19
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Systematic Analysis of Self-Reported Comorbidities in Large Cohort Studies – A Novel Stepwise Approach by Evaluation of Medication

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective

          In large cohort studies comorbidities are usually self-reported by the patients. This way to collect health information only represents conditions known, memorized and openly reported by the patients. Several studies addressed the relationship between self-reported comorbidities and medical records or pharmacy data, but none of them provided a structured, documented method of evaluation. We thus developed a detailed procedure to compare self-reported comorbidities with information on comorbidities derived from medication inspection. This was applied to the data of the German COPD cohort COSYCONET.

          Methods

          Approach I was based solely on ICD10-Codes for the diseases and the indications of medications. To overcome the limitations due to potential non-specificity of medications, Approach II was developed using more detailed information, such as ATC-Codes specific for one disease. The relationship between reported comorbidities and medication was expressed by a four-level concordance score.

          Results

          Approaches I and II demonstrated that the patterns of concordance scores markedly differed between comorbidities in the COSYCONET data. On average, Approach I resulted in more than 50% concordance of all reported diseases to at least one medication. The more specific Approach II showed larger differences in the matching with medications, due to large differences in the disease-specificity of drugs. The highest concordance was achieved for diabetes and three combined cardiovascular disorders, while it was substantial for dyslipidemia and hyperuricemia, and low for asthma.

          Conclusion

          Both approaches represent feasible strategies to confirm self-reported diagnoses via medication. Approach I covers a broad spectrum of diseases and medications but is limited regarding disease-specificity. Approach II uses the information from medications specific for a single disease and therefore can reach higher concordance scores. The strategies described in a detailed and reproducible manner are generally applicable in large studies and might be useful to extract as much information as possible from the available data.

          Related collections

          Most cited references19

          • Record: found
          • Abstract: found
          • Article: not found

          Agreement between self-report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure.

          Questionnaires are used to estimate disease burden. Agreement between questionnaire responses and a criterion standard is important for optimal disease prevalence estimates. We measured the agreement between self-reported disease and medical record diagnosis of disease. A total of 2,037 Olmsted County, Minnesota residents > or =45 years of age were randomly selected. Questionnaires asked if subjects had ever had heart failure, diabetes, hypertension, myocardial infarction (MI), or stroke. Medical records were abstracted. Self-report of disease showed >90% specificity for all these diseases, but sensitivity was low for heart failure (69%) and diabetes (66%). Agreement between self-report and medical record was substantial (kappa 0.71-0.80) for diabetes, hypertension, MI, and stroke but not for heart failure (kappa 0.46). Factors associated with high total agreement by multivariate analysis were age 12 years, and zero Charlson Index score (P < .05). Questionnaire data are of greatest value in life-threatening, acute-onset diseases (e.g., MI and stroke) and chronic disorders requiring ongoing management (e.g.,diabetes and hypertension). They are more accurate in young women and better-educated subjects.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Self-reports and general practitioner information on the presence of chronic diseases in community dwelling elderly. A study on the accuracy of patients' self-reports and on determinants of inaccuracy.

            The object of the study is to investigate the (in)accuracy of patients' self-reports, as compared with general practitioners' information, regarding the presence of specific chronic diseases, and the influence of patient characteristics. Questionnaire data of 2380 community-dwelling elderly patients, aged 55-85 years, on the presence of chronic non-specific lung disease, cardiac disease, peripheral atherosclerosis, stroke, diabetes, malignancies, and osteoarthritis/rheumatoid arthritis were compared with data from the general practitioners, using the kappa-statistic. Associations between the accuracy of self-reports and patient characteristics were studied by multiple logistic regression analyses. Kappa's ranged from 0.30 to 0.40 for osteoarthritis/rheumatoid arthritis and atherosclerosis, to 0.85 for diabetes mellitus. In the multivariate analyses, educational level, level of urbanization, deviations in cognitive function, and depressive symptomatology had no influence on the level of accuracy. An influence of gender, age, mobility limitations, and recent contact with the general practitioner was shown for specific diseases. For chronic non-specific lung disease, both "underreporting" and "overreporting" are more prevalent in males, compared to females. Furthermore, males tend to overreport stroke and underreport malignancies and arthritis, whereas females tend to overreport malignancies and arthritis. Both overreporting and underreporting of cardiac disease are more prevalent as people are older. Also, older age is associated with overreporting of stroke, and with underreporting of arthritis. The self-reported presence of mobility limitations is associated with overreporting of all specific diseases studied, except for diabetes mellitus, and its absence is associated with underreporting, except for diabetes mellitus and atherosclerosis. Recent contact with the general practitioner is associated with overreporting of cardiac disease, atherosclerosis, malignancies and arthritis, and with less frequent underreporting of diabetes and arthritis. Results suggest that patients' self-reports on selected chronic diseases are fairly accurate, with the exceptions of atherosclerosis and arthritis. The associations found with certain patient characteristics may be explained by the tendency of patients to label symptoms, denial by the patient, or inaccuracy of medical records.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The association between chronic illness, multimorbidity and depressive symptoms in an Australian primary care cohort.

