Elgar Fleisch

Title

Prof. Dr.

Last Name

Fleisch

First name

Elgar

elgar.fleisch@unisg.ch

ORCID

0000-0002-4842-1117

Phone

+41 71 224 7241

Web Site

http://www.item.unisg.ch

http://www.im.ethz.ch/

Now showing 1 - 10 of 478

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Blockchain for the IoT: Privacy-Preserving Protection of Sensor Data
(Assoc. of Information Systems)
Chanson, Mathieu
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Bogner, Andreas
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Bilgeri, Dominik
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Fleisch, Elgar
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Wortmann, Felix
A constantly growing pool of smart, connected Internet of Things (IoT) devices poses completely new challenges for business regarding security and privacy. In fact, the widespread adoption of smart products might depend on the ability of organizations to offer systems that ensure adequate sensor data integrity while guaranteeing sufficient user privacy. In light of these challenges, previous research indicates that blockchain technology may be a promising means to mitigate issues of data security arising in the IoT. Building upon the existing body of knowledge, we propose a design theory, including requirements, design principles, and features, for a blockchain-based sensor data protection system (SDPS) that leverages data certification. We then design and develop an instantiation of an SDPS (CertifiCar) in three iterative cycles that prevents the fraudulent manipulation of car mileage data. Furthermore, we provide an ex-post evaluation of our design theory considering CertifiCar and two additional use cases in the realm of pharmaceutical supply chains and energy microgrids. The evaluation results suggest that the proposed design ensures the tamper-resistant gathering, processing, and exchange of IoT sensor data in a privacy-preserving, scalable, and efficient manner.
Type:journal article
Journal:Journal of the Association for Information Systems
Volume:Vol. 20, Issue 9
Issue:Article 10
DOI:10.17705/1jais.00567
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/116717
Scopus© Citations 160
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Development, Deployment, and Evaluation of DyMand: Wearable AI for In-Situ Detection and Capture of Couples’ Dyadic Interactions in Chronic Disease Management
(Association for Computing Machinery (ACM), 2026-07-24)
Boateng, George
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Santhanam, Prabhakaran
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Elgar Fleisch
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Lüscher, Janina
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Pauly, Theresa
Dyadic interactions of couples are of interest as they provide insight into relationship quality and chronic disease management. Existing sensing systems primarily infer social structure within groups retrospectively, or capture couples’ interactions at random or scheduled times, which could miss meaningful interpersonal interactions between partners. In this work, we developed a smartwatch-based algorithm that detects interaction moments between partners and enables interaction-aware data capture in everyday settings. It uses the Bluetooth signal strength between two smartwatches, each worn by one partner, and a voice activity detection machine-learning model that we trained, to infer that the partners are interacting and then trigger data collection. We operationalized this sensing approach by developing, deploying, and evaluating DyMand, an open-source smartwatch and smartphone system that integrates multimodal sensor and self-report data collection in situ. We deployed the DyMand system in a 7-day field study and collected and analyzed data about social support and diabetes discussions from 13 (N=26) Swiss-based heterosexual couples managing diabetes mellitus type 2 of one partner. Our system evaluation showed that 77.6% of algorithm-triggered recordings contained partners’ conversation moments compared to 43.8% for scheduled triggers, and that DyMand was easy to use. Preliminary insights into disease management behavior revealed that 5.2% of couples’ conversation moments contained social support, and partners discussed diabetes management 2.4% of the time based on the audio data analyses. In contrast, the self-report data showed that patients received support in 67.7% of couples’ interactions and caregivers provided support in 71.8% of couples’ interactions. DyMand enables insights into dyadic behavior in-situ, and could be used by social, clinical, or health psychology researchers to understand the social dynamics of couples that are managing chronic diseases in everyday life to inform the development and delivery of behavioral interventions.
Type:journal article
Journal:ACM Transactions on Computing for Healthcare
DOI:10.1145/3833380
URI:https://alexandria.unisg.ch/handle/20.500.14171/133092
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Structured Large Language Model Workflows for Motivational Interviewing in Health Behavior Change: Proof-of-Concept Study
(JMIR Publications, 2026-07-06)
Shenoi, Akshaye
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Li, Tianze
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Jabir, Ahmad Ishqi
