Best Healthcare Technology Solution

Recognizes the best solution for improving care quality, patient safety, efficiency, medical information and/or data exchange to healthcare professionals or consumers. Population health or fee-for-value solutions include the development of new payment and care models, care coordination, readmission management, med adherence, health optimization/wellness, telemedicine, telehealth, and innovations in disease management. May include Revenue Cycle Management Software.

Cloudticity Healthcare DataHub, Cloudticity - Cloudticity

Cloudticity Healthcare DataHub - a real-time analytics environment, built on Amazon Web Services (AWS), makes data insights available in moments. Just deploy the cloud-native ingestion engine, configure and normalize the data, and within minutes, analysts, data leaders, and epidemiologists can begin creating dashboards, heatmaps, and reports. 

The Challenge - Traditionally, ingesting massive quantities of healthcare data like FHIR, HL7, and CCDAs requires integration engines that are fickle, difficult to maintain, and prone to failure – not to mention expensive. Other vendors have built new products on top of legacy integration engines –“innovating” based on what had come before. This approach works – sort of – but eventually you run into new problems that are difficult or impossible to solve with last-generation products.

The Solution - By integrating off-the-shelf AWS services with Cloudticity-developed software components, we built a modern solution that allows companies to ingest vast numbers of healthcare messages at incredible scale without the need for physical infrastructure. Now, healthcare organizations can integrate data for a fraction of the price.

 

4 Common Use Cases:

 

  1. Reducing Readmissions - Since one of the most common causes of patient readmissions is congestive heart failure, we analyzed millions of records for congestive heart failure cases and built a machine learning model using that data. When new patients were admitted for congestive heart failure, the machine learning tool analyzed their records and compared them to historical data. This technology was able to determine the probability that a patient would be readmitted to the hospital, allowing healthcare providers to take appropriate actions to lower that probability, translating directly to higher revenues.
  2. Increasing the Efficacy of Clinical Decisions - Determining which medications will be best for each patient is related to that person’s genetic makeup. Our architecture gives providers the ability to match a patient’s symptoms and genomics with millions of other similar cases. Then, applying machine learning, you can identify the best treatment for each individual patient.
  3. Improving The Patient Experience - With our system, everything is tracked from the time a patient arrives to the time they leave. When a patient arrives, it triggers a message in the hospital’s patient information system. When the patient sees the doctor, it triggers another message. This transparency gives providers an amazing advantage because they can see in real time how long each phase of the visit lasts. The hospital can then make adjustments to decrease wait times and create a more efficient visit, translating to better patient experiences.
  4. Driving Additional Revenue - Many small daily procedures or treatment actions – like giving Tylenol to a patient with a headache – are never billed. This adds up to a significant amount of lost revenue over time. To solve this problem, our system identifies physician clinical notes and codes them for billing, helping providers capture additional revenue.

 

Now healthcare organizations can:

 

  •  Securely ingest massive amounts of FHIR, HL7, and CCDAs, normalize data, execute EMPI matching
  • Give validated users the ability to easily query and discover insights
  • Train and leverage machine learning models, including natural language process that is aware of healthcare terminology, in order to find deeper correlations
  • Visualize data in real-time, create valuable dashboards that inform both clinical and business decisions
  • Integrate healthcare data at 90% cost reduction compared to non-cloud-native tools

 

Proof point: In 2020, Cloudticity partnered with the New York State Department of Health (NYSDOH) and AWS to create the nation's first COVID-19 data registry for the analysis of critical clinical data needed to flatten the coronavirus curve. Utilizing Cloudticity Healthcare DataHub, in just 6 days NYSDOH was able to roll out a cloud-based solution to collate disparate data being received from six separate healthcare information exchanges (HIEs) across the state. This data lake enabled NYSDOH to gain important insights into COVID-19-related comorbidities, hospital capacity, geographic swells, and more so it could quickly move from red to green during the first surge.

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    Studycast - Core Sound Imaging, Inc.

    More than a PACS, the Studycast system is a comprehensive imaging workflow solution.

    As a true cloud solution, it allows you to work from anywhere, anytime.

    Streamlined and intuitive, the Studycast system provides a single workflow from exam to archive. Add on the optional integration interfaces, and the system goes full circle from order to results.

     

    The Studycast system allows you to manage, upload, store and share images from any source, to any recipient, securely.

     

    The powerful data management that is built into Studycast means not only can you manage medical imaging but you can automate the workflow by receiving data from any source and routing that data to any destiation. Elimintating data entry, increasing efficiency and optimizing patient care.

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  • PatientPass, Elsevier Inc. - Elsevier Inc.

    The typical American patient spends less than 0.1% of their time with a healthcare provider, which means the health decisions made by patients on their own every day are critically important to improving health. And yet 80 million Americans struggle with “health literacy” – the ability to gather, understand, and make use of health information. Elsevier, a global leader in information and analytics solutions for healthcare, is working to overcome these challenges with the launch of its new patient education solution, PatientPass.

    Educating patients is a vital component of the healthcare journey, and yet antiquated processes make patient education difficult for clinicians to conduct, for patients to learn, and for hospital leaders to analyze. PatientPass makes every step of the patient education process easier.

