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Building Digital Bridges to connect you to your Audiences Digi-Bridges can help!

In today’s world, digital media have revolutionized marketing and communication for people and businesses alike. A foundational piece of your business’ success became the efficient integration of well thought out Digital Marketing and Social Media strategies and tactics. Book us for an initial consultation to discuss how we can address your specific needs.

25/02/2026

2025 was a defining year for digital health. Reading this piece, I am struck by how clearly 2026 will test whether data driven health businesses can balance innovation and regulation.

On one hand, hyper personalisation is no longer aspirational. AI driven decision support is moving tailored care into the mainstream. The direction of travel is obvious. Patients increasingly expect proactive, personalised and seamless digital services.

On the other hand, the regulatory environment is crystallising fast. The European Health Data Space Regulation, the EU AI Act, updated ICO guidance, and the UK Data Use and Access Act 2025 all signal the same message. AI in health is welcome, but only with robust governance, interoperability standards, clear lawful bases, and demonstrable operational readiness.

What I find particularly interesting is the growing clarity around pseudonymisation and secondary use. The relative approach confirmed by the CJEU, alongside updated UK guidance, opens meaningful opportunities for research and AI training. But it also raises the bar on governance. Claims that data is no longer personal must be backed by rigorous risk assessment and technical safeguards.

The tension is clear. Data is the engine of hyper personalised care and scalable AI. Yet it is also the primary source of legal, ethical and reputational risk. Competitive advantage in 2026 will not come from AI capability alone. It will come from embedding compliance, transparency and interoperability into product design from day one.

For digital health leaders, the question is no longer whether to invest in AI and data infrastructure. It is whether their governance models are mature enough to sustain trust at scale.

https://www.osborneclarke.com/insights/data-driven-digital-health-businesses-challenged-balancing-ai-advances-and-tighter

19/02/2026

This new report from Graphite Digital should make pharma pause.

65% of clinicians say they have reduced or stopped engaging with pharma companies because of poor digital experiences. More than a third say digital interactions now shape their perception of a company as much as, or more than, in-person meetings.
That is a big shift.

The message from 225 senior clinicians across the UK, US and Germany is surprisingly clear and consistent. The problem is not digital per se. It is irrelevance, overload and friction.

52% say they receive too many messages. The same proportion find communications overly promotional and not useful enough. 58% feel most digital content is repetitive or irrelevant. Many would rather search for information themselves when they need it.
Three themes stand out: relevance, utility and experience.

Clinicians want practical, evidence-based content that supports real clinical tasks. They value tools for exploring treatment options, professional development resources, patient education materials and adherence support. They want concise summaries with the option to go deeper. And they expect fast, simple access with no unnecessary barriers or technical glitches.

This is more than a UX issue. It is a trust issue.

If digital becomes synonymous with hard sells and noise, it undermines credibility. If it becomes a frictionless source of high-quality, objective and clinically relevant information, it can strengthen relationships.

In a world where clinicians are time poor and digitally fluent, pharma digital strategy can no longer be volume driven. It needs to be value driven.

Less push. More pull. Less promotion. More evidence.

https://www.healthtechdigital.com/poor-digital-experiences-drive-65-of-clinicians-away-from-pharma-companies/

17/02/2026

A new study from the University of Oxford raises an important red flag about using AI chatbots for medical advice.

In a simulated experiment, people who used AI to interpret symptoms such as severe headache or postnatal exhaustion received a mix of accurate and misleading responses. Many struggled to know what to ask, and small changes in wording led to different answers. When chatbots offered several possible conditions, users were left guessing which one applied to them and whether they should see a GP or go to A&E.

This matters. More than a third of UK residents reportedly use AI for mental health or wellbeing support. The appeal is obvious: instant access, no waiting room, no judgment. But this study highlights a key challenge. AI may provide information, yet that does not automatically translate into actionable, safe advice.

There is also a deeper issue. AI systems are trained on existing medical data, which means they can reproduce long-standing biases and gaps in care. And while clinicians are not perfect either, they operate within professional, ethical and legal frameworks that chatbots currently do not.

Health-dedicated AI tools are emerging, and they may perform better than general chatbots. But improvement alone is not enough. We need robust evaluation, regulatory guardrails and clear communication about what these systems can and cannot do.

