Innovation in value-based Healthcare

Innovation in value-based Healthcare

This research group aims to develop interdisciplinary methods to assess value in health and support the paradigm shift to value-based healthcare.

With a focus on Digital Health, we are developing and validating innovative methodologies to measure outcomes and costs in healthcare. Furthermore, we are developing methodologies for real-context validation and value assessment of digital healthcare innovations.

The main research topics are:

  • Health and care pathway design and value analysis;
  • Healthcare Data science and machine learning methods;
  • Outcomes collection and Cost analysis;
  • Digital and health literacy for patient empowerment;
  • Real-context validation of digital health technologies;
  • Service design in digital healthcare;
  • Human-computer interaction for better health and personal outcomes.
     

Due to our interdisciplinary approach, we develop research projects collaboratively, with multiple stakeholders in Healthcare. 

Our approach is to include clinical teams in all the projects. We support clinical teams in assessing value of their healthcare interventions. We also develop pilot studies to support developers and medtech suppliers in assessing the value of digital innovations in healthcare.

In terms of methodology, research in the area of Innovation in Value-based Healthcare is developed using diverse methodologies, due to the multidisciplinary nature of the researchers in this group. 

Data from real health care settings is essentially used for retrospective or prospective analyses of clinical outcomes as well as of costs or socio-economic impact. Quantitative data is collected by importing data from healthcare facilities or by measurements obtained through digital applications or internet-of-things (IoT) devices. For quantitative analysis, statistical methods and advanced machine learning methods are used. Qualitative data is collected through interviews, questionnaires or focus groups, and its analysis uses descriptive methods, inductive or deductive analysis. Different methods are used to collect and analyze direct and indirect costs in order to evaluate the economic impact of health interventions. The most commonly used tools for data analysis and visualization are software programs for statistical analysis and programming environments in Python, R, among others. The mapping of patient-centered processes is worked with process modelling tools.

Our Researchers

Adalberto Campos Fernandes

Ana Catarina Maia

Ana Escoval

Ana Filipa Mourão

Ana Londral

Ana Lúcia João

Ana Margarida Advinha

Ana Maria

Ana Rita Lameiras

Ana Rodrigues

Carlota Louro

David Ferreira

David Mendes

Eduardo B. Cruz

Ermelinda Caldeira

Francisco Von Hafe

Helena Canhão

Helena Telles Antunes

JESUS CORTES

Joana Lobo Pimentel

Jorge Bravo

José Alberto Parraça

Lara Guedes de Pinho

Liliana Laranjo

Luís Gomes

Manuel Lopes

Maria Chora

Maria Margarida Goes

Maria Otília Zangão

Mariana Peyroteo

Marta M. Marques

Patricia Ribeiro Brito

Paulo Faria Boto

Pedro Dias

Rita Gonçalves

Rui Almeida

Rúben Araújo

Salomé Azevedo

Sofia Azeredo

Sofia Pinheiro

Sofia de Oliveira Martins

Soraia Ferreira

Susana Duarte

Sérgio Laranjo