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MAST – an evaluative framework for telemedicine innovations

Mon. 10. Dec 2018 12:36

In ImpleMentAll, our ultimate goal is to develop a toolkit for tailored eHealth implementation, the ItFits-toolkit. Our assessment of the ItFits-toolkit as a potentially valuable innovation will be based on several frameworks. The “Model for Assessment of Telemedicine” (MAST) is one of them.

MAST is a framework for assessment and evaluation of telemedicine innovations in the healthcare sector.

The model was developed to provide a basis for the decision of whether a telemedicine innovation is beneficial to the patients and the healthcare system or not. Many digital innovations do not give value for money the first times they are implemented, this is just how innovations work; they are implemented, assessed, and then altered before being implemented again. MAST provides a structure to help decision makers gather the knowledge necessary to form a foundation for the right decision.

When developing MAST, the researchers asked 50 different European healthcare decision makers what they would like to know before deciding whether an innovation should be implemented. Based on these answers, they detected 7 domains that are crucial to explore when making this decision:

  • The first domain concerns which health problem the innovation will deal with and the innovative technology that is used to solve the problem.
  • The second domain concerns the patient’s safety in relation to the innovation, including clinical and technical safety.
  • The third domain is clinical effectiveness, that is, which effect the innovation has on the life and health of the patient.
  • The fourth domain is patient perspectives; this concerns the patient’s experience of the innovation.
  • The fifth domain concerns the economic aspects: how much the innovation costs to buy and implement and what are the economic consequences.
  • The sixth domain is the organisational aspects, including how the staff experiences the innovation when working with it.
  • The seventh and last domain concerns the socio-cultural and legal aspects such as law and ethics.

The information used to describe the outcomes of telemedicine within each domain must be based on science and scientific methods. In some cases, e.g. when the telemedicine service involves moving hospital treatment of patients with serious illnesses to their own home, a randomised trial with a significant number of participants is needed. In other cases, interviews with a small cohort of patients with experience with the telemedicine service may be sufficient.

”The seven domains of MAST are based on what European healthcare decision makers need when making decisions on whether to buy new telemedicine services or not. Therefore, MAST can help companies and innovators in identifying the most relevant information about their new technology and avoid unnecessary data collection,” says Kristian Kidholm, one of the developers of MAST.

The assessment must start with preceding considerations to determine whether it is relevant for an organisation to carry out the assessment and whether the technology and the organisation are sufficiently matured and prepared. After the preceding considerations, the multidisciplinary assessment is carried out to describe and assess the different outcomes of the innovation. The outcomes and description of patients and the innovation can be divided into the seven domains described above. Finally, in relation to the description of the outcomes, an assessment should also be made of the transferability of the results.

Commenting on the value and effectivity of MAST, Kristian Kidholm says, ”Our delphi study from 2017 showed that MAST is valid and does provide the information about telemedicine that decision makers need.”

To match the project's complexity, the evaluation carried out in IMA will be based on and inspired by several frameworks, including MAST. If you have any questions or comments on MAST, please make sure to write them below, we would love to hear your inputs!

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 733025.
This content reflects only the author's view and the European Commission is not responsible for any use that may be made of the information it contains.
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