AI can support health literacy. It should not quietly replace clinical judgment.

https://www.bbc.com/news/articles/c3093gjy2ero

03/02/2026

AI in cardiology is no longer a future promise, it is already shaping daily practice. What stands out in this piece is the emphasis on responsibility alongside innovation.

The European Society of Cardiology makes a clear case that better algorithms alone are not enough. Safe and meaningful AI in cardiology depends on data quality, shared evaluation frameworks, and close collaboration between clinicians, researchers, regulators, and policymakers. Without this, even the most advanced tools risk being unreliable or misaligned with real clinical needs.

I appreciate the strong focus on governance. Europe’s regulatory momentum, from AI regulation to the European Health Data Space, creates opportunity, but also leaves open questions around liability, validation, and accountability. Scientific societies stepping in to bridge evidence, practice, and policy feels not just helpful, but necessary.

If AI is to really empower clinicians and improve cardiovascular outcomes, it must be built on high-quality data, transparent methods, and continuous dialogue across disciplines. Innovation is moving fast, but trust and safety still need careful, collective work.

https://www.escardio.org/public-health/priorities/responsible-ai--digital-health-new/

31/01/2026

After ChatGPT Health, both Anthropic and Google have now launched healthcare-specific AI tools. Claude for Healthcare focuses on helping patients and clinicians make sense of records, lab results and trends, while Google’s MedGemma expands into advanced imaging like CT, MRI and pathology. The promise is familiar: better understanding, better preparation, and more efficient care.

But the timing is telling. Google has already had to pull back some AI health summaries after safety concerns, and regulators are openly warning that these tools are not ready to replace professional medical advice. That tension is hard to ignore. We are seeing rapid capability growth, but governance, validation and accountability are still catching up.

What feels increasingly clear is that the near-term future is not AI replacing healthcare professionals, but AI reshaping how patients prepare, how clinicians work, and how data is interpreted. Whether this becomes empowering or risky will depend less on the models themselves and more on how responsibly they are deployed, regulated and integrated into real clinical workflows.

https://www.digitalhealth.net/2026/01/anthropic-and-google-follow-chatgpt-to-launch-healthcare-ai/

26/01/2026

The FDA has shifted the goalposts for digital health and AI.

With updated guidance on Clinical Decision Support and General Wellness products, the agency is trying to reduce friction for low-risk AI and wearable technologies, while signaling a broader rethink of how regulation should keep pace with innovation. Non-invasive wearables measuring things like blood pressure or glucose may now sit outside active FDA oversight if marketed strictly for wellness, and CDS tools that offer single recommendations or risk scores are no longer automatically treated as regulated devices.

This responds to long-standing industry concerns about overregulation and innovation being pushed into artificial constraints. At the same time, it raises an important tension: moving faster and regulating less only works if safety, validation, and accountability are not treated as optional extras. Shifting oversight downstream makes post-market evidence, transparency, and responsible deployment even more critical.

The FDA’s message: less paternalism, more trust in clinicians, and smarter oversight rather than blanket control. The real test will be whether this balance between innovation and patient safety holds once these tools are widely deployed in everyday care.

https://tinyurl.com/5e74mdd5

12/01/2026

Less than two years after closing its physical health clinics, Walmart is back in healthcare with a very different strategy. Its new Better Care Services platform bundles telehealth, urgent care, behavioral health and nutrition guidance into a single digital experience, tightly linked to pharmacy, grocery and delivery.

This feels like a more Walmart-native approach. Instead of running clinics, the company is leaning into what it does best: scale, convenience, price and logistics. Telehealth visits flow directly into prescriptions, OTC purchases and nutrition choices, all reinforced by delivery perks and in-store touchpoints like its nationwide Wellness Events.

The integration of AI-driven nutrition recommendations is particularly telling. By connecting food baskets, health signals and care access, Walmart is blurring the line between retail and healthcare in ways few others can replicate. For CPG brands and health systems alike, this creates both opportunity and pressure.

At the same time, the big question remains impact. Convenience and affordability are powerful, but coordinating quality, continuity and accountability across third-party providers is not trivial. Walmart may not be delivering care directly, but it is shaping how people access it.

