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

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Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions: A Methodological Systematic Review. / Benedetto, Valerio; Filipe, Luís; Harris, Catherine et al.
In: Medical Decision Making, Vol. 43, No. 1, 01.01.2023, p. 125-138.

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Benedetto V, Filipe L, Harris C, Spencer J, Hickson C, Clegg A. Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions: A Methodological Systematic Review. Medical Decision Making. 2023 Jan 1;43(1):125-138. Epub 2022 Oct 19. doi: 10.1177/0272989x221132741

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Benedetto, Valerio ; Filipe, Luís ; Harris, Catherine et al. / Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions : A Methodological Systematic Review. In: Medical Decision Making. 2023 ; Vol. 43, No. 1. pp. 125-138.

Bibtex

@article{e242ea0b7dcc456b9863e00464f1b6ac,
title = "Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions: A Methodological Systematic Review",
abstract = "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. 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.",
keywords = "Health Policy",
author = "Valerio Benedetto and Lu{\'i}s Filipe and Catherine Harris and Joseph Spencer and Carmel Hickson and Andrew Clegg",
year = "2023",
month = jan,
day = "1",
doi = "10.1177/0272989x221132741",
language = "English",
volume = "43",
pages = "125--138",
journal = "Medical Decision Making",
issn = "0272-989X",
publisher = "SAGE Publications Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - Analytical Frameworks and Outcome Measures in Economic Evaluations of Digital Health Interventions

T2 - A Methodological Systematic Review

AU - Benedetto, Valerio

AU - Filipe, Luís

AU - Harris, Catherine

AU - Spencer, Joseph

AU - Hickson, Carmel

AU - Clegg, Andrew

PY - 2023/1/1

Y1 - 2023/1/1

N2 - 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. 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.

AB - 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. 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.

KW - Health Policy

U2 - 10.1177/0272989x221132741

DO - 10.1177/0272989x221132741

M3 - Journal article

C2 - 36259354

VL - 43

SP - 125

EP - 138

JO - Medical Decision Making

JF - Medical Decision Making

SN - 0272-989X

IS - 1

ER -