Mobility of patients within Healthcare Institutions 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

Mobility of patients within Healthcare Institutions Presentation Summary Introduction Objective Methods Results/Discussion Discussion Synthesis Limitations - Bias

Mobility of patients within Healthcare Institutions Objective To study patients’ mobility within healthcare institutions.

Mobility of patients within Healthcare Institutions Study Classification Analytic: relates the variables in study Observational: studies the characteristics of the target population Transversal: data is collected in a single moment Retrospective: information refers to the previous year Analysis Unit: all the individuals over 65 years old per household Methods

Mobility of patients within Healthcare Institutions Sample design Random sample of 83 adult individuals out of the available population Methods Target population: individuals over 65 years old of Oporto region (Espinho, Gondomar, Matosinhos, Maia, Oporto, Paredes, Stª Maria da Feira, Trofa, Valongo, Vila do Conde, Vila Nova de Gaia) Available population: individuals over 65 years old of Oporto region with household phone number starting with 22.

Mobility of patients within Healthcare Institutions Methods Data collection Random Digit Dialling – revision of the method by Mitofsky and Waksberg Questionnaire design The questionnaire included sociodemographic characteristics (age, sex, city) Questions related to the subject in study. Scale pilot - interview with six subjects, in which the five questions were developed 

Mobility of patients within Healthcare Institutions Methods Statistic Issues  Simple frequency distribution - to show the characteristics of the subjects and their answers  Variance was calculated for every variable.  Relations between variables were defined using cross tabs and multiple response tables  Analyses performed with SPSS for Windows 13.0

Mobility of patients within Healthcare Institutions Results/Discussion Sample Results: 56 women and 26 men Mean number of age 72.6 years old Ages between 65 and 89 years old

Results/Discussion The mean number of different healthcare institutions visited in 2005 was 4.8 People go to different types of institutions or to different institutions within the same type?

Mobility of patients within Healthcare Institutions Table 1 – Mean numbers of attended healthcare institutions, within the same type, by men and women separately and both genders together. Results/Discussion The median of healthcare institutions attended to within the same type is one. People usually go to one medical institution per type. Hospitals Health Centres Private Laboratories Private Physicians Pharmacies Men 0,810,690,920,961,15 Women 1,130,860,960,681,34 Both Genders 1,040,800,940,761,27 

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Mobility of patients within Healthcare Institutions Results/Discussion Hospitals: 25% went to more than one hospital vs 51% that only went to one hospital Health Centres: Low variability – only 5% attended more than one institution Pharmacies: 28% went to more than one pharmacy vs 57% that went to one 

Mobility of patients within Healthcare Institutions Number of distinct types of institutions Number of people2 (2%)8 (10%)22 (27%)30 (36%)21 (25%) Table 2 – Number of types of institutions visited and the corresponding amount of people who visited them. Results/Discussion 61% of the individuals go to more than three distinct types of healthcare institutions – existence of certain mobility.

Mobility of patients within Healthcare Institutions Table 3 – H: Hospitals; PL: Private laboratories; HC: Health Centres; PP: Private Physicians; P: Pharmacies; Y/Y: Went to both institutions; N/N: Attended none of the institutions; Y/N; Attended only one of the institutions. The results presented in the table regard the 83 questionnaires obtained. Crossing of 2 different healthcare institutions Y/YN/NY/N P + PL56 (67%)3 (4%)24 (29%) HC + P54 (66%)6 (7%)23 (27%) H + P52 (63%)2 (2%)29 (35%) HC + PL51 (61%)7 (8%)25 (31%) H + PL50 (60%)4 (5%)29 (35%) H + HC50 (60%)9 (11%)24 (29%) P + PP40 (48%)4 (5%)39 (47%) PL + PP40 (48%)8 (10%)35 (42%) H + PP37 (45%)8 (10%)38 (45%) HC + PP34 (41%)7 (8%)42 (51%) Doctors Private Labs Pharmacies Results/Discussion

Mobility of patients within Healthcare Institutions Based on the statistics there should be an exchange of medical information between pharmacies and private labs, provided by information systems. The previous institutions are intrinsically linked to physicians, therefore with the public places where they work. Hospitals, health centres, private labs and pharmacies, should be informatically linked, because more than 60% of the individuals attended each association of two institutions. Results/Discussion

Mobility of patients within Healthcare Institutions Results/Discussion Of the 83 inquired individuals: 20 (24%)didn’t go to any hospital; 63 (76%) went to at least one. HSJ: 30% VNG: 24% HSA: 21%

Mobility of patients within Healthcare Institutions Results/Discussion Of the 19 inquiries that went to HSJ: 4 (21%) also attended HSA; 2 (10%) went to IPO as well; 2 attended Hospital de Valongo.

Mobility of patients within Healthcare Institutions Results/Discussion Men and Women – are there any differences? Women often go, in average, to more health institutions than men. This difference is not significant – our sample is too small. Statement supported by values of median (equals one, in both men and women separately). 

Mobility of patients within Healthcare Institutions Discussion Synthesis Patients’ mobility has been registered: More pronounced between different types of healthcare institutions Less distinct among the same type of medical institutions Patients would indeed benefit from an information linkage between different types of healthcare institutions

Mobility of patients within Healthcare Institutions Discussion Synthesis If there is to exist information systems that link different medical institutions, those should preferably be: Pharmacies and Private Laboratories: 67% Health Centres and Pharmacies: 66% Hospitals and Pharmacies: 63% Health Centres and Private Laboratories: 61% Hospitals and Private Laboratories: 60% Hospitals and Health Centres: 60%

Mobility of patients within Healthcare Institutions Not every individual in target population owns a household phone number Restricted time period of interviews Limitations - Bias Some of the phone numbers starting with 22 include places out of the Oporto region Data collected in one moment may not also reflect the reality due to people’s memory lapses Individuals that refuse to participate