Methods of Data Analysis

22M1149

Master

Englisch

5.0

nur Sommersemester

1 Semester

This module covers topics related to data-driven planning and evaluation of management interventions in health care. It aims to enable students to use and understand quantitative data for controlling and evaluating management interventions in order to be able to better manage change and innovation. Thus, this course lays the foundation for evidence-based strategic management and change management.

1) Introduction to data-driven control and related designs 2) Introduction to empirical evaluation and related designs 3) Statistical methods of prediction 3.1) Regression methods 3.2) Time series analyses 3.3) Application and exercises 4) Statistical methods of evaluation 4.1) Univariate and multivariate methods of comparing groups 4.2) Application and exercises (1) 4.3) Mixed methods research: combining quantitative and qualitative methods 4.4) Application and exercises

Der Arbeitsaufwand für das Modul umfasst insgesamt 150 Stunden (siehe auch "ECTS-Leistungspunkte und Benotung").

• Pr?sentation oder
• Referat (mit schriftlicher Ausarbeitung) oder
• Portfolio-Prüfungsleistung

The portfolio exam covers 100 points and consists of a learning diary (LTP) and one-hour written examination. The LTB is weighted by 40 points and the K1 by 60 points.

Presentation: approx. 20-40 minutes

Report (R): presentation of approx. 20-40 minutes with written report of approx. 5-10 pages

Portfolio exam:

• Written examination: in accordance with the valid study regulations
• Learning diary: approx. 10-15 pages

The requirements are specified in the respective class.

Descriptive statistics (distribution parameters, correlation, regression, graphical representations), Inductive statistics (type I and II error, p-value, confidence interval, significance test)

Becoming familiar with statistical methods for management practice.

Having knowledge of the prerequisites, areas of application and limitations of the statistical methods covered.

Solving problems in contexts that require healthcare planning, prediction, and evaluation.

The students acquire knowledge and skills in the use of electronic tools for the application of statistical methods regarding different professional use cases.

Students are able to use the insights gained from data analyses both in the context of corporate management and in the context of the corresponding scientific domains.

Communicating the procedures, limitations, and interpretation of results of predictions and evaluations.

Students are able to reflect on the possibilities and limitations of data-driven management in health organisations. They internalise the premise of underpinning management decisions with data as far as possible, but are also aware of the epistemological, methodological and economic limitations of the approaches used in each case.

This course lays the foundation for evidence-based strategic management and change management. As such, it prepares students for the specialisation "Change management in health care organisations".

• Management im Gesundheitswesen, M.A. (01.09.2024)

• Hübner, Ursula Hertha

• Hübner, Ursula Hertha