Oler Health

Oler Health

Hospitals and Health Care

We help post-acute healthcare providers avoid papercuts.

About us

Oler's software helps post-acute healthcare providers review referral paperwork more efficiently and thoroughly. Clinicians using Oler save time while finding additional documentation for patient care planning, value-based reimbursement, and quality measures.

Industry
Hospitals and Health Care
Company size
2-10 employees
Headquarters
Boston
Type
Privately Held
Founded
2022

Locations

Employees at Oler Health

Updates

  • View organization page for Oler Health, graphic

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    This is Oler's transparency post! 🔍 What is our Mission? 🏔 To serve post-acute & long term care professionals by making paperwork less painful and more productive. We aim to help with thoughtful care planning and appropriate reimbursement, while saving folks a little time. What is Oler's pricing? 💵 Oler's current enterprise (chain-wide) pricing is $300 per building per month for unlimited MDS, clinical reimbursement, health information management, nursing, and therapy team users. Individual centers may sign up at $450 per building per month. Who is behind Oler? 😃 Justin and Jerry lead Oler, with employees and advisors having important voices as well. Always feel free to send us your feedback (positive and constructive), or reach out 24/7! Do you have any other questions for us? Post them in the comments and we'll be right back to you! 🙌

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    SNF value-based reimbursement, compared to the system used to finance managed care.  A tale of two cities 🏙 🌆 . Adjusting payment for patient acuity & frailty enables more equitable access to care, particularly for the most vulnerable members of the community 😷. While skilled nursing’s Patient-Driven Payment Model (PDPM) is neat, it is orders of magnitude more complex 🏋♂️ as compared to Medicare Advantage’s equivalent (v28 HCC RAF model) 💰. Oler is grateful to help post-acute clinicians succeed in PDPM – while also saving them time and supporting robust transitions of care 🤝.

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    Skilled nursing MDS 👨⚕️ 👩⚕️ and nuclear science. The International Atomic Energy Agency ☢ published an early “Manual for the Operation of Research Reactors” in 1965. Totaling 214 pages 📚 , that manual explained guidelines for the safe operation and efficient utilization of nuclear reactors. How long is the resident assessment manual used by MDS nurses (the "RAI")?  1,710 pages 🏔 !  And counting. MDS nurses have a considerable workload, and deserve quality tools to help with their mission-critical role in each skilled nursing community ❤️ .

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  • View organization page for Oler Health, graphic

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    MDS reports used to be much shorter. Today, an MDS nurse fills out more than 50 pages of documentation for a nursing home comprehensive item set (MDS 3.0 NC). That’s nearly 10 times the length of the initial reports rolled out for the MDS/resident assessment instrument’s inception in 1991. Fortunately, there are more and more technology options to help MDS nurses manage their intensely demanding (and vital) workflows. Empowered MDS nurses can view resident assessment as a “pivotal aspect to improving case and care outcomes, not simply as a burdensome regulatory requirement.” Quote credit: Journal of Gerontological Nursing.

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  • View organization page for Oler Health, graphic

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    Happy Labor Day to all the hard-working, dedicated folks who make quality care possible in skilled nursing facilities. And as a special shout-out, Oler Health would like to celebrate the contributions of MDS Coordinators. We applaud everything they do to: 🤝 Enable seamless transitions of care 💝 Thoughtfully plan care for residents 💰 Ensure appropriate clinical reimbursement ⭐ Support strong quality measures 😃 And much more! Those multi-tasking nurses are a vital part of the Team! Next time you see one, please give them a high five 🙌 and a thank you 🙏.

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    Insightful analysis by Dr. Woojin Kim at Rad AI. Even for the most sophisticated AI models, there are serious risks to their use without close human supervision. "Human in the loop" design is critical, and AI should be considered a sidekick - not the superhero.

    View profile for Woojin Kim, graphic
    Woojin Kim Woojin Kim is an Influencer

    Chief Medical Information Officer at Rad AI | CMO at ACR DSI | MSK Radiologist | Imaging Informaticist | Entrepreneur | Advisor/Consultant | Speaker | AI Artist | Travel Photographer

    🚨 The authors of this paper state, "among correctly answered questions, GPT-4V may fail to understand or interpret medical scenarios correctly at individual rationales." 🚨🚨 However, the "flaws" are even deeper than presented. 🚨 First, when you test closed-source LMMs like GPT-4V using data from the Web (i.e., NEJM Image Challenge), you risk data contamination. For example, you can directly access the Figure 1 case online. 🛑 We need to stop testing these LLMs and LMMs on data from the Web! In this case, the GPT model doesn't even need the image to answer the question correctly. In fact, you don't even need the answer choices for it to get the correct answer. (See slide #3) Impressive? But can you be absolutely certain the model didn't simply memorize the answer? 🤔 What if you give it a different image? I supplied a CT image of liver metastases. CT image descriptions are all made up. (See slide #4) As others like Laura Heacock, MD, FSBI have shown, GPT-4V should NOT be used for medical imaging! I would even challenge its multiple-choice capability, which the authors mentioned. When I changed the correct answer choice to "None of the above," the GPT model gave a different answer each time! In fact, it didn't pick "None of the above" until the fifth attempt. (See slide #5) 🚨 The authors concluded, "comprehensive evaluations beyond mere multi-choice accuracy are needed before these models can be integrated into clinical practices." 🚨🚨 I agree, but we must also be careful with our research methods to avoid misinterpreting these models' capabilities. 🔗 The link to the original paper is in the first comment. #DataContamination #LLMs #LMMs #VisionLanguageModels #GenAI #MedicalImaging #Radiology #RadiologyAI

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    Artificial Intelligence. AI. It's a topic which is getting a lot of buzz these days. Oler’s perspective: 1️⃣ AI works best when it's set up as a “sidekick” to humans. 2️⃣ Especially in high-stakes environments like healthcare, there is no replacing the clinical judgement and critical thinking of seasoned clinicians. 3️⃣ The business case for AI should be measured in benefits, not buzzwords. Is it actually saving time? Is it helping find "needles in the haystack"?

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    Oler is thrilled to be an Innovator Partner for the American Association of Post-Acute Care Nurses (AAPACN)!   AAPACN represents more than 19,000 post-acute care nurses and professionals.  These healthcare professionals are dedicated to providing the highest quality care to our most frail and vulnerable population.   Also, AAPACN puts on an amazing conference!  We hope to see you all in Louisville next year.

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