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Pitkethly, Amanda
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Elgar Fleisch
Background Motivational interviewing (MI) is an effective approach for supporting health behaviorchange, but face-to-face delivery is resource-intensive and difficult to scale. Rule-based conversational agents (CAs) can improve access; however, their scripted interactions and limited language flexibility constrain MI delivery. While large language models (LLMs) are increasingly being used for MI coaching, their conversational fidelity and quality compared with human coaches and rule-based CAs remain understudied. Objective This study aimed to describe the development of an LLM-based CA, Artificially Intelligent Motivational Interviewing (Aimi), orchestrated with structured workflows, and to evaluate its feasibility, conversational fidelity, and user perceptions during MI coaching interactions. Methods We developed Aimi using structured LLM workflows designed to enhance MI fidelity. We conducted a within-participants study, where 18 adults interacted with (1) Aimi, (2) a novice MI-trained human coach, and (3) a rule-based CA during live text-based role-play coaching sessions. Transcripts were independently evaluated by an MI expert using the Motivational Interviewing Skill Code, Version 2.0 (MISC-2), to assess MI competency and fidelity. Participants completed a user experience questionnaire to provide general feedback and to assess session alliance, dialogue relevance, empathy, engagement, linguistic quality, and perceived motivation to change. Feedback from users was thematically summarized and categorized under strengths and weaknesses for each approach. Results Aimi achieved fidelity scores comparable to those of the novice human coach and higher than those of the rule-based CA on summary metrics, including higher reflection-to-question ratios (median 0.84, IQR 0.62-0.92 vs 0.62, IQR 0.42-0.74 vs 0.25, IQR 0.17-0.38), more complex reflections (median 66.67%, IQR 46.97%-76.92% vs 50%, IQR 34.38%-61.88% vs 0.00%, IQR 0%-50%), and greater elicitation of client change talk (median 90.83%, IQR 85.89%-100% vs 73.21%, IQR 63.10%-83.19% vs 66.67%, IQR 57.86%-81.94%). User experience ratings showed no significant differences across conditions. User feedback revealed distinct strengths and limitations across the coaching interactions. Participants described Aimi’s interactions as personalized, fluid, and adaptive, though sometimes overly reflective and lengthy. The novice human coach was viewed as empathetic and supportive but slow to respond, whereas the rule-based coach was viewed as efficient and structured yet limited in depth and personalization. Conclusions This study demonstrates the technical feasibility of structured LLM-workflows for MI coaching and their capacity to maintain conversational fidelity comparable to that of a novice MI-trained human coach. Given the role-play paradigm, single-rater coding, and small convenience sample, these comparative findings should be interpreted as exploratory. Our findings serve as a foundational baseline for the development of scalable behavior change interventions in clinical settings.
Type:journal article
Journal:JMIR Formative Research
Volume:10
DOI:10.2196/94036
URI:https://alexandria.unisg.ch/handle/20.500.14171/131145
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Early health technology assessment of digital diabetes screening in Switzerland: cost-effectiveness and budget impact analyses
(2026-02-11)
Wasu Mekniran
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Victoria Brügger
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Magdalena Fuchs
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Qiuhan Jin
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Benjamin Wirth
Objectives Digital biomarkers offer scalable screening for type 2 diabetes, yet adoption is stalled by uncertainty regarding economic viability. This study evaluates the cost-effectiveness and budget impact of digital screening compared to opportunistic screening from a Swiss payer perspective. Methods A probabilistic Markov cohort model was developed to simulate at-risk Swiss adults (age ≥45, BMI ≥25 kg/m²) over a 40-year horizon. The model incorporates a digital attrition parameter, inputs derived from Swiss-specific sources (e.g., the CoLaus study and FSO life tables), and statutory tariffs. Costs and outcomes were discounted at 3.0%. Results In the deterministic base-case, digital screening yielded an incremental cost-effectiveness ratio of CHF 2,912 per quality-adjusted life-year gained. Probabilistic sensitivity analysis indicated a 93.2% probability of cost-effectiveness at the CHF 50,000 threshold. The budget impact analysis estimated a Year 1 gross investment budget of CHF 27 million to identify prevalent cases, followed by long-term savings from averted complications. Conclusions Digital screening can be highly cost-effective in Switzerland. While the required Year 1 gross investment poses a liquidity challenge, reimbursement via pathway-oriented models under the Swiss tariff could align incentives with long-term complication avoidance.
Type:journal article
Journal:MedRxiv
URL:https://www.medrxiv.org/content/10.64898/2026.02.10.26345992v1
DOI:10.64898/2026.02.10.26345992
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/125108
