Technisierter Alltag oder veralltäglichte Technik? Wie die Strukturierungstheorie für techniksoziologische Fragestellungen nutzbar gemacht werden kann

"Das vorliegende Paper stellt eine theoretische und exemplarisch empirische Auseinandersetzung mit dem Verhältnis von Mensch und Technik dar. Der teilweise in einigen Ansätzen bis heute noch konstatierte Dualismus zwischen Mensch und Technik soll unter der Verwendung der Strukturierungstheorie von Anthony Giddens aufgelöst werden. Hierzu erfolgt unter anderem eine Auseinandersetzung mit verschiedenen technikdeterministischen und sozialdeterministischen Ansätzen. Technik wird unter der Verwendung der Theorie der Strukturierung verstanden als ein Komplex von Regeln und Ressourcen und kann in das Modell der Dimensionen des Sozialen von Giddens integriert werden. Akteur und Technik stehen somit in einem wechselseitigen Verhältnis zueinander und nicht in einem deterministischen. Relevant sind in diesem Zusammenhang die alltäglichen Verwendungsweisen von Technik durch die Akteure. Im Rahmen einer Kooperation der Universität Duisburg-Essen mit dem Institut für Mikroelektronische Schaltungen und Systeme der Fraunhofer Gesellschaft Duisburg, konnte für die vorliegende Studie das 'intelligente Haus' (inHaus) für eine exemplarisch-empirische Untersuchung zur Veralltäglichung von Technisierungsprozessen genutzt werden." (Autorenreferat

Patterns of ambulatory medical care utilization in elderly patients with special reference to chronic diseases and multimorbidity

BACKGROUND: In order to estimate the future demands for health services, the analysis of current utilization patterns of the elderly is crucial. The aim of this study is to analyze ambulatory medical care utilization by elderly patients in relation to age, gender, number of chronic conditions, patterns of multimorbidity, and nursing dependency in Germany. METHODS: Claims data of the year 2004 from 123,224 patients aged 65 years and over which are members of one nationwide operating statutory insurance company in Germany were studied. Multimorbidity was defined as the presence of 3 or more chronic conditions of a list of 46 most prevalent chronic conditions based on ICD 10 diagnoses. Utilization was analyzed by the number of contacts with practices of physicians working in the ambulatory medical care sector and by the number of different physicians contacted for every single chronic condition and their most frequent triadic combinations. Main statistical analyses were multidimensional frequency counts with standard deviations and confidence intervals, and multivariable linear regression analyses. RESULTS: Multimorbid patients had more than twice as many contacts per year with physicians than those without multimorbidity (36 vs. 16). These contact frequencies were associated with visits to 5.7 different physicians per year in case of multimorbidity vs. 3.5 when multimorbidity was not present. The number of contacts and of physicians contacted increased steadily with the number of chronic conditions. The number of contacts varied between 35 and 54 per year and the number of contacted physicians varied between 5 to 7, depending on the presence of individual chronic diseases and/or their triadic combinations. The influence of gender or age on utilization was small and clinically almost irrelevant. The most important factor influencing physician contact was the presence of nursing dependency due to disability. CONCLUSION: In absolute terms, we found a very high rate of utilization of ambulatory medical care by the elderly in Germany, when multimorbidity and especially nursing dependency were present. The extent of utilization by the elderly was related both to the number of chronic conditions and to the individual multimorbidity patterns, but not to gender and almost not to age

Multimorbidity Patterns in the Elderly: A New Approach of Disease Clustering Identifies Complex Interrelations between Chronic Conditions

Objective: Multimorbidity is a common problem in the elderly that is significantly associated with higher mortality, increased disability and functional decline. Information about interactions of chronic diseases can help to facilitate diagnosis, amend prevention and enhance the patients ’ quality of life. The aim of this study was to increase the knowledge of specific processes of multimorbidity in an unselected elderly population by identifying patterns of statistically significantly associated comorbidity. Methods: Multimorbidity patterns were identified by exploratory tetrachoric factor analysis based on claims data of 63,104 males and 86,176 females in the age group 65+. Analyses were based on 46 diagnosis groups incorporating all ICD-10 diagnoses of chronic diseases with a prevalence $ 1%. Both genders were analyzed separately. Persons were assigned to multimorbidity patterns if they had at least three diagnosis groups with a factor loading of 0.25 on the corresponding pattern. Results: Three multimorbidity patterns were found: 1) cardiovascular/metabolic disorders [prevalence female: 30%; male: 39%], 2) anxiety/depression/somatoform disorders and pain [34%; 22%], and 3) neuropsychiatric disorders [6%; 0.8%]. The sampling adequacy was meritorious (Kaiser-Meyer-Olkin measure: 0.85 and 0.84, respectively) and the factors explained a large part of the variance (cumulative percent: 78 % and 75%, respectively). The patterns were largely age-dependent an

Which chronic diseases and disease combinations are specific to multimorbidity in the elderly? Results of a claims data based cross-sectional study in Germany

<p>Abstract</p> <p>Background</p> <p>Growing interest in multimorbidity is observable in industrialized countries. For Germany, the increasing attention still goes still hand in hand with a small number of studies on multimorbidity. The authors report the first results of a cross-sectional study on a large sample of policy holders (n = 123,224) of a statutory health insurance company operating nationwide. This is the first comprehensive study addressing multimorbidity on the basis of German claims data. The main research question was to find out which chronic diseases and disease combinations are specific to multimorbidity in the elderly.</p> <p>Methods</p> <p>The study is based on the claims data of all insured policy holders aged 65 and older (n = 123,224). Adjustment for age and gender was performed for the German population in 2004. A person was defined as multimorbid if she/he had at least 3 diagnoses out of a list of 46 chronic conditions in three or more quarters within the one-year observation period. Prevalences and risk-ratios were calculated for the multimorbid and non-multimorbid samples in order to identify diagnoses more specific to multimorbidity and to detect excess prevalences of multimorbidity patterns.</p> <p>Results</p> <p>62% of the sample was multimorbid. Women in general and patients receiving statutory nursing care due to disability are overrepresented in the multimorbid sample. Out of the possible 15,180 combinations of three chronic conditions, 15,024 (99%) were found in the database. Regardless of this wide variety of combinations, the most prevalent individual chronic conditions do also dominate the combinations: Triads of the six most prevalent individual chronic conditions (hypertension, lipid metabolism disorders, chronic low back pain, diabetes mellitus, osteoarthritis and chronic ischemic heart disease) span the disease spectrum of 42% of the multimorbid sample. Gender differences were minor. Observed-to-expected ratios were highest when purine/pyrimidine metabolism disorders/gout and osteoarthritis were part of the multimorbidity patterns.</p> <p>Conclusions</p> <p>The above list of dominating chronic conditions and their combinations could present a pragmatic start for the development of needed guidelines related to multimorbidity.</p

Overlapping of multimorbidity patterns (in %) related to the total male population.

<p>Overlapping of multimorbidity patterns (in %) related to the total male population.</p

Overlapping of multimorbidity patterns (in %) related to the total female population.

<p>Overlapping of multimorbidity patterns (in %) related to the total female population.</p

Prevalence by age for multimorbidity patterns of female patients.

<p>CMD: cardiovascular and metabolic disorders; ADS/P: anxiety, depression, somatoform disorders and pain; NPS: neuropsychiatric disorders.</p

Loadings of factors with eigenvalue ≥1 in diagnosis groups of female patients.

<p> <b>Factor loadings <.25 have been omitted. CMD: cardiovascular and metabolic disorders; ADS/P: anxiety, depression, somatoform disorders and pain; NPS: neuropsychiatric disorders.</b></p