The 9th Workshop in Behavioral and Experimental Health Economics will take place on October 07-08, 2024 at HCHE in Hamburg.

The workshop brings together economists and behavioral scientists who apply behavioral-economics insights and experimental methods to study health-related decision making. The workshop is part of the activities of the Behavioral Experiments in Health Network: www.beh-net.org.

Deadline for submissions is May 15th, 2024. Submissions should be uploaded via this submission portal. Authors will be notified regarding the acceptance of their paper by July 31st, 2024. The workshop is taking place in the central office of the HCHE in Hamburg on October 7th and 8th, 2024.

If you have any questions about the Call for Papers or the event, please contact us: beh.hche@uni-hamburg.de

For further information see the attached PDF

The 2nd CINCH-dggö Academy in Health Economics will take place from August 19th-August 23rd 2024 at the University of Duisburg-Essen.

We are proud to launch the second edition of the CINCH-dggö Academy in Health Economics focusing this year on the “economics of mental health” and recent “developments in difference- in-differences methods”. The workshop is jointly organised by CINCH, the national research centre for health economics at the University of Duisburg-Essen, and the dggö, the German Society for Health Economics.

The workshop will bring together a group of junior and senior researchers to share a week of expert lectures, research presentations, and special sessions. Expert lectures on the economics of mental health will be given by Meltem Daysal (University of Copenhagen) and on recent developments in difference-in-differences estimation by Andrew Goodman-Bacon (Federal Reserve Bank of Minneapolis). Special sessions include a “Meet the Editor” session with Manisha Shah, editor at the Journal of Health Economics and professor at the University of California (Berkeley), and sessions on academic publishing, the academic job market, and speed networking with senior researchers. Each day will conclude with an attractive social and cultural program.

Target audience: PhD students and early career postdocs working on health economics and closely related topics. Only 21 students will be admitted.

Seniors speakers for special sessions: Libertad Gonzalez (Universitat Pompeu Fabra), Martin Halla (University of Linz), Annika Herr (University of Hannover), Hendrik Schmitz (University of Paderborn), Bettina Siflinger (Tilburg University).

Best Paper Award: A prize of EUR 500 and publication in the CINCH working paper series will be awarded to the best paper of the workshop.

Registration fees: EUR 350; exemptions available for participants from low-income countries. Fees cover accommodation, lunches and dinners, and the social and cultural program—conditional on attending the entire workshop. Please indicate if you need assistance with travel costs.

Application: We accept all submissions within health economics, particularly those aligning with our core themes. To apply, send your CV and a full paper to cinch.academy@wiwinf.uni-due.de. We strongly encourage female students and students from disadvantaged backgrounds to apply.

Local organiser: Contact Daniel Kühnle, University of Duisburg-Essen, if you have any questions!

Deadline for applications: 30 April 2024

Fore more information see attached PDF

Der 11. dggö Talk wird die Reihe zu KI im Gesundheitswesen, die mitorganisiert wurde durch den Ausschuss Gesundheitsökonometrie, abschließen.

Noemi Kreif (University of York) spricht am 28.02.2024, 17-18 Uhr zum Thema „Machine learning in health economics and outcomes research: opportunities and some key challenges“.

Hier ist der Link zum Zoom-Meeting: https://uni-due.zoom-x.de/j/62465328399?pwd=RlJIRy9hejlPUksrMXhmWGZxN29Fdz09

In the first half of the talk she will outline the current landscape of using machine learning (ML) for health economics and outcomes research (HEOR). Noemi will focus on supervised ML, and its current application in key HEOR tasks. In the second, main part of the talk she will focus on three key challenges that researchers using ML in HEOR need to tackle: causality, interpretability, and estimation of uncertainty. Noemi will discuss the risks of the naive use of machine learning prediction models to inform treatment decisions, using published examples from clinical medicine. Next, she will bring examples from my own research on data-driven health policy targeting rules, showing the importance of careful adjustment for confounding via causal machine learning. A case study will demonstrate the potential for even state of the art methods to provide counterintuitive and even harmful recommendations, and she will discuss the utility of interpretable ML models in avoiding misleading results. Noemi will discuss the necessity of estimating uncertainty of ML predictions, for these to be used in decision analysis. Finally, she will try to generate an interactive discussion around the varying levels of openness of HEOR stakeholders to start using ML.

Dies ist der Letzte der drei dggö-Talks über KI, ML und das Gesundheitswesen. Für diejenigen, die das Thema vertiefen möchten, findet am 6./7. Juni in Potsdam ein Workshop zum Thema "Applied Economics in Digital Health" statt. Den Call for Papers (Deadline 15. März) finden Sie hier.

