Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
Annals of Surgical Oncology
Published in: Annals of Surgical Oncology 13/2019

01-12-2019 | Care | Health Services Research and Global Oncology

Deficits in the Palliative Care Process Measures in Patients with Advanced Pancreatic Cancer Undergoing Operative and Invasive Nonoperative Palliative Procedures

Authors: Brooks V. Udelsman, MD, MHS, Elizabeth J. Lilley, MD, MPH, Motaz Qadan, PhD, David C. Chang, PhD, MBA, MPH, Keith D. Lillemoe, MD, Charlotta Lindvall, MD, PhD, Zara Cooper, MD, MSc

Published in: Annals of Surgical Oncology | Issue 13/2019

Login to get access

Abstract

Background

Given survival measured in months, metrics, such as 30-day mortality, are poorly suited to measure the quality of palliative procedures for patients with advanced cancer. Nationally endorsed process measures associated with high-quality PC include code-status clarification, goals-of-care discussions, palliative-care referral, and hospice assessment. The impact of the performance of these process measures on subsequent healthcare utilization is unknown.

Methods

Administrative data and manual review were used to identify hospital admissions with performance of palliative procedures for advanced pancreatic cancer at two tertiary care hospitals from 2011 to 2016. Natural language processing, a form of computer-assisted abstraction, identified process measures in associated free-text notes. Healthcare utilization was compared using a Cox proportional hazard model.

Results

We identified 823 hospital admissions with performance of a palliative procedure. PC process measures were identified in 68% of admissions. Patients with documented process measures were older (66 vs. 63; p = 0.04) and had a longer length of stay (9 vs. 6 days; p < 0.001). In multivariate analysis, patients treated by surgeons were less likely to have PC process measures performed (odds ratio 0.19; 95% confidence interval 0.10–0.37). Performance of PC process measures was associated with decreased healthcare utilization in a Cox proportional hazard model.

