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Cost-Effectiveness of Pain Management Strategies in Advanced Cancer

Published online by Cambridge University Press:  15 March 2019

David M. Meads*
Affiliation:
Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, United Kingdom
John L. O'Dwyer
Affiliation:
Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, United Kingdom
Claire T. Hulme
Affiliation:
Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, United Kingdom
Rocio Rodriguez Lopez
Affiliation:
Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, United Kingdom
Michael I. Bennett
Affiliation:
Academic Unit of Palliative Care, Leeds Institute of Health Sciences, University of Leeds, United Kingdom St Gemma's Academic Unit, St Gemma's Hospice, Leeds, United Kingdom
*
Author for correspondence: David Meads, E-mail: d.meads@leeds.ac.uk

Abstract

Objectives

Uncontrolled pain in advanced cancer is a common problem and has significant impact on individuals’ quality of life and use of healthcare resources. Interventions to help manage pain at the end of life are available, but there is limited economic evidence to support their wider implementation. We conducted a case study economic evaluation of two pain self-management interventions (PainCheck and Tackling Cancer Pain Toolkit [TCPT]) compared with usual care.

Methods

We generated a decision-analytic model to facilitate the evaluation. This modelled the survival of individuals at the end of life as they moved through pain severity categories. Intervention effectiveness was based on published meta-analyses results. The evaluation was conducted from the perspective of the U.K. health service provider and reported cost per quality-adjusted life-year (QALY).

Results

PainCheck and TCPT were cheaper (respective incremental costs -GBP148 [-EUR168.53] and -GBP474 [-EUR539.74]) and more effective (respective incremental QALYs of 0.010 and 0.013) than usual care. There was a 65 percent and 99.5 percent chance of cost-effectiveness for PainCheck and TCPT, respectively. Results were relatively robust to sensitivity analyses. The most important driver of cost-effectiveness was level of pain reduction (intervention effectiveness). Although cost savings were modest per patient, these were considerable when accounting for the number of potential intervention beneficiaries.

Conclusions

Educational and monitoring/feedback interventions have the potential to be cost-effective. Economic evaluations based on estimates of effectiveness from published meta-analyses and using a decision modeling approach can support commissioning decisions and implementation of pain management strategies.

Type
Assessment
Copyright
Copyright © Cambridge University Press 2019 

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Footnotes

This report presents independent research commissioned by the National Institute for Health Research under its Programme Grants for Applied Research programme (“Improving the Management of Pain from Advanced Cancer in the Community (IMPACCT)” RP-PG-0610-10114). The views expressed in this report are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. The authors would like to thank the centers and patients who participated in the IMPACCT patient survey. As this study did not include primary research with patients or clinicians, ethical approval was not required. The authors would like to thank the centers and patients who participated in the IMPACCT patient survey.

