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Estimation of Seasonal Quality-Adjusted Life-Year Using Seemingly Unrelated Regression Equation Models With an
Gurprit Grover1, Deepak Goyal2, Radhika Magan1
1Department of Statistics, University of Delhi, New Delhi, India.
Value in Health Regional Issues
|December 7, 2021
Summary
This study introduces a cost-effectiveness model for orthopedic surgery implants using regression equations. It estimates health and cost impacts, calculating quality-adjusted life-year (QALY) values for improved healthcare services.
Area of Science:
- Orthopedic Surgery
- Health Economics
- Biostatistics
Background:
- Technological advancements in orthopedics necessitate cost-effective healthcare solutions.
- Evaluating the dual impact of health outcomes and financial costs in orthopedic surgery is crucial.
Purpose of the Study:
- To propose a model for estimating the simultaneous effects of health and cost in orthopedic surgery implants.
- To utilize seemingly unrelated regression equations for this estimation.
Main Methods:
- Simultaneous equations modeling to represent the relationship between patient health status and surgical costs.
- Estimation of utility functions for calculating quality-adjusted life-year (QALY) values.
Main Results:
- Seasonal QALY values were derived using seemingly unrelated regression equations with 2018-2019 data.
- Simple averages were employed to measure seasonal variations in QALY values.
Conclusions:
- Established a framework to analyze orthopedic patient health and expenditure relationships for both inpatients and outpatients.
- Developed a method for computing QALY values incorporating direct and indirect costs.
- Highlighted the utility of patient-reported outcome measures in assessing disease state changes and clinical improvements.
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