Solving the Malady of Financial Toxicity Using Augmented Intelligence

Bhattacharyya, Gouri Shankar; Bothra, Sneha; Malhotra, Hemant; Govindbabu, K.

doi:10.1200/cci.20.00155

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…62 The application of artificial intelligence for this purpose is also promising. 63 With the recent development of a machine learning model to predict FT, the algorithm was studied in about 600 patients with breast cancer and accurately predicted patients experiencing FT. Key factors associated with FT in this model included neoadjuvant therapy and autologous reconstruction (rather than implant-based reconstruction), but notably did include tumor stage and radiation therapy. 64 Regardless of the specific tool used, all FT screening methods should contain questions to identify patients with HRSN that may further affect development of FT, for example, housing insecurity, transportation costs, social isolation, or uninsurance/underinsurance.…”

Section: Health Care Utilizationmentioning

confidence: 99%

Section: Approaches To Address Ftmentioning

confidence: 99%

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Financial Toxicity in Cancer Care: Implications for Clinical Care and Potential Practice Solutions

Khan

Ramsey

Shankaran

2023

JCO

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Patients with cancer face an array of financial consequences as a result of their diagnosis and treatment, collectively referred to as financial toxicity (FT). In the past 10 years, the body of literature on this subject has grown tremendously, with a recent focus on interventions and mitigation strategies. In this review, we will briefly summarize the FT literature, focusing on the contributing factors and downstream consequences on patient outcomes. In addition, we will put FT into context with our emerging understanding of the role of social determinants of health and provide a framework for understanding FT across the cancer care continuum. We will then discuss the role of the oncology community in addressing FT and outline potential strategies that oncologists and health systems can implement to reduce this undue burden on patients with cancer and their families.

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Section: Health Care Utilizationmentioning

confidence: 99%

Section: Approaches To Address Ftmentioning

confidence: 99%

Financial Toxicity in Cancer Care: Implications for Clinical Care and Potential Practice Solutions

Khan

Ramsey

Shankaran

2023

JCO

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Interventions to mitigate cancer‐related medical financial hardship: A systematic review and meta‐analysis

Rashidi,

Jung,

Kao

et al. 2024

Cancer

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BackgroundThis study systematically reviewed interventions mitigating financial hardship in patients with cancer and assessed effectiveness using a meta‐analytic method.MethodsPubMed, Cochrane, Scopus, CINAHL, and Web of Science were searched for articles published in English during January 2000–April 2023. Two independent reviewers selected prospective clinical trials with an intervention targeting and an outcome measuring financial hardship. Quality appraisal and data extraction were performed independently by two reviewers using a quality assessment tool. A random‐effects model meta‐analysis was performed. Reporting followed the preferred reporting items for systematic review and meta‐analyses guidelines.ResultsEleven studies (2211 participants; 55% male; mean age, 59.29 years) testing interventions including financial navigation, financial education, and cost discussion were included. Financial worry improved in only 27.3% of 11 studies. Material hardship and cost‐related care nonadherence remained unchanged in the two studies measuring these outcomes. Four studies (373 participants; 37% male, mean age, 55.88 years) assessed the impact of financial navigation on financial worry using the comprehensive score of financial toxicity (COST) measure (score range, 0–44; higher score = lower financial worry) and were used for meta‐analysis. There was no significant change in the mean of pooled COST score between post‐ and pre‐intervention (1.21; 95% confidence interval, –6.54 to 8.96; p = .65). Adjusting for pre‐intervention COST, mean change of COST significantly decreased by 0.88 with every 1‐unit increase in pre‐intervention COST (p = .02). The intervention significantly changed COST score when pre‐intervention COST was ≤14.5.ConclusionA variety of interventions have been tested to mitigate financial hardship. Financial navigation can mitigate financial worry among high‐risk patients.

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Solving the Malady of Financial Toxicity Using Augmented Intelligence

Cited by 2 publications

References 11 publications

Financial Toxicity in Cancer Care: Implications for Clinical Care and Potential Practice Solutions

Financial Toxicity in Cancer Care: Implications for Clinical Care and Potential Practice Solutions

Interventions to mitigate cancer‐related medical financial hardship: A systematic review and meta‐analysis

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