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Dos Santos Leandro G, Moro CMC, Cruz-Correia RJ, Portela Santos EA. FHIR Implementation Guide for Stroke: A dual focus on the patient's clinical pathway and value-based healthcare. Int J Med Inform 2024; 190:105525. [PMID: 39033722 DOI: 10.1016/j.ijmedinf.2024.105525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 06/06/2024] [Accepted: 06/13/2024] [Indexed: 07/23/2024]
Abstract
BACKGROUND Stroke management requires a coordinated strategy, adhering to clinical pathways (CP) and value-based healthcare (VBHC) principles from onset to rehabilitation. However, the discrepancies between these pathways and actual patient experiences highlight the need for ongoing monitoring and addressing interoperability issues across multiple institutions in stroke care. To address this, the Fast Healthcare Interoperability Resource (FHIR) Implementation Guide (IG) standardizes the information exchange among these systems, considering a specific context of use. OBJECTIVE Develop an FHIR IG for stroke care rooted in established stroke CP and VBHC principles. METHOD We represented the stroke patient journey by considering the core stroke CP, the International Consortium for Health Outcomes Measurement (ICHOM) dataset for stroke, and a Brazilian case study using the Business Process Model and Notation (BPMN). Next, we developed a data dictionary that aligns variables with existing FHIR resources and adapts profiling from the Brazilian National Health Data Network (BNHDN). RESULTS Our BPMN model encompassed three critical phases that represent the entire patient journey from symptom onset to rehabilitation. The stroke data dictionary included 81 variables, which were expressed as questionnaires, profiles, and extensions. The FHIR IG comprised nine pages: Home, Stroke-CP, Data Dictionary, FHIR, ICHOM, Artifacts, Examples, Downloads, and Security. We developed 96 artifacts, including 7 questionnaires, 27 profiles with corresponding example instances, 3 extensions, 18 value sets, and 14 code systems pertinent to ICHOM outcome measures. CONCLUSION The FHIR IG for stroke in this study represents a significant advancement in healthcare interoperability, streamlining the tracking of patient outcomes for quality enhancement, facilitating informed treatment choices, and enabling the development of dashboards to promote collaborative excellence in patient care.
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Affiliation(s)
- Gabrielle Dos Santos Leandro
- Graduate Program in Health Technology, Pontifícia Universidade Católica do Paraná, Curitiba, Brazil; Center for Health Technology and Service Research - CINTESIS, Porto, Portugal; Prefeitura Municipal de Joinville, Joinville, Brazil.
| | | | - Ricardo João Cruz-Correia
- Center for Health Technology and Service Research - CINTESIS, Porto, Portugal; Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, Porto, Portugal
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Odeh Y, Al-Ruzzieh M, Al Rifai A, Mustafa H, Odeh M. Towards digital readiness of evidence-based practice in a regional cancer center using role-based business process and data modeling. Digit Health 2024; 10:20552076241281193. [PMID: 39286787 PMCID: PMC11403675 DOI: 10.1177/20552076241281193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Accepted: 08/19/2024] [Indexed: 09/19/2024] Open
Abstract
Introduction Evidence-based practice is a problem-based solving approach to clinical practice that encourages nurses providing personalized patient care while utilizing the necessary scientific evidence for a better understanding of risks and benefits of diagnostic tests and treatments. Digital transformation of an organization begins with attaining an acceptable digital readiness level. One approach entails specifying and modeling their processes and the respective data models. Objectives In Jordan, at King Hussein Cancer Center-an international and regional accredited cancer care hospital-their nursing practice requires obtaining a standardized specification of evidence-based practice processes and their respective conceptual data model that is currently not specified for digital readiness. Methods The design science research methodology was adopted to deliver two increments. The first was concerned with the design, development, and demonstration of eight evidence-based practice processes specified using BPMN. The second was related to the design and development, demonstration, and evaluation of a respective derived data model of the case study. Both increments involved interviews with domain experts for elicitation and validation. Results Eight evidence-based practice process models were identified and specified using BPMN along with their associated data models, where one representative process model was utilized in this research to demonstrate the effectiveness of process and data modeling towards digital readiness of evidence-based practice in regional cancer center. Conclusions Both deliverables enabled the evidence-based practice management to attain common understanding to identify inefficiencies, redundancies, and areas for improvement that can be addressed through digital solutions. Evidence -based practice BPMN process models were considered as a road map to follow up a project implementation and a rich visualization to perform data analytics to identify evidence-based practice trends, patterns, and insights that can inform strategic data-driven decisions. Both deliverables were concluded necessary for developing respective information systems in the journey towards digital transformation.
