Sapien's Requisition Management Software: Reducing Administrative Burden and Processing Time 📈 Sapien's Requisition Management software utilizes AI 🧠 to streamline radiology requisition processing, significantly reducing administrative burden and processing times ⏳ for healthcare providers. One hospital group that implemented Sapien's OCR solution saw a decreased burden of work so 1 could do the job of 10 previously. Another hospital group experienced a remarkable decrease in processing time, from 14 days to under one day. Sapien's software offers several benefits that contribute to these improvements: Redeployed staff: By automating many tasks, Sapien's solution minimizes the need for manual data entry and processing, enabling healthcare providers to redeploy their staff to do other tasks in the organization. Faster Processing: Sapien's AI-powered system rapidly extracts critical information from requisitions, leading to significantly faster processing times. Improved Accuracy: Automation reduces human error, resulting in more accurate data entry and reduced need for rework. Sapien understands the challenges healthcare providers face with rising administrative costs 💸, increasing workloads 😫, and difficulty in hiring qualified personnel. Sapien's targeted AI solution with deep domain knowledge provides a compelling answer to these challenges, allowing healthcare providers to: Redeploy valuable HR resources to higher-value tasks. Focus on patient care while improving operational efficiency. To learn more about how Sapien's Requisition Management software can help your organization, visit their website at sapiensecure.io.
SapienSecure
Hospitals and Health Care
Vancouver, British Columbia 370 followers
Patient Flow and Revenue Cycle Management Transformation Through AI | Computer Vision and NLP
About us
At SapienSecure, we're not just changing the game; we're transforming the field of healthcare management. Our mission is clear: to leverage cutting-edge Artificial Intelligence, including advanced NLP and vision AI technologies, to bring unparalleled efficiency and accuracy to healthcare operations. We are at the forefront of automating Revenue Cycle Management (RCM), billing processes, and patient flow optimization, setting new standards for what technology can achieve in healthcare. PROBLEMS WE SOLVE 1) Billing Audit - Billing review is time-consuming and imperfect. Leveraging NER and ML, Sapien makes it fast and easy. 2) Billing Automation - Billing coding is time-consuming and imperfect. Leveraging NER and ML, Sapien makes it fast and easy. 3) Requisition Automation - Manually processing image-based (e.g. faxed )requisitions is time-consuming and imperfect. Sapien uses OCR and NLP to scan inbound requisitions and extract text, and NLP to protocol them for their next step. Sapien makes it fast and easy. 4) Data De-identification - manually deidentifying data is time-consuming and imperfect. Sapien uses OCR and NLP to strip PII and PHI from images and unstructured text. Health data stewards want to share their data to support research and expand hospital resources, but not expose patients private information. Sapien makes it fast, easy, and safe.
- Website
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https://sapiensecure.io/
External link for SapienSecure
- Industry
- Hospitals and Health Care
- Company size
- 2-10 employees
- Headquarters
- Vancouver, British Columbia
- Type
- Privately Held
- Founded
- 2019
- Specialties
- Artificial Intelligence , Billing Audit & Automation, Requisition Automation, Medical Coding, Clinical Documentation Improvement, Revenue Cycle Management , RCM, OCR, Natural Language Processing, Healthcare, Medical AI, Medicine, Radiology, Interventional Radiology, and AI for Healthcare
Locations
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Primary
Get directions
Vancouver, British Columbia V3N0B4, CA
Employees at SapienSecure
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Scott Holmes
Brand Architect I Web3 I MASSIVE AI I IMMORDL I SPFM | Kings of Fi$H I JOLTZ | SapienSecure I Board Advisor Vitamin Angels I Founder United…
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Alireza Mojibian
Medical Research Project Manager | AI-driven Medical Technology | Clinical Trial Ethics | Bridging Teams & Innovating in Medicine
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William Parker
Cardiovascular Radiologist MD, DABR, FRCPC | Founder and CEO of SapienSecure
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Brian Lee
Chief Technology Officer at SapienML
Updates
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SapienSecure’s founder William Parker co-authored new #deID paper with the #NationalCancerInstitute. Check it out!
