An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologies
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 de...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2019-02-01
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| Series: | BMC Health Services Research |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12913-019-3914-7 |
| _version_ | 1818025200975872000 |
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| author | Devin Incerti John Browne Caroline Huber Christine L. Baker Geoff Makinson Amir Goren Richard Willke Warren Stevens |
| author_facet | Devin Incerti John Browne Caroline Huber Christine L. Baker Geoff Makinson Amir Goren Richard Willke Warren Stevens |
| author_sort | Devin Incerti |
| collection | DOAJ |
| description | 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 HR-QOL 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. |
| first_indexed | 2024-12-10T04:12:20Z |
| format | Article |
| id | doaj.art-6a8811dec20541adad9f9fcd06044c4a |
| institution | Directory Open Access Journal |
| issn | 1472-6963 |
| language | English |
| last_indexed | 2024-12-10T04:12:20Z |
| publishDate | 2019-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Health Services Research |
| spelling | doaj.art-6a8811dec20541adad9f9fcd06044c4a2022-12-22T02:02:42ZengBMCBMC Health Services Research1472-69632019-02-0119111110.1186/s12913-019-3914-7An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologiesDevin Incerti0John Browne1Caroline Huber2Christine L. Baker3Geoff Makinson4Amir Goren5Richard Willke6Warren Stevens7Precision Health EconomicsUniversity College CorkPrecision Health EconomicsPfizer, Inc.Pfizer, Inc.Kantar HealthInternational Society for Pharmacoeconomics and Outcomes ResearchParexel InternationalAbstract 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 HR-QOL 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.http://link.springer.com/article/10.1186/s12913-019-3914-7Unmet needQuality of lifeHealthcare inefficiencyAccess to healthcareHealth economicsInequality |
| spellingShingle | Devin Incerti John Browne Caroline Huber Christine L. Baker Geoff Makinson Amir Goren Richard Willke Warren Stevens 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 Unmet need Quality of life Healthcare inefficiency Access to healthcare Health economics Inequality |
| title | An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologies |
| title_full | An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologies |
| title_fullStr | An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologies |
| title_full_unstemmed | An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologies |
| title_short | An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologies |
| title_sort | empirical tool for estimating the share of unmet need due to healthcare inefficiencies suboptimal access and lack of effective technologies |
| topic | Unmet need Quality of life Healthcare inefficiency Access to healthcare Health economics Inequality |
| url | http://link.springer.com/article/10.1186/s12913-019-3914-7 |
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