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Affiliation(s)
- Yousra Odeh
- Software Engineering Department, Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Amman, Jordan
- Cancer Care Informatics Program, King Hussein Cancer Center, Amman, Jordan
| | | | - Anwar Al Rifai
- Nursing Department, King Hussein Cancer Center, Amman, Jordan
| | - Hiba Mustafa
- Cancer Care Informatics Program, King Hussein Cancer Center, Amman, Jordan
| | - Mohammad Odeh
- Cancer Care Informatics Program, King Hussein Cancer Center, Amman, Jordan
- College of Art, Technology and Environment, University of the West of England, Bristol, UK
- Global Academy for Digital Health, Bristol, UK
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3
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Junger D, Just E, Brandenburg JM, Wagner M, Schaumann K, Klenzner T, Burgert O. Toward an interoperable, intraoperative situation recognition system via process modeling, execution, and control using the standards BPMN and CMMN. Int J Comput Assist Radiol Surg 2024; 19:69-82. [PMID: 37620748 PMCID: PMC10770268 DOI: 10.1007/s11548-023-03004-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 07/17/2023] [Indexed: 08/26/2023]
Abstract
PURPOSE For the modeling, execution, and control of complex, non-standardized intraoperative processes, a modeling language is needed that reflects the variability of interventions. As the established Business Process Model and Notation (BPMN) reaches its limits in terms of flexibility, the Case Management Model and Notation (CMMN) was considered as it addresses weakly structured processes. METHODS To analyze the suitability of the modeling languages, BPMN and CMMN models of a Robot-Assisted Minimally Invasive Esophagectomy and Cochlea Implantation were derived and integrated into a situation recognition workflow. Test cases were used to contrast the differences and compare the advantages and disadvantages of the models concerning modeling, execution, and control. Furthermore, the impact on transferability was investigated. RESULTS Compared to BPMN, CMMN allows flexibility for modeling intraoperative processes while remaining understandable. Although more effort and process knowledge are needed for execution and control within a situation recognition system, CMMN enables better transferability of the models and therefore the system. Concluding, CMMN should be chosen as a supplement to BPMN for flexible process parts that can only be covered insufficiently by BPMN, or otherwise as a replacement for the entire process. CONCLUSION CMMN offers the flexibility for variable, weakly structured process parts, and is thus suitable for surgical interventions. A combination of both notations could allow optimal use of their advantages and support the transferability of the situation recognition system.
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Affiliation(s)
- Denise Junger
- School of Informatics, Research Group Computer Assisted Medicine (CaMed), Reutlingen University, Reutlingen, Germany.
| | - Elisaveta Just
- School of Informatics, Research Group Computer Assisted Medicine (CaMed), Reutlingen University, Reutlingen, Germany
| | - Johanna M Brandenburg
- Department of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany
- National Center for Tumor Diseases Heidelberg, Heidelberg, Germany
| | - Martin Wagner
- Department of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany
- National Center for Tumor Diseases Heidelberg, Heidelberg, Germany
- Center for the Tactile Internet With Human in the Loop (CeTI), Technical University Dresden, Dresden, Germany
| | - Katharina Schaumann
- Department of Otorhinolaryngology, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Thomas Klenzner
- Department of Otorhinolaryngology, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Oliver Burgert
- School of Informatics, Research Group Computer Assisted Medicine (CaMed), Reutlingen University, Reutlingen, Germany
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Bobelyn A, Unteregger R, Höffken JI, Reymen I. Problem exploration for creating value propositions when developing point-of-care solutions. Biosens Bioelectron 2023; 241:115636. [PMID: 37703642 DOI: 10.1016/j.bios.2023.115636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 06/06/2023] [Accepted: 08/24/2023] [Indexed: 09/15/2023]
Abstract
Point-of-care (POC) testing has been increasingly proposed as one of the most promising solutions for improving healthcare provision as it enables fast and accurate testing both inside and outside hospital settings. Many of these POC device stem from academic research. Yet, the commercialization of these devices through academic spin-offs is not straigthforward. Many academic spin-offs fail due to an inproperly articulated value proposition. To create a value proposition with biosensors it is crucial to understand how they can be used to address problems in the current diagnostics processes and protocols. Therefore, this paper studies how different university teams engage in problem exploration to better understand how they can translate the technical features of their POC testing solutions into an attractive value proposition. To be able to study this, a qualitative case study research design was chosen. In particular, 11 university student teams participating in the SensUs contest were studied. The main findings show that teams adopting search patterns involving a 'broader' (i.e., considering a wider range of problems and stakeholders) and a more 'interconnected' (i.e., thematically linking problems with one another) problem-exploration were more successful in creating contest outcomes (biosensing solutions) with greater commercial viability. Moreover, teams that sougth direct feedback from market experts generated more commercially viable projects than teams that relied primarly on advice from technical experts.