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Digital health technologies and stakeholder incentives in type-2 diabetes prevention
(Sage, 2026-03-12)
Wasu Mekniran
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Wilma Diethelm
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Victoire Stalder
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Elgar Fleisch
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Tobias Kowatsch
Background Type-2 diabetes (T2D) is largely preventable through sustained lifestyle change, yet healthcare systems face challenges in implementing and sustaining lifestyle interventions at scale. Digital health technologies (DHTs), offering personalized risk assessments, remote monitoring, and behavior change support, may support T2D prevention. However, the systemic role of DHTs within the T2D prevention ecosystem remains poorly understood. This study examines (RQ1) What stakeholder incentives are associated with prevention engagement among payers, providers, and individuals? (RQ2) What incentive patterns are associated with DHT adoption in T2D prevention? (RQ3) How is DHT adoption associated with value exchange among stakeholders in the T2D prevention ecosystem? Methods We conducted a systematic literature review to identify existing incentives in preventive care (RQ1). Business model data from leading DHT companies in T2D prevention (via PitchBook and Crunchbase) were analyzed to examine emerging incentive patterns (RQ2). We conducted expert interviews (N = 26) and synthesized findings using the e3-value framework to map stakeholder relationships (RQ3). Results Our findings show that financial and non-financial incentives for prevention are often temporally misaligned. Engagement in lifestyle-based prevention is linked to short-term rewards, health, and convenience benefits for individuals and long-term cost savings for payers. DHT adoption for T2D prevention is associated with three key patterns: enhancing personalization and convenience for individuals, supporting value-based payment models for payers, and improving workflow efficiency for providers. Conclusions DHTs may help align stakeholder incentives by promoting (1) sustained engagement in lifestyle prevention programs (i.e., continuous glucose monitoring with real-time dietary or activity feedback) and providing individuals with micro-rewards (i.e., for behavior change and improved clinical outcomes). These coordinated feedback loops could be embedded within (2) outcome-based reimbursements for payers and linked to (3) automated workflows to improve provider efficiency (i.e., risk stratification). Realizing this potential requires updated reimbursement models, integrated stakeholder coordination, and supportive policy frameworks.
Type:journal article
Journal:DIGITAL HEALTH
Volume:12
URL:https://journals.sagepub.com/doi/10.1177/20552076261425402
DOI:10.1177/20552076261425402
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/125276
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Nutrition Info and Other Front-of-Package Labels and Simulated Food and Beverage Purchases
(American Medical Association (AMA), 2025-10-17)
Anna H. Grummon
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Kevin O’Sullivan
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Joshua Petimar
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Cristina J. Y. Lee
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Amanda B. Zeitlin
Importance In January 2025, the US Food and Drug Administration (FDA) released a proposed rule to require front-of-package nutrition information (Nutrition Info) labels that would signal when packaged foods contain low, medium, or high levels of saturated fat, sodium, or added sugars (ie, nutrients of concern). However, it is unknown whether this labeling system would encourage healthier food and beverage purchases. Objectives To test whether Nutrition Info labels similar to those proposed by the FDA could lead to healthier food and beverage purchases compared with other existing or proposed labeling systems. Design, Setting, and Participants This randomized clinical trial was conducted online from October 31 to November 21, 2024. Participants included a national sample of US adults who reported being their household’s primary shopper. Data were analyzed from November 26, 2024, to August 27, 2025. Intervention Participants were randomized to exposure to 1 of 6 front-of-package labeling systems: positive labels (ie, labels that communicate only the positive attributes of a food) only, Nutrition Info labels (similar to the FDA’s proposal), positive plus Nutrition Info labels, “High In” labels (similar to designs the FDA tested to signal when products contain high levels of nutrients of concern), positive plus High In labels, or spectrum labels (similar to designs used internationally rating products from least to most healthy). Main Outcomes and Measures Participants shopped for foods and beverages in a large, simulated online grocery store. The primary outcome was healthfulness of participants’ food and beverage selections, assessed using the United Kingdom’s Ofcom Nutrient Profiling Model scores (ranging from 0 to 100, with higher scores indicating healthier choices). Scores were compared between groups using the average differential effect (ADE). Results A