Healthcare Analytics Tools

Working with an interdisciplinary team, we have developed a website to communicate how the White House's proposed cuts to health research would cause losses of $16B and 68,500 jobs. Find out how your community may be impacted at SCIMaP: https://scienceimpacts.org As context, on Feb. 7th, 2025, the White House ordered across-the-board cuts to NIH funded research. The order drastically reduces the amount that universities/hospitals/institutes receive for essential facilities, services, and staff required for health research. Nearly two dozen states and allied institutions sued leading to a temporary injunction to across-the-board cuts nationwide. The NIH distributes approximately $37B in external grants/awards in FY 2024. These grants/awards have a force-magnifying effect, generating $2.56 of economic activity for each $1 supported, i.e., more than $94B in activity and more than 400K jobs (source: United for Medical Research). But this impact is hard to see and interpret. You might wonder: perhaps the impacts are focused only on a few, potentially 'elite' institutions? The answer is far different. Soon after the executive order was released, it became apparent that these across the board cuts would have damaging & consequential effects in communities across the United States, in places like State College, PA, Birmingham, AL, and across the medical research infrastructure of Texas. Led by the efforts of Allie Sinclair joint with Emily Falk, Clio Andris and more, we have developed an interactive visualization of the impact of federal cuts to health research in communities nationally. In practice, we take anticipated reductions in NIH supported grants and then leverage US census data on commuting to project the impact of these cuts across and within communities. Through interactive, data-driven visualizations, we aim to help Americans explore how research fuels the economy, supports jobs, and improves health outcomes. This website and interactive visualization is a step in that direction, with more to come joint with Alyssa (Allie) Sinclair (now at UPenn), Emily Falk (UPenn), Clio Andris (GT) + others in The Science and Community Impacts Mapping Project: https://scienceimpacts.org

Epic has announced Comet, a new AI platform built on Epic Cosmos to predict patient health journeys. Trained on over 100 billion de-identified medical events, Comet aims to simulate future scenarios such as disease risks, complications, or length of stay, offering clinicians data-driven insights into what might happen next. This development represents an important shift. Rather than focusing on single-disease models, the tool attempts to capture the complexity of real-world patient care, providing multiple possible pathways instead of a single prediction. It reflects a move toward more holistic, longitudinal AI in healthcare. But significant challenges remain: Predictions are only as strong as the underlying data. Health records are often incomplete, inconsistently coded, or fragmented across systems. Without harmonisation of data and consistent quality, there is a risk that AI-generated futures may reinforce existing blind spots or inequities rather than illuminate them. There are also practical questions: - How will clinicians interpret and act on simulated futures without overreliance on algorithmic forecasts? - Can such insights be embedded into workflows without adding cognitive overload? - And what safeguards will ensure transparency, fairness, and accountability? #AIinHealthcare #DigitalHealth #EHR #HealthTech #ClinicalAI #PredictiveAnalytics #HealthcareInnovation #PatientCentricCare #HealthData #FutureOfMedicine https://lnkd.in/d8RXFA6T

🚑 Heart Failure Analysis using Power BI In this data-driven project, I built an interactive Power BI dashboard to uncover critical health insights from patient data. 🔍 Key Insights Unlocked: KPI Overview: Tracked key metrics like Survival Rate, Average Age of Survivors, Total Survivals & Deaths to understand patient outcomes. Age-Based Trends: 📊 Survival Count & Avg Serum Creatinine by Age Group: Revealed how kidney function markers correlate with survival. 📉 Survival Count & Avg Ejection Fraction by Age: Showed how heart function varies with age among survivors. 📈 Survival Rate by Age Group: Identified age-related risk patterns in patient outcomes. Ribbon Chart Analysis: Assessed the influence of smoking, high blood pressure, diabetes, and anaemia on different age groups using visual ribbons for intuitive risk comparison. 🧠 Dynamic Filtering: Used slicers to explore how survival trends differ by gender. 🔧 Tools Used: Power BI, DAX, data modeling, and advanced visualizations. ✅ The project not only enhanced my skills in healthcare analytics but also taught me how to communicate health risks effectively through interactive visuals. #powerbiproject #dataanalytics #visualizations #powerbi #datacleaning #dataanalysis