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Zerbato F, Pufahl L, Teije AT. Preface: Special Issue on Knowledge Representation and Reasoning for Healthcare Processes. Artif Intell Med 2023; 143:102631. [PMID: 37673588 DOI: 10.1016/j.artmed.2023.102631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 08/07/2023] [Indexed: 09/08/2023]
Affiliation(s)
- Francesca Zerbato
- Institute of Computer Science, University of St. Gallen, St. Gallen, Switzerland.
| | - Luise Pufahl
- Information Systems, Technical University of Munich, Heilbronn, Germany
| | - Annette Ten Teije
- Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Michalowski M, Rao M, Wilk S, Michalowski W, Carrier M. Using graph rewriting to operationalize medical knowledge for the revision of concurrently applied clinical practice guidelines. Artif Intell Med 2023; 140:102550. [PMID: 37210156 DOI: 10.1016/j.artmed.2023.102550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 04/03/2023] [Accepted: 04/05/2023] [Indexed: 05/22/2023]
Abstract
Clinical practice guidelines (CPGs) are patient management tools that synthesize medical knowledge into an actionable format. CPGs are disease specific with limited applicability to the management of complex patients suffering from multimorbidity. For the management of these patients, CPGs need to be augmented with secondary medical knowledge coming from a variety of knowledge repositories. The operationalization of this knowledge is key to increasing CPGs' uptake in clinical practice. In this work, we propose an approach to operationalizing secondary medical knowledge inspired by graph rewriting. We assume that the CPGs can be represented as task network models, and provide an approach for representing and applying codified medical knowledge to a specific patient encounter. We formally define revisions that model and mitigate adverse interactions between CPGs and we use a vocabulary of terms to instantiate these revisions. We demonstrate the application of our approach using synthetic and clinical examples. We conclude by identifying areas for future work with the vision of developing a theory of mitigation that will facilitate the development of comprehensive decision support for the management of multimorbid patients.
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Affiliation(s)
| | | | - Szymon Wilk
- Poznan University of Technology, Poznan, Poland
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7
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Verga M, Viganò GL, Capuzzo M, Duri C, Ignoti LM, Picozzi P, Cimolin V. The digitization process and the evolution of Clinical Risk Management concept: The role of Clinical Engineering in the operational management of biomedical technologies. Front Public Health 2023; 11:1121243. [PMID: 36817927 PMCID: PMC9932586 DOI: 10.3389/fpubh.2023.1121243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
Introduction Digital transformation and technological innovation which have influenced several areas of social and productive life in recent years, are now also a tangible and concrete reality in the vast and strategic sector of public healthcare. The progressive introduction of digital technologies and their widespread diffusion in many segments of the population undoubtedly represent a driving force both for the evolution of care delivery methods and for the introduction of new organizational and management methods within clinical structures. Methods The CS Clinical Engineering of the "Spedali Civili Hospital in Brescia" decided to design a path that would lead to the development of a software for the management of biomedical technologies within its competence inside the hospital. The ultimate aim of this path stems from the need of Clinical Engineering Department to have up-to-date, realistic, and systematic control of all biomedical technologies present in the company. "Spedali Civili Hospital in Brescia" is not just one of the most important corporate realities in the city, but it is also the largest hospital in Lombardy and one of the largest in Italy. System development has followed the well-established phases: requirement analysis phase, development phase, release phase and evaluating and updating phase. Results Finally, cooperation between the various figures involved in the multidisciplinary working group led to the development of an innovative management software called "SIC Brescia". Discussion The contribution of the present paper is to illustrate the development of a complex implementation model for the digitization of processes, information relating to biomedical technologies and their management throughout the entire life cycle. The purpose of sharing this path is to highlight the methodologies followed for its realization, the results obtained and possible future developments. This may enable other realities in the healthcare context to undertake the same type of pathway inspired by an accomplished model. Furthermore, future implementation and data collection related to the proposed Key Performance Indicators, as well as the consequent development of new operational management models for biomedical technologies and maintenance processes will be possible. In this way, the Clinical Risk Management concept will also be able to evolve into a more controlled, safe, and efficient system for the patient and the user.
