An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologies
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Published version
Supplementary file
Date
2019-02-11
Authors
Incerti, Devin
Browne, John P.
Huber, Caroline
Baker, Christine L.
Makinson, Geoff
Goren, Amir
Willke, Richard
Stevens, Warren
Journal Title
Journal ISSN
Volume Title
Publisher
BioMed Central Ltd
Published Version
Abstract
Background: Although there has been growing attention to the measurement of unmet need, which is the overall epidemiological burden of disease, current measures ignore the burden that could be eliminated from technological advances or more effective use of current technologies. Methods: We developed a conceptual framework and empirical tool that separates unmet need from met need and subcategorizes the causes of unmet need into suboptimal access to and ineffective use of current technologies and lack of current technologies. Statistical models were used to model the relationship between health-related quality of life (HR-QOL) and treatment utilization using data from the National Health and Wellness Survey (NHWS). Predicted HRQOL was combined with prevalence data from the Global Burden of Disease Study (GBD) to estimate met need and the causes of unmet need due to morbidity in the US and EU5 for five diseases: rheumatoid arthritis, breast cancer, Parkinson’s disease, hepatitis C, and chronic obstructive pulmonary disease (COPD). Results: HR-QOL was positively correlated with adherence to medication and patient-perceived quality and negatively correlated with financial barriers. Met need was substantial across all disease and regions, although significant unmet need remains. While the majority of unmet need was driven by lack of technologies rather than ineffective use of current technologies, there was considerable variation across diseases and regions. Overall unmet need was largest for COPD, which had the highest prevalence of all diseases in this study. Conclusion: We developed a methodology that can inform decisions about which diseases to invest in and whether those investments should focus on improving access to currently available technologies or inventing new technologies
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Keywords
Unmet need , Quality of life , Healthcare inefficiency , Access to healthcare , Health economics , Inequality
Citation
Incerti, D., Browne, J., Huber, C., Baker, C.L., Makinson, G., Goren, A., Willke, R. and Stevens, W. (2019). An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologies. BMC health services research, 19(1), 113. (11pp) doi: 10.1186/s12913-019-3914-7