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41129-01 - Lecture with practical courses: Advanced Statistics: Analysing quality of care data 3 CP

Semester spring semester 2023
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)
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 installed R and RStudio.
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
unregelmässig See individual dates

Dates

Date Time Room
Wednesday 22.02.2023 10.15-16.00 Kollegienhaus, Seminarraum 103
Wednesday 08.03.2023 10.15-16.00 Kollegienhaus, Seminarraum 103
Wednesday 15.03.2023 10.15-16.00 Kollegienhaus, Seminarraum 103
Wednesday 29.03.2023 10.15-16.00 Kollegienhaus, Seminarraum 103
Wednesday 12.04.2023 10.15-16.00 Kollegienhaus, Seminarraum 103
Wednesday 03.05.2023 10.15-16.00 Kollegienhaus, Seminarraum 103
Wednesday 10.05.2023 09.15-16.00 Bernoullistrasse 28, Seminarraum U01
Wednesday 14.06.2023 10.15-16.00 Bernoullistrasse 28, Seminarraum 7
Modules Modul Vertiefung Research (Master's Studies: Nursing)
Assessment format continuous assessment
Assessment details The exams consist of an abstract, a 10-minute oral presentation including 10-minute discussion.
The oral presentation and discussion will be on 14th June 2023!
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

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