CV

CURRICULUM VITAE

PERSONAL DATA

NAME: Kim Rose Olsen

ADDRESS: Department of Public Health, University of Southern Denmark, JB Winsløws Vej 9B  DK-5000 Odense C

PHONE: (+45) 29125767

EMAIL:  krolsen@sdu.dk

OFFICIAL HOMEPAGE: www.sdu.dk/ansat/krolsen

EDUCATION

2010: Ph.d., Economics, University of Southern Denmark

2007-2010: Various research visits, Centre for Health Economics, University of York

2001:  Visiting Research Student, London School of Economics

1999: M.Sc., Economics (Cand.polit.), University of Copenhagen

1997: Nordplus exchange student, University of Oslo.

WORK EXPERIENCE (selected)

2019 –    Professor, DaCHE, University of Southern Denmark

2017 – 2019 Associate professor, DaCHE, University of Southern Denmark

2013 – 2017 Associate professor and director COHERE Analysis, Department of Business and Economics, University of Southern Denmark

2010-2013: Health Economist/Assistant professor, Department of Public Health University of Southern Denmark

2003 – 2010 Senior Research associate at DSI (now ViVE )

RESEARCH INTERESTS, FUNDING AND RESEARCH PROJECTS

I apply methods from Health Economics, Applied Microeconometrics, Epidemiology, Health Data Science and Real World Evidence to health economic research questions as inequality in access to health care, health and behaviour of the health care workforce, efficiency and productivity measurement, financial and non-financial incentives and evaluation of health care policies. I have extensive expertise with interdisciplinary research collaborations. Some examples:

  • HoW research programme: Research Program on Hospital Workforce (ca 1 mio DKK various funding, PI) LINK
  • LightCOMM: Research project on obesity (180 mio DKK, Novo Nordisk Foundation, co-applicant) LINK
  • Modernizing the GP scheme: (15 mio NOK, Det Norske Forskningsråd, co-applicant) LINK
  • PINCH: Incentives in general practice (10 mio DKK, Novo Nordisk Foundation, co-PI) LINK
  • FOKUS & FORDYB Trials: Scientific protocol for a Randomized Controlled Trial for Primary Care Remuneration (4 mio DKK, Sundhedsministeriet og Finansministeriet,  PI) LINK
  • IQCE – ETN: EU Marie Curie Phd network collaboration with 7 Universities and 15 phd students (€3.9 million, co-applicant and lead supervisor) LINK

TEACHING

I am coordinating the Health Data Science profile at the Data Science graduate program at SDU (https://www.sdu.dk/en/uddannelse/kandidat/data-science). We follow the definition of Health Data Science by Hernan et al. (2019)* and aim at giving students skills in Datamanagement, Prediction (machine learning) and Causal Analysis. I teach the course “From data to Evidence” focusing on quasi experimental methods.

*Hernan et al (2019). A Second Chance to Get Causal Inference Right: A Classification of Data Science Tasks. CHANCE, 2019 32:1, 42-49–

PHD STUDENTS:

Current:

  • Amalie Wiben (main supervisor): Backdisorder and occupational workload.
  • Louise Schubert Paaske (main supervisor): Health consequences of unplanned overtime among hospital staff.
  • Sasja Maria Pedersen (co-supervisor): Optimizing diabetic retinopathy screening in Denmark: Application of machine learning algorithms and stated preference experiment
  • Kristoffer Panduro Madsen (co-supervisor on one chapter): Effects of initiating insulin pump therapy in the real world: a nationwide, register-based study of adults with type 1 diabetes.
  • Mickael Kriegbaum (co-supervisor): Long-term individual and societal consequences of untreated vertebral osteoporotic fractures.
  • Søren Grøn (co-supervisor): Self-management and health care utilization in people with low back pain.

Past:

  • Ryan Pulleyblank (main supervisor): Impacts of Danish Healthcare System Changes Affecting Care of Patients with Type 2 Diabetes.
  • Morten Sahl (co-supervisor): Evaluating organisational changes using quasi-experimental study designs – evidence from a case study including low back pain patients.
  • Anne Sophie Oxholm (co-supervisor): Physician Quality and Financial Incentives.

MASTER THESIS STUDENTS

  • Anders Aagaard (2023) – data science, SDU. Predicting diabetes complications with Machine Learning using administrative health data. Co-supervised by Richard Röttger (Department of mathematics and computer science SDU).
  • Christoffer Severin Jensen (2023) – data science, SDU. Using machine learning on images of sensory neurons to study chemotherapy neurotoxicity. Co-supervised by Richard Röttger & Tore B. Stage.
  • Mohamed Ahmed Dhagane & Mohammad Ibrahim Irshad (2023) – data science, SDU. Combining Record and Survey Data for Suicidal Behavior Prediction in Danish Youth – A Machine Learning Approach. Co-supervised by Marie Kruse & Lau Caspar Thygesen
  • Majid Amin (2023) – data science, SDU. A Machine Learning approach to analyzing and predicting early suicidal behaviors and tendencies amongst the Danish youth through the utilization of register and survey data. Co-supervised by Marie Kruse & Lau Caspar Thygesen.
  • Annika Andersen & Palle Sorth Bendix (2022) – data science, SDU. Predicting Mental Resilience in Terms of Sickness Absence – a Prospective Machine Learning Approach. Co-supervised by Richard Röttger (Department of mathematics and computer science SDU) and Anne Helene Garde (Nationalt forskningscenter for Arbejdsmiljø). 
  • Bastian Dam & Anne Marie Schriver (2021) – data science, SDU. The Influence of Health, Digital and Social Behavior on Suicidal Thoughts Among Young People in Denmark- Using machine learning to predict suicidal thoughts. Co-supervised by Richard Röttger (Department of mathematics and computer science SDU, Stephan Jänicke (Department of mathematics and computer science SDU) and Lau Caspar Thygesen (National Institute of Public Health).
  • Louise Schubert Paaske & Christine Midtgaard (2020) – Sundhedsfaglig kandidatuddannelse, SDU. The effect of patient-controlled hospital admissions on use of coercive measures among patients with severe mental disorder: A register-based prospective cohort study. Co-supervised by Liza Sopina (DaCHE – SDU).
  • Kristian Nørregaard Larsen (2016) – cand oecon, SDU.The analysis of economic performance when merging hospital departments- A natural experiment utilizing patient-level data.
  • Khiem Van Nguyen (2016) – cand oecon, SDU. Exploring the challenges in the Danish home care nursing sector with focus on organizing economic incentives.
  • Mads Bager Hoffman (2013) – cand polit, KU. Efficiensanalyse af Almen Lægepraksis
  • Lærke Olesen (2013) – cand oecon, SDU. Præstationsaflønning i almen praksis i Danmark – Vurdering på baggrund af en analyse af behandlingskvaliteten i almen praksis.

MEMBERSHIPS

HESG

NFA economics reference group

REVIEW

Reviewer for the Research Council of Norway 2023

Reviewer for the Research Council of Norway 2022

Reviewer for: Health Economics, Social Science & Medicine, Scandinavian Journal of Public Health, Scandinavian Journal of Economics, BMJ Open, ViVE, SiF, European Journal of Health Economics.