Evidence-based Management (5 ECTS)

Objective

The purpose of the course is to strengthen the student’s competence in evidence-based management in the developing operating environments of the health care and social services sector. The purpose is to deepen information search, utilisation and dissemination skills in evidence-based health care.

The student is familiar with the developing operating environments in the health care and social services sector and enhances their knowledge of service systems. The student internalises the importance and potential of evidence-based management for different needs and in various situations. The student adopts evidence-based activities as the starting point for their work and understands the connection between evidence-based activities and RDI activities. The student is able to assess current practices, their development using evidence-based methods, areas in need of development and the staff’s competence needs related to a certain subject.

The student is able to systematically search, utilise and assess condensed researched information and to critically analyse its importance in the development of consistent practices and in decision-making.

Content

- Evidence-based management in developing operating environments
- Future changes in the health care and social services operating environment
- Evidence-based health care, concepts and processes used in operations as part of evidence-based management as a whole
- Systematic information search, quality control and condensation of knowledge
- Dissemination and implementation of knowledge

Location and time

The online meetings according to the course timetable will take place in Teams as follows:

Mon 6.10.2025 at 13.00-16.00
Mon 3.11.2025 at 13.00-16.00
Thu 6.11.2025 at 13.00-16.00
Mon 1.12.2025 at 13.00-16.00

The Teams link can be found for each lecture in the timetable and in the Moodle learning space.

Materials

The course material is available on Moodle and will be opened one week before the course starts. It is recommended to use, for example, reliable online sources, up-to-date news and library material to support learning.

Students accepted for the course will receive a link to the Moodle learning environment and a course key from the OMA workspace.

The use of artificial intelligence in learning tasks is encouraged, provided that this is clearly stated. Separate instructions on this will be provided in Moodle.

Teaching methods

COURSE FOR MASTER'S DEGREE STUDENTS
The course is delivered entirely online; in Moodle and Teams. The course consists of four online meetings, assignments and interaction in Moodle/Teams according to the timetable.

The lectures will be recorded and available for viewing in the Moodle learning environment for students of the course for one month after the end of the course. Privacy policy: the Metropolia Student and Course Data Register https://www.metropolia.fi/fi/metropoliasta/tietosuoja-ja-gdpr/tietosuojaselosteet/metropolian-opiskelija-ja-opintotietorekisteri

Employer connections

N/A

Exam schedules

No exams.

International connections

N/A

Completion alternatives

No optional performance modes.

Student workload

A total of five credits means 135 hours of student work.
(1 credit = 27 h, 5 credits = 135 h)

Content scheduling

The course will open in Moodle on 29.9.2025 and the deadline for completion of assignments is 7.12.2025 at 21:00. The content may be opened in stages and/or supplemented with e.g. topical materials.

Further information

The student confirms his/her place in the course by returning the first learning assignment according to the given timetable. If a registered student does not attend the course, the teacher responsible for the course may remove the student from the course two weeks after the start of the course.

AHOT (Accreditation of prior learning)
The course can be accredited if the student has played a key role in digital projects in the field of health and social care and/or has a Master's degree level of studies corresponding to the content of this course.

Use of AI
The use of AI in learning tasks is encouraged, provided that this is clearly stated. As a general rule, the general guidelines for the use of AI at Metropolia will be followed. Separate instructions on this will be provided in Moodle.

Evaluation scale

0-5

Assessment criteria, satisfactory (1)

The student demonstrates that they understand the basic content of the course but there are shortcomings in their ability to independently acquire and interpret information and apply what they have learned.

Assessment criteria, good (3)

The student demonstrates that they have a good understanding of the content of the course. They actively acquire information and interpret the key connections between different pieces of information. The student has the ability to analyse what they have learned and to apply it in practice.

Assessment criteria, excellent (5)

The student demonstrates that they have a diverse and broad understanding of the content of the course. They possess excellent information acquisition skills that are suited to the purpose at hand. The student demonstrates independence and responsibility in the choices they make. They have a creative and broad-based ability to apply what they have learned in practice.

Assessment criteria, approved/failed

Approved: The student demonstrates that they understand the basic content of the course but there are shortcomings in their ability to independently acquire and interpret information and apply what they have learned in practice.

Assessment methods and criteria

All course assignments must be passed with a pass or at least a grade of 1 in order to complete the course in full. There are assignments in the course that are graded pass/fail and an additional assignment that is graded 0-5.

Assessment scale 0-5

Satisfactory 1-2
Students demonstrate mastery of the basic content of the course, but show weaknesses in independent knowledge acquisition, interpretation and ability to apply what they have learned.

Good 3-4
The student demonstrates a good command of the course content. He/she actively seeks knowledge and interprets its key contexts. They are able to analyse and apply what they have learned in practice.

Excellent 5
The student demonstrates a broad and comprehensive understanding of the content of the course. He/she has excellent knowledge acquisition skills appropriate to the purpose of the course. He/she demonstrates independence and responsibility in the decisions he/she makes. His/her ability to apply what he/she has learned in practice shows creativity and breadth.

Course evaluation criterion, approved
Approved: The student demonstrates mastery of the basic content of the course, but has weaknesses in independent knowledge acquisition, interpretation and the ability to apply what he/she has learned.

Further information

RPL (Recognition of Prior Learning)
The course can be accredited with prior Master’s degree level studies the contents of which correspond to the contents of this course, or with strong competence with similar content obtained in other ways (e.g. through working in a group tasked with preparing clinical treatment recommendations).

Further information

RPL (Recognition of Prior Learning)
The course can be accredited with prior Master’s degree level studies the contents of which correspond to the contents of this course, or with strong competence with similar content obtained in other ways (e.g. through working in a group tasked with preparing clinical treatment recommendations).