Empirische Versorgungsforschung in der Notfall- und Akutmedizin

Autor: M Schmiedhofer, V. Krobisch, Alice Schneider, Tobias Inhoff, Matthias Rose, J. Deutschbein, Martin Möckel, Ursula Müller-Werdan, Thomas Keil, Liane Schenk, Christoph Heintze
Rok vydání: 2019
Předmět:
Zdroj: Medizinische Klinik - Intensivmedizin und Notfallmedizin. 115:125-133
ISSN: 2193-6226
2193-6218
DOI: 10.1007/s00063-018-0522-y
Popis: Background Up until now, research data on the implementation of empirical health services research in emergency departments in Germany are scarce. Study aim A monitoring instrument applied in a multicenter prospective cohort study in emergency departments (EDs) is described and discussed regarding requirements for the control and supervision of data collection. Materials and methods Patients with cardiac diseases, respiratory tract infections, and hip fractures were recruited in eight EDs located in a central district of Berlin. Enrolment figures and nonresponder reasons were analyzed through descriptive statistics. Potential sample bias was examined in terms of response rates as well as the distribution of age and sex in the group of participants and nonresponders. Qualitative content analysis was applied to data from routine supervisory and feedback meetings with study nurses. Results Within the first 8 months of data collection, 61.1% of the aimed 1104 patients were recruited. Most frequently stated nonresponder reasons were the dense work and care processes in EDs (41.9%) and patients' disease burden (24.7%). Moreover, qualitative results revealed problems with identifying potentially eligible participants and difficulties because of missing research infrastructure in study centers. The response rate of 50.7% and approximately equal distribution of age and sex in participants and nonresponders do not indicate sample biases. Discussion The monitoring instrument has proven to be suited for empirical research in EDs and revealed optimization potential. We recommend using qualitative and quantitative data systematically.
Databáze: OpenAIRE