References

1.Haumann, J, Joosten, EBA, Everdingen, M (2017) Pain prevalence in cancer patients: Status quo or opportunities for improvement? Curr Opin Support Palliat Care 11, 99104.Google Scholar
2.Breivik, H, Cherny, N, Collett, B, et al. (2009) Cancer-related pain: A pan-European survey of prevalence, treatment, and patient attitudes. Ann Oncol 20, 14201433.Google Scholar
3.Shi, Q, Smith, TG, Michonski, JD, Stein, KD, Kaw, C, Cleeland, CS (2011) Symptom burden in cancer survivors 1 year after diagnosis. Cancer 117, 27792790.Google Scholar
4.Fortner, BV, Okon, TA, Portenoy, RK (2002) A survey of pain-related hospitalizations, emergency department visits, and physician office visits reported by cancer patients with and without history of breakthrough pain. J Pain 3, 3844.Google Scholar
5.Adam, R, Wassell, P, Murchie, P (2014) Why do patients with cancer access out-of-hours primary care? A retrospective study. Br J Gen Pract 64, e99e104.Google Scholar
6.Adam, R, Bond, C, Murchie, P (2015) Educational interventions for cancer pain. A systematic review of systematic reviews with nested narrative review of randomized controlled trials. Patient Educ Couns 98, 269282.Google Scholar
7.Martinez, KA, Aslakson, RA, Wilson, RF, et al. (2014) A systematic review of health care interventions for pain in patients with advanced cancer. Am J Hosp Palliat Care 31, 7986.Google Scholar
8.Bickel, K, Ozanne, E (2017) Importance of costs and cost effectiveness of palliative care. J Oncol Pract 13, 287289.Google Scholar
9.Cost-effective commissioning of end of life care: Understanding the health economics of palliative and end of life care. London: Public Health England; 2017. https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/612377/health-economics-palliative-end-of-life-care.pdf.Google Scholar
10.McCaffrey, N, Cassel, JB, Coast, J (2017) An economic view on the current state of the economics of palliative and end-of-life care. Palliat Med 31, 291292.Google Scholar
11.Bennett, MI, Mulvey, MR, Campling, N, et al. (2017) Self-management toolkit and delivery strategy for end-of-life pain: The mixed-methods feasibility study. Health Technol Assess 21, 1292.Google Scholar
12.National Institute for Health and Care Excellence (2013) Guide to the methods of technology appraisal. London. http://www.nice.org.uk/article/pmg9/resources/non-guidance-guide-to-the-methods-of-technology-appraisal-2013-pdf.Google Scholar
13.Serlin, RC, Mendoza, TR, Nakamura, Y, Edwards, KR, Cleeland, CS (1995) When is cancer pain mild, moderate or severe? Grading pain severity by its interference with function. Pain 61, 277–84.Google Scholar
14.Curtis, L (2016) Unit costs of health and social care 2015: Kent: Personal Social Services Research Unit; 2016.Google Scholar
15.Dolan, P, Gudex, C, Kind, P, Williams, A (1995) A social tariff for EuroQol: Results from a UK general population survey. York: Centre for Health Economics University of York.Google Scholar
16.Rowen, D, Brazier, J, Young, T, et al. (2011) Deriving a preference-based measure for cancer using the EORTC QLQ-C30. Value Health 14, 721731.Google Scholar
17.Wichmann, AB, Adang, EM, Stalmeier, PF, et al. (2017) The use of quality-adjusted life years in cost-effectiveness analyses in palliative care: Mapping the debate through an integrative review. Palliat Med 31, 306322.Google Scholar
18.Al-Janabi, H, Flynn, TN, Coast, J (2012) Development of a self-report measure of capability wellbeing for adults: The ICECAP-A. Qual Life Res 21, 167176.Google Scholar
19.Jensen, MP, McFarland, CA (1993) Increasing the reliability and validity of pain intensity measurement in chronic pain patients. Pain 55, 195203.Google Scholar
20.Meads, DM, Marshall, A, Hulme, CT, Dunn, JA, Ford, HE (2016) The cost effectiveness of docetaxel and active symptom control versus active symptom control alone for refractory oesophagogastric adenocarcinoma: Economic analysis of the COUGAR-02 Trial. PharmacoEconomics 34, 3342.Google Scholar
21.Zylla, D, Steele, G, Gupta, P (2017) A systematic review of the impact of pain on overall survival in patients with cancer. Support Care Cancer 25, 16871698.Google Scholar
22.Kroenke, K, Theobald, D, Wu, J, et al. (2010) Effect of telecare management on pain and depression in patients with cancer: A randomized trial. JAMA 304, 163171.Google Scholar
23.de Wit, R, van Dam, F (2001) From hospital to home care: A randomized controlled trial of a Pain Education Programme for cancer patients with chronic pain. J Adv Nurs 36, 742754.Google Scholar
24.Fenwick, E, O'Brien, BJ, Briggs, A (2004) Cost-effectiveness acceptability curves–facts, fallacies and frequently asked questions. Health Econ 13, 405415.Google Scholar
25.Claxton, KP, Sculpher, MJ (2006) Using value of information analysis to prioritise health research: Some lessons from recent UK experience. PharmacoEconomics 24, 10551068.Google Scholar
26.Office for National Statistics (2017) Death registrations summary tables - England and Wales. London: Office for National Statistics. https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/deathregistrationssummarytablesenglandandwalesreferencetables.Google Scholar
27.Strong, M, Oakley, JE, Brennan, A (2014) Estimating multiparameter partial expected value of perfect information from a probabilistic sensitivity analysis sample: A nonparametric regression approach. Med Decis Making 34, 311326.Google Scholar
28.Ling, CC, Lui, LY, So, WK (2012) Do educational interventions improve cancer patients' quality of life and reduce pain intensity? Quantitative systematic review. J Adv Nurs 68, 511520.Google Scholar
29.Bennett, MI, Bagnall, AM, Raine, G, et al. (2011) Educational interventions by pharmacists to patients with chronic pain: Systematic review and meta-analysis. Clin J Pain 27, 623630.Google Scholar
30.Santos Salas, A, Fuentes Contreras, J, Armijo-Olivo, S, et al. (2016) Non-pharmacological cancer pain interventions in populations with social disparities: A systematic review and meta-analysis. Support Care Cancer 24, 9851000.Google Scholar
31.Sellick, SM, Zaza, C (1998) Critical review of 5 nonpharmacologic strategies for managing cancer pain. Cancer Prev Control 2, 714.Google Scholar
32.Jho, HJ, Myung, SK, Chang, YJ, Kim, DH, Ko, DH (2013) Efficacy of pain education in cancer patients: A meta-analysis of randomized controlled trials. Support Care Cancer 21, 19631971.Google Scholar
33.Lee, YJ, Hyun, MK, Jung, YJ, Kang, MJ, Keam, B, Go, SJ (2014) Effectiveness of education interventions for the management of cancer pain: A systematic review. Asian Pac J Cancer Prev 15, 47874793.Google Scholar
34.Marie, N, Luckett, T, Davidson, PM, Lovell, M, Lal, S (2013) Optimal patient education for cancer pain: A systematic review and theory-based meta-analysis. Support Care Cancer 21, 35293537.Google Scholar
35.Adam, R, Burton, CD, Bond, CM, De Bruin, M, Murchie, P (2017) Can patient-reported measurements of pain be used to improve cancer pain management? A systematic review and meta-analysis. BMJ Support Palliat Care 7, 0.Google Scholar
36.Bennett, MI, Bagnall, AM, José Closs, S (2009) How effective are patient-based educational interventions in the management of cancer pain? Systematic review and meta-analysis. Pain 143, 192199.Google Scholar
37.Round, J, Jones, L, Morris, S (2015) Estimating the cost of caring for people with cancer at the end of life: A modelling study. Palliat Med 29, 899907.Google Scholar
38.Gardiner, C, Ingleton, C, Ryan, T, Ward, S, Gott, M (2017) What cost components are relevant for economic evaluations of palliative care, and what approaches are used to measure these costs? A systematic review. Palliat Med 31, 323337.Google Scholar
39.Meads, DM, O'Dwyer, JL, Hulme, CT, Chintakayala, P, Vinall-Collier, K, Bennett, MI (2017) Patient preferences for pain management in advanced cancer: Results from a discrete choice experiment. Patient 10, 643651.Google Scholar
40.Bennett, MI, Ziegler, L, Allsop, M, Daniel, S, Hurlow, A (2016) What determines duration of palliative care before death for patients with advanced disease? A retrospective cohort study of community and hospital palliative care provision in a large UK city. BMJ Open 6, e012576.Google Scholar
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