New #papers on #medical #data #DeID! Summary of the National Cancer Institute 2023 Virtual Workshop on Medical Image De-identification from #NCI Amazing team and a lot of work went into collating this information, led by David Clunie. Hopefully they are helpful! 1) https://lnkd.in/gdQyQQJN 2) https://lnkd.in/gTrGDp-y Keyvan Farahani, Judy Gichoya, Juergen Klenk, Fred Prior, Ying Xiao, Adam Taylor, Michael W. Rutherford, Steven Moore, Christian Ludwigs, Abraham Gutman, Haridimos Kondylakis, Daniel Marcus, Bob Lou, Tony O’Sullivan, Jiri Dobes, Tom Bisson, David Gutman, Christopher Schwarz, Douglas Greve, George Shih, Adrienne Kline, MD, PhD , Ben Kopchick, Carolyn Kelley Klinger, Ulrike Wagner, Linmin Pei (PhD)
Summary of the National Cancer Institute 2023 Virtual Workshop on Medical Image De-identification—Part 1: Report of the MIDI Task Group - Best Practices and Recommendations, Tools for Conventional Approaches to De-identification, International Approaches to De-identification, and Industry Panel on Image De-identification - Journal of Imaging Informatics in Medicine
link.springer.com
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Top Five Billing Mistakes that Lose Radiologists Money, and How to Diagnose Them, and Fix Them Ever found a billing mistake? Corrected it? How did it feel? Great? Like it’s your birthday? Perhaps you’ve heard your billing team “is on the ball”... “got it covered?” What if you could send one email, or look at one report, and you could get a little evidence with that gut feel? Jeff earned $5,645.27 in just one hour. How? By checking the top list of billing errors made by radiologists. Do you want to be like Jeff? Want the list of the top billing errors made by radiologists and their billing teams? What if that list came with: a) Tests - A quick diagnostic test to see if it applied to your team, and b) Corrections - A prescription for finding the problems, and a wrote solution for fixing them - so you can resubmit them, and c) Future Proofing - A solution to helping you and your team never make that mistake again? Now what if all that was… FREE? Well it is… And all you have to do is comment on this post “I want the Sapien billing test”. We’ll DM you to share the whitepaper with the quick tests, the corrections, and the future proofing. #RadiologyBilling #MedicalBilling #Radiology #HealthcareFinance #BillingErrors #RevenueCycleManagement #MedicalCoding #HealthcareAdministration #FinancialHealth #HealthcareEfficiency #SapienSolutions #BillingSolutions #FreeResource #HealthcareTips
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🌟 Is AI the Future of Radiology? Artificial Intelligence (AI) is changing radiology in amazing ways. It's bringing new chances for better patient care and innovation. But what does this mean for the future of healthcare? Let's explore the current impact, limitations, and what needs to be done to fully harness AI's potential. 📊 Current Impact: AI is making diagnostic work more accurate and efficient. It helps in all radiology areas, like CT scans, MRIs, ultrasounds, and nuclear imaging. Think about faster, more accurate diagnoses that lead to better patient outcomes (1-3). ⚖️ Key Limitations: - Data Quality: We need high-quality, diverse data to avoid bias and ensure AI systems are reliable (1,4). - Ethical Considerations: Privacy, consent, and fairness are very important. We must handle these challenges to keep patient trust and safety (2,5). - Integration Challenges: It’s hard to fit AI into current workflows, but it’s necessary for widespread use (2,6). 💡 What’s Needed: - Rigorous Evaluation: We must continuously monitor and validate AI tools to ensure they are safe and effective (2,7). - Collaboration: Strong partnerships between developers, clinicians, and regulators is vital (2,5). - Education: Radiologists need ongoing training to fully understand and use AI’s capabilities (1,8). 🔬 Recent Findings: Recent reviews show AI's wide-ranging applications in radiology. But there are still big challenges, especially around validation and professional uptake. Many AI tools lack a lot of peer-reviewed evidence, showing the need for more support in smaller organizations (1,2,5). Even with these challenges, AI has great potential to reduce diagnostic errors, decrease workload, and improve patient outcomes. By focusing on these key areas, we can drive the next frontier in radiology and healthcare. What are your thoughts on AI in radiology? Share your insights below! 👇💬 #Radiology #AIinHealthcare #MedicalImaging #HealthcareInnovation #machinelearning
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🌟 How is AI Shaping the Future of Diagnostic Radiology? Vizient released its 2024 report on the top trends transforming radiology. No surprise, they highlight how AI is improving efficiency and patient care. 📈 Let’s dive in! 🤝 First up, Systemness. Radiology departments are teaming up to share resources and solve challenges together. With AI, remote scanning allows experts to assist and operate equipment from a different location. 🕒 Remote imaging is on the rise too. Remote Scanning helps manage workload and staff shortages, ensuring patients get timely care. AI enhances remote imaging with real-time support, making remote care reliable. ⚕ Then there’s Workforce Challenges. With fewer radiologists, healthcare providers use remote reading programs and AI to manage workloads. AI automates routine tasks, letting radiologists focus on complex cases. 