Effectiveness of palliative care services: A population-based study of end-of-life care for cancer patients

Abstract

Background:

Multiple studies demonstrate substantial utilization of acute hospital care and, potentially excessive, intensive medical and surgical treatments at the end-of-life.

Aim:

To evaluate the relationship between the use of home and facility-based hospice palliative care for patients dying with cancer and service utilization at the end of life.

Design:

Retrospective, population-level study using administrative databases. The effect of palliative care was analyzed between coarsened exact matched cohorts and evaluated through a conditional logistic regression model.

Setting/participants:

The study was conducted on the cohort of 34,357 patients, resident in Emilia-Romagna Region, Italy, admitted to hospital with a diagnosis of metastatic or poor-prognosis cancer during the 6 months before death between January 2013 and December 2015.

Results:

Patients who received palliative care experienced significantly lower rates of all indicators of aggressive care such as hospital admission (odds ratio (OR) = 0.05, 95% confidence interval (CI): 0.04–0.06), emergency department visits (OR = 0.23, 95% CI: 0.21–0.25), intensive care unit stays (OR = 0.29, 95% CI: 0.26–0.32), major operating room procedures (OR = 0.22, 95% CI: 0.21–0.24), and lower in-hospital death (OR = 0.11, 95% CI: 0.10–0.11). This cohort had significantly higher rates of opiate prescriptions (OR = 1.27, 95% CI: 1.21–1.33) (p < 0.01 for all comparisons).

Conclusion:

Use of palliative care at the end of life for cancer patients is associated with a reduction of the use of high-cost, intensive services. Future research is necessary to evaluate the impact of increasing use of palliative care services on other health outcomes. Administrative databases linked at the patient level are a useful data source for assessment of care at the end of life.

Keywords

Palliative care health resources advanced cancer retrospective studies quality of health care terminal care Italy humans

Get full access to this article

View all access options for this article.

References

Morrison

Penrod

Cassel

et al . Cost savings associated with US hospital palliative care consultation programs. Arch Intern Med 2008; 168(16): 1783–1790.

Morrison

Dietrich

Ladwig

et al . Palliative care consultation teams cut hospital costs for Medicaid beneficiaries. Health Aff 2011; 30(3): 454–463.

Bekelman

Halpern

Blankart

et al . Comparison of site of death, health care utilization, and hospital expenditures for patients dying with cancer in 7 developed countries. JAMA 2016; 315(3): 272–283.

Brooks

Uno

et al . Acute hospital care is the chief drive of regional spending variation in Medicare patients with advanced cancer. Health Aff 2014; 33(10): 1793–1800.

Teno

Gozalo

Bynum

JPW

et al . Change in end-of-life care for Medicare beneficiaries: site of death, place of care, and health care transitions in 2000, 2005, and 2009. JAMA 2013; 309(5): 470–477.

Schnipper

Smith

Raghavan

et al . American Society of Clinical Oncology identifies five key opportunities to improve care and reduce costs: the top five list for oncology. J Clin Oncol 2012; 30(14): 1715–1724.

Kwok

Semel

Lositz

et al . The intensity and variation of surgical care at the end of life: a retrospective cohort study. Lancet 2011; 378: 1408–1413.

Higginson

Sen-Gupta

Place of care in advanced cancer: a qualitative systematic literature review of patient preferences. J Palliat Med 2000; 3(3): 287–300.

Barnato

Herndon

Anthony

et al . Are regional variations in end-of-life care intensity explained by patient preferences? A study of the US Medicare population. Med Care 2007; 45(5): 386–393.

10.

Morden

Chang

Jacobson

et al . End-of-life care for Medicare beneficiaries with cancer is highly intensive overall and varies widely. Health Aff 2012; 31(4): 786–796.

11.

Gomes

Higginson

Calanzani

et al . Preferences for place of death if faced with advanced cancer: a population survey in England, Flanders, Germany, Italy, the Netherlands, Portugal and Spain. Ann Oncol 2012; 23: 2006–2015.

12.

Beccaro

Costantini

Rossi

et al . Actual and preferred place of death of cancer patients. Results from the Italian survey of the dying of cancer (ISDOC). J Epidemiol Community Health 2006; 60(5): 412–416.

13.

Krumholz

Nuti

Downing

et al . Mortality, hospitalizations, and expenditures for the Medicare population aged 65 years or older,1999-2013. JAMA 2015; 314(4): 355–365.

14.

Louis

Hegarty

Leoni

et al . Variation in hospital utilization at the end of life in patients with cancer in the Emilia-Romagna region of Italy. Tumori 2016; 102(6): 614–620.

15.

Regione Emilia-Romagna. Riorganizzazione della rete locale di cure palliative, 2015, http://bur.regione.emilia-romagna.it/dettaglio-inserzione?i=f986d752e68f4b689c49fd26e36536f1 (accessed 26 October 2017).

