Reveles’ Post

One-Size-Fits-All Approaches Miss the Mark: Traditional healthcare engagement strategies often rely on broad demographic categories like age, gender, or ethnicity. These methods assume homogeneity within these groups, failing to account for the individual variations in lifestyle, cultural background, and health needs. As a result, many patients feel unseen and unheard, leading to disengagement and lower participation rates. We excited about the infinity potential of our new Generative AI solutions, Personali™. 🤫👏🏽👊🏽 More to come in 2025! Have a wonderful holiday season! #personali #personalizedengagement #beyonddemographics

The last days have been a bit emotional but also gave me the opportunity to connect once again with friends and many good ex-colleagues. In one of those discussions, I was advised to switch off during the summer time to recharge my batteries. Therefore, I excuse myself in advance of not being daily present in the coming weeks, but I will try my best to find the right balance between having some private time and time together. Such introduction does not have many learnings, but it is still a way to bridge to our next topic on #Insights. “The value of an insight is the ability to capture & respond to learnings based on data, facts, & observations from sources beyond the organisation.” Such sources can be: - #MedicalField, collects insights via their external-phasing role & engagement with HCPs and/or patient associations. - #MedicalInformation remains the biggest source of insights & their quantification via #NLP / #AI technology unlocks hidden trends. - #AdvisoryBoards with participation of HCPs, patients or any other external stakeholders are helping to understand HCPs decisions, the use of #RWE in daily clinical practice, etc. - #SocialListening help in the characterisation of patients’ journey, capture patients’ experience & any barriers related to patient care. Furthermore, social listening can be used in a longitudinal way looking for shifts in opinions. - #LiteratureSearch remains one of the cornerstones in the development of strategy by capturing competitors’ data & in the characterisation of products’ safety. - #Surveys conducted with participation of HCPs, Payers, etc. allow quick collection of insights, while we should be mindful on any unintentional bias. - #RWE is considered as a separate source of insights through the collection of #RWD. Such knowledge can be used to inform HCPs, regulators & payers’ decisions, trial designs, etc. However, in my opinion RWE includes all above, since everything is related to the real life. For last, I kept one of the most known pain points, that is hearing on the name “silos”. Quite often there are parallel activities on insights collection organised by different functions. Such an example is field force insights processed by #Commercial, AbBoards & Literature Search organised by #RWE, #HEOR, or #MedicalAffairs, patient surveys executed by #PatientAdvocacy, etc. Since all these insights are utilised in the development of the brand strategy and #IntegratedEvidencePlan, it is advisable that there is a strong cross-functional mindset during their collection and managment process. Furthermore, knowing the reasons that insights are collected, but also how will be used in practice, “ensures that insights have purpose and create direction, rather than simply existing to exist.” Disclaimer: The content is inspired by the book of Medical Affairs Professional Society “Medical Affairs (2024)”. The opinions shared are solely my own and do not express the views or opinions of any of my employers.

Can artificial intelligence help deliver #HealthForAll? With representatives from governments, schools, healthcare, and tech companies, as well as human and civil rights groups, #TeamBayer recently took part in the #UnitedNations Population Fund’s Global Dialogue on Technology. Here, they discussed the transformative power – and critical challenges – of #AI in promoting global population health and well-being. Learn from Franziska Lobig how #BayerInRadiology for example is exploring new ways to deliver unbiased, accessible #AI solutions matching the UN's Sustainable Development Goals (SDGs): http://spr.ly/6043gLvbU

Addressing Global Disparities in AI-Enabled Clinical Studies Bowhead Health is committed to bridging the gap in global health equity highlighted in a recent npj Digital Medicine article by Rui Yang et al. The study, published by Nature Magazine, reveals significant geo-economic and gender disparities in 159 AI-enabled clinical studies, spotlighting the pressing need for more equitable research methodologies. Key findings show a concentration of studies in high-income countries, with North America, Europe, and East Asia leading. Alarmingly, only a fraction of research includes lower-income regions, which may lead to healthcare solutions that are less effective for diverse global populations. Moreover, gender disparities persist, with few studies achieving a balanced representation of male and female participants, potentially influencing the effectiveness of medical AI applications across different demographics. At Bowhead Health, we advocate for: 1) Inclusive research that involves diverse groups to ensure AI tools are effective for all populations. 2) Expansion of international multicenter studies to include more lower-income countries, helping to tailor AI applications to varied healthcare systems and needs. Discover more about how AI can be developed equitably to benefit global health: https://lnkd.in/dk9YcwWF #AIinHealthcare #HealthEquity #GlobalHealth #BowheadHealth

Biden Backs AI for Women’s Health. The inclusion of women & minorities in clinical research funded by the National Institutes of Health wasn’t required by law until 1993. A 2020 study from The University of Chicago Pritzker School of Medicine and University of California, Berkeley found that women are widely overmedicated and disproportionately subject to side effects, due to the lack of women in clinical drug studies. Hopefully, there is movement to change that. In an executive order from Monday (18th March), Joe Biden’s administration presses federal agencies to expand and prioritise research on women’s health, using technology, such as AI. The executive order: -Builds on an initiative on women’s health research launched by The White House in 2023 led by Jill Biden.  -Also includes directions for U.S. Department of Health and Human Services (HHS) and the National Science Foundation (NSF) to consider using AI to advance research on women’s health. -Was accompanied by a range of actions & commitments from agencies to close research gaps. This acknowledgement of existing gaps & press for U.S federal agencies is of course positive, but there must be a fundamental shift in how we approach, design, evaluate trials to ensure a diverse population is studied & evaluated. Hopefully AI can help with that shift. #womenshealth #biden #healthcareai #clinicaltrialdiversity #healthai https://lnkd.in/eu9-3ZEe

Are traditional patient recruitment methods holding your clinical trials back? With AI-driven behavioral profiling, patient matching is no longer just about eligibility—it’s about finding participants who are behaviorally aligned for better engagement and retention. Check out our latest BEKblog to learn more. #clinicaltrials #patientrecruitment #AI #pharma

MIT News reporter Adam Zewe covers a recent work from Shomik J., Kathleen Creel, and MIT Jameel Clinic - AI & Health PI Ashia Wilson that highlights the weaknesses in traditional notions of algorithmic fairness, from companies screening resumes to choose job interview candidates or aiding hospitals in ranking kidney transplant patients based on their likelihood of survival. In this paper, the researchers propose a new randomization approach that aims to improves fairness in certain scenarios. 📰 Read more in MIT News: https://lnkd.in/gzKPfhef #aiforgood #aiforhealth #healthcareinnovation #machinelearningsolutions

Failing to achieve enrollment targets can undermine your trial by delaying milestones, increasing costs, impairing data quality, and compromising patient retention. IQVIA Recruitment Insight Analytics (RIA) harnesses our AIML-driven algorithms and vast historical recruitment data to predict monthly enrollment volume, and identify potential gaps. Discover more with our fact sheet. https://bit.ly/3YLBk1t #clinicaltrials #AI #ML

Stanford CDH is hosting a national survey to gather healthcare professionals perspectives on #AI in medicine. See the link below to take the anonymous survey and contribute to this great research!

Failing to achieve enrollment targets can undermine your trial by delaying milestones, increasing costs, impairing data quality, and compromising patient retention. IQVIA Recruitment Insight Analytics (RIA) harnesses our AIML-driven algorithms and vast historical recruitment data to predict monthly enrollment volume, and identify potential gaps. Discover more with our fact sheet. https://bit.ly/4e7QqVi #clinicaltrials #AI #ML