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The geriatric information flow model

An abstract information flow model for geriatric patient treatment
  • Lars Rölker-Denker
  • Andreas Hein
Original Paper

Abstract

An abstract information flow model is proposed for geriatric care, the geriatric information flow model (GIFM) by adopting an information model from cancer care and introduce characteristics for geriatric care (patient population, multidisciplinary and multi-professional approach, cross-sectoral approach). The ideal-typical geriatric patient treatment process flow is introduced. Actors (patients, physicians, therapists, organizations), information objects, and information relations as well as information flows are defined. Process flow, actors, information object, and information relations are proved with qualitative material from an accompanying study. The GIFM is validated by mapping four typical knowledge processes (multi-professional geriatric team session, interdisciplinary clinical case conferences, tumor boards, transition management) onto the model. The GIFM is stated as useful for understanding information flows and relations in geriatric care. All processes for validation can be mapped onto GIFM. In future work the GIFM should be tested with more knowledge process and could also be used for identifying gaps in the IT support of geriatric care. A study on high and low information quality in geriatric care is also proposed.

Keywords

Information flow model Geriatric care Knowledge processes Organizational learning 

Notes

Acknowledgments

The authors would like to thank the Metropolregion Bremen-Oldenburg (reference number: 23-03-13) for partly supporting this work.

