claims and is exposed to the possibility of selection bias. Further, using observational data from a single health care organization makes generalizing to a larger population problematic. Thus, it is not clear to what extent the patterns observed in the iCare data are prevalent in the larger population. However, even with these limitations, this study adds important information to the knowledge about the effectiveness (or noneffectiveness) of AD use in reducing end-of-life costs at a time when policy makers are considering legislation to further their use. Future research may help untangle the social and economic conditions under which ADs are effective tools for patients and health care professionals, as they may be in La Crosse County.

Notes   1. Singer PA, Lowy FH. Rationing, patient preferences and cost of care at the end of life. Arch Intern Med. 1992 Mar;152(3):478–80.  2. Kessler J, Lexer S, Kendall D. Transforming end-of-life care. Washington, DC: The Third Way Economic Program, 2009. Available at: http://content.thirdway.org /publications/179/Third_Way_Idea_Brief_-_Transforming_End-of-Life_Care.pdf.

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  3. Glendinning D, Silva C. Medicare about-face on end-of-life planning pay. American Medical News. 2011 Jan;54(2). Available at: http://www.ama-assn.org/amed news/2011/01/10/gvl20110.htm.   4. Garson A Jr, Engelhard CL. The economics of dying-myth: most medical care dollars are spent in the last six months of life. Governing the States and Localities. 2009 Mar 31. Available at: www.governing.com/topics/health-human-services/The-Economicsof-Dying.html.   5. Riley G, Lubitz J. Long-term trends in Medicare payments in the last year of life. Health Serv Res. 2010 Apr;45(2):565–76. Epub 2010 Feb 9.  6. Boulton G. La Crosse health care systems offer a model of efficiency: integrated systems hold down costs while keeping up quality. Milwaukee, WI: Journal Sentinel, 2009. Available at: www.jsonline.com/business/59087997.html.   7. Hammes BJ, Rooney BL, Gundrum JD. A comparative, retrospective, observational study of the prevalence, availability and specificity of advance care plans in a county that implemented an advance care planning microsystem. J Am Geriatr Soc. 2010 Jul;58(7):1249–55.   8. Vawter L, Ratner E. The need for POLST: Minnesota’s initiative. Minn Med. 2010 Jan; 93(1):42–6.   9. Wilkinson A, Wenger N, Shugarman LR. Literature review on advanced directives. Washington, DC: U.S. Department of Health and Human Services, 2007. Available at: http://aspe.hhs.gov/daltcp/reports/2007/advdirlr.pdf. 10. Jones AL, Moss AJ, Harris-Kojetin LD. Use of advance directives in long-term care populations. NCHS Data Brief. 2011 Jan;(54):1–8. 11. Tan T, Jatoi A. End-of-life hospital costs in cancer patients: do advance directives or routes of hospital admission make a difference? Oncology. 2011;80(1–2):118–22. Epub 2011 Jun 14. 12. Kelley AS, Ettner SL, Morrison RS, et al. Determinants of medical expenditures in the last 6 months of life. Ann Intern Med. 2011 Feb 15;154(4):235–42. 13. Halpern NA, Pastores SM, Chou JF, et al. Advance directives in an oncologic intensive care unit: a contemporary analysis of their frequency, type, and impact. J Palliat Med. 2011 Apr;14(4):483–9. Epub 2011 Mar 18. 14. Emanuel EJ. Cost savings at the end-of-life: what do the data show? JAMA. 1996 Jun 26;275(24):1907–14. 15. Hoffmann DE, Zimmerman SI, Tompkins CJ. The dangers of directives or the false security of forms. Journal of Law, Medicine and Ethics. 1996;24(1):5–17. 16. Fried TR, O’Leary J, Van Ness P, et al. Inconsistency over time in the preferences of older persons with advanced illness for life-sustaining treatment. J Am Geriatr Soc. 2007 Jul;55(7):1007–14. 17. Hawkins NA, Ditto PH, Danks JH, et al. Micromanaging death: process preferences, values, and goals in end-of-life medical decision making. Gerontologist. 2005 Feb;45(1):107–17. 18. Lopez R, Guarino A. Uncertainty and decision making for residents with dementia. Clin Nurs Res. 2011 Aug;20(3):228–40. 19. Shalowitz DI, Garrett-Mayer E, Wendler D. The accuracy of surrogate decision makers: a systematic review. Arch Intern Med. 2006 Mar 13;166(5):493–7. 20. Wittink MN, Morales KH, Meoni LA, et al. Stability of preferences for end-of-life treatment after 3 years of follow-up: The Johns Hopkins Precursors Study. Arch Intern Med. 2008 Oct 27;168(19):2125–30.

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