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Innovations in Integrated Health Care Plans
Two innovations in healthcare in integrated health care plans in treating patients include the use of big data to treat rare diseases and the use of artificial intelligence (AI) to deliver personalized radiation therapy. Because we were unable to find a third innovation, we are submitting this brief as a Partial Client Update.
BIG DATA TO TREAT RARE DISEASES
- The healthcare startup RDMD is using AI to analyze data from medical records to find commonalities in rare disease cases.
- Overview of the innovation:
- RDMD aggregates and analyzes medical records and sells the data to pharmaceutical companies to help them develop medicines. In exchange for access to the data, patients get their fragmented medical records organized into an app they can use to track their treatment and get second opinions.
- With RDMD’s app, a patient’s medical history, which is strewn across hospitals and health facilities, can be compiled, organized and synthesized. Handwritten physicians’ notes and faxes are digitized with optical character recognition, structuring the data for scientific research.
- RDMD lays out patients’ records in a disease-specific timeline that summarizes their data and can be kept updated, delivered to specialists for consultations, or shared with their family and caregivers.
- Issue that RDMD addresses:
- Over 7,000 rare diseases exist, affecting 1 in 10 people, and yet less than five percent of them have an FDA-approved therapy.
- Initial impact of RDMD:
- RDMD has 150 patients with neurofibromatosis, a disease that affects only one in 30,000 people.
- RDMD has raised $3 million to build a health-data repository for rare diseases.
AI TO DELIVER PERSONALIZED RADIATION THERAPY
- The Cleveland Clinic's new AI center uses medical scans and health records to personalize the dose of radiation therapy used to treat cancer patients.
- Overview of the innovation:
- The research team developed an AI framework based on patients' computerized tomography (CT) scans and electronic health records.
- The center aims to find new applications of AI for diagnostics, disease prediction, and treatment planning.
- Dr. Mohamed Abazeed says that this approach will help doctors tailor dosage schedules to patients to more effectively minimize side effects and maximized effectiveness.
- Issue that this technique addresses:
- This technique does not address an issue as much as it demonstrates Cleveland Clinic's position at the forefront of medical innovation, creating proactive solutions with technology.
- Initial impact:
- The framework was built using CT scans and the electronic health records of 944 lung cancer patients treated with high-dose radiation.
- Pre-treatment scans were input into a deep-learning model, which analyzed the scans to create an image signature that predicts treatment outcomes.
- This image signature was then combined with data from patient health records to generate a personalized radiation dose.
Research Strategy:
Your research team was only able to find two innovations in healthcare in integrated health care plans, which is why we are submitting this brief as a Partial Client Update. We specifically provide innovations in which integrated healthcare plans and health providers are working together to treat patients.
We implemented three strategies for finding the requested information.
First, we started by searching for precompiled information through survey or consumer reports, or case study analysis innovations in healthcare specifically in integrated healthcare plans. Our primary focus was to find precompiled information specifically about innovations in integrated health and information, insights, and data surrounding the process of innovation in integrated health plans. We discovered that almost all such articles discuss innovations regarding telehealth, Health Wearables, 3D Printing, and genomics, among others.
Our second strategy involved searching for data from medical and hospital care website that compiles healthcare plans services and looks for innovations in treating patients. However, most of the data found were not new, which was the first criteria in this research; the request asked for an "innovation" which is something new, a completely fresh capability, or ideas that resonate and excite people. So, this strategy failed to result in relevant information.
Last, we tried to look for information to be used as proxy data points by looking for the different users and tools used in integrated health care plans. The goal was to triangulate the required information through proxy or parallel data points. The data points included sharing of data and integration access to patients' records. We also tried to look for information for a bigger healthcare component, but the specific segment of integrated health care plans was not available. One reason for the limited availability of such information may be because healthcare companies do not want to publicize information about recent innovations for proprietary concerns.
Finally, we gathered the relevant available information to provide helpful findings for the client’s request. After developing a list of articles and blogs with information on innovations in healthcare, we sorted out these case studies in terms of relevance and consistency. We then listed out two of the most common innovation in healthcare in integrated healthcare plans and provided the information requested in the prompt for each of them.