[Good Practice of Secondary Data Analysis (GPS): guidelines and recommendations]. / Gute Praxis Sekundärdatenanalyse (GPS): Leitlinien und Empfehlungen.

In 2005, the Working Group for the Survey and Utilisation of Secondary Data (AGENS) of the German Society for Social Medicine and Prevention (DGSMP) and the German Society for Epidemiology (DGEpi) first published "Good Practice in Secondary Data Analysis (GPS)" formulating a standard for conducting secondary data analyses. GPS is intended as a guide for planning and conducting analyses and can provide a basis for contracts between data owners. The domain of these guidelines does not only include data routinely gathered by statutory health insurance funds and further statutory social insurance funds, but all forms of secondary data. The 11 guidelines range from ethical principles and study planning through quality assurance measures and data preparation to data privacy, contractual conditions and responsible communication of analytical results. They are complemented by explanations and practical assistance in the form of recommendations. GPS targets all persons directing their attention to secondary data, their analysis and interpretation from a scientific point of view and by employing scientific methods. This includes data owners. Furthermore, GPS is suitable to assess scientific publications regarding their quality by authors, referees and readers. In 2008, the first version of GPS was evaluated and revised by members of AGENS and the Epidemiological Methods Working Group of DGEpi, DGSMP and GMDS including other epidemiological experts and had then been accredited as implementation regulations of Good Epidemiological Practice (GEP). Since 2012, this third version of GPS is on hand and available for downloading from the DGEpi website at no charge. Especially linguistic specifications have been integrated into the current revision; its internal consistency was increased. With regards to contents, further recommendations concerning the guideline on data privacy have been added. On the basis of future developments in science and data privacy, further revisions will follow.

[Efficacy and efficiency of searches for a physician using physician search and evaluation portals in comparison with Google]. / Effektivität und Effizienz der Arztsuche mit Arztsuch- und Bewertungsportalen und Google.

OBJECTIVES: The Internet provides ways for patients to obtain information about doctors. The study poses the question whether it is possible and how long it takes to find a suitable doctor with an Internet search. It focuses on the effectiveness and efficiency of the search. Specialised physician rating and searching portals and Google are analysed when used to solve specific tasks. METHODS: The behaviour of volunteers when searching a suitable ophthalmologist, dermatologist or dentist was observed in a usability lab. Additionally, interviews were carried out by means of structured questionnaires to measure the satisfaction of the users with the search and their results. Three physician rating and searching portals that are frequently used in Germany (Jameda.de, DocInsider.de and Arztauskunft.de) were analysed as well as Google. RESULTS: When using Arztauskunft and Google most users found an appropriate physician. When using Docinsider or Jameda they found fewer doctors. Additionally, the time needed to locate a suitable doctor when using Docinsider and Jameda was higher compared to the time needed when using the Arztauskunft and Google. The satisfaction of users who used Google was significantly higher in comparison to those who used the specialised physician rating and searching portals. CONCLUSION: It emerged from this study that there is no added value when using specialised physician rating and searching portals compared to using the search engine Google when trying to find a doctor having a particular specialty. The usage of several searching portals is recommended to identify as many suitable doctors as possible.

[Hospitalisations for acute myocardial infarction--comparing data from three different sources]. / Stationäre Behandlung des Akuten Myokardinfarktes--ein Vergleich unterschiedlicher Datenquellen.

OBJECTIVES: The aim of this study is to compare information on hospitalisations for acute myocardial infarction (AMI) from three different sources. METHODS: (A) The national hospital discharge statistics, covering all hospitalisations in Germany, is representative for this population. However, the information is limited, as data are collected case-related containing only few characteristics. (B) In contrast, claims data of sickness funds can be analysed longitudinally and contain more characteristics. The data have to be collected from single sickness funds. As for the data from registries (C) these data cannot be assumed to be representative. RESULTS: Data from the included sickness fund showed good consistency when compared to data from the national hospital discharge statistics regarding most, but not all, results. Comparisons with the register in Augsburg lead to divergent results regarding case fatality rates and rates of utilisation of technologies. CONCLUSIONS: None of the three sources can be considered ideal. Part of the differences could be explained by methodological and regional effects. More insight could be gained by comparing data at the individual level. According to recent legislation, data from all statutory sickness funds are supposed to be merged. This would simplify such comparisons and most likely would allow for more valid information regarding the incidence and treatment of AMI and many other diseases.

[Work based on data of the Gmünder Ersatzkasse. An exemplary overview]. / Arbeiten mit Daten der Gmünder Ersatzkasse. Ein exemplarischer Uberblick.

Since the 1990s, administrative data sources of statutory health insurance companies in Germany have significantly expanded. However, general statements with regard to data availability are not possible. Taking the example of the Gmünder Ersatzkasse (GEK) with currently about 1.6 million insured persons, this article will give an impression, which data, and since when, could have been used for scientific analysis. Examples of different topics (unemployment, alcohol abuse, outpatient psychotherapy, coronary revascularization) are given. Data exist on almost all sectors of health insurance coverage since the availability of information on outpatient care in the year 2004. Research opportunities - and hence the scientific value of these data - are mainly resulting from the acquisition of data at the personlevel. Only with person-level data can longitudinal and trans-sectoral analysis capabilities with clearly defined denominator populations arise. Due to the availability of data for large populations, previously nonexisting analysis options are now available.