Impact of remote symptom monitoring program on payor-specific healthcare costs.

G Gabrielle Betty Rocque (O'Neal Comprehensive Cancer Center at The University of Alabama at Birmingham, Birmingham, AL) J Jeffrey Franks (Division of Hematology and Oncology, The University of Alabama at Birmingham, Birmingham, AL) S Sandra C. Olisakwe (Division of Hematology and Oncology, University of Alabama at Birmingham, Birmingham, AL) L Luqin Deng (Division of General Internal Medicine and Population Science, University of Alabama at Birmingham, Birmingham, AL) A Andres Azuero (School of Nursing, University of Alabama at Birmingham, Birmingham, AL) N Nicole E. Caston (The University of North Carolina at Chapel Hill, Chapel Hill, NC) A Ashley Lovingood (O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL) D Dorothea Staursky (O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL) B Baylie Mullinax (1University of Alabama at Birmingham, Division of Hematology and Oncology, Birmingham, United States) N Nicole Lynn Henderson (Division of Hematology and Oncology, The University of Alabama at Birmingham, Birmingham, AL) J James Nicholas Odom (School of Nursing, University of Alabama at Birmingham, Birmingham, AL) J Jennifer Young Pierce (University of South Alabama, Mobile, AL) E Ethan Basch (The University of North Carolina at Chapel Hill, Chapel Hill, NC) C Courtney Williams

Abstract

1632 Background: Remote symptom monitoring (RSM) programs are currently being implemented across oncology practices nationwide; however, the impact of RSM on costs by payor has been understudied. Methods: This is a secondary analysis of a hybrid implementation-effectiveness trial of electronic, patient reported outcome-based RSM for patients with cancer initiating systemic therapy (May 2021-May 2024). Differences in costs for healthcare services for RSM-enrolled patients were compared to historical controls. Outcomes included overall, monthly, payor-, and service-specific costs of care received at 3 and 6 months after RSM-enrollment date or initiation of systemic therapy for controls. Adjusted generalized linear models estimated predicted mean costs, mean cost ratios (MR) and 95% confidence intervals (CIs) for RSM-enrolled patients versus controls. Results: Patients receiving RSM (n=968) were 25% Black, 44% privately insured, and 27% living in a highly disadvantaged neighborhood. Historical controls (n=3,488) were demographically similar. Though non-statistically significant, RSM enrolled patients had 5% lower mean costs 3 months post-index date compared to historical controls (MR 0.95, 95% CI 0.78-1.16), translating to an estimated cost savings of $1,347 per patient (95% CI -$3,596, $6,290). Medicare Fee-for-Service (FFS) beneficiaries showed the greatest, though non-statistically significant, cost reductions, with RSM FFS beneficiaries having 10% lower costs than FFS controls (MR 0.90, 95% CI 0.67-1.19) at 3 months post-index date. Though non-statically significant, RSM-enrolled patients had 23% lower costs for radiation, 14% lower inpatient costs, 9% lower costs for labs, scans, or tests, and 2% lower outpatient costs compared to controls at 3 months post-index date. At one-month post-index date, RSM enrolled patients had statistically significantly lower payor costs compared to controls ($11,849 [95% CI $9,364-$14,335] vs. $15,706 [$14,291-$17,121]; p=.004). Costs for RSM enrolled patients and controls were similar two to six-months post-index date. Conclusions: We observed payor cost savings of $1,347 in the 3 months of RSM enrollment compared to controls. As the largest payor cost differences were seen for Medicare FFS beneficiaries, our results suggest RSM may address a gap in the provision of care coordination to patients not offered these services through their insurer. Cost savings were most prominent within the first month of treatment initiation; thus, RSM may aid in reducing acute care needs and optimizing resource utilization for patients with cancer. Our results support future research in potential risk-stratification methods to improve RSM engagement and delivery to reduce costs and improve outcomes for patients with cancer.

Article Details

Volume / Issue Vol. 44, Issue 16_suppl
Published June 01, 2026
Pages 1632-1632
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (14)

G

Gabrielle Betty Rocque

O'Neal Comprehensive Cancer Center at The University of Alabama at Birmingham, Birmingham, AL

J

Jeffrey Franks

Division of Hematology and Oncology, The University of Alabama at Birmingham, Birmingham, AL

S

Sandra C. Olisakwe

Division of Hematology and Oncology, University of Alabama at Birmingham, Birmingham, AL

L

Luqin Deng

Division of General Internal Medicine and Population Science, University of Alabama at Birmingham, Birmingham, AL

A

Andres Azuero

School of Nursing, University of Alabama at Birmingham, Birmingham, AL

N

Nicole E. Caston

The University of North Carolina at Chapel Hill, Chapel Hill, NC

A

Ashley Lovingood

O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL

D

Dorothea Staursky

O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL

B

Baylie Mullinax

1University of Alabama at Birmingham, Division of Hematology and Oncology, Birmingham, United States

N

Nicole Lynn Henderson

Division of Hematology and Oncology, The University of Alabama at Birmingham, Birmingham, AL

J

James Nicholas Odom

School of Nursing, University of Alabama at Birmingham, Birmingham, AL

J

Jennifer Young Pierce

University of South Alabama, Mobile, AL

E

Ethan Basch

The University of North Carolina at Chapel Hill, Chapel Hill, NC

C

Courtney Williams