Health monitoring of refugees in reception centres for asylum seekers: Decentralized surveillance network for the analysis of routine medical data

Refugees and asylum seekers living in reception centres tend to be not adequately included in population-based studies, routine medical data and official statistics. As part of the research project ‘Health and primary-care sentinel surveillance in reception- and accommodation-centres for asylum-seekers in Germany’ (PriCare), a health-monitoring approach was developed for the secondary use of routine medical data from on-site outpatient clinics in reception centres. To this end, a software application (Refugee Care Manager, RefCare©) for the digitisation and harmonisation of medical records was designed and implemented in reception centres in three German federal states. The approach of distributed computing in a surveillance network allows for the decentralised, harmonised analysis of the routine medical data stored in RefCare© in a manner that fully complies with data protection regulations and circumvents the need for centralised data storage. RefCare© provides an integrated surveillance feature that enables analyses of 64 indicators on population, morbidity, healthcare processes and quality of care to be undertaken across multiple facilities. This article describes the conceptual and practical approach and the technical procedures put in place to do so, and provides examples of the results that have been gained so far

Assessing self-management in patients with diabetes mellitus type 2 in Germany: validation of a German version of the Summary of Diabetes Self-Care Activities measure (SDSCA-G)

Kamradt M, Bozorgmehr K, Krisam J, et al. Assessing self-management in patients with diabetes mellitus type 2 in Germany: validation of a German version of the Summary of Diabetes Self-Care Activities measure (SDSCA-G). Health and Quality of Life Outcomes. 2014;12(1): 185

Gesundheitsmonitoring bei geflüchteten Menschen in Aufnahmeeinrichtungen: dezentrale Analyse medizinischer Routinedaten im Verbund

Geflüchtete Menschen in Aufnahmeeinrichtungen werden in bevölkerungsbezogenen Erhebungen, Routinedaten und amtlichen Statistiken bislang unzureichend berücksichtigt. Im Rahmen des Forschungs- und Entwicklungsvorhabens „Surveillance der Gesundheit und primärmedizinischen Versorgung von Asylsuchenden in Aufnahmeeinrichtungen“ (PriCare) wurde daher ein Ansatz für ein Gesundheitsmonitoring durch Sekundärnutzung medizinischer Routinedaten in den Ambulanzen der Aufnahmeeinrichtungen für geflüchtete Menschen entwickelt. Hierzu wurde eine Dokumentationssoftware (Refugee Care Manager, RefCare©) zur Digitalisierung und Harmonisierung der Primärdokumentation entwickelt und in Aufnahmeeinrichtungen dreier Bundesländer implementiert. Der Ansatz des verteilten Rechnens in einem Surveillancenetzwerk ermöglicht durch dezentrale aber harmonisierte Analysen, die datenschutzkonforme Sekundärnutzung dieser medizinischen Routinedaten ohne zentrale Speicherung personenbezogener Informationen. Durch eine integrierte Monitoringfunktion können 64 Indikatoren zur Population, Morbidität sowie zu Versorgungsprozessen und -qualität routinemäßig und einrichtungsübergreifend ausgewertet werden. Der Beitrag beschreibt das konzeptionelle und praktische Vorgehen, das technische Verfahren sowie exemplarische Ergebnisse dieses Monitoringsystems

Surveillance der Gesundheit und primärmedizinischen Versorgung von Asylsuchenden in Aufnahmeeinrichtungen: Konzept, Entwicklung und Implementierung

Nöst S, Jahn R, Aluttis F, et al. Surveillance der Gesundheit und primärmedizinischen Versorgung von Asylsuchenden in Aufnahmeeinrichtungen: Konzept, Entwicklung und Implementierung. Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz. 2019;62(7):881-892

Health-Related Quality of Life in Primary Care: Which Aspects Matter in Multimorbid Patients with Type 2 Diabetes Mellitus in a Community Setting?

<div><p>Background and Objective</p><p>Knowledge about predictors of health-related quality of life for multimorbid patients with type 2 diabetes mellitus in primary care could help to improve quality and patient-centeredness of care in this specific group of patients. Thus, the aim of this study was to investigate the impact of several patient characteristics on health-related quality of life of multimorbid patients with type 2 diabetes mellitus in a community setting.</p><p>Research Design and Methods</p><p>A cross-sectional study with 32 primary care practice teams in Mannheim, Germany, and randomly selected multimorbid patients with type 2 diabetes mellitus (N = 495) was conducted. In order to analyze associations of various patient characteristics with health-related quality of life (EQ-5D index) a multilevel analysis was applied.</p><p>Results</p><p>After excluding patients with missing data, the cohort consisted of 404 eligible patients. The final multilevel model highlighted six out of 14 explanatory patient variables which were significantly associated with health-related quality of life: female gender (r = -0.0494; p = .0261), school education of nine years or less (r = -0.0609; p = .0006), (physical) mobility restrictions (r = -0.1074; p = .0003), presence of chronic pain (r = -0.0916; p = .0004), diabetes-related distress (r = -0.0133; p < .0001), and BMI (r = -0.0047; p = .0045).</p><p>Conclusion</p><p>The findings of this study suggest that increased diabetes-related distress, chronic pain, restrictions in (physical) mobility, female gender, as well as lower education and, increased BMI have a noteworthy impact on health-related quality of life in multimorbid patients with type 2 diabetes mellitus seen in primary care practices in a community setting. The highlighted aspects should gain much more attention when treating multimorbid patients with type 2 diabetes mellitus.</p></div

Description of the EQ-5D index with respect to the presence of the combination of chronic heart failure (ICD 10: I50), depression (ICD 10: F32-F33) and chronic pain (ICD 10: R52) next to type 2 diabetes.

<p>Means unadjusted, p-values adjusted for multilevel structure.</p

Sample description (included patients) with observed means and standard deviation for continuous, and absolute and relative frequencies for categorical variables.

<p>Sample description (included patients) with observed means and standard deviation for continuous, and absolute and relative frequencies for categorical variables.</p

Description of the EQ-5D index with respect to the presence of a specific comorbidity next to type 2 diabetes.

<p>Means unadjusted, p-values adjusted for multilevel structure.</p