Hoitotyön johtamisen ja näyttöön perustuvan toiminnan vahvistaminen tutkimusyhteistyön ja koulutuksen avulla
Turun yliopiston hoitotieteen laitoksen vuonna 2023 alkaneessa hankkeessa keskitytään kaksikielisen Varsinais-Suomen hyvinvointialueen (Varha) hoitotyön johtamisen kehittämiseen. Hanketta rahoittaa Stiftelsen Eschnerska Frilasarettet -säätiö. Hankkeen tavoitteena on, että Turun yliopiston hoitotieteen laitos ja Varha luovat yhdessä mallin, jossa hoitotyön johtamista tukevat johtajakoulutus, tutkimus ja käytäntö.
Hanke toteutetaan yhteistyössä hoitotyön lähiesihenkilöiden kanssa, mikä varmistaa, että käytännön tarpeet ja haasteet otetaan huomioon. Hankkeen aikana luodaan toimintamalli, jossa integroidaan tutkimus, koulutus ja käytännön johtamistyö eläväksi kokonaisuudeksi luoden pohjan entistä paremmalle hoitotyölle.
Rahoittaja
Stiftelsen Eschnerska Frilasarettet säätiö on saanut alkunsa Turussa 1800-luvulla vaikuttaneen Carl-Gustav Eschnerin testamentista. Säätiö tukee lahjoituksillaan Turun ja ympäröivän alueen sosiaali- ja terveydenhuollon toimintaa.
Hoitotieteen laitos
Anna Axelin
Laura-Maria Peltonen
Riitta Askola
Jaakko Varpula
Varha
Tarja Heino-Tolonen
Miia Lindström
Smart Healthcare Leadership and Management
Purpose
We explore opportunities and impact of applying information technologies to supporting decision-making in different levels in heath care.
Projects
The purpose of this project is to determine the content, the source and the presentation format of important information, as well as quality indicators that are valid in health service provision. Simultaneously, the project explores the needs and possibilities of new technology solutions in strategic and operative management in a new type of health service delivery and in decision-making related to patients and nursing staff. As a result different users are offered relevant information depending on their position. One key area is to utilise real-time data and advanced analytics to improve decision-making for improved operational efficiency in healthcare settings. The ultimate goal is to create a more agile and responsive healthcare system that can adapt to dynamic and complex operational environments.
For further information please contact laura-maria.peltonen(at)utu.fi
The aim of this research project is to enhance knowledge-based management in perioperative nursing and thereby develop the efficiency of perioperative nursing from the clinical, administrative and patient perspective. The decision-making in perioperative nursing and its management requires relevant and reliable information that meets the users' needs in ensuring surgical patients' safe and evidence-based care.
For further information please contact kristiina.junttila@hus.fi.
In this project, a federated health data network will be developed, geared towards secondary use of health data. The project utilises distributed machine learning, specifically federated learning, to ensure data privacy and ownership. The federated health data network will be built upon privacy-preserving and secure distributed training of multilingual clinical language models in Norwegian, Swedish, Danish, Finnish, and Estonian. Additionally, the solution incorporates a distributed ledger with smart contracts and blockchain technology, enhancing transparency and security. Two use cases will be used to demonstrate the innovation potential of unstructured clinical text data: the detection of medical implants and the detection of adverse drug reactions.
The project is led by the Norwegian Centre for E-health Research, Tromsø, Norway, in collaboration with the partners:
- University of Turku, Finland
- Stockholm University, Sweden
- County Council of Östergötland/Linköping University Hospital, Sweden
- DNV, Norway
- University of Copenhagen, Denmark
- University of Tartu, Estonia
- Omilon, Denmark
- Cambio, Sweden
This project is one out of two projects funded under the Life Science and Health Tech program and the AI and Data program and supported by the Nordic Ministerial Council for Digitalization, which encompasses cooperation between the Nordic countries and Estonia, Latvia and Lithuania.
For further information please contact laura-maria.peltonen(at)utu.fi
In this project we explore and evaluate the application of natural language processing (NLP) technologies within the healthcare sector, particularly in areas pertaining to leadership and management. The project's primary objectives include utilising electronic health record data (EHR) to develop intelligent tools that enable healthcare leaders to better monitor service provision and quality of provided care for more informed decisions. This project involve sinterdisciplinary collaboration between computer scientists, healthcare professionals, ethicists and data privacy experts, all working towards leveraging NLP to enhance healthcare leadership and management.
For further information please contact laura-maria.peltonen(at)utu.fi
The project aims to develop and enhance leadership capabilities within healthcare and wellfare leaders to positively impact both staff well-being and services. By focusing on competencies such as communication, decision-making and team management, the project seeks to evaluate the impact on educational interventions developed and improve the overall operational effectiveness and create a supportive and efficient work environment. Ultimately, the goal is to cultivate leaders who can effectively navigate the complexities of healthcare operations and drive positive outcomes for both staff and patients in an interdisciplinary manner.
For further information please contact laura-maria.peltonen(at)utu.fi
The goal of this project is to develop and implement strategies for effective leadership aimed at engaging employees within the organisation. We will focus on identifying and utilising practical tools that foster a positive work environment, enhance communication, and encourage collaboration. By emphasising the importance of strong leadership, we aim to increase employee satisfaction, motivation and productivity. This project seeks to create a supportive and empowering workplace culture through the implementation of tailored leadership practices and initiatives.
For further information please contact laura-maria.peltonen(at)utu.fi
The project determines explores the meaning, components and the levels of situational awareness in healthcare operations management across settings. By measuring the impact of integrating various data sources and leveraging technologies the project aims to enhance situational awareness for healthcare operations leadership, leading to better resource allocation, improved patient care and overall operational effectiveness.
For further information please contact laura-maria.peltonen(at)utu.fi
Machine Learning for Clinical Information Analytics (ML4CIA)
Laura-Maria Peltonen, Department of Nursing Science, University of Turku
Hans Moen, Department of Future Technologies, University of Turku
This project aims to assess the content of documented care data of adult cardiac patients and to explore the use of machine learning methods and tools to support managers, clinicians, patients and researchers for the purpose of delivering individual-centered, safe and efficient care. Our main focus is on the free-text narratives written by nurses, physicians and allied health professionals, supported by structured data about the patients and their care.
Instruments developed
- The Hospital Shift Leaders' Information Needs Questionnaire
- The Instrument for the Evaluation of Advanced Life Support Performance
- The Instrument for the Assessment of Situational Awareness in Operational Management
For further information please contact laura-maria.peltonen(at)utu.fi
Principal Investigator
Research personnel
- Laura-Maria Peltonen Docent, RN, MHSc, PhD, FEANS, FIAHSI
- Kristiina Junttila Docent, RN, MHSc, PhD
- Outi Tuominen
- Jani Paulin
- Maria Pulkkinen
- Hanna von Gerich
- Tanja Liukas
- Lilli Ristevirta
- Mikael Helenius
- Marjut Asunmaa
- Pia-Maria Tanttu
- Janne Kommusaar
- Lili Schöler
- Ilze Steenkamp
- Emmi Myllymäki
- Johanna Sillantie-Korja
- Merituuli Eriksson
- Mirva Kuutti
- Ella Valkeapää
- Milla Haapala
- Vilma Blomros
- Reino Tissari
- Rosa Salmela