This move suggests the future of consumer health may look less like clinics and more like platforms, where healthcare quietly sits inside everyday retail journeys.

https://tinyurl.com/3a98fhka

31/12/2025

The FDA is piloting a new approach to digital health regulation with TEMPO, a voluntary program that allows certain chronic care digital devices to be used in reimbursed care before traditional premarket authorization. In return, manufacturers must share real-world data to support ongoing FDA assessment.

On the one hand, this is a meaningful shift. By linking earlier access with real-world evidence generation, the FDA is acknowledging that innovation in digital health does not always fit neatly into existing regulatory pathways. It could lower barriers for smaller players and speed access to tools that support people living with chronic conditions.

On the other hand, it raises important questions. Relying on post-market data places more weight on real-world monitoring, governance, and enforcement. The success of this model will depend on how rigorously safety and performance are tracked, and how clearly expectations are set for eventual authorization.

TEMPO signals a move toward more adaptive regulation, aligned with value-based care models from Center for Medicare and Medicaid Innovation. If done well, it could balance innovation with patient protection. If not, it risks creating uneven standards across the digital health landscape.

https://tinyurl.com/ynn8uzju

29/12/2025

We often talk about FOMO, fear of missing out. But this article introduces a quieter and arguably more consequential phenomenon: FOFO, the fear of finding out.

FOFO helps explain why so many people delay or avoid routine health screenings, even when they know these tests can be lifesaving. Recent surveys suggest screening rates are falling, driven less by access and more by anxiety, embarrassment, or fear of bad news. Avoidance becomes a way to regain a sense of control, even if only temporarily.

What struck me is how human this is. In the short term, not knowing feels safer. In the long term, it often carries far greater risk. FOFO is not about ignorance but about anxiety, past experiences with healthcare, shame, or fear of being forced into difficult decisions.

This also has implications for how we design care and digital health tools. If fear of results keeps people away, better reminders or more data will not solve the problem on their own. We need more empathetic communication, shorter waiting times, psychological safety, and support that acknowledges fear rather than dismissing it.

Prevention only works if people feel able to engage with it. Addressing FOFO may be just as important as improving access to screening itself.

https://tinyurl.com/26k98srx

26/12/2025

As AI becomes part of everyday healthcare, one question remains surprisingly unanswered across much of Europe: who is responsible when AI gets it wrong?

A new WHO Europe report shows that only a handful of countries have any standards to determine liability for AI-related harm in healthcare, and just one fully meets WHO criteria. This gap is striking given that most countries are already using AI for diagnostics and patient-facing tools.

The risk is not hypothetical. Without clear rules, clinicians may hesitate to use AI out of fear of legal consequences, or rely on it too heavily assuming responsibility lies elsewhere. Both scenarios can undermine patient safety. The challenge is that AI does not fit neatly into existing legal frameworks. Responsibility is often shared across developers, healthcare organisations and clinicians, and adaptive systems make it harder to trace decisions back to a single actor.

This is less a technical problem and more a governance one. Many countries have AI strategies, but far fewer have invested in the legal and accountability structures needed to support safe adoption. The EU AI Act will help, but meaningful rules for high-risk health AI are still years away.

Until then, accountability will remain uneven and highly local. If AI is to earn trust in clinical care, clarity on responsibility, transparency and human oversight must catch up with deployment. Otherwise, we risk scaling innovation without the safeguards patients and professionals need.

https://tinyurl.com/23fc8fc4

19/12/2025

New research adds an important nuance to the AI scribe conversation: The study suggests that ambient listening alone is not enough. When patient history is added to the scribing process, documentation quality improves meaningfully, with completeness scores more than doubling in chronic care scenarios.

This should not come as a surprise. Clinicians rarely verbalise lab values, trends or comorbidities during a visit, yet these details are essential for care quality, continuity and reimbursement. Without context from the record, AI scribes risk producing clean notes that still miss what matters most.

AI scribes can reduce documentation burden, but only if they are deeply integrated with clinical data and workflows. Pulling structured history from EHRs is technically and operationally hard, but this study suggests it is also non negotiable for real clinical value.

As more vendors move toward context aware scribing, buyers will need to ask harder questions about data access, interoperability and how historical information is blended into notes. Efficiency gains are useful, but accuracy, completeness and clinical relevance are what ultimately determine impact.

https://tinyurl.com/46f8zjj6

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