total of 5636 participants completed the trial (3400 [60%] women; mean [SD] age, 40.3 [12.6] years). The spectrum labels led to healthier purchases compared with both the positive labels only (ADE, 2.42; 95% CI, 1.66-3.17; P &lt; .001) and all other labeling systems (range of ADEs, −1.87 [95% CI, −2.63 to −1.11] to −2.45 [95% CI, −3.21 to −1.69]; P &lt; .001). By contrast, the Nutrition Info, positive plus Nutrition Info, High In, and positive plus High In labels did not lead to healthier purchases compared with the positive labels only (range of ADEs, −0.04 [95% CI, −0.80 to 0.72; P = .92] to 0.54 [95% CI, −0.22 to 1.30; P = .16]). Label effects did not differ by nutrition literacy, household income, or educational attainment. Conclusions and Relevance In this randomized clinical trial of food labeling systems, spectrum labels that rate foods from least to most healthy led to healthier purchases than positive labels and Nutrition Info labels similar to those proposed by the FDA. These findings suggest that spectrum labels may be more promising than both existing positive labels and the FDA’s proposed labels for promoting healthier food purchases. Trial Registration ClinicalTrials.gov Identifier: NCT06516627
Type:journal article
Journal:JAMA Network Open
Volume:8
Issue:10
DOI:10.1001/jamanetworkopen.2025.37389
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/124698
Scopus© Citations 8
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Feasibility of the LvL UP digital lifestyle coaching intervention designed to prevent non-communicable diseases and common mental disorders
(Springer Science and Business Media LLC, 2025-12-22)
Jacqueline L. Mair
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Ahmad I. Jabir
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Alicia Salamanca-Sanabria
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Oscar Castro
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Shenglin Zheng
LvL UP is a smartphone-based lifestyle coaching intervention aimed at improving health behaviours, mental well-being, and preventing noncommunicable diseases and common mental disorders. It features a ‘talk and tools’ approach, combining automated health literacy coaching via conversational agent with digital tools such as journaling, life hacks, and slow-paced breathing exercises. An ‘in-the-wild’ mixed-methods study was conducted in Singapore to evaluate LvL UP’s feasibility and acceptability to inform a future definitive trial. The app was available on iOS and Android from March to August 2023 and was promoted through online and offline strategies. Data collection included in-app surveys, usage metrics, and interviews, summarised using descriptive statistics and template analysis. The app was downloaded 307 times. Data from 99 active users were analysed. Most users were female and aged 21–35 years with mild to moderate vulnerabilities in physical activity, diet, and depressive symptoms. Engagement was highest during the first eight days, with 9% remaining engaged for up to 50 days. Users rated technology acceptance highly, finding the app enjoyable, easy to use, and informative. Suggested improvements included streamlined onboarding, fixing bugs, shortening dialogues, and adding rewards. The findings support LvL UP’s feasibility and have informed enhancements for future trials.
Type:journal article
Journal:Scientific Reports
DOI:10.1038/s41598-025-30960-z
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/124784
Scopus© Citations 1
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A single specific and actionable swap recommendation can lead to substantial reductions in households’ dietary carbon footprints
(Elsevier BV, 2025-10)
Kevin O'Sullivan
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Verena Tiefenbeck
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Matthias Stucki
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Sebastian Bradford
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Klaus Ludwig Fuchs
Dietary change can lower environmental impacts, yet current guidance can still lack the specific, actionable instructions to prompt actual behaviour change. We use household food purchase data collected via the loyalty program of a major Swiss retailer (N = 347 households; 713,645 purchases; 73,662 baskets) to identify and simulate dietary change strategies that provide specific and actionable product swap recommendations to households based on their real-world purchasing behaviours. Assuming complete acceptance of swap recommendations to determine the maximum carbon emissions reduction potential, our simulations show that households could cut the carbon emissions of their food purchases by 26 % by swapping just one animal product for its plant-based alternative per shopping trip, representing two-thirds of the total potential reduction from replacing all animal product purchases (40 %). Alternatively, swapping a single food category (e.g. pork meat), personalised according to their historic purchases, leads to an average reduction of 15 %. These findings suggest that existing retailer infrastructure can be utilised to provide consumers with specific and actionable recommendations, personalised according to their past purchases or delivered in real-time, to meaningfully lower their carbon emissions.
Type:journal article