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Affiliation(s)
- Matteo Verga
- ASST Spedali Civili di Brescia - SC Ingegneria Clinica, Brescia, Italy
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Gian Luca Viganò
- ASST Spedali Civili di Brescia - SC Ingegneria Clinica, Brescia, Italy
| | - Martina Capuzzo
- ASST Spedali Civili di Brescia - SC Ingegneria Clinica, Brescia, Italy
| | - Claudia Duri
- ASST Spedali Civili di Brescia - SC Ingegneria Clinica, Brescia, Italy
| | | | - Paola Picozzi
- ASST Spedali Civili di Brescia - SC Ingegneria Clinica, Brescia, Italy
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Veronica Cimolin
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
- S. Giuseppe Hospital, Istituto Auxologico Italiano, IRCCS, Piancavallo, Italy
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8
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Dragoni M, Eccher C, Ferro A, Bailoni T, Maimone R, Zorzi A, Bacchiega A, Stulzer G, Ghidini C. Supporting patients and clinicians during the breast cancer care path with AI: The Arianna solution. Artif Intell Med 2023; 138:102514. [PMID: 36990591 DOI: 10.1016/j.artmed.2023.102514] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 12/09/2022] [Accepted: 02/17/2023] [Indexed: 02/24/2023]
Abstract
The onset of cancer disease is a traumatic experience for both patients and their families that suddenly change the patient's life and is accompanied by important physical, emotional, and psycho-social problems. The complexity of this scenario has been exacerbated by the COVID-19 pandemic which dramatically affected the continuity of the provision of optimal care to chronic patients. Telemedicine can support the management of oncology care paths by furnishing a suite of effective and efficient tools to monitor the therapies of cancer patients. In particular, this is a suitable setting for therapies that are administered at home. In this paper, we present an AI-based system, called Arianna, designed and implemented to support and monitor patients treated by the professionals belonging to the Breast Cancer Unit Network (BCU-Net) along the entire clinical path of breast cancer treatment. We describe in this work the three modules composing the Arianna system (the tools for patients and clinicians, and the symbolic AI-based module). The system has been validated in a qualitative way and we demonstrated how the Arianna solution reached a high level of acceptability by all types of end-users by making it suitable for a concrete integration into the daily practice of the BCU-Net.
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ProDeM: A Process-Oriented Delphi Method for systematic asynchronous and consensual surgical process modelling. Artif Intell Med 2023; 135:102426. [PMID: 36628778 DOI: 10.1016/j.artmed.2022.102426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 08/10/2022] [Accepted: 10/11/2022] [Indexed: 11/22/2022]
Abstract
Surgical process models support improving healthcare provision by facilitating communication and reasoning about processes in the medical domain. Modelling surgical processes is challenging as it requires integrating information that might be fragmented, scattered, and not process-oriented. These challenges can be faced by involving healthcare domain experts during process modelling. This paper presents ProDeM: a novel Process-Oriented Delphi Method for the systematic, asynchronous, and consensual modelling of surgical processes. ProDeM is an adaptable and flexible method that acknowledges that: (i) domain experts have busy calendars and might be geographically dispersed, and (ii) various elements of the process model need to be assessed to ensure model quality. The contribution of the paper is twofold as it outlines ProDeM, but also demonstrates its operationalisation in the context of a well-known surgical process. Besides showing the method's feasibility in practice, we also present an evaluation of the method by the experts involved in the demonstration.
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10
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Pecoraro F, Luzi D. Using Unified Modeling Language to Analyze Business Processes in the Delivery of Child Health Services. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:13456. [PMID: 36294033 PMCID: PMC9602458 DOI: 10.3390/ijerph192013456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/27/2022] [Accepted: 10/03/2022] [Indexed: 06/16/2023]
Abstract
Business Process Management (BPM) has been increasingly used in recent years in the healthcare domain to analyze, optimize, harmonize and compare clinical and healthcare processes. The main aim of this methodology is to model the interactions between medical and organizational activities needed to deliver health services, measure their complexity, variability and deviations to improve the quality of care and its efficiency. Among the different tools, languages and notations developed in the decades, UML (Unified Modeling Language) represents a widely adopted technique to model, analyze and compare business processes in healthcare. We adopted its diagrams in the MOCHA project to compare the different ways of organizing, coordinating and delivering child care across 30 EU/EEA countries both from an organization and control-flow perspectives. This paper provides an overview of the main components used to represent the business process using UML diagrams, also highlighting how we customized them to capture the specificity of the healthcare domain taking into account that processes are reconstructed on the basis of country experts' responses to questionnaires. The benefits of the application of this methodology are demonstrated by providing examples of comparing different aspects of child care.