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The 11th dggö Talk will conclude the series on AI in healthcare, which was co-organised by the Health Econometrics Committee.

Noemi Kreif (University of York) 28 February 2024, 5-6 pm, will speak on the topic "Machine learning in health economics and outcomes research: opportunities and some key challenges."

Here is the link to the zoom meeting: https://uni-due.zoom-x.de/j/62465328399?pwd=RlJIRy9hejlPUksrMXhmWGZxN29Fdz09

In the first half of the talk she will outline the current landscape of using machine learning (ML) for health economics and outcomes research (HEOR). Noemi will focus on supervised ML, and its current application in key HEOR tasks. In the second, main part of the talk she will focus on three key challenges that researchers using ML in HEOR need to tackle: causality, interpretability, and estimation of uncertainty. Noemi will discuss the risks of the naive use of machine learning prediction models to inform treatment decisions, using published examples from clinical medicine. Next, she will bring examples from my own research on data-driven health policy targeting rules, showing the importance of careful adjustment for confounding via causal machine learning. A case study will demonstrate the potential for even state of the art methods to provide counterintuitive and even harmful recommendations, and she will discuss the utility of interpretable ML models in avoiding misleading results. Noemi will discuss the necessity of estimating uncertainty of ML predictions, for these to be used in decision analysis. Finally, she will try to generate an interactive discussion around the varying levels of openness of HEOR stakeholders to start using ML.

This will be the last of the three dggö Talks on AI, ML and health care. For those interested to dig deeper into the topic, there will be a workshop on “Applied Economics in Digital Health” on 6th/7th June in Potsdam. The Call for Papers (deadline 15th March) can be accessed here.

Workshop Health and care from early life to old age

On February 16 and 17 2024 the Committee for International Cooperation organised the Workshop Health and care from early life to old age at the Hamburg Center of Health Economics. Speakers and discussants from many different countries (Denmark, Germany, the Netherlands, Norway, UK, USA) engaged in lively discussions. Please see the program below.

Workshop program

*** English version below ***

Sehr geehrte Mitglieder der dggö,

ein frohes neues Jahr. Dies ist eine Erinnerung an den 10. dggö Talk, der am Mittwoch, 10.01.2024 um 12 Uhr stattfindet.

Ariel Dora Stern wird über "The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives“ sprechen.

Hier ist der Link zum Zoom-Konferenzraum:

https://uni-due.zoom-x.de/j/68515120272?pwd=NVFDWVdpVkVvWDdlNjFPNndSVUFFUT09

Abstract: For those who follow health and technology news, it is difficult to go more than a few days without reading about a compelling new application of Artificial Intelligence (AI) to health care. AI has myriad applications in medicine and its adjacent industries, with AI-driven tools already in use in basic science, translational medicine, and numerous corners of health care delivery, including administrative work, diagnosis, and treatment. In diagnosis and treatment, a large and growing number of AI tools meet the statutory definition of a medical device or that of an in-vitro diagnostic. Those that do are subject to regulation by local authorities, resulting in both practical and strategic implications for manufacturers, along with a more complex set of innovation incentives. We present background on medical device regulation—especially as it relates to software products—and quantitatively describe the emergence of AI among FDA-regulated products. The empirical analysis explores characteristics of AI-supported/driven medical devices (“AI devices”) in the United States. It presents data on their origins (by firm type and country), their safety profiles (as measured by associated adverse events and recalls), and concludes with a discussion of the implications of regulation for innovation incentives in medical AI.

Ariel Dora Stern ist Associate Professor of Business Administration an der Harvard Business School und hat sich auf Technologiemanagement und Innovation im Gesundheitswesen spezialisiert. Ihre Forschung befasst sich mit den regulatorischen, strategischen und wirtschaftlichen Aspekten des Gesundheitswesens, insbesondere mit der Entwicklung neuer Produkte und der Einführung und Nutzung medizinischer Technologien. Ihr besonderes Interesse gilt den Schnittstellen zwischen Regulierung, Unternehmensstrategie und Ökonomie im Gesundheitswesen. Darüber hinaus untersucht sie die digitale Transformation der Medizintechnik und des Gesundheitswesens, was ihr die Aufmerksamkeit renommierter Quellen wie Bloomberg, The New York Times und National Public Radio eingebracht hat. Ab April 2024 wird sie als Gewinnerin einer renommierten Humboldt-Professur am Hasso-Plattner-Institut und der Universität Potsdam forschen und lehren.

Der 11. dggö Talk wird die Reihe zu KI im Gesundheitswesen, die mitorganisiert wurde durch den Ausschuss Gesundheitsökonometrie, abschließen. Sie können sich das Datum schon einmal vormerken: am 28.02.2024, 17-18 Uhr spricht Noemi Kreif (University of York) zum Thema „Machine learning in health economics and outcomes research: opportunities and some key challenges“.