    *****

    PatientPass is an innovative healthcare technology solution that integrates seamlessly into a hospital's Electronic Health Records (EHR) to support:

     - clinicians in assigning the right patient education for their patients at any stage in their care journey

    - patients in consuming patient education handouts and videos that match their levels of health literacy, any time and anywhere

    - hospital leaders in assessing how well their patient education program is working, so they can ensure patients are always getting the information they need to make informed health decisions

    *****

    To understand how PatientPass helps, consider a hypothetical patient named Maria. She is 68 years old and scheduled to have her knee replaced. She is nervous about the procedure. What might happen if her hospital lacks PatientPass?

    • Maria arrives at the hospital for her procedure not knowing what to expect. 
    • Maria’s surgeon explains the procedure in English, but Maria’s first language is Spanish, and she doesn’t fully understand.
    • Maria undergoes the procedure and her son arrives to take her home; just before leaving the hospital, Maria’s nurse hands her a stack of English documents that explain the procedure that was performed and how Maria must now take care of herself.
    • Maria never reads the documents, which she accidentally leaves in her son’s car.
    • Maria’s home, which was not adequately prepared for her recovery, includes several tripping hazards; unfortunately, three days after the surgery Maria slips on a rug and ends up in the emergency room.

     What might have happened to Maria if her hospital had used PatientPass?

    • Three days before Maria’s procedure, her hospital uses PatientPass to automatically send her short videos to watch that instruct her on how to prepare her home for recovery and on what to expect the day of the procedure.
    • The videos that Maria receives are in Spanish, which is her preferred language according to hospital records. 
    • Maria shares the videos with her son, who changes the language to English and watches them; he then helps Maria prepare her home for recovery by removing tripping hazards like small floor rugs.
    • Maria arrives for the procedure comfortable and confident. The surgeon and nurses can see in PatientPass that Maria received and watched the videos; they ask her if she has any follow-up questions.
    • The procedure is successful, and Maria’s son takes her to her home, which has been prepared for her recovery.

    PatientPass makes the education experience intuitive for patients likes Maria no matter their level of health literacy. PatientPass supports clinicians in their important work, while also generating data that hospital leaders can track to ensure their patient education program is working.

    *****

    UPDATE: More and more health systems are choosing PatientPass to manage their patient education programs, 14 and counting as of this writing, including Advent Health, Henry Ford Health System, Robert Wood Johnson Barnabas Health, Baptist Health (FL), Baptist Health (KY), LifeSpan, OU Medicine, Integris, Wellforce, and more!

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    Forcura Care Coordination Platform, Forcura - Forcura

    Forcura gives home healthcare, hospice and rehabilitative therapy providers control over the referral and orders management processes through a cloud-based care coordination platform that centralizes and digitizes documents, streamlines workflows, facilitates secure clinical communications, and enables data-driven decisions. The Forcura solution makes patient care safer as people transition from one care setting to the next. Our core product offering, Forcura Care Coordination Platform, is a cloud-based software solution that digitizes and centralizes referral, orders and other patient-related documentation in one location. Users can annotate, label, and track documentation, then sync data to integrated electronic health record systems (EHRs) with a click. Users know at any time what documentation is in process, outstanding or completed, making their operations more transparent, and their financials more predictable. It also helps clinical staff be as efficient as possible by ensuring that the patient information they need most is where it needs to be and available to those who need it. In 2020, the Forcura Care Coordination Platform was updated with three important new features: 1. Analytics - an integrated suite of business intelligence reports and drill-down data that enables clients to assess at a glance key referrals and orders management indicators, as well as staff performance metrics. With Analytics, clients can monitor the health of their operations, isolate workflow-related areas that require action, and easily prove the value of Forcura within their organization. 2. Referral Automation with IQ - Using artificial intelligence, new referral documents are immediately identified, classified and diverted to a priority work queue. Patient demographic information is automatically indexed, can be matched to existing patient records and a new patient record can be created if no existing patient is identified. This IQ feature saves most clients over two hours of manual work, enabling them to accept and onboard new patients faster, reduces keying errors which could delay patient care, and gives clinical teams more time to prepare their plans of care. 3. Provider dashboard with follow-up tracking - Our home healthcare, hospice and rehab therapy clients depend on external physicians to approve care plans, and physician signatures are required for billing (otherwise our clients cannot get paid). This feature enables clients to track all contact attempts with these physicians, make notes on the status of outstanding documents, and improves their efficiencies by eliminating duplicate efforts. External physicians benefit from our clients' more streamlined communications. And our clients can more easily hit their billing targets.

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    iOrder, iPro Healthcare - iPro Healthcare

    iPro Healthcare's iOrder solution supports the exchange of medical information between hospitals and referring physicians by delivering the knowledge of the hospital to the initial point of patient care with the referring doctor. This improves patient safety and care quality by minimizing incorrect coding and unnecessary procedures, ensuring that an appropriate exam is always ordered. Referring physicians gain confidence in referral decisions; a quick, painless scheduling process; simple avenues for seeking assistance when needed; and timely and consistent patient order/test updates. No other product on the market today brings healthcare organizations this unique combination of information exchange, clinical and financial validation, and digitial patient engagement around ambulatory orders. 