              To assess the link between multimorbidity, type of chronic physical health problems and depressive symptoms The study was a cross-sectional postal survey conducted in 30 General Practices in Victoria, Australia as part of the diamond longitudinal study. Participants included 7,620 primary care attendees; 66% were females; age range from 18 to 76 years (mean = 51 years SD = 14); 81% were born in Australia; 64% were married and 67% lived in an urban area. The main outcome measures include the Centre for Epidemiologic Studies Depression Scale (CES-D) and a study-specific self-report check list of 12 common chronic physical health problems. The prevalence of probable depression increased with increasing number of chronic physical conditions (1 condition: 23%; 2 conditions: 27%; 3 conditions: 30%; 4 conditions: 31%; 5 or more conditions: 41%). Only 16% of those with no listed physical conditions recorded CES-D scores of 16 or above. Across the listed physical conditions the prevalence of 'probable depression' ranged from 24% for hypertension; 35% for emphysema; 35% for dermatitis to 36% for stroke. The dose-response relationship is reduced when functional limitations and self-rated health are taken into account, suggesting that these factors mediate the relationship. A clear dose-response relationship exists between the number of chronic physical problems and depressive symptoms. The relationship between multimorbidity and depression appears to be mediated via self-perceived health related quality of life. Primary care practitioners will identify more cases of depression if they focus on those with more than one chronic health problem, no matter what the problems may be, being especially aware in the group who rate their health as poor/fair.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                28 October 2016
                2016
                : 11
                : 10
                : e0163408
                Affiliations
                [1 ]Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, University Hospital LMU Munich, München, Germany
                [2 ]Comprehensive Pneumology Center Munich, DZL, German Center for Lung Research, München, Germany
                [3 ]Center for International Health, Ludwig-Maximilian University Munich, München, Germany
                [4 ]German Research Center for Environmental Health, Institute of Health Economics and Health Care Management, Member of the German Center for Lung Research, Comprehensive Pneumology Center Munich (CPC-M), Neuherberg, Germany
                [5 ]Institute for Biostatistics, Hannover Medical School, Hannover, Germany
                [6 ]Thoracic Oncology Center Munich (TOM), University Hospital LMU Munich, München, Germany
                [7 ]Pulmonary and Critical Care Medicine, Department of Medicine, University Medical Centre Giessen and Marburg, Philipps-University, Marburg, Germany
                [8 ]Department of Respiratory Medicine, Allergology and Sleep Medicine, Klinikum Nuremberg, Nürnberg, Germany
                [9 ]Paracelsus Medical University Nuremberg, Nürnberg, Germany
                [10 ]Walther-Straub-Institute for Pharmacology and Toxicology, Ludwig-Maximilian University Munich, München, Germany
                Hunter College, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: TL R. Herrera MW HM RAJ.

                • Formal analysis: TL R. Herrera RAJ.

                • Investigation: TL R. Herrera HM RAJ.

                • Methodology: TL R. Herrera MW HM RAJ.

                • Resources: SS DN RMH MW R. Holle FB CV.

                • Software: TL R. Herrera.

                • Supervision: DN RMH CV JHF RAJ.

                • Validation: FB.

                • Visualization: TL.

                • Writing – original draft: TL RAJ.

                • Writing – review & editing: MW R. Holle FB DN RMH SS CV JHF.

                ¶ Membership of the COSYCONET-Consortium is listed in the Supporting Information ( S1 COSYCONET Consortium).

                Article
                PONE-D-15-55458
                10.1371/journal.pone.0163408
                5085029
                27792735
                78770b98-fcc1-4556-88ee-4979a758be28
                © 2016 Lucke et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 22 December 2015
                : 8 September 2016
                Page count
                Figures: 2, Tables: 5, Pages: 14
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: 01GI0881
                Award Recipient :
                The study was performed within the COSYCONET network which is supported by the Federal Ministry of Education and Research (BMBF; FKZ 01G10881) as well as unrestricted grants from the pharmaceutical industry. None of the authors received specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Cardiology
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Pulmonology
                Asthma
                Medicine and Health Sciences
                Pulmonology
                Chronic Obstructive Pulmonary Disease
                Medicine and Health Sciences
                Vascular Medicine
                Blood Pressure
                Hypertension
                Medicine and Health Sciences
                Vascular Medicine
                Coronary Heart Disease
                Medicine and Health Sciences
                Cardiology
                Coronary Heart Disease
                Medicine and Health Sciences
                Cardiovascular Medicine
                Cardiovascular Diseases
                Medicine and Health Sciences
                Metabolic Disorders
                Dyslipidemia
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized
                Uncategorized

                Comments

                Comment on this article