Health Resource and Cost Savings Achieved in a Multidisciplinary Lung Cancer Clinic

Christopher J L Stone; Ana P Johnson; Danielle Robinson; Andriy Katyukha; Rylan Egan; Sophia Linton; Christopher Parker; Andrew Robinson; Geneviève C Digby

doi:10.3390/curroncol28030157

Health Resource and Cost Savings Achieved in a Multidisciplinary Lung Cancer Clinic

Curr Oncol. 2021 Apr 29;28(3):1681-1695. doi: 10.3390/curroncol28030157.

Authors

Christopher J L Stone¹, Ana P Johnson², Danielle Robinson³, Andriy Katyukha³, Rylan Egan⁴, Sophia Linton⁵, Christopher Parker⁵, Andrew Robinson⁶, Geneviève C Digby^{5

6}

Affiliations

¹ Department of Medicine, University of Ottawa, Ottawa, ON K1H 8L6, Canada.
² Department of Public Health Science, Queen's University, Kingston, ON K7L 3N6, Canada.
³ School of Medicine, Queen's University, Kingston, ON K7L 3N6, Canada.
⁴ School of Nursing, Queen's University, Kingston, ON K7L 3N6, Canada.
⁵ Department of Medicine, Queen's University, Kingston, ON K7L 5P9, Canada.
⁶ Department of Oncology, Queen's University, Kingston, ON K7L 5P9, Canada.

Abstract

Background: Lung cancer (LC) care is resource and cost intensive. We launched a Multidisciplinary LC Clinic (MDC), where patients with a new LC diagnosis received concurrent oncology consultation, resulting in improved time to LC assessment and treatment. Here, we evaluate the impact of MDC on health resource utilization, patient and caregiver costs, and secondary patient benefits. Methods: We retrospectively analyzed patients in a rapid assessment clinic with a new LC diagnosis pre-MDC (September 2016-February 2017) and post-MDC implementation (February 2017-December 2018). Data are reported as means; unpaired t-tests and ANOVA were used to assess for significance. We also conducted a cost analysis. Resource utilization, out-of-pocket costs, procedure-related costs, and indirect costs were evaluated from the societal perspective and presented in 2019 Canadian dollars (CAD); multi-way worst/best case and threshold sensitivity analyses were conducted. Results: We reviewed 428 patients (78 traditional model, 350 MDC). Patients in the MDC model required significantly fewer oncology visits from LC diagnosis to first LC treatment (1.62 vs. 2.68, p < 0.001), which was significant for patients with stage 1, 3, and 4 disease. Compared with the traditional model, there was no change in mean biopsies/patient (1.32 traditional vs. 1.17 MDC, p = 0.18) or staging investigations/patient (2.24 traditional vs. 2.02 MDC, p = 0.20). Post-MDC, there was an increase in invasive mediastinal staging for patients with stage 2/3 LC (15.0% vs. 60.0%, p < 0.001). Over 22 months, MDC resulted in savings of CAD 48,389 including CAD 24,167 CAD in direct patient out-of-pocket expenses. For the threshold analyses, MDC was estimated to cost CAD 25,708 per quality-adjusted life year (QALY), considered to be below current willingness to pay thresholds (at CAD 80,000 per QALY). MDC also facilitated oncology assessment for 29 non-LC patients. Conclusions: An MDC led to a reduction in patient visits and direct patient and caregiver costs.

Keywords: health economics; lung cancer; patient care; quality improvement; resource utilization.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Canada
Cost Savings
Health Resources*
Humans
Lung Neoplasms* / diagnosis
Lung Neoplasms* / therapy
Retrospective Studies