ISLA Santarém 26691

Health Data Analysis I

• ApresentaçãoPresentation

     
• ProgramaProgramme

  1. Integration and interoperability of Electronic Health Records (EHR) among healthcare systems. 2. Transition from the Fee-for-Service (FFS) reimbursement model to a value-based model: patient-centered care and the role of PROMs and PREMs. 3. Advanced utilization of health questionnaires: critical analysis of effectiveness in measuring patient outcomes and experiences. 4. Advanced analysis of health research data sets: clustering techniques and factorial analysis for pattern identification and insights.
• ObjectivosObjectives

  O1. Deepen understanding of Electronic Health Records (EHR), exploring their integration and interoperability across healthcare systems.  O2. Study in detail the transition from the Fee-for-Service (FFS) reimbursement model to a value-based model, emphasizing patient- centered care and the importance of patient well-being indicators (PROMs and PREMs). O3. Develop advanced skills in using health questionnaires and critically analyze their effectiveness in measuring patient outcomes and experiences. O4. Expand proficiency in analyzing health research data sets, employing advanced techniques such as clustering and factorial analysis to identify meaningful patterns and insights in the healthcare field.
• BibliografiaBibliography

  Davis, N. A., & Shiland, B. J. (2015). Statistics & Data Analytics for Health Data Management. Elsevier Health Sciences.  Huynh, K. (2023). Power Query for Power BI and Excel: Transform and Shape Data. Martinez, E. Z. (2021). Bioestatística para os cursos de graduação da área da saúde. Editora Blucher. Tanwar, P., Jain, V., Liu, C.-M., & Goyal, V. (2020). Big Data Analytics and Intelligence: A Perspective for Health Care. Emerald Group Publishing.
• MetodologiaMethodology

  The classes will be mixed (theoretical-practical and practical) using the following methodologies: Synchronous sessions: MET 1. Expository, interrogative, and interactive methods: Presentation/explanation of concepts using the expository, interrogative, and interactive methods. All pedagogical support materials are made available through the Moodle platform. In-person sessions: MET 2. Active methodologies: Practical application through exercises and assignments in a classroom setting. Autonomous work: MET 3. Reading of the recommended bibliography. Completion of practical exercises not covered during practical classes and others proposed by the instructor. These materials and exercises are made available on the Moodle platform. MET 4. The instructor provides feedback (Tutorial Guidance - OT) on the results obtained by the student in solving these proposed problems via the Moodle platform.
• LínguaLanguage

  Português
• TipoType

  Semestral
• ECTS

  6
• NaturezaNature

  Mandatory
• EstágioInternship

  Não
• AvaliaçãoEvaluation

  Avaliação Curricular (contínua (presencial):
  Esta modalidade de avaliação é constituída por:
  AVAL 1. Portfólio de trabalhos/exercícios de aula AVAL 2. Trabalho prático (relatório e projeto).
  AVAL 3. Teste final teórico/prático.
  A classificação final é calculada através da fórmula Classificação Final = 0,2*AVAL 1+0,4*AVAL 2 + 0,4 *AVAL 3. O estudante é aprovado se obtiver classificação igual ou superior a 9,5 valores em 20.
  Avaliação Final (presencial): O estudante realiza o exame teórico-prático (A = 100%) e é aprovado se obtiver uma classificação igual ou superior a 9,5 valores em 20.
  Época de Recurso e Época Especial (presencial): O estudante realiza o exame teórico-prático (A = 100%) e fica aprovado se obtiver uma classificação igual ou superior a 9,5 valores em 20.