I've been saying for over a year that multimodal large language models will become the ultimate interface between physicians and a range of AI-based solutions. Here is the proof! In this study, the authors developed and evaluated an autonomous clinical AI agent leveraging GPT-4 with multimodal precision oncology tools to support personalized clinical decision-making. They used multiple sources such as histopathology slides, radiological images and search tools like OncoKB, PubMed and Google. "Evaluated on 20 realistic multimodal patient cases, the AI agent autonomously used appropriate tools with 87.5% accuracy, reached correct clinical conclusions in 91.0% of cases and accurately cited relevant oncology guidelines 75.5% of the time. Compared to GPT-4 alone, the integrated AI agent drastically improved decision-making accuracy from 30.3% to 87.2%." Source: https://lnkd.in/dwjGvxcH

How a 250 bed hospital turned a 4 hr emergency delay into a 30 min turnaround, using predictive analytics. This hospital was struggling: - Emergency surgeries were delayed due to unavailability of blood units - Critical care beds were full, with no visibility on patient discharge - Inventory spend was skyrocketing, yet they often ran out of essentials - Staff burnout was rising due to mismanaged scheduling They were losing patients and trust. That’s when they decided to act. We helped them implemented a predictive analytics platform built on historical patient data, seasonal demand patterns and supply chain analytics. Within 6 months, here’s what transformation we bring in: 1) Emergency response time dropped from 4 hours to 30 minutes 2) 28% decrease in wastage of medicines and surgical tools 3) ICU bed utilization improved by 35% 4) Staff schedules aligned better with actual patient flow A report by McKinsey highlights AI, traditional machine learning and deep learning are projected to generate net savings in the U.S. healthcare sector of $200 bn to $360 bn annually In a sector where seconds matter, prediction is the edge. In healthcare domain, your hospital doesn't need to be the biggest. It needs to be the smartest to expand and impact more lives! Agree? #Healthcareinnovation #Predictiveanalytics #Hospital #Healthtech

Ever wonder why we tend to solve problems the hard way? 🤔 The key is in how we connect the dots. A cancer hospital was facing a major challenge. Patients, often anxious, needed timely care without added delays. Doctors relied on quick access to medical images to make this possible. For most hospitals, loading images within three seconds is the standard. But cancer patients often have extensive imaging records, making this target a significant challenge. This created escalating pressure in an environment that's already stretched to its limits The hospital consulted several firms. They all suggested the same thing: a costly network upgrade that would disrupt daily operations and inconvenience patients even more. The proposed solution was out of the question, the hospital needed something affordable that wouldn’t disrupt patient care. A consulting firm graciously recommended me for the task. I saw the problem from a different angle. IT experts looked at the network. But as a Health Informatician, I focus on using data and technology to design health services that support optimal care delivery. Instead of waiting for doctors to request images, why not load them in advance? By preparing the images during the patient’s wait time, we created a seamless workflow without costly upgrades. The results were immediate and impactful. 😊 The hospital easily met the three-second target, and patients noticed the improvement with shorter wait times. The cost savings were substantial, all without any disruption to care. "Adam, you literally performed magic!” shared the hospital’s clinical operations lead. Sometimes, the simplest solutions make the biggest difference. The key was understanding how health services connect and using technology to support these connections. These days, as a digital health transformation coach, I continue to co-design sustainable, human-centered innovations that improve how information is used to advance health outcomes. Ever found a simple solution to a complex challenge? I’d love to hear your insights and share approaches that make an impact. #HealthcareInnovation #LeadershipLessons #DigitalTransformation

Dissecting HCC Risk Scores Reveals the True Story of Chronic Care Management The HCC risk score is fundamental to Medicare program operations, but viewing it only as a whole can mask critical insights. Let me share what happened when we dissected these scores for two practices at one of falcon health's clients. In the chart above, we've isolated a specific component of the risk score by: 1. Filtering for Annual Wellness Visits (AWVs) performed by PCPs or peer doctors 2. Applying the new V28 algorithm 3. Calculating scores using only chronic condition HCCs Why this matters: HCCs encompass both acute and chronic conditions, with PCPs having limited influence over acute events but substantial responsibility for ongoing chronic care. While ACOs financially reward AWVs, their true value lies in creating structured opportunities for PCPs to thoroughly document, assess, and coordinate care for patients' chronic conditions. This documentation isn't just paperwork—it's the foundation of effective care management. Since chronic conditions typically persist and often increase over time in senior populations, the chronic risk score captured during AWVs should either increase or remain stable—but rarely decrease. The data tells an interesting story: the blue practice shows steadily increasing chronic condition management through AWVs, while the red practice shows concerning decline. Yet surprisingly, if you looked at the overall risk scores for both practices, they both trend upward consistently. This raises the critical question: Which practice do you think managed costs better in the long run? When we break down metrics into meaningful components, we often discover insights that drive more effective care management strategies. We need to understand the true intent of the program. That's why at falcon health, we are trying to uphold the value of the original intent of the program.

