Agreement between self-reported and general practitioner-reported chronic conditions among multimorbid patients in primary care : results of the MultiCare Cohort Study

  • Background: Multimorbidity is a common phenomenon in primary care. Until now, no clinical guidelines for multimorbidity exist. For the development of these guidelines, it is necessary to know whether or not patients are aware of their diseases and to what extent they agree with their doctor. The objectives of this paper are to analyze the agreement of self-reported and general practitioner-reported chronic conditions among multimorbid patients in primary care, and to discover which patient characteristics are associated with positive agreement. Methods: The MultiCare Cohort Study is a multicenter, prospective, observational cohort study of 3,189 multimorbid patients, ages 65 to 85. Data was collected in personal interviews with patients and GPs. The prevalence proportions for 32 diagnosis groups, kappa coefficients and proportions of specific agreement were calculated in order to examine the agreement of patient self-reported and general practitioner-reported chronic conditions. Logistic regression models were calculated to analyze which patient characteristics can be associated with positive agreement. Results: We identified four chronic conditions with good agreement (e.g. diabetes mellitus κ = 0.80;PA = 0,87), seven with moderate agreement (e.g. cerebral ischemia/chronic stroke κ = 0.55;PA = 0.60), seventeen with fair agreement (e.g. cardiac insufficiency κ = 0.24;PA = 0.36) and four with poor agreement (e.g. gynecological problems κ = 0.05;PA = 0.10).Factors associated with positive agreement concerning different chronic diseases were sex, age, education, income, disease count, depression, EQ VAS score and nursing care dependency. For example: Women had higher odds ratios for positive agreement with their GP regarding osteoporosis (OR = 7.16). The odds ratios for positive agreement increase with increasing multimorbidity in almost all of the observed chronic conditions (OR = 1.22-2.41). Conclusions: For multimorbidity research, the knowledge of diseases with high disagreement levels between the patients' perceived illnesses and their physicians' reports is important. The analysis shows that different patient characteristics have an impact on the agreement. Findings from this study should be included in the development of clinical guidelines for multimorbidity aiming to optimize health care. Further research is needed to identify more reasons for disagreement and their consequences in health care.

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Author:Heike Hansen, Ingmar Schäfer, Gerhard Schön, Steffi Gerlinde Riedel-Heller, Jochen GensichenORCiDGND, Siegfried Weyerer, Juliana Petersen, Hans-Helmut König, Horst Bickel, Angela Fuchs, Susanne Höfels, Birgitt Wiese, Karl Wegscheider, Hendrik van den Bussche, Martin Scherer
URN:urn:nbn:de:hebis:30:3-333967
DOI:https://doi.org/10.1186/1471-2296-15-39
ISSN:1471-2296
Pubmed Id:https://pubmed.ncbi.nlm.nih.gov/24580758
Parent Title (English):BMC family practice
Publisher:BioMed Central
Place of publication:London
Document Type:Article
Language:English
Date of Publication (online):2014/04/09
Date of first Publication:2014/03/01
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2014/04/09
Tag:Agreement; Chronic diseases; Multimorbidity; Physician report; Primary care; Self-report
Volume:15
Issue:39
Page Number:14
First Page:1
Last Page:14
Note:
© 2014 Hansen et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
HeBIS-PPN:364443278
Institutes:Medizin / Medizin
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 2.0