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The Association between Treatment Preferences and Trajectories of Care at the End-of-Life

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Journal of General Internal Medicine Aims and scope Submit manuscript

Abstract

Background

Honoring patients’ treatment preferences is a key component of high-quality end-of-life care.

Objective

To determine the association of preferences with end-of-life care.

Design

Observational cohort study.

Participants

118 community-dwelling persons age ≥65 years with advanced disease who died in a study which prospectively assessed treatment preferences.

Measurements

End-of-life care was categorized according to four pathways: (1) relief of symptoms only, (2) limited attempt to reverse acute process with rapid change to symptomatic relief, (3) more intensive attempt to reverse acute process with eventual change to symptomatic relief, and (4) highly intensive attempt to reverse acute process with no change in goal.

Results

Adjusting for diagnosis, those with greater willingness to undergo intensive treatment (defined as a desire for invasive therapies despite ≥50% chance of death) were significantly more likely to receive care with an initial goal of life prolongation (pathways 2–4) [odds ratio 4.73 (95% confidence interval 1.39–16.08)] than those with lower willingness. Nonetheless, mismatches between preferences and pathways were frequent. Only 1 of 27 participants (4%) with lower willingness to undergo intensive treatment received highly intensive intervention (pathway 4); 53 of 91 participants (58%) with greater willingness to undergo intensive treatment received symptom control only (pathway 1).

Conclusions

The association between preferences and trajectories of end-of-life care suggests that preferences are used to guide treatment decision-making. In contrast to concerns that patients are receiving unwanted aggressive care, mismatches between preferences and trajectories were more frequently in the direction of patients receiving less aggressive care than they are willing to undergo.

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Acknowledgments

The authors thank Carm Joncas, RN, and Barbara Mendes, RN, for their extraordinary interviewing skills and Martha Oravetz, RN, for her meticulously conducted chart reviews. This project was supported by grant PCC-98-070-1 from VA HSR&D, R01 AG19769 from the National Institute on Aging, P30 AG21342 from the Claude D. Pepper Older Americans Independence Center at Yale, and a Paul Beeson Physician Faculty Scholars Award. Dr. Pisani is supported by K23 AG23023 from the National Institute on Aging. Dr. Fried is supported by K02 AG20113 from the National Institute on Aging. Dr. Bradley is supported by the Patrick and Catherine Weldon Donaghue Medical Research Foundation Investigator Award (Grant #02-102).

Conflict of Interest

None disclosed.

Author information

Authors and Affiliations

  1. Department of Medicine, Yale University School of Medicine, New Haven, CT, USA

    JoAnne Alissi Cosgriff MD, MPH, Margaret Pisani MD, MPH & Terri R. Fried MD

  2. Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA

    Elizabeth H. Bradley PhD

  3. Program on Aging, Yale University School of Medicine, New Haven, CT, USA

    John R. O’Leary MA

  4. Clinical Epidemiology Research Center 151B, VA Connecticut Healthcare System, 950 Campbell Avenue, West Haven, CT, 06516, USA

    Terri R. Fried MD

Authors
  1. JoAnne Alissi Cosgriff MD, MPH
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  2. Margaret Pisani MD, MPH
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  3. Elizabeth H. Bradley PhD
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  4. John R. O’Leary MA
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  5. Terri R. Fried MD
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Corresponding author

Correspondence to Terri R. Fried MD.

Additional information

Supported by grant PCC-98-070-1 from VA HSR&D, R01 AG19769 from the National Institute on Aging, P30 AG21342 from the Claude D. Pepper Older Americans Independence Center at Yale, and a Paul Beeson Physician Faculty Scholars Award. Dr. Pisani is supported by K23 AG23023 from the National Institute on Aging. Dr. Fried is supported by K02 AG20113 from the National Institute on Aging. Dr. Bradley is supported by the Patrick and Catherine Weldon Donaghue Medical Research Foundation Investigator Award (Grant #02-102).

Appendix

Appendix

Preference Assessment Item

Think about if you were suddenly to get sick with an illness that would require you to be in the hospital for at least a month. It would either be that your [CHF, COPD, cancer] worsened, or you got sick with a different illness. In the hospital, you would need to have many minor tests, such as x-rays and blood draws, and you would require more tests, such as CT scans. You would need major therapies such as being in the intensive care unit, receiving surgery, or having a breathing machine. Without the treatment, you would not survive. If this treatment would get you back to your current state of health, would you want to have it?

If NO: Question complete.

If YES: Now, what if the doctor told you that there was a 50/50 chance that it would work and get you back to your current state of health. If it did not work, you would not survive. Without the treatment, then you would not survive for certain. Would you want the treatment?

If NO: Now what if the doctor told you there were a 90% (99%) chance that it would work and get you back to your current state of health and a 10% (1%) chance that it would not. Without the treatment, then you would not survive for certain. Would you want the treatment?

If YES: Now, what if the doctor told you there was a 10% (1%) chance that it would work and get you back to your current state of health and a 90% (99%) chance that it would not work. Without the treatment, then you would not survive for certain. Would you want the treatment?

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Cosgriff, J.A., Pisani, M., Bradley, E.H. et al. The Association between Treatment Preferences and Trajectories of Care at the End-of-Life. J GEN INTERN MED 22, 1566–1571 (2007). https://doi.org/10.1007/s11606-007-0362-6

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  • DOI: https://doi.org/10.1007/s11606-007-0362-6

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