Common infections are becoming harder to treat. The World Health Organization warned new data shows that 1 in 6 bacterial infections globally are resistant to standard antibiotics, endangering millions and straining health systems worldwide. https://lnkd.in/eTjZ-Dk6
BITSCOPIC
Hospitals and Health Care
Palo Alto, California 4,645 followers
Clinical Surveillance | Infection Prevention | Pharmacogenomics | Precision Medicine | Healthcare Analytics
About us
Bitscopic is a healthcare technology company delivering decision-ready data to support clinical, operational, and research excellence. Our interoperable solutions help health systems turn complex data into clear, actionable insights that improve outcomes and accelerate innovation. With a decade of experience in federal and commercial health, we’re trusted by the people making the most important decisions in healthcare.
- Website
-
https://bitscopic.com
External link for BITSCOPIC
- Industry
- Hospitals and Health Care
- Company size
- 11-50 employees
- Headquarters
- Palo Alto, California
- Type
- Privately Held
- Founded
- 2012
- Specialties
- biosurveillance, infection control, clinical trials, antimicrobial stewardship, Clinical Surveillance, healthcare data analytics, healthcare software, pharmacogenomics , Veterans Health Administration, precision oncology, data analytics, dry lab software, and PGx
Locations
-
Primary
Get directions
Palo Alto, California 94303, US
-
Get directions
3010 77th Ave SE
Mercer Island, Washington 98005, US
Employees at BITSCOPIC
-
Farshid Sedghi
Co-Founder@Bitscopic- Turning healthcare data into actionable insights and decisions | Product guy | Ex-Microsoft
-
Gene Mitelman
Senior Software Developer, Financial Coach
-
Bill Maher
Director, Business Development at Bitscopic
-
William Mohabbati
Product Management | CPHIMS, PMP | HealthTech & Enterprise Solutions | AI/ML | Data Platforms
Updates
-
Emerging evidence suggests moderate fever may support immune response in sepsis—challenging routine antipyretic use. A thought-provoking read for hospital clinicians: https://lnkd.in/e6C3hvJe #Sepsis #InfectiousDisease
-
🗓️ October 15 is Global Handwashing Day! 👏 Washing your hands is the single most effective way to stop the spread of germs, helping to prevent respiratory and gastrointestinal infections. At Bitscopic, we know that patient safety starts with prevention. PraediAlert empowers healthcare teams with timely data to manage and stop the spread of infections. Commit to the 20-second scrub today! See the simple steps here: https://lnkd.in/eZJNR-5z #GlobalHandwashingDay #InfectionPrevention #PraediAlert #HealthTech
-
A “negative” dalbavancin trial doesn’t mean a dead end—it means opportunity. 💡 @PaulSaxMD highlights why even when results aren’t what we hoped for, there’s room for optimism in innovation, stewardship, and trial design. Read more 👉 https://lnkd.in/e4XxEzBD #AntibioticStewardship #Dalbavancin
-
PGx at scale often stalls on workflow. Here are 5 pitfalls to avoid so reports are fast, consistent, and audit ready. https://lnkd.in/eUkRXZJD #PraediGene #PGx #HealthIT
-
A recent study in Cambridge Care reveals how recurring C. difficile infections can cause a financial burden on healthcare organizations. How are you preventing these infections to protect patients and reduce costs at your facility? #PraediAlert #Cdiff https://lnkd.in/ehNsWu-M
-
🚨 LISTERIA OUTBREAK: 4 deaths, 19 hospitalized. Foodborne illness requires rapid reporting to trace the source! PraediAlert by Bitscopic enables you to share case data quickly with public health to accelerate investigations. CDC: https://lnkd.in/guCdAbYS #Listeria #FoodSafety #Bitscopic #PraediAlert
-
New study finds primary oral vancomycin prophylaxis reduced C. difficile infection in high-risk hospitalized patients, with few adverse events. Raises key questions for clinicians on dosing, resistance, and stewardship. https://lnkd.in/eYbcuUgn #AMS #Cdiff
-
How do you reward hand hygiene heroes? This study shows that a hospital observed an 11.45% increase in hand hygiene compliance after implementing a daily reward program for top performers. #HandHygiene #PraediAlert https://lnkd.in/eQGt3aPb
-
Transparency is foundational to clinical trust. At Bitscopic, we believe explainability shouldn’t stop at the algorithm, it must extend through data integration, model design, and real-world validation. That’s why PraediGene emphasizes decision-ready data, clear provenance, and clinician-readable outputs that make AI insights actionable at the point of care. #AIinHealthcare #ExplainableAI #DecisionReadyData #PraediGene #PGx
Medical AI can't earn clinicians' trust if we can't see how it works - this review shows where transparency is breaking down and how to fix it. 1️⃣ Most medical AI systems are "black boxes", trained on private datasets with little visibility into how they work or why they fail. 2️⃣ Transparency spans three stages: data (how it's collected, labeled, and shared), model (how predictions are made), and deployment (how performance is monitored). 3️⃣ Data transparency is hampered by missing demographic details, labeling inconsistencies, and lack of access - limiting reproducibility and fairness. 4️⃣ Explainable AI (XAI) tools like SHAP, LIME, and Grad-CAM can show which features models rely on, but still demand technical skill and may not match clinical reasoning. 5️⃣ Concept-based methods (like TCAV or ProtoPNet) aim to explain predictions in terms clinicians understand - e.g., redness or asymmetry in skin lesions. 6️⃣ Counterfactual tools flip model decisions to show what would need to change, revealing hidden biases like reliance on background skin texture. 7️⃣ Continuous performance monitoring post-deployment is rare but essential - only 2% of FDA-cleared tools showed evidence of it. 8️⃣ Regulatory frameworks (e.g., FDA's Total Product Lifecycle, GMLP) now demand explainability, user-centered design, and ongoing updates. 9️⃣ LLMs (like ChatGPT) add transparency challenges; techniques like retrieval-augmented generation help, but explanations may still lack faithfulness. 🔟 Integrating explainability into EHRs, minimizing cognitive load, and training clinicians on AI's limits are key to real-world adoption. ✍🏻 Chanwoo Kim, Soham U. Gadgil, Su-In Lee. Transparency of medical artificial intelligence systems. Nature Reviews Bioengineering. 2025. DOI: 10.1038/s44222-025-00363-w (behind paywall)
-