16.

National Institute of Statistics. Main geographic statistics, https://www.istat.it/it/archivio/156224 (accessed 26 October 2017).

17.

Iezzoni

Heeren

Foley

et al . Chronic conditions and risk of in-hospital death. Health Serv Res 1994; 29(4): 435–460.

18.

Berke

Smith

Song

et al . Cancer care in the United States: identifying end-of-life cohorts. J Palliat Med 2009; 12(2): 128–132.

19.

Gonnella

Louis

Gozum

et al . Clinical criteria for disease staging, 6th ed. Ann Arbor, MI: Truven Health Analytics, 2012.

20.

National Quality Forum. Palliative and end-of-life care 2015-2016: technical report. Washington, DC: National Quality Forum, 2016.

21.

Agency for Healthcare Research and Quality RM. HCUP procedure classes, http://www.hcup-us.ahrq.gov/toolssoftware/procedure/procedure.jsp (accessed 26 October 2017).

22.

ATC codes of opioids, http://www.cos.it/medicinadelterritorio/wp-content/uploads/2016/05/ATC_oppioidi.pdf (accessed 26 October 2017).

23.

Obermeyer

Makar

Abujaber

et al . Association between the Medicare hospice benefit and health care utilization and costs for patients with poor-prognosis cancer. JAMA 2014; 312(18): 1888–1896.

24.

Iacus

King

Porro

Multivariate matching methods that are monotonic imbalance bounding. JASA 2011; 106(493): 345–361.

25.

Austin

Grootendorst

Anderson

A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study. Stat Med 2007; 26(4): 734–753.

26.

Wright

Keating

Ayanian

et al . Family perspectives on aggressive cancer care near the end of life. JAMA 2016; 315(3): 284–292.

27.

Kelley

Deb

et al . Hospice enrollment saves money for Medicare and improves care quality across a number of different lengths-of-stay. Health Aff 2013; 32(3): 552–561.

28.

Teno

Clarridge

Casey

et al . Family perspectives on end-of-life care at the last place of care. JAMA 2004; 291(1): 88–93.

29.

Gawande

Quantity and quality of life: duties of care in life-limiting illness. JAMA 2016; 315(3): 267–269.

30.

Maltoni

Scarpi

Dall’Agata

et al . Systematic versus on-demand early palliative care: results from a multicentre, randomised clinical trial. Eur J Cancer 2016; 65: 61–68.

31.

Maltoni

Scarpi

Dall’Agata

et al . Systematic versus on-demand early palliative care: a randomised clinical trial assessing quality of care and treatment aggressiveness near the end of life. Eur J Cancer 2016; 69: 110–118.

32.

Haun

Estel

Rücker

et al . Early palliative care for adults with advanced cancer. Cochrane Database Syst Rev 2017; 6: CD011129.

33.

Kumar

Wright

Hatfield

et al . Family perspectives on hospice care experiences of patients with cancer. J Clin Oncol 2017; 35(4): 432–439.

34.

Teno

Gozalo

Quality and costs of end-of-life care: the need for transparency and accountability. JAMA 2014; 312(18): 1868–1869.

35.

Chitnis

Georghiou

Steventon

et al . Effect of a home-based end-of-life nursing service on hospital use at the end of life and place of death: a study using administrative data and matched controls. BMJ Support Palliat Care 2013; 3: 422–430.

36.

Seow

Brazil

Sussman

et al . Impact of community based, specialist palliative care teams on hospitalisations and emergency department visits late in life and hospital deaths: a pooled analysis. BMJ 2014; 348: g3496.

37.

Bachman

Barua

Single-person households: another look at the changing American family. Deloitte University Press, 2015, https://dupress.deloitte.com/dup-us-en/economy/behind-the-numbers/single-person-households-and-changing-american-family.html (accessed 23 May 2017).

38.

National Institute of Statistics. Italian statistical yearbook 2014, https://www.istat.it/it/archivio/134686

39.

Fisher

Wennberg

Stukel

et al . Associations among hospital capacity, utilization, and mortality of U.S. Medicare beneficiaries, controlling for sociodemographic factors. Health Serv Res 2000; 34(6): 1351–1362.

40.

Brooks

Sharma

et al . Regional variation in spending and survival for older adults with advanced cancer. J Natl Cancer Inst 2013; 105(9): 634–642.

41.

Setoguchi

Earle

Glynn

et al . Comparison of prospective and retrospective indicators of the quality of end-of-life cancer care. J Clin Oncol 2008; 26(35): 5671–5678.

42.

Brameld

Spilsbury

Rosenwax

et al . Issues using linkage of hospital records and death certificate data to determine the size of a potential palliative care population. Palliative Med 2017; 31(6): 537–543.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.06 MB