Die dggö ist neben unserer Webseite, wo Sie aktuelle Informationen zu Aktivitäten und den Ausschüssen finden, und dem RSS-Feed, den Sie abonnieren können, auch auf LinkedIn aktiv. Hier können Sie sich vernetzen und uns folgen.

Mit den besten Grüßen
Annika Herr

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Dear members of the dggö,

This is a reminder for the upcoming 10th dggö Talk, which will take place on Wednesday, 10 January 2024 at 12 noon.

Ariel Dora Stern (Harvard Business School) will talk about "The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives".

Here is the link to the zoom meeting:

https://uni-due.zoom-x.de/j/68515120272?pwd=NVFDWVdpVkVvWDdlNjFPNndSVUFFUT09

Abstract: For those who follow health and technology news, it is difficult to go more than a few days without reading about a compelling new application of Artificial Intelligence (AI) to health care. AI has myriad applications in medicine and its adjacent industries, with AI-driven tools already in use in basic science, translational medicine, and numerous corners of health care delivery, including administrative work, diagnosis, and treatment. In diagnosis and treatment, a large and growing number of AI tools meet the statutory definition of a medical device or that of an in-vitro diagnostic. Those that do are subject to regulation by local authorities, resulting in both practical and strategic implications for manufacturers, along with a more complex set of innovation incentives. We present background on medical device regulation—especially as it relates to software products—and quantitatively describe the emergence of AI among FDA-regulated products. The empirical analysis explores characteristics of AI-supported/driven medical devices (“AI devices”) in the United States. It presents data on their origins (by firm type and country), their safety profiles (as measured by associated adverse events and recalls), and concludes with a discussion of the implications of regulation for innovation incentives in medical AI.

Ariel Dora Stern is an Associate Professor of Business Administration at Harvard Business School, specializing in technology management and innovation in healthcare. Her research explores the regulatory, strategic, and economic aspects of healthcare, emphasizing new product development, adoption, and utilization of medical technologies. Stern is particularly interested in the intersection of regulation, firm strategy, and healthcare economics, and she also investigates the digital transformation of medical technology and healthcare delivery, garnering attention from reputable sources such as Bloomberg, The New York Times, and National Public Radio. From April 2024, she will be researching and teaching at the Hasso Plattner Institute and University of Potsdam as the winner of a prestigious Humboldt Professorship.

The 11th dggö Talk will conclude the series on AI in healthcare, which was co-organised by the Health Econometrics Committee. You can already make a note of the date: on 28 February 2024, 5-6 pm, Noemi Kreif (University of York) will speak on the topic of "Machine learning in health economics and outcomes research: opportunities and some key challenges"

With best regards
Annika Herr

Dear Colleagues,

We are excited to inform you that the Call for Abstracts for the upcoming EuHEA Conference, to be held in Vienna, Austria, from 30th June to 3rd July 2024, is now open. The theme of the conference is ‘Opening up perspectives on health economics’ and submissions from all areas of health economics are welcome.

We are very pleased also to announce that Carol Propper (Imperial College London) and Owen O’Donnell (Erasmus University Rotterdam) will join the EuHEA Conference 2024 as keynote speakers.

Please submit your abstract or organised session via this link by latest 21st January 2024. Kindly ensure that your abstract does not exceed 2,800 characters and includes objectives, methods, results, and discussion. We look forward to receiving your submission.

For more information regarding the conference program, the pre-conference workshops, and hotel reservations please visit the conference website.

The conference will be hosted by the Vienna University of Economics and Business (WU) and the Institute for Advanced Studies (IHS), supported by the Austrian Public Health Institute (Gesundheit Österreich GmbH).

We are looking forward to welcoming you at the EuHEA Conference 2024 in Vienna.

Servus in Wien!

The Vienna Local Organising Committee

der dggö-Ausschuss „Ökonomische Evaluation und Entscheidungsfindung“ wird sich am Freitag, den 24. November 2023 (10:00-15:45 Uhr online via MS Teams) treffen.

Als Hauptredner*innen konnten wir Prof. Dr. Johanna Kokot (Universität Hamburg & Hamburg Center for Health Economics), Prof. Dr. Thomas Mayrhofer (Hochschule Stralsund & Harvard Medical School) und Prof. Dr. Alexander Konnopka (Universitätsklinikum Hamburg-Eppendorf & MSH Medical School Hamburg) gewinnen.

