An empirical tool for estimating the share of unmet need due to healthcare inefficiencies, suboptimal access, and lack of effective technologies

Devin Incerti,Geoff Makinson,Caroline Huber,Warren Stevens,Amir Goren,Christine L Baker,Richard Willke,John Browne

doi:10.1186/s12913-019-3914-7

Abstract

BackgroundAlthough 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.MethodsWe 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).ResultsHR-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.ConclusionWe 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.

Highlights

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
Measures of unmet need generally describe the gap between disease burden and the degree to which that burden can currently be overcome, but these measures ignore the burden that could be eliminated through technological advances [6,7,8,9]
disability-adjusted life year (DALY) usually are not measured at the individual patient level, which is required to link determinants of unmet need, such as insurance coverage, with treatment utilization. In light of these limitations, and a need to better understand the needs of patients, we developed a conceptual framework and empirical tool that allows unmet need to be measured using a single outcome measure shared across all diseases, and separates unmet from met need and subcategorizes the causes of unmet need

Summary

Introduction

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. A number of studies have described conceptual models of unmet need [1, 4, 5]. In these studies, measures of unmet need generally describe the gap between disease burden and the degree to which that burden can currently be overcome, but these measures ignore the burden that could be eliminated through technological advances [6,7,8,9]. Few studies have attempted to measure unmet need across multiple diseases while using uniform methodologies and outcome measures [10, 16, 17]

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