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Londral A, Azevedo S, Dias P, Ramos C, Santos J, Martins F, Silva R, Semedo H, Vital C, Gualdino A, Falcão J, Lapão LV, Coelho P, Fragata JG. Developing and validating high-value patient digital follow-up services: a pilot study in cardiac surgery. BMC Health Serv Res 2022; 22:680. [PMID: 35597936 PMCID: PMC9123610 DOI: 10.1186/s12913-022-08073-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 05/06/2022] [Indexed: 11/22/2022] Open
Abstract
Background The existing digital healthcare solutions demand a service development approach that assesses needs, experience, and outcomes, to develop high-value digital healthcare services. The objective of this study was to develop a digital transformation of the patients’ follow-up service after cardiac surgery, based on a remote patient monitoring service that would respond to the real context challenges. Methods The study followed the Design Science Research methodology framework and incorporated concepts from the Lean startup method to start designing a minimal viable product (MVP) from the available resources. The service was implemented in a pilot study with 29 patients in 4 iterative develop-test-learn cycles, with the engagement of developers, researchers, clinical teams, and patients. Results Patients reported outcomes daily for 30 days after surgery through Internet-of-Things (IoT) devices and a mobile app. The service’s evaluation considered experience, feasibility, and effectiveness. It generated high satisfaction and high adherence among users, fewer readmissions, with an average of 7 ± 4.5 clinical actions per patient, primarily due to abnormal systolic blood pressure or wound-related issues. Conclusions We propose a 6-step methodology to design and validate a high-value digital health care service based on collaborative learning, real-time development, iterative testing, and value assessment.
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Affiliation(s)
- A Londral
- Value for Health CoLAB, Lisbon, Portugal. .,Comprehensive Health Research Center, Nova Medical School, Nova University of Lisbon, Lisbon, Portugal.
| | - S Azevedo
- Value for Health CoLAB, Lisbon, Portugal.,Comprehensive Health Research Center, Nova Medical School, Nova University of Lisbon, Lisbon, Portugal.,CEG-IST, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal
| | - P Dias
- Value for Health CoLAB, Lisbon, Portugal.,Comprehensive Health Research Center, Nova Medical School, Nova University of Lisbon, Lisbon, Portugal
| | - C Ramos
- Value for Health CoLAB, Lisbon, Portugal.,Comprehensive Health Research Center, Nova Medical School, Nova University of Lisbon, Lisbon, Portugal
| | - J Santos
- Comprehensive Health Research Center, Nova Medical School, Nova University of Lisbon, Lisbon, Portugal.,Hospital de Santa Marta, Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal
| | - F Martins
- Value for Health CoLAB, Lisbon, Portugal.,NOVA-LINCS, NOVA School of Science and Technology, Nova University of Lisbon, Lisbon, Portugal
| | - R Silva
- Value for Health CoLAB, Lisbon, Portugal.,NOVA CLUNL - Center of Linguistics, Nova University of Lisbon, Lisbon, Portugal
| | - H Semedo
- Hospital de Santa Marta, Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal
| | - C Vital
- Hospital de Santa Marta, Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal
| | - A Gualdino
- Hospital de Santa Marta, Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal
| | - J Falcão
- Hospital de Santa Marta, Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal
| | - L V Lapão
- Comprehensive Health Research Center, Nova Medical School, Nova University of Lisbon, Lisbon, Portugal.,UNIDEMI, NOVA School of Science and Technology, Nova University of Lisboa, Lisbon, Portugal
| | - P Coelho
- Comprehensive Health Research Center, Nova Medical School, Nova University of Lisbon, Lisbon, Portugal.,Hospital de Santa Marta, Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal
| | - J G Fragata
- Comprehensive Health Research Center, Nova Medical School, Nova University of Lisbon, Lisbon, Portugal.,Hospital de Santa Marta, Centro Hospitalar Universitário Lisboa Central, Lisbon, Portugal
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