Beyond the Numbers: Measuring the Real-Life Impact of Medical Treatments via Patient-Level Modeling
Author(s)
Kristen Cribbs, MPH, PhD1, Ethan Donnelly, BE2, Linda Upchurch, MBA, MHA3, Samantha Watson, MBA4, Betsy J. Lahue, MPH2.
1Research Director, Alkemi LLC, New York, NY, USA, 2Alkemi LLC, Manchester Center, VT, USA, 3AngioDynamics, Inc., Latham, NY, USA, 4Samantha Watson Consulting, Manchester Center, VT, USA.
1Research Director, Alkemi LLC, New York, NY, USA, 2Alkemi LLC, Manchester Center, VT, USA, 3AngioDynamics, Inc., Latham, NY, USA, 4Samantha Watson Consulting, Manchester Center, VT, USA.
Presentation Documents
OBJECTIVES: The 2021 U.S. price transparency regulations required providers to disclose costs and aimed to empower patients. While tools now exist to estimate out-of-pocket costs related to health care services, there are a dearth of models estimating comprehensive patient-level resources and economic outcomes across treatment options.
METHODS: Using the 2023 Academy Health Patient and Caregiver Economic Impact Framework, our team of health economists developed an excel-based model to estimate both clinical outcomes and “financial toxicity” (i.e., financial burden) related to discrete treatment choices. The model perspective was the patient and caregiver. Initial inputs were informed by peer-reviewed literature with assumptions provided by a specialty physician. Two patient advocates critically reviewed assumptions, inputs, and outputs. ISPOR budget impact standards were followed. A simulated scenario compared 3 oncology treatments to assess functionality, usability, and data visualization.
RESULTS: The patient-impact model is user modifiable and projects relevant outcomes and costs from the patient and caregiver perspective across three treatment phases (pre-treatment, treatment, post-treatment). The model allows both a 1- and 5-year horizon for prioritized patient- and caregiver-relevant financial toxicity factors (e.g., out-of-pocket responsibility, lost wages, travel expenses), medical services consumed, missed work, and clinical and quality-of-life impacts. Results, presented annually and over 5 years, are stratified by insurance type (Medicare, Medicare Advantage, Commercial) for each treatment pathway. Outcomes include per-patient/caregiver and cohort-level resource utilization, costs, and health outcomes for each treatment phase. Following review of the comparative oncology treatment simulation, experts suggested output simplification to enhance provider and patient interpretation.
CONCLUSIONS: This first-known patient impact model offers a novel approach to projecting clinical and socioeconomic factors to enable transparent cost discussions. By providing comparative analysis of relevant outcomes such as direct and indirect patient costs across the treatment journey, patient-impact models can support informed patient-provider discussions and foster patient-centric decision-making.
METHODS: Using the 2023 Academy Health Patient and Caregiver Economic Impact Framework, our team of health economists developed an excel-based model to estimate both clinical outcomes and “financial toxicity” (i.e., financial burden) related to discrete treatment choices. The model perspective was the patient and caregiver. Initial inputs were informed by peer-reviewed literature with assumptions provided by a specialty physician. Two patient advocates critically reviewed assumptions, inputs, and outputs. ISPOR budget impact standards were followed. A simulated scenario compared 3 oncology treatments to assess functionality, usability, and data visualization.
RESULTS: The patient-impact model is user modifiable and projects relevant outcomes and costs from the patient and caregiver perspective across three treatment phases (pre-treatment, treatment, post-treatment). The model allows both a 1- and 5-year horizon for prioritized patient- and caregiver-relevant financial toxicity factors (e.g., out-of-pocket responsibility, lost wages, travel expenses), medical services consumed, missed work, and clinical and quality-of-life impacts. Results, presented annually and over 5 years, are stratified by insurance type (Medicare, Medicare Advantage, Commercial) for each treatment pathway. Outcomes include per-patient/caregiver and cohort-level resource utilization, costs, and health outcomes for each treatment phase. Following review of the comparative oncology treatment simulation, experts suggested output simplification to enhance provider and patient interpretation.
CONCLUSIONS: This first-known patient impact model offers a novel approach to projecting clinical and socioeconomic factors to enable transparent cost discussions. By providing comparative analysis of relevant outcomes such as direct and indirect patient costs across the treatment journey, patient-impact models can support informed patient-provider discussions and foster patient-centric decision-making.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
PCR231
Topic
Patient-Centered Research
Topic Subcategory
Instrument Development, Validation, & Translation
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, SDC: Oncology