#AI Just Took a Giant Leap in #Healthcare! Imagine a world where AI not only assists doctors but predicts diseases before symptoms appear. That future is here! A new AI model has just demonstrated early detection of pancreatic cancer—one of the deadliest cancers—with over 90% accuracy. In my recent TEDx talk, I emphasized the critical shift from reactive medicine—treating illnesses after they occur—to proactive medicine, where early detection and prevention are key. This breakthrough aligns perfectly with that vision. With AI’s ability to identify risk factors before symptoms emerge, we can intervene earlier, improve outcomes, and truly transform patient care. 🔬 Supporting studies, like one published in Nature (Choi et al., 2023), demonstrate how AI-driven predictive models significantly enhance diagnostic precision and lead to more timely interventions. These findings reinforce the urgent need for healthcare systems to move toward a more proactive approach, leveraging AI to save lives and reduce long-term healthcare costs. 💭 What does this mean for the future of medicine? AI is no longer just a tool—it’s becoming a partner in proactive healthcare, catching what the human eye can’t. 👇 Would you trust AI to screen for early disease detection? Let’s discuss! #AIinHealthcare #FutureOfMedicine #ProactiveMedicine #EarlyDetection #DrGPT

New AI tool can help select the most suitable treatment for cancer patients: 🧬The tool DeepPT developed by the National Cancer Institute (NCI) in America and Pangea Biomed works by predicting a patient's messenger RNA (mRNA) profile 🧬This mRNA - essential for protein production - is also the key molecular information for personalised cancer medicine 🧬Impressively, if the tool predicted that a patient would respond to a given therapy, they would be Two to Five times more likely to respond than a patient who was predicted not to respond to it 🧬The inputs are histopathology images, essentially stained slides of patient tumour tissue, which are routinely available, cheap and fast to process - reducing delays associated with traditional molecular data processing. 🧬DeepPT was trained on over 5,500 patients across 16 prevalent cancer types, including breast, lung, head and neck, cervical and pancreatic cancers 👇Link to articles and study in comments #digitalhealth #AI

The recent executive orders have far-reaching negative implications for healthcare in the U.S., impacting access to care, scientific research, public health communication, and the healthcare workforce. These changes affect every single person in this country, jeopardizing healthcare quality, equity, and progress. Key Concerns: 1. Reduced Access to Care: - Hiring freezes at federal health agencies, including the VA, have led to job losses for newly hired healthcare providers, limiting access to essential services, particularly for veterans. -Hiring freeze affects federally funded health programs, like community health initiatives, rural healthcare services, and public health response teams. This limits the ability to respond to health emergencies, provide preventive care, address public health crises such as infectious disease outbreaks. - The rollback of drug pricing initiatives is expected to increase medication costs, disproportionately affecting vulnerable populations and those on Medicare and Medicaid. 2. Threats to Research and Innovation: - Funding freezes for the National Institutes of Health (NIH) and the National Cancer Institute (NCI) jeopardize critical research initiatives, delaying progress in cancer treatment, chronic disease management, and public health solutions. - Researchers face uncertainty, hindering groundbreaking work that could lead to new treatments and therapies. These cuts weaken the U.S.’s position as a global leader in medical research and reduce opportunities for early-career scientists, particularly women and minorities, who are already underrepresented in research leadership. 3. Public Health Communication Disruptions: - Restrictions on agencies like the CDC and FDA limit the dissemination of vital health information, leading to misinformation and public confusion. Without timely updates on disease outbreaks, food recalls, and health policies, communities may face increased health risks. 4. Global Health Challenges: - Withdrawal from the WHO undermines U.S. participation in global health initiatives, delaying responses to pandemics and limiting international collaboration on pressing health issues. 5. Worsening Health Disparities: Low-income and minority communities will bear the brunt of these policies, with reduced access to preventive care, screenings, and treatment options, further exacerbating existing health inequities. 6. Erosion of Trust in Healthcare Institutions: - Regulatory rollbacks and suppression of scientific information may reduce public confidence in healthcare institutions, leading to lower compliance with critical health initiatives such as vaccinations and cancer screenings. These policy shifts are threatening the health of millions, slowing medical progress, and creating long-term challenges for healthcare systems and communities across the country. Now more than ever, it is crucial to advocate for policies that prioritize accessible, affordable, and evidence-based healthcare for all.