🌍 Let’s not forget the environment. Sustainable Imaging is gaining traction. Radiology departments adopt green practices to reduce energy use and carbon footprints. AI optimizes equipment energy consumption, supporting sustainability. ⚖️ AI is hot, but balance is key. Artificial Intelligence in radiology improves efficiency and accuracy, but human oversight is crucial. AI isn’t and shouldn’t be replacing radiologists; it should be helping them deliver better care faster. 💡 What’s the big picture? The future of diagnostic radiology is bright. AI can drive efficiency and improve patient care across the board. However, challenges remain in integrating AI into workflows, ensuring data quality, and addressing ethical concerns. What are your thoughts on these trends? How do you see the future of diagnostic radiology using AI? Share your thoughts and experiences in the comments below! 👇💬 #Radiology #HealthcareInnovation #AIinHealthcare #MedicalImaging #vizient #2024 #diagnosticradiology For more insights, check out the full report: https://lnkd.in/gvV28VNX
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🌟 Can AI Tackle Healthcare Burnout? Burnout is a major problem in healthcare. It’s made worse by endless paperwork and repetitive tasks. Can AI offer a solution? 🤔 Reducing Administrative Tasks: RevCycleIntelligence says automating tasks can reduce paperwork, letting healthcare workers focus more on patients. Support for Physicians: The CFPC suggests reducing administrative work to help doctors. This can improve their work-life balance and mental health. AI Transformations: HyScaler discusses how AI can ease administrative burdens, reduce burnout, and improve patient care. 🧩 Common Theme: These reports highlight the need to address administrative burdens! 💡 Our Approach: Our clients use AI to streamline workflows, boost efficiency, and improve work-life balance. Why is this important? Balancing efficiency and support for healthcare workers is crucial. Automation can reduce errors, save money, and enhance patient care without hurting healthcare workers' well-being. 📅 Want to learn more? Book your free consultation with us - [email protected] ✍ We'd love to hear your thoughts! What steps are you taking to support your team? Comment below! 💭 Read the full articles: 1) https://lnkd.in/gECtuVDt 2) https://lnkd.in/gdc34j3n 3) https://lnkd.in/gNJZj6cy #HealthcareBurnout #MedicalBilling #RevenueCycleManagement #RequisitionManagement #HealthcareAutomation #EthicalAI #HealthTech #OnPremSolutions #PatientCare #AIinHealthcare #HealthcareManagement #WorkLifeBalance
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🌟 Is Ethical Automation in Radiology Billing Possible? Automation is transforming radiology billing, making it faster and more efficient. But what about the ethical concerns? 🤔 HackerNoon highlights that "automation can improve cost-effectiveness and productivity, but ethical concerns like bias and patient privacy need addressing." PwC projects a 7% rise in medical costs in 2024 due to inflation and workforce shortages. This increases the need for cost-effective solutions like automation. Insights10 notes the rapid growth in Canada’s medical billing outsourcing market, driven by technology and complex reimbursement procedures. 💡 Our clients are tackling these challenges by adopting an on-prem approach. By installing models within their firewalls to ensure better control and security. Why is this important? Balancing efficiency with ethics is crucial for trust and sustainability in healthcare. Properly managed automation can reduce errors, save costs, and enhance patient care without compromising ethical standards. Want to learn more? 📅 Book your free consultation with us - https://lnkd.in/dzTeHaDm ✍ We'd love to hear your thoughts! How can we balance efficiency with ethics in radiology billing? Comment below! 💭 Read the full articles: 1) https://lnkd.in/dES5psj6 2) https://lnkd.in/e6sdmmz 3) https://lnkd.in/d9FM3nzn #RadiologyBilling #MedicalBilling #HealthcareAutomation #EthicalAI #HealthTech #MedicalCost #OnPremSolutions #PatientCare #AIinHealthcare #Radiology #MedicalEthics #HealthData #AutomationEthics
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#McKinsey Reports on Challenges Facing Medical Groups… Same for Your Group? A recent McKinsey report based on interviews of 100 healthcare leaders says, that despite rising revenues, academic medical centers face tightening margins. Other insights from the report: 🚨Revenue Cycle Management Underperforming: A staggering 83% state RCM as crucial yet underperforming. 🤝Administrative Support Growing and Needed: 75% are bolstering their admin teams to enhance operational efficiency. 🔬 Education and Research Budgets Should Expect Cuts: Specifically, 31% foresee cuts to education and research. They expect cuts within 3 years. 💬 Sound familiar? How are you tackling these challenges? Please post in the comments below. Some of our clients are using AI to tackle all three. Contact us at [email protected] to find out how. Link to Original Report: https://lnkd.in/eZDtNfHC #RevenueCycleManagement #AIinHealthcare #AIinMedicine #HealthcareInovation