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    DrAid, VinBrain LLC - VinBrain LLC

    VinBrain LLC is a medical AI-focused company established in April 2019. In June 2020, we launched DrAidTM, our flagship AI-powered healthcare product.

    DrAidTM provides AI-based automated chest X-ray diagnosis and screening to radiologists and contains comprehensive features to optimize their daily tasks.

    DrAid’s AI is trained on our self-curated dataset of 1.3 million X-ray images sourced from public and private sources. It applies our patented labelling methodology and utilizes clean medical image data process supported by a group of top expert radiologists. We have also utilized our proprietary graph convolution neural network (G-CNN) deep learning and active learning technologies. Each time a diagnosis is completed, DrAidTM combines knowledge from the image analysis and medical report to further train its model through a feedback loop system.

    Currently, DrAidTM can detect the 20 most common chest X-ray abnormalities and diseases including COVID-19, tuberculosis, pneumonia, and chest fracture with an average F1 score of 88%. In our A/B tests, we observe that radiologists achieve between 9-25% higher accuracy by diagnosing with our product.

    In hospitals, DrAidTM can easily integrate with their systems, e.g. picture archiving and communication systems (PACS or medical imaging machines, to transfer images to the cloud and process them in near real-time. DrAidTM can also integrate directly with health information systems (HIS) to minimize onboarding efforts and costs. Front-end, we support web-based, desktop-based, Android and iOS-based apps, as well as via an DrAid™ Cognitive API service for any 3rd party integration.

    Once integrated, image upload and interpretation take place in the VinBrain cloud. To ensure privacy protection for patients and hospitals, we have built-in AI pre-processor models to remove any PII (Personal Identifiable Information) to stay compliant with medical privacy laws. As for security, data in DrAidTM is encrypted in transit via HTTPS and at rest in the cloud.

    In detailed, information from Xray machines is transferred to VB Loader/VB OneBox following DICOM standards (information is still in the hospital network system). VB Loader/VB OneBox will remove any PII on DICOM file (including blackening patient information on the images and deleting patient information from DICOM medata) and use HTTPS to send DICOM to DrAid Cloud. Doctors will access DrAidTM by AI conclusion browser from Chrome via HTTPS for diagnosis.

    Our data center on PACS cloud has acquired the following security certificates: CIS Benchmarks, ISO 27001:2013: Information technology — Security techniques — Information security management systems — Requirements, ISO 22301:2019: Security and resilience — Business continuity management systems — Requirements, ISO 27017:2015: Information technology — Security techniques — Code of practice for information security controls based on ISO/IEC 27002 for cloud services; and PCI DSS. DICOM server follows two standards which are DICOM and HL7.

    In a situation where the hospital does not have existing PACS, VinBrain will store data in at least two independent places (offline and online) within Vietnam, and back up every 5 minutes with changes occurring. Data is encrypted using 256-bit AES encryption.

    After analyzing the uploaded X-ray, DrAidTM sends notifications to doctors if it detects any abnormalities in the images. Every finding from DrAidTM comes with a probability score, a standardized description and a heatmap identifying abnormal areas. For patients with multiple records, DrAidTM can compare and give detailed information about size and location changes over time.

    Doctors can also further interact with and analyze the medical image using various image analysis tools. Once the diagnosis is finalized, DrAidTM automatically generates a medical report that can be modified by typed or voice-based commands. Our medical report follows international standard format using NLP techniques.  The accuracy score of our voice recognition model in Vietnamese language medical domain is 6.6 WER (Word Error Rate) which is much better than Google’s general purpose Vietnamese voice recognition model at 22.1 WER in medical domain. Doctors can also share the images and report with their patient or refer the case to a second doctor by a secured link and QR code.

    Currently DrAid has been deployed in 82 hospitals and being actively used by 464 doctors in Vietnam. Till now more than 325,000 X-rays have been diagnosed with DrAid’s help. We are on track for deployment in 150 hospitals in Vietnam and 7 hospitals in Myanmar in 2021. We have also started US FDA submission process and hope to deploy DrAid to US hospitals/clinics after FDA approval.

    We are also organizing a joint X-ray diagnosis competition with Stanford for improving state of the art AI techniques in the world. An international organization called Friends for International TB Relief has selected us among top partners in the world for automated AI diagnosis of TB. It demonstrated diagnosis for TB with remarkable specificity (99%), sensitivity (90.1%) and F1 Score (90.5%). We are also currently working with FIT and the division of global TB of CDC USA on the computer-aided diagnosis protocol using AI in TB triage testing. The protocol is expected to be approved by CDC Atlanta in the 2nd Quarter of 2021. Once approved, it will be submitted to WHO and be officially recommended as a diagnosis tool for TB.

    In recognition of these achievements, we recently won the “Best Digital Solutions Make-in-Vietnam” award from the Government of Vietnam.

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