Patient Institution Mobility Inês Videira, Inês Jorge, Iolanda Ferreira, Ivete Afonso, Jennifer Pires, Joana Ribeiro, Joana Vaz, Joana Fernandes, Joana Costa, Joana Magalhães Faculdade de Medicina da Universidade do Porto Introdução à Medicina Turma /2006

Patient Institution Mobility Presentation Summary Introduction Objective Methods Expected Results Gantt Chart

Patient Institution Mobility Introduction Development of Medicine and Informatics contributed to the organization of healthcare [1] [1] Haux, R. Health information systems – past, present, future. Int J Med Inform Sep 15 [2] Wyatt, JC. Clinical Data Systems, part 1: Data and medical records. Lancet Dec 3; 344 (8936): Medical information, present in medical records, “helps decision making” [2]

Patient Institution Mobility Organizing patient’s information is essential [3] [3] Branger PJ, van’t Hooft A, Duisterhout JS, van der Lei J. A standardized message for supporting shared care. Proc Annu Symp Comput Appl Med Care. 1994;473-7 [4] Katehakis DG, Sfakianakis S,m Tsiknakis M, Orphanoudakis SC. An infrastructure for integrated electronic health record services: the role of XML (Extensible Markup Language). J Med Internet Res Jan-Mar; 3(1): E7. Communication between healthcare services influences the quality of the provided service [4] Introduction

Patient Institution Mobility Patient’s data is spread in various healthcare structures as a result of patient’s institution mobility [5,6] [5] Lambrinoudakis C, Gritzalis S. Managing medical and insurance information through a smart-card-based information system. J Med Syst Aug; 24(4): [6] Kerkri EM, Quantin C, Grison T, Allaert FA, Tchounikine A, Yetongnon K. A virtual intranet and data- warehousing for healthcare co-operation. Medinfo. 2001; 10 (Pt 1): Introduction

Patient Institution Mobility Objective Find out which healthcare institutions patients of Oporto’s population go to.

Patient Institution Mobility Study Classification Analytic: relates the variables in study Observational: describes the characteristics of the population in study Transversal: data is collected in a single moment Retrospective: information refers to the previous year Analysis Unit: One adult per family Methods

Patient Institution Mobility Sample design   Random sample of 200 adult individuals out of the available population Methods Target population: adult individuals of Oporto’s region (Oporto, Matosinhos, Maia, Gondomar, Valongo, Vila Nova de Gaia, Espinho) Available population: adult individuals of Oporto’s region with household phone number starting with 22.

Patient Institution Mobility Statistic treatment by SPSS Random digit dialling Telephone interviews Data collection Methods

Patient Institution Mobility Limitations - Bias Not every individual in target population owns a household phone number Restricted time period of interviews Target population does not include children Accuracy of telephone method selected is being seeked Methods Some of the phone numbers starting with 22 include places out of the Oporto’s region. 

Patient Institution Mobility Expected Results Obtain data that proves patient’s delocalization between different healthcare institutions.

Patient Institution Mobility Gantt Chart Link

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