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"The sad reality is that if the volume is going up, and the budget to accommodate it isn’t rising equivalently, that can only mean one thing: a reduction in price for the service." Dr. Parker's thoughts raise important questions about the sustainability of our healthcare providers under financial strain. What do you think will be the outcome? 👉 Join the discussion, comment below and help shape our understanding of these critical healthcare issues. #Healthcare #CancerCare #BCGov #MedicalDiagnostics #radiologybilling #medicalbilling
🌟 What do you think the impact on billing will be for the recently announced expanded access for cancer diagnosis by the British Columbia Government? Some friends we’ve been chatting with are secretly a little worried about the upcoming plan for growth in cancer diagnoses. Not heard? - https://lnkd.in/gv98ubiR On the face of it, that sounds like great news for radiologists… more diagnostic procedures. But just last summer, we heard about dire financial issues for diagnostic clinics… - https://lnkd.in/gaerzbup On the verge of shutting their doors - and it’s not because of low patient volume. You can see in the article, frequent references to patient wait times. So that leaves only one possibility: insufficient remuneration. Now it's not like the BC health system has tons of extra funding. On the contrary, the BC government is committing significant resources to the challenge. - https://lnkd.in/grHyqPpY Recently negotiated additional federal funding won’t cover this: https://lnkd.in/gwHjKP5j So where’s the shortfall for the 16000 to 44000 new diagnostic procedures - almost tripling going to come from? The sad reality is that if the volume is going up, and the budget to accommodate it isn’t rising equivalently, that can only mean one thing: a reduction in price for the service. Now, we’re not saying that’s what’s going to happen, but we ARE starting to hear whispers of concerns about this. More cost pressures for the service? Wouldn’t surprise me, but during a time of significant inflation, might this break the back of diagnostic imaging providers? What do you think? POLL - Share your vote in the comments below! ✅ Yes - we expect some significant reduction in cancer diagnostic fee codes. ✅ No - we don’t expect a significant reduction in cancer diagnostic fee codes. ✅ No Way - there’s already a shortage of radiologists, and reductions in fee codes would just push qualified staff away, there’s no WAY the government could reduce the fee codes, heck, I expect them to increase them. ✅ Not Sure - there’s augments both ways
BC invests $31M in cancer diagnostics and research | CityNews Vancouver
https://vancouver.citynews.ca
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🌟 Will AI work with your data as a “mother tongue” or as a phrasebook tourist? Children learn a “mother tongue” by hearing and speaking it regularly. LANGUAGE LEARNING - MOTHER TONGUE VS. PHRASEBOOK TOURIST - IT’S NOT THE SAME Then when they learn other languages, they learn basic words. But, it takes a lot longer to learn the subtleties - the construction, the grammar, the idioms. Those come by translation from the mother tongue. This causes wrong grammar and literal idiom translation. People learn when native speakers correct them. But, what happens when that doesn't happen? The errors perpetuate. An article looked at accent development in Antarctica. (reference: https://lnkd.in/gqMWXX4Z). The article shows how isolation caused shifts in language. The shifts included pronunciation and meaning. LEARNING TASKS - IT TAKES TIME AND WORKS BETTER ON TASKS DIRECTLY TRAINED TASKS Now imagine transitioning healthcare admin staff. They take months to learn the local language. The nuance, the assumptions, the rules… As they do, their productivity improves as well. No surprise - people take time to learn. And they improve their performance on tasks on which they train. The same is true for LLMs. The performance of models on tasks improves with prior training on those tasks. (https://lnkd.in/grbShDGQ). But isn’t healthcare data absolute… scientific? From an LLM perspective… no. Radiologist strategies for reporting often differ. (Reference: https://lnkd.in/gsR2WFc9). IS NOT SHARING YOUR DATA HURTING LLMS FROM WORKING WELL WITH YOUR DATA - LOSING YOU “MODEL SHARE”? So, if you don’t share your data with model development, you might prevent AI from working for you. And if you never share it, AI might never work as well for your group as it will for others that have. But how is this playing out elsewhere? In marketing, many top copywriters are sharing their secrets. They are sharing them with: a) technology companies, and b) other copywriters. Why? So the AI works better for them. They, and their followers, are training the models to think of copywriting the way they think of it. They’re developing “model share”. And that raises a question. Is not sharing your data with model developers going to cost you model share? Are you going to pay for not sharing one transaction at a time? Because when the models eventually hit your data, it: a) doesn't work as well, and b) requires more human effort? All because you don’t have model share? Put another way, will LLMs use your data as a “mother tongue” or as a phrasebook tourist? #AIinHealthcare #DataSharing #LargeLanguageModels #MachineLearning #HealthcareInnovation #NLP #ArtificialIntelligence #ModelTraining #DigitalTransformation #TechTrends #businessinsider #sciencedirect
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