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A proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online PRESENT patient experience dashboard as a case example
BACKGROUND: Constrained budgets within healthcare systems and the need to efficiently allocate resources often necessitate the valuation of healthcare interventions and services. However, when a technological product is developed for which no market exists it is a challenge to understand how to plac...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7245892/ https://www.ncbi.nlm.nih.gov/pubmed/32448286 http://dx.doi.org/10.1186/s12911-020-1098-z |
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author | Mentzakis, Emmanouil Tkacz, Daria Rivas, Carol |
author_facet | Mentzakis, Emmanouil Tkacz, Daria Rivas, Carol |
author_sort | Mentzakis, Emmanouil |
collection | PubMed |
description | BACKGROUND: Constrained budgets within healthcare systems and the need to efficiently allocate resources often necessitate the valuation of healthcare interventions and services. However, when a technological product is developed for which no market exists it is a challenge to understand how to place the product and which specifications are the most sought after and important for end users. This was the case for a dashboard we developed, displaying analyses of patient experience survey free-text comments. METHOD: We describe a customisation and evaluation process for our online dashboard that addresses this challenge, using a Discrete Choice Experiment (DCE). We were not interested in the exact content of the dashboard, which was determined in previous stages of our larger study, but on the availability of features and customization options and how they affect individuals’ purchasing behaviours. RESULTS: Our DCE completion rate was 33/152 (22%). Certain features were highly desirable - the search function, filtering, and upload own data - and would contribute significant added value to the dashboard. Purchasing behaviour was dependent on the dashboard features, going from a 10 to 90% probability to purchase when we moved from a baseline to a fully-featured dashboard. The purchasing behaviour elicited in this study assumes individuals already have buy-in to the online dashboard, so we assessed only how the various features of our dashboard influence the probability of purchasing the product. Results were used to inform development of a generic checklist of desirable healthcare dashboard features as well as to refine the dashboard itself. Our study suggests the development of the online dashboard and its roll-out in the market would result in a positive net benefit in terms of utilities. The cost-benefit analysis offers a lower bound estimate of the net benefit as it does not acknowledge or incorporate non-monetary benefits that would result from the use of the online dashboard, such as from improved healthcare management. CONCLUSION: DCEs can be successfully used to inform development of an online dashboard by determining preferences for particular features and customisation options and how this affects individuals’ purchasing behaviours. The process should be transferable to the development of other technologies. |
format | Online Article Text |
id | pubmed-7245892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72458922020-06-01 A proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online PRESENT patient experience dashboard as a case example Mentzakis, Emmanouil Tkacz, Daria Rivas, Carol BMC Med Inform Decis Mak Research Article BACKGROUND: Constrained budgets within healthcare systems and the need to efficiently allocate resources often necessitate the valuation of healthcare interventions and services. However, when a technological product is developed for which no market exists it is a challenge to understand how to place the product and which specifications are the most sought after and important for end users. This was the case for a dashboard we developed, displaying analyses of patient experience survey free-text comments. METHOD: We describe a customisation and evaluation process for our online dashboard that addresses this challenge, using a Discrete Choice Experiment (DCE). We were not interested in the exact content of the dashboard, which was determined in previous stages of our larger study, but on the availability of features and customization options and how they affect individuals’ purchasing behaviours. RESULTS: Our DCE completion rate was 33/152 (22%). Certain features were highly desirable - the search function, filtering, and upload own data - and would contribute significant added value to the dashboard. Purchasing behaviour was dependent on the dashboard features, going from a 10 to 90% probability to purchase when we moved from a baseline to a fully-featured dashboard. The purchasing behaviour elicited in this study assumes individuals already have buy-in to the online dashboard, so we assessed only how the various features of our dashboard influence the probability of purchasing the product. Results were used to inform development of a generic checklist of desirable healthcare dashboard features as well as to refine the dashboard itself. Our study suggests the development of the online dashboard and its roll-out in the market would result in a positive net benefit in terms of utilities. The cost-benefit analysis offers a lower bound estimate of the net benefit as it does not acknowledge or incorporate non-monetary benefits that would result from the use of the online dashboard, such as from improved healthcare management. CONCLUSION: DCEs can be successfully used to inform development of an online dashboard by determining preferences for particular features and customisation options and how this affects individuals’ purchasing behaviours. The process should be transferable to the development of other technologies. BioMed Central 2020-05-24 /pmc/articles/PMC7245892/ /pubmed/32448286 http://dx.doi.org/10.1186/s12911-020-1098-z Text en © The Author(s). 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Mentzakis, Emmanouil Tkacz, Daria Rivas, Carol A proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online PRESENT patient experience dashboard as a case example |
title | A proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online PRESENT patient experience dashboard as a case example |
title_full | A proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online PRESENT patient experience dashboard as a case example |
title_fullStr | A proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online PRESENT patient experience dashboard as a case example |
title_full_unstemmed | A proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online PRESENT patient experience dashboard as a case example |
title_short | A proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online PRESENT patient experience dashboard as a case example |
title_sort | proof-of-concept framework for the preference elicitation and evaluation of health informatics technologies: the online present patient experience dashboard as a case example |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7245892/ https://www.ncbi.nlm.nih.gov/pubmed/32448286 http://dx.doi.org/10.1186/s12911-020-1098-z |
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