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41129-01 - Lecture with practical courses: Advanced Statistics: Analysing quality of care data (3 CP)
| Semester | spring semester 2025 |
| Course frequency | Every spring sem. |
| Lecturers |
Catherine Blatter (catherine.blatter@unibas.ch)
Sarah Musy (sarah.musy@unibas.ch) Michael Simon (m.simon@unibas.ch, Assessor) Diana Trutschel (diana.trutschel@unibas.ch) |
| Content | • A lecture-seminar-workshop format will be used. • The complete process from conceptualizing, analyzing, and presenting data of quality-of-care data will be used. • Regression-based techniques for between provider comparisons (provider profiling) • Statistical process control to describe quality of care over time within organizations. |
| Learning objectives | According to the WHO quality health care can be defined in many ways, but quality health services should be: effective, safe, and people-centered. To realize these benefits health services must be: timely, equitable, integrated, and efficient [1]. In order to achieve these goals multiple approaches exists, with data-driven quality improvement and public reporting as key means to describe and assess quality of care. The goal of this course is to introduce students to two areas of quantitative data analysis, which are commonly used in applied analyses of quality-of-care data: provider profiling and statistical process control. With the successful completion of the course students will be able to: 1. Describe basic concepts of quality of care and their theoretical underpinnings 2. Develop an appropriate question in the context of quality of care and the available data. 3. Evaluate the scope and limitations of the available quality of care data. 4. Analyze quality of care data with your own or a provided data set 5. Present and discuss quality of care data with different audiences [1] https://www.who.int/health-topics/quality-of-care#tab=tab_1 |
| Bibliography | Please bring your own laptop with an up-to-date installation of R and RStudio. Instructions for installation: https://posit.co/download/rstudio-desktop/ Literature is available on ADAM. |
| Comments | Slides, data & code will be available on ADAM. Sessions will be recorded and posted on Panopto. |
| Weblink | Login ADAM |
| Admission requirements | Successful completion of Statistics I (LV10537) & II (LV 10538). Please look again at course content and topcis of Statistics I and II in order to be able to follow the course! |
| Course application | in Services belegen |
| Language of instruction | English |
| Use of digital media | Online, mandatory |
| Interval | Weekday | Time | Room |
|---|---|---|---|
| wöchentlich | Wednesday | 10.15-16.00 | Kollegienhaus, Hörsaal 117 |
Dates
| Date | Time | Room |
|---|---|---|
| Wednesday 05.03.2025 | 10.15-16.00 | Kollegienhaus, Hörsaal 117 |
| Wednesday 19.03.2025 | 10.15-16.00 | Kollegienhaus, Hörsaal 117 |
| Wednesday 02.04.2025 | 10.15-16.00 | Kollegienhaus, Hörsaal 117 |
| Wednesday 09.04.2025 | 10.15-16.00 | Kollegienhaus, Hörsaal 117 |
| Wednesday 16.04.2025 | 10.15-16.00 | Kollegienhaus, Hörsaal 117 |
| Wednesday 30.04.2025 | 10.15-12.00 | Kollegienhaus, Hörsaal 117 |
| Wednesday 28.05.2025 | 09.00-17.00 | Bernoullistrasse 28, Seminarraum U01 |
| Modules |
Modul Vertiefung Research (Master's Studies: Nursing) |
| Assessment format | continuous assessment |
| Assessment details | The exam consist of an abstract (20% of the course grade) and an oral exam (80% of the course grade). |
| Assessment registration/deregistration | Registration: course registration: deregistration: institute |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,1 |
| Repeated registration | one repetition |
| Responsible faculty | Faculty of Medicine |
| Offered by | Institut für Pflegewissenschaft |