Economic Evaluations for Service Delivery in Autism Spectrum Disorders

Angjellari-Dajci, Fjorentina; Lawless, William F.; Stachura, Max E.; Wood, Elena; DiBattisto, Caroline

doi:10.4018/978-1-4666-3990-4.ch002

Cited by 1 publication

(4 citation statements)

References 48 publications

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Section: Resultsmentioning

confidence: 99%

“…As shown by Davalos et al 5 and Bongiovanni-Delarozière and Le Goff-Pronost, 34 asking users to supply information about their WTP for different factors and attempting to convert health outcomes into monetary units can be challenging. Unlike other types of tradable commodities, health outcomes are not typically attached to a visible price, which may complicate the valuation of health improvements generated by DHIs, as stressed by Reardon and Angjellari-Dajci et al 24 , 36 …”

Section: Resultsmentioning

confidence: 99%

“…The included studies were published between 1997 and 2021. All had a theoretical or methodological design: 6 were (or included) reviews of the literature 5,7,13,24,25,34 , 6 were theoretical studies or had a theoretical component, 6,12,22,26,27,35 2 proposed theoretical frameworks, 36,37 and 1 was a methodological guideline. 23 The arguments extracted from the included studies pertained to analytical frameworks (from 14 studies, equal to 93%), generic outcome measures (5 studies, 33%), techniques used to elicit utility values (3 studies, 20%), and disease-specific outcome measures and instruments to collect health states data (2 studies, 13%).…”

Section: Overall Summary Of Included Studiesmentioning

confidence: 99%

“…12,25,35 However, other studies point to the limits of using CBAs. As shown by Davalos et al 5 and Bongiovanni-Delarozie`re and Le Goff-Pronost, 34 asking users to supply information about their WTP for different factors and attempting to convert health outcomes into 24,36 Cost-effectiveness analysis (n = 3 studies). Reardon 24 provided insights on the importance of choosing the outcome measure in cost-effectiveness analyses (CEAs).…”

Section: Synthesis Of Argumentsmentioning

confidence: 99%

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Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions: A Methodological Systematic Review

et al. 2022

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Background Digital health interventions (DHIs) can improve the provision of health care services. To fully account for their effects in economic evaluations, traditional methods based on measuring health-related quality of life may not be appropriate, as nonhealth and process outcomes are likely to be relevant too. Purpose This systematic review identifies, assesses, and synthesizes the arguments on the analytical frameworks and outcome measures used in the economic evaluations of DHIs. The results informed recommendations for future economic evaluations. Data Sources We ran searches on multiple databases, complemented by gray literature and backward and forward citation searches. Study Selection We included records containing theoretical and empirical arguments associated with the use of analytical frameworks and outcome measures for economic evaluations of DHIs. Following title/abstract and full-text screening, our final analysis included 15 studies. Data Extraction The arguments we extracted related to analytical frameworks (14 studies), generic outcome measures (5 studies), techniques used to elicit utility values (3 studies), and disease-specific outcome measures and instruments to collect health states data (both from 2 studies). Data Synthesis Rather than assessing the quality of the studies, we critically assessed and synthesized the extracted arguments. Building on this synthesis, we developed a 3-stage set of recommendations in which we encourage the use of impact matrices and analyses of equity impacts to integrate traditional economic evaluation methods. Limitations Our review and recommendations explored but not fully covered other potentially important aspects of economic evaluations that were outside our scope. Conclusions This is the first systematic review that summarizes the arguments on how the effects of DHIs could be measured in economic evaluations. Our recommendations will help design future economic evaluations. Highlights Using traditional outcome measures based on health-related quality of life (such as the quality-adjusted life-year) may not be appropriate in economic evaluations of digital health interventions, which are likely to trigger nonhealth and process outcomes. This is the first systematic review to investigate how the effects of digital health interventions could be measured in economic evaluations. We extracted and synthesized different arguments from the literature, outlining advantages and disadvantages associated with different methods used to measure the effects of digital health interventions. We propose a methodological set of recommendations in which 1) we suggest that researchers consider the use of impact matrices and cost-consequence analysis, 2) we discuss the suitability of analytical frameworks and outcome measures available in economic evaluations, and 3) we highlight the need for analyses of equity impacts.

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