Conclusions

PC process measures were not performed in almost one-third of hospital admissions for palliative procedures in patients with advanced pancreatic cancer. Performance of established high-quality process measures for seriously ill patients undergoing palliative procedures may help patients to avoid burdensome, high-intensity care at the end-of-life.
Appendix
Available only for authorised users
Literature
1.
2.
Lim JE, Chien MW, Earle CC. Prognostic factors following curative resection for pancreatic adenocarcinoma: a population-based, linked database analysis of 396 patients. Ann Surg. 2003;237(1):74–85.CrossRef
3.
Conrad C, Lillemoe KD. Surgical palliation of pancreatic cancer. Cancer J. 2012;18(6):577–583.CrossRef
4.
Committee on Approaching Death: Addressing Key End of Life Issues; Institute of Medicine. Dying in America: improving quality and honoring individual preferences near the end of life. Washington, DC: Institute of Medicine; 2014.
5.
Task Force on Surgical Palliative Care; Committee on Ethics. Statement of principles of palliative care. Bull Am Coll Surg. 2005;90(8):34–35.
6.
7.
Lilley EJ, Lindvall C, Lillemoe KD, Tulsky JA, Wiener DC, Cooper Z. Measuring processes of care in palliative surgery: a novel approach using natural language processing. Ann Surg. 2018;267(5):823–5.CrossRef
8.
Bernacki RE, Block SD, American College of Physicians High Value Care Task Force. Communication about serious illness care goals: a review and synthesis of best practices. JAMA Intern Med. 2014;174(12):1994–2003.CrossRef
9.
Zhang B, Wright AA, Huskamp HA, et al. Health care costs in the last week of life: associations with end-of-life conversations. Arch Intern Med. 2009;169(5):480–8.CrossRef
10.
Wright AA, Zhang B, Ray A, et al. Associations between end-of-life discussions, patient mental health, medical care near death, and caregiver bereavement adjustment. JAMA. 2008;300(14):1665–73.CrossRef
11.
Mack JW, Cronin A, Keating NL, et al. Associations between end-of-life discussion characteristics and care received near death: a prospective cohort study. J Clin Oncol. 2012;30(35):4387–95.CrossRef
12.
Hua M, Li G, Clancy C, Morrison RS, Wunsch H. Validation of the V66. 7 code for palliative care consultation in a single academic medical center. J Palliat Med. 2017;20(4):372–7.CrossRef
13.
Feder SL, Redeker NS, Jeon S, et al. Validation of the ICD-9 diagnostic code for palliative care in patients hospitalized with heart failure within the veterans health administration. Am J Hosp Palliat Med. 2018;35(7):959–65.CrossRef
14.
Murff HJ, FitzHenry F, Matheny ME, et al. Automated identification of postoperative complications within an electronic medical record using natural language processing. JAMA. 2011;306(8):848–55.CrossRef
15.
Yim WW, Yetisgen M, Harris WP, Kwan SW. Natural language processing in oncology: a review. JAMA Oncol. 2016;2(6):797–804.CrossRef
16.
Udelsman B, Chien I, Ouchi K, Brizzi K, Tulsky JA, Lindvall C. Needle in a haystack: natural language processing to identify serious illness. J Palliat Med. 2018;22:179–82.CrossRef
17.
Davies JM, Gao W, Sleeman KE, et al. Using routine data to improve palliative and end of life care. BMJ Support Palliat Care. 2016;6(3):257–62.CrossRef
18.
Halpern SD. Toward evidence-based end-of-life care. N Engl J Med. 2015;373(21):2001–3.CrossRef
19.
Easson AM, Asch M, Swallow CJ. Palliative general surgical procedures. Surg Oncol Clin N Am. 2001;10(1):161–84.CrossRef
20.
Wright AA, Keating NL, Ayanian JZ, et al. Family perspectives on aggressive cancer care near the end of life. JAMA. 2016;315(3):284–92.CrossRef
21.
Detering KM, Hancock AD, Reade MC, Silvester W. The impact of advance care planning on end of life care in elderly patients: randomised controlled trial. BMJ. 2010;340:c1345.CrossRef
22.
Bischoff KE, Sudore R, Miao Y, Boscardin WJ, Smith AK. Advance care planning and the quality of end-of-life care in older adults. J Am Geriatr Soc. 2013;61(2):209–14.CrossRef
23.
Fried TR, Bradley EH, Towle VR, Allore H. Understanding the treatment preferences of seriously ill patients. N Engl J Med. 2002;346(14):1061–6.CrossRef
24.
Cooper Z, Koritsanszky LA, Cauley CE, et al. Recommendations for best communication practices to facilitate goal-concordant care for seriously ill older patients with emergency surgical conditions. Ann Surg. 2016;263(1):1–6.CrossRef
25.
Lorenz KA, Rosenfeld K, Wenger N. Quality indicators for palliative and end-of-life care in vulnerable elders. J Am Geriatr Soc. 2007;55(Suppl 2):S318–26.CrossRef
26.
Sanders JJ, Curtis JR, Tulsky JA. Achieving goal-concordant care: a conceptual model and approach to measuring serious illness communication and its impact. J Palliat Med. 2018;21(S2):S17–27.CrossRef
27.
Cauley CE, Block SD, Koritsanszky LA, et al. Surgeons’ perspectives on avoiding nonbeneficial treatments in seriously ill older patients with surgical emergencies: a qualitative study. J Palliat Med. 2016;19(5):529–37.CrossRef
28.
Pecanac KE, Kehler JM, Brasel KJ, et al. It’s big surgery: preoperative expressions of risk, responsibility, and commitment to treatment after high-risk operations. Ann Surg. 2014;259(3):458–63.CrossRef
29.
Cooper Z, Courtwright A, Karlage A, Gawande A, Block S. Pitfalls in communication that lead to nonbeneficial emergency surgery in elderly patients with serious illness: description of the problem and elements of a solution. Ann Surg. 2014;260(6):949–57.CrossRef
30.
Modes ME, Engelberg RA, Downey L, Nielsen EL, Curtis JR, Kross EK. Did a goals-of-care discussion happen? Differences in the occurrence of goals-of-care discussions as reported by patients, clinicians, and in the electronic health record. J Pain Symp Manag. 2019;57(2):251–9.CrossRef
Metadata
Title
Deficits in the Palliative Care Process Measures in Patients with Advanced Pancreatic Cancer Undergoing Operative and Invasive Nonoperative Palliative Procedures
Authors
Brooks V. Udelsman, MD, MHS
Elizabeth J. Lilley, MD, MPH
Motaz Qadan, PhD
David C. Chang, PhD, MBA, MPH
Keith D. Lillemoe, MD
Charlotta Lindvall, MD, PhD
Zara Cooper, MD, MSc
Publication date
01-12-2019
Publisher
Springer International Publishing
Published in
Annals of Surgical Oncology / Issue 13/2019
Print ISSN: 1068-9265
Electronic ISSN: 1534-4681
DOI
https://doi.org/10.1245/s10434-019-07757-2

Other articles of this Issue 13/2019

Annals of Surgical Oncology 13/2019 Go to the issue

Breast Oncology

Does Breast Density Increase the Risk of Re-excision for Women with Breast Cancer Having Breast-Conservation Therapy?

ASO Author Reflections

ASO Author Reflections: Should Breast Density Influence Patient Selection for Breast-Conserving Surgery?

Sarcoma

Outcome of Primary Desmoid Tumors at All Anatomic Locations Initially Managed with Active Surveillance

Breast Oncology

Flipping a Coin? Predicting Nodal Status After Neoadjuvant Chemotherapy

Endocrine Tumors

A Novel N Staging System for Predicting Survival in Patients with Medullary Thyroid Cancer

Sarcoma

Functional Outcome Measurement in Patients with Lower-Extremity Soft Tissue Sarcoma: A Systematic Literature Review