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Mobility of elderly patients across healthcare institutions Inês Videira, Inês Jorge, Iolanda Ferreira, Ivete Afonso, Jennifer Pires, Joana Ribeiro, Joana.

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Presentation on theme: "Mobility of elderly patients across healthcare institutions Inês Videira, Inês Jorge, Iolanda Ferreira, Ivete Afonso, Jennifer Pires, Joana Ribeiro, Joana."— Presentation transcript:

1 Mobility of elderly patients across 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 Class 10 2005/2006

2 Mobility of elderly patients across healthcare institutions Presentation Summary Introduction Aim Methods Results/Discussion Discussion Synthesis Limitations - Bias

3 Mobility of elderly patients across healthcare institutions Introduction Progress in Medicine and Informatics influences the development of health information systems Wyatt, JC. Clinical Data Systems, part 1: Data and medical records. Lancet. 1994 Dec 3; 344 (8936): 1543-7 Medical information, present in medical records, helps decision making ( sic ) Haux, R. Health information systems – past, present, future. Int J Med Inform. 2005 Sep 15

4 Mobility of elderly patients across healthcare institutions Organizing patients’ information is essential 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. 2001 Jan-Mar; 3(1): E7. Communication between healthcare services influences the quality of the provided service Introduction 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

5 Mobility of elderly patients across healthcare institutions Patients’ data is spread in all the places where they have received clinical services 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. 2001 Jan-Mar; 3(1): E7. Introduction Elderly people demand much of health services [1], being the main consumers of the NHS [2] [1] Scanaill CN, Carew S, Barralon P, Noury N, Lyons D, Lyons GM. A Review of Approaches to Mobility Telemonitoring of the Elderly in Their Living Environment. Ann Biomed Eng. 2006 Mar 21 [2] Victor C R, Higginson I. Effectiveness of care for older people: a review. Qual Health Care 1994;3:210­6.

6 Mobility of elderly patients across healthcare institutions In Central and Northern Portugal, elderly people do not usually attend the doctor when facing a disease Santana P. Ageing in Portugal: regional iniquities in health and healthcare. Soc Sci Med. 2000 Apr;50(7-8):1025-36. Introduction Effective care and treatment is required for this group [1], which may be enhanced with information systems [1] Victor C R, Higginson I. Effectiveness of care for older people: a review. Qual Health Care 1994;3:210­6.

7 Mobility of elderly patients across healthcare institutions Aim To study elderly patients’ mobility across healthcare institutions.

8 Mobility of elderly patients across healthcare institutions Study Classification Observational: the observer only collects data, without interference in the manipulation of variables Transversal: data is collected in a single moment Retrospective: information refers to the previous year Analysis Unit: all the individuals aged 65 years old or over per household Methods

9 Mobility of elderly patients across healthcare institutions Sample design   Random sample of elderly individuals out of the available population (elderly individuals with household phone numbers) Methods Target population: individuals aged 65 years old or over of Oporto’s region (Espinho, Gondomar, Matosinhos, Maia, Oporto, Paredes, Stª Maria da Feira, Trofa, Valongo, Vila do Conde, Vila Nova de Gaia) Available population: individuals aged 65 years old or over of Oporto’s region with household phone number starting with 22.

10 Mobility of elderly patients across healthcare institutions Methods Data collection Random Digit Dialling - two stage random sample Telephone interviews Questionnaire design The questionnaire included sociodemographic characteristics (age, sex, town) Questions related to the aim of the study Scale pilot - interview with seven subjects, in which the five questions were developed 

11 Mobility of elderly patients across healthcare institutions Methods The telephone number was randomly selected, using two computer generated directories for prefix and suffix The following situations have been rejected: Non existent phone numbers Non residential phone numbers Within the valid households, these did not result into questionnaires: Insufficient Age Refused to Answer 100 questionnaires have been obtained within the time available for the telephone interviews

12 Mobility of elderly patients across 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, multiple response tables and compute variables  Analyses performed with SPSS for Windows 13.0

13 Mobility of elderly patients across healthcare institutions Results Table 1. Characterization of telephone calls (approximated percentages related to the total amount of telephone calls) Of the 1892 telephone calls made, only 100 questionnaires were obtained  response rate = 58% Non-existent numbers1226 (65%) Non-residential telephone numbers312 (16%) Total amount of invalid telephone calls1538 (81%) Insufficient age182 (10%) Refused to answer72 (4%) Answered questionnaires100 (5%) Total amount of valid telephone calls354 (19%) Total amount of telephone calls1892

14 Mobility of elderly patients across healthcare institutions Results Sample Results: 65 women, 34 men and 1 missing Mean number of age was 72,7 years old Ages between 65 and 90 years old

15 Mobility of elderly patients across healthcare institutions Results/Discussion The mean number of different healthcare institutions visited in 2005 was 4.83, whether within the same type or across different types Figure 1. Bar chart showing the amount of people by number of healthcare institutions attended.

16 Mobility of elderly patients across healthcare institutions Mobility patterns: 41% attended at least four different institutions There is certain mobility among different types of institutions Results/Discussion Figure 2. Mobility pattern considering distinct types of institutions. Linking medical institutions appears to be a relevant issue

17 Mobility of elderly patients across healthcare institutions Figure 2. Number of healthcare institutions attended to within the same type and the corresponding amount of inquiries who visited them, in percentage (sample of 100 individuals) Results/Discussion People usually go to one medical institution per type.

18 Mobility of elderly patients across healthcare institutions Results/Discussion Hospitals: 24% attended more than one Pharmacies: 33% of the inquired individuals went to more than one There is a certain mobility within the same type of these medical institutions

19 Results/Discussion 42% of HSJ users establish connections with other hospitals HSJ should be primary linked to HSA, with a long term benefit for 5% of the elderly population The second most relevant linkage should be HSJ-IPO (3%) Table 2. Existing relations between all the hospitals visited and the associated amount of elderly people. Hospital patternCases (N) HSJ……………………………………..24 Just HSJ………………………….14 With others………………………10 HSJ-HSA…………………..5 Just HSJ-HSA……….4 HSJ-HSA-Valongo….1 HSJ-IPO……………………3 Just HSJ-IPO...............2 HSJ-IPO-Prelada.........1 HSJ-Valongo……………….2 Just HSJ-Valongo........1 HSJ-Valongo-IPO.......1 HSJ-Prelada...........................2 Just HSJ-Prelada.........1 HSJ-IPO-Prelada…….1

20 Mobility of elderly patients across healthcare institutions Results/Discussion Figure – Mobility pattern focusing on number of different institutions per type Mobility patterns: Most common: 1H, 1HC, 1PL, 0P, 1Ph In an hypothetical priority list these institutions should be the first ones to be linked

21 Mobility of elderly patients across healthcare institutions Results/Discussion Men and Women Women often go, in average, to more hospitals, health centres and pharmacies Men go, in average, to more private laboratories and physicians Typical elderly individual – attends one medical institution per type HospitalsHealth CentresPrivate LaboratoriesPrivate PhysiciansPharmacies Men0.760.710.970.791.41 Women1.140.820.910.661.45 Both Genders1.020.770.930.701.42 Table 3. Mean numbers of attended healthcare institutions, within the same type, by men and women separately and both genders together.

22 Mobility of elderly patients across 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

23 Mobility of elderly patients across 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’s region  Data collected in one moment may not also reflect the reality due to people’s memory lapses Individuals that refuse to participate


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