Learnings From the Development of a Disease-Specific Utility Instrument for Economic Evaluation

2020 ◽  
Author(s):  
Tracy Comans ◽  
Kim-Huong Nguyen ◽  
Alyssa Welch
Author(s):  
Susan Cleary

Abstract Health systems strengthening (HSS) is firmly on the global health and development agenda. While a growing evidence base seeks to understand the effectiveness of HSS, there is limited evidence regarding cost and cost-effectiveness. Without such evidence, it is hard to argue that HSS represents value for money and the level of investment needed cannot be quantified. This paper seeks to review the literature regarding the economic evaluation of HSS from low- and middle-income country (LMIC) settings, and to contribute towards the development of methods for the economic evaluation of HSS. A systematic search for literature was conducted in PubMed, Scopus and the Health Systems Evidence database. MeSH terms related to economic evaluation were combined with key words related to the concept of HSS. Of the 204 records retrieved, 52 were retained for full text review and 33 were included. Of these, 67% were published between January 2015 and June 2019. While many HSS interventions have system wide impacts, most studies (71%) investigated these impacts using a disease-specific lens (e.g. the impact of quality of care improvements on uptake of facility deliveries). HSS investments were categorized, with the majority being investments in platform efficiency (e.g. quality of care), followed by simultaneous investment in platform efficiency and platform capacity (e.g. quality of care and task shifting). This review identified a growing body of work seeking to undertake and/or conceptualize the economic evaluation of HSS in low- and middle-income countries. The majority assess HSS interventions using a disease-specific or programmatic lens, treating HSS in a similar manner to the economic evaluation of medicines and diagnostics. While this approach misses potential economies of scope from HSS investments, it allows for a preliminary understanding of relative value for money. Future research is needed to complement the emerging evidence base.


Haemophilia ◽  
2005 ◽  
Vol 11 (1) ◽  
pp. 49-57 ◽  
Author(s):  
J. Wasserman ◽  
L. A. Aday ◽  
C. E. Begley ◽  
C. Ahn ◽  
D. R. Lairson

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2205-2205
Author(s):  
Joan E. Wasserman ◽  
William K. Hoots

Abstract Research has shown that disease-specific health-related quality of life (HRQoL) instruments are more responsive than generic instruments to particular disease conditions. However, only a few studies have used disease-specific instruments to measure HRQoL in hemophilia. The goal of this project was to develop a disease-specific utility instrument that measures patient preferences for various hemophilia health states. The visual analog scale (VAS), a ranking method, and the standard gamble (SG), a choice-based method incorporating risk, were used to measure patient preferences. Study participants (n=128) were recruited from the UT/Gulf States Hemophilia and Thrombophilia Center and stratified by age: 0 – 18 years and 19 +. Test retest reliability was demonstrated for both VAS and SG instruments, overall within-subject correlation coefficients were 0.91 and 0.79, respectively. Results showed statistically significant differences in responses between pediatric and adult participants when using the SG (p=.045). However, no significant differences were shown between these groups when using the VAS (p=.636). When responses to VAS and SG instruments were compared, statistically significant differences in both pediatric (p<.0001) and adult (p<.0001) groups were observed. Stratification of the study sample into mild, moderate and severe disease categories yielded no statistically significant differences in patient preference values among the three groups for both instruments (VAS (p =0.578 for mild vs. moderate, p =0.590 for mild vs. severe and p= 0.920 for moderate vs. severe and SG (p= 0.578 for mild vs. moderate, p = 0.590 for mild vs. severe and p=0.920 for moderate vs. severe). The utility measures obtained from this study can be applied in economic evaluations and decision models that analyze the cost/utility of alternative hemophilia treatments. Results derived from the SG indicate that age can influence patients’ preferences regarding their state of health. This may have implications for considering treatment options based on the mean age of the population under consideration. Data from this study also demonstrated that persons with varying severity of disease were able to objectively evaluate a wide range of health states for hemophilia. When assessing HRQoL for a rare disease such as hemophilia, it is important to establish that HRQoL measurements can be applied broadly across the population. Although the VAS and SG independently demonstrated reliability and validity, results indicate that the two measures may not be interchangeable.


BJPsych Open ◽  
2018 ◽  
Vol 4 (4) ◽  
pp. 160-166 ◽  
Author(s):  
Thor Gamst-Klaussen ◽  
Admassu N. Lamu ◽  
Gang Chen ◽  
Jan Abel Olsen

BackgroundMany clinical studies including mental health interventions do not use a health state utility instrument, which is essential for producing quality-adjusted life years. In the absence of such utility instrument, mapping algorithms can be applied to estimate utilities from a disease-specific instrument.AimsWe aim to develop mapping algorithms from two widely used depression scales; the Depression Anxiety Stress Scales (DASS-21) and the Kessler Psychological Distress Scale (K-10), onto the most widely used health state utility instrument, the EQ-5D-5L, using eight country-specific value sets.MethodA total of 917 respondents with self-reported depression were recruited to describe their health on the DASS-21 and the K-10 as well as the new five-level version of the EQ-5D, referred to as the EQ-5D-5L. Six regression models were used: ordinary least squares regression, generalised linear models, beta binomial regression, fractional logistic regression model, MM-estimation and censored least absolute deviation. Root mean square error, mean absolute error and r2 were used as model performance criteria to select the optimal mapping function for each country-specific value set.ResultsFractional logistic regression model was generally preferred in predicting EQ-5D-5L utilities from both DASS-21 and K-10. The only exception was the Japanese value set, where the beta binomial regression performed best.ConclusionsMapping algorithms can adequately predict EQ-5D-5L utilities from scores on DASS-21 and K-10. This enables disease-specific data from clinical trials to be applied for estimating outcomes in terms of quality-adjusted life years for use in economic evaluations.Declaration of interestNone.


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