Funding

Metropolregion Bremen-Oldenburg partly supported the work (reference number: 23–03-13).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. 1.
    Chamberlain-Salaun J, Mills J, Usher K. Terminology used to describe health care teams: an integrative review of the literature. J Multidiscip Healthc. 2013;6:65–74.CrossRefGoogle Scholar
  2. 2.
    Mangoni AA. Geriatric medicine in an aging society: up for a challenge? Front Med. 2014;1:10.CrossRefGoogle Scholar
  3. 3.
    Rölker-Denker L, Hein A. Knowledge process models in health care organisations - ideal-typical examples from the field. Proc I Conf Health Inform (Healthinf2015). 2015. p 312–317.Google Scholar
  4. 4.
    Snyder CF, Wu AW, Miller RS, Jensen RE, Bantug ET, Wolff AC. The role of informatics in promoting patient-centered care. Cancer J. 2011;17:211–8.CrossRefGoogle Scholar
  5. 5.
    Soriano RP, Fernandez HM, Cassel CK, Leipzig RM. Fundamentals of geriatric medicine : a case-based approach. New York: Springer; 2007.CrossRefGoogle Scholar
  6. 6.
    Kolb GF, Weißbach L. Demographic change: changes in society and medicine and developmental trends in geriatrics. Urologe. 2015;54:1701. [German]CrossRefGoogle Scholar
  7. 7.
    Federal Statistical Office. Household projections in Germany. 2017. https://www.destatis.de/EN/FactsFigures/SocietyState/Population/HouseholdsFamilies/Tables/ProjectionHousehold.html. Accessed 25 Aug 2017.
  8. 8.
    Nau R, Djukic M, Wappler M. Geriatrics -- an interdisciplinary challenge. Nervenarzt. 2016;87:603–8.CrossRefGoogle Scholar
  9. 9.
    Tanaka M. Multidisciplinary team approach for elderly patients. Geriatr Gerontol Int. 2003;3(2):69–72.CrossRefGoogle Scholar
  10. 10.
    Kolb G, Breuninger K, Gronemeyer S, van den Heuvel D, Lübke N, Lüttje D, et al. 10 Jahre geriatrische frührehabilitative Komplexbehandlung im DRG-System. Z Gerontol Geriatr. 2014;47:6–12.CrossRefGoogle Scholar
  11. 11.
    Soriano RP. The comprehensive geriatric assessment. In: Soriano RP, editor. Fundamentals of geriatric medicine. A case-based approach. New York: Springer; 2007. p. 20–38.CrossRefGoogle Scholar
  12. 12.
    Mahoney F, Barthel D. Functional evaluation. The Barthel index. Md State Med J. 1965;14:61–5.Google Scholar
  13. 13.
    Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189–98.CrossRefGoogle Scholar
  14. 14.
    Watson YI, Arfken CL, Birge SJ. Clock completion: an objective screening test for dementia. J Am Geriatr Soc. 1993;41:1235–40.CrossRefGoogle Scholar
  15. 15.
    Podsiadlo D, Richardson S. The timed up and go. A test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39:142–8.CrossRefGoogle Scholar
  16. 16.
    Tinetti ME. Performance-oriented assessment of mobility problems in elderly patients. J Am Geriatr Soc. 1986;34:119–26.CrossRefGoogle Scholar
  17. 17.
    Lachs MS, Feinstein AR, Cooney LMJ, Drickamer MA, Marottoli R, Pannill FC, et al. A simple procedure for general screening for functional disability in elderly patients. Ann Intern Med. 1990;112:699–706.CrossRefGoogle Scholar
  18. 18.
    Swift CG. The problem-oriented approach to geriatric medicine. In: MSJ P, Sinclair AJ, Morley JE, editors. Principles and practice of geriatric medicine. Hoboken: Wiley; 2006. p. 223–38.Google Scholar
  19. 19.
    Soriano RP. Overview of palliative care and non-pain symptom management. In: Soriano RP, editor. Fundamentals of geriatric medicine. A case-based approach. New York: Springer; 2007. p. 547–72.CrossRefGoogle Scholar
  20. 20.
    Huber TP, Shortell SM, Rodriguez HP. Improving care transitions management: examining the role of accountable care organization participation and expanded electronic health record functionality. Health Serv Res. 2017;52(4):1494–510.CrossRefGoogle Scholar
  21. 21.
    Rölker-Denker L, Hein A. Abstract information model for geriatric patient treatment - actors and relations in daily geriatric care. Proc I Conf Health Inform (Healthinf2017). 2017. p 222–229.Google Scholar
  22. 22.
    Wenger E. Communities of practice and social learning systems. Organization. 2000;7:225–46.CrossRefGoogle Scholar
  23. 23.
    Li LC, Grimshaw JM, Nielsen C, Judd M, Coyte PC, Graham ID. Use of communities of practice in business and health care sectors: a systematic review. Implement Sci. 2009;4:27.CrossRefGoogle Scholar
  24. 24.
    Rölker-Denker L, Seeger I, Hein A. Knowledge processes in German Hospitals. First findings from the Network for Health Services Research Metropolitan Region Bremen-Oldenburg. Proc eKNOW. 2015;2015:53–7.Google Scholar
  25. 25.
    Rölker-Denker L, Seeger I, Hein A. Überleitung aus Sicht der Krankenhäuser - Ergebnisse aus semi-strukturierten Leitfadeninterviews auf Ebene der Geschäftsführung in der Region Metropolregion Bremen-Oldenburg. Proc Deut Kongress Versorgungsforschung 2015. Düsseldorf: German Medical Science GMS Publishing House; 2015. DocP152.Google Scholar
  26. 26.
    Feldman E. The interdisciplinary case conference. Acad Med. 1999;74:594.CrossRefGoogle Scholar
  27. 27.
    Magnuson A, Wallace J, Canin B, Chow S, Dale W, Mohile SG, et al. Shared goal setting in team-based geriatric oncology. J Oncol Pract. 2016;12:1115–22.CrossRefGoogle Scholar
  28. 28.
    Ansmann L, Kowalski C, Pfaff H, Wuerstlein R, Wirtz MA, Ernstmann N. Patient participation in multidisciplinary tumor conferences. Breast. 2014;23:865–9.CrossRefGoogle Scholar
  29. 29.
    Arve S, Ovaskainen P, Randelin I, Alin J, Rautava P. The knowledge management on the elderly care. Int J Integr Care. 2009;9:e128.CrossRefGoogle Scholar
  30. 30.
    HL7 Clinical Information Modeling Initiative. Clinical Information Modeling Initiative. 2016. http://www.hl7.org/Special/Committees/cimi/index.cfm. Accessed 25 Aug 2017.
  31. 31.
    Laugesen J, Hassanein K, Yuan Y. The impact of internet health information on patient compliance: a research model and an empirical study. J Med Internet Res. 2015;17:e143.CrossRefGoogle Scholar

Copyright information

© IUPESM and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Health Services ResearchUniversity of OldenburgOldenburgGermany

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