Journal:Journal of Cleaner Production
Volume:526
DOI:10.1016/j.jclepro.2025.146577
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/124697
Scopus© Citations 1
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Barriers and facilitators of implementing value-based care: The case of SwissDiabeter
(Sage Publications, 2025-05-06)
Odile-Florence Giger
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Elgar Fleisch
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Tobias Kowatsch
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Jovanova, Mia
Objective Global spending on diabetes care soared to $966 billion in 2021, a 316% surge over the past 15 years. This sharp increase underscores a need for more efficient and cost-effective care strategies. Value-based care (VBC), which prioritizes patient outcomes while controlling expenses, presents a promising solution. However, its real-world implementation remains challenging, particularly in diabetes care. This study examines SwissDiabeter, a proposed diabetes clinic initiative in Switzerland inspired by a Dutch VBC-based Diabeter clinic. We examine key barriers and facilitators during Diabeter's implementation in the Netherlands and assess forthcoming challenges and enablers for SwissDiabeter in Switzerland. Methods We employ a deep, extensive embedded single-case design conducting 27 interviews with healthcare professionals, insurers, and patient groups in Switzerland and the Netherlands. The main interview data were complemented by various secondary sources to enhance contextual comprehension, widen perspectives, and validate findings. Results We identify four key factors for successful VBC adoption: leadership in driving change, financial restructuring, operational improvements, and enabling digital technologies. We next derive practical recommendations to guide the implementation of value-based diabetes care, redesigning financial incentives for healthcare providers, partnering up with key stakeholders such as insurers or policy makers, and measuring outcomes on a voluntary and anonymous basis. Conclusion This study enhances the global discourse on VBC by analyzing key barriers and facilitators in implementing SwissDiabeter, drawing insights from the Diabeter model in the Netherlands. Our findings highlight the need for strong leadership, financial incentives, digital infrastructure, and interdisciplinary collaboration to drive outcome-driven care. Beyond diabetes, these insights provide a framework for scaling VBC across chronic disease management, promoting cost-effective, high-quality healthcare.
Type:journal article
Journal:Digital Health
Volume:11
DOI:10.1177/20552076251336322
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/122902
Scopus© Citations 4
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Digital health technologies and innovation patterns in diabetes ecosystems
(SAGE Publications, 2025-01)
Odile-Florence Giger
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Estelle Pfitzer
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Wasu Mekniran
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Hannes Gebhardt
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Elgar Fleisch
Background The global rise in type-2 diabetes (T2D) has prompted the development of new digital technologies for diabetes management. However, despite the proliferation of digital health companies for T2D care, scaling their solutions remains a critical challenge. This study investigates the digital transformation of T2D ecosystems and seeks to identify key innovation patterns. We examine: (1) What are emerging organizations in digital diabetes ecosystems? (2) What are the value streams in digital T2D ecosystems? (3) Which innovation patterns are present in digital T2D ecosystems? Methods We conducted a literature review and market analysis to characterize organizations and value streams in T2D ecosystems, pre- and post-digital transformation. We used the e3-value methodology to visualize T2D ecosystems (RQ1 and RQ2) and conducted expert interviews to identify emerging innovation patterns in digital diabetes ecosystems (RQ3). Results Our analyses revealed the emergence of eight organization segments in digital diabetes ecosystems: real-world evidence analytics, healthcare management platforms, clinical decision support, diagnostic and monitoring, digital therapeutics, wellness, online community, and online pharmacy (RQ1). Visualizing the value streams among these organizations highlights the crucial importance of individual health data (RQ2). Furthermore, our analysis revealed four major innovation patterns within the digital diabetes ecosystem: open ecosystem strategies, outcome-based payment models, platformization, and user-centric software (RQ3). Conclusions Our findings illustrate the transition from traditional value chains in T2D care to platform-based and outcome-oriented models. These innovation patterns can inform strategic decisions for companies and healthcare providers, potentially helping anticipate new digital trends in diabetes care and across other chronic disease ecosystems.
Type:journal article
Journal:DIGITAL HEALTH
Volume:11
DOI:10.1177/20552076241311740
URI:https://www.alexandria.unisg.ch/handle/20.500.14171/121937
Scopus© Citations 12

Elgar Fleisch

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