Wir freuen uns auch über die Vorstellung der Nachwuchswissenschaftler*innen Maximilian Zinn (Heinrich-Heine Universität Düsseldorf & DDZ), Léon Kreis (UKE Hamburg) und Benedicta Hermanns (Universität Hamburg & Hamburg Center for Health Economics).

Zudem wird es wieder Berichte aus den Arbeitsgruppen und Zeit zum gemeinsamen Austausch geben. Hier finden Sie das Programm.

Interessierte können sich bis zum 19. November 2023 per Email direkt an Nadja.Kairies-Schwarz@uni-duesseldorf.de anmelden.

Der 9. dggö Talk findet am Mittwoch, den 8.11.2023 um 17 Uhr statt.

Nikhil Agarwal (MIT) wird über "Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology“ sprechen.

Ein Teil von Nikhil Agarwals Forschung am MIT konzentriert sich auf die Nutzung künstlicher Intelligenz (KI), um die Gesundheitsversorgung und medizinische Entscheidungsfindung zu verbessern. Seine Arbeit untersucht KI-Anwendungen zur Optimierung der Gesundheitsversorgung, der Patientenergebnisse und der Ressourcenzuweisung, wobei ein besonderer Schwerpunkt auf der Beseitigung von Ungleichheiten im Gesundheitswesen liegt.

Nutzen Sie zur Teilnahme bitte den folgenden Link:

https://uni-due.zoom-x.de/j/65312652242?pwd=UVRRaFp1TkF0bjNQMmwwVWFuSElJQT09

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The 9th dggö Talk will take place on Wednesday, November 8th, 2023 at 5 p.m.

Nikhil Agarwal (MIT) will speak on "Combining Human Expertise with Artificial Intelligence: Experimental Evidence from Radiology".

One part of Nikhil Agarwal's research at MIT focuses on leveraging artificial intelligence (AI) to enhance healthcare and medical decision-making. His work explores AI applications in optimizing healthcare delivery, patient outcomes, and resource allocation, with a particular emphasis on addressing healthcare disparities.

To participate, please use the following link

https://uni-due.zoom-x.de/j/65312652242?pwd=UVRRaFp1TkF0bjNQMmwwVWFuSElJQT09

Ab dem 02.10.2023 ist der Call for Papers für die Jahrestagung 2024 in Halle (Saale) unter https://dggoe.de/konferenzen/2024/einreichen eröffnet. Die Einreichung einzelner Abstracts für Vorträge oder Poster sowie organisierter Sitzungen bestehend aus mehreren Vorträgen ist bis zum 15. November 2023 möglich.

Die 16. Jahrestagung der dggö wird am 4. und 5. März 2024 an der Martin-Luther-Universität in Halle an der Saale unter dem Kernthema „Ethik und Ökonomie im Gesundheitssystem“ stattfinden. Zu diesem Thema werden wir Plenarvorträge von Kristina Orfali, Professorin für Bioethik in der Pädiatrie am Columbia Medical Center New York und Daniel M. Hausman, Research Professor an der Rutgers University, hören und hoffen, darüber den interdisziplinären Austausch über die Allokation knapper Ressourcen im Gesundheitssystem weiter anzuregen.

Nähere Informationen zum Tagungsort, Unterkünften, Gebühren und dem Tagungsprogramm finden Sie auf der Konferenzhomepage. Hervorheben möchten wir, dass während der Tagung gegen eine geringe Eigenbeteiligung von 10 Euro/Tag eine professionelle Kinderbetreuung an der Universität Halle bereitgestellt wird. Zur Anmeldung für die Kinderbetreuung senden Sie bitte bis spätestens 10. Januar 2024 eine Email an geschaeftsstelle@dggoe.de

Wir möchten Sie an dieser Stelle auch auf den dggö Wissenschaftspreis aufmerksam machen. Die dggö zeichnet im Rahmen der kommenden Jahrestagung die beste publizierte bzw. zur Publikation angenommene gesundheitsökonomische Arbeit des Jahres 2023 aus. Die Auszeichnung ist mit einem Preisgeld in Höhe von 5.000 € dotiert. Einreichungen sind bis zum 31.12.2023 möglich. Weitere Informationen zu diesem Preis finden Sie hier.

Wir freuen uns auf Ihre Teilnahme an der 16. dggö Jahrestagung in Halle, einen regen akademischen Austausch, spannende Reflexionen aber auch die Gelegenheit, persönliche Kontakte zu pflegen.

Interessierte können sich ab sofort für den Workshop am 17. und 18. November 2023 an der Carl von Ossietzky Universität Oldenburg anmelden. Bitte senden Sie hierzu eine Email bis zum 20. Oktober 2023 an dggoe2023@uni-oldenburg.de.

Das vorläufige Programm des Workshops finden sie hier.