I find this interesting, especially #6,7 & 9. Could something like this, generate specific treatment plans for chronic pain pt who have had their pain meds decreased or cut and BP increases and 4 or 5 different BP meds and their BP doesn’t change. Would the AI be smart enough, to realize the cause & effect of increased BP and the reduction of pain management and recommend that pain meds be restarted and recommend increased pain meds dose if the BP goes down some, but not down to expected BP range.
For those of you who watch the TV show Chicago Med, what they call OR 2.0 seems to have wall to wall large video screens and cameras and a AI interactive voice that monitors just about everything that goes on… including comparing the surgeon’s activity/movement as compare to their previous surgeries and have called out a surgeon that was not up to his “normal movement/proficiencies.
Of course, these AI program can be designed with biases, like prohibited from recommending the implementation or increasing opioids or control meds.
25 Ways Generative AI Will Change Healthcare
https://shulkinblog.com/f/twenty-ways-generative-ai-will-change-healthcare
It seems Generative AI (GA) is all that everyone is talking about. Some futurists are predicting major changes to the way we live our lives and others even suggest that we are facing an existential risk to mankind. The truth is that we are clearly in unchartered territory and none of us really know where this is going to lead.
There is no doubt that GA will be disruptive to healthcare’s status quo. As GA grows in sophistication, it will change or even eliminate many traditional healthcare roles. GA will also raise new concerns about ownership and privacy of patient data. And no doubt there will be other unintended consequences that arise from this technology. But the potential for improving care and outcomes is probably the most exciting to think about.
Rather than looking too far into my crystal ball, I’ve chosen to look at the most likely places we will see5 the impact of GA in healthcare. GA is already being used in a number of the areas that I have listed below. Where possible, I’ve identified companies that are already demonstrating results from their work.
1. Medical Imaging and Pathology – Generative AI will help will soon become standard of care in radiology and pathology to ensure more accurate diagnosis, improve the efficiency of processing and reading studies, and address workforce shortages. (Ibex is a company using AI to improve diagnostic accuracy in pathology readings)2.
2. Patient Empowerment and Navigation- GA will dramatically improve the ability of patients to get information about their health and treatment options. This will fundamentally change the nature of the patient-provider relationship GA will enable chatbots to create personalized medical advise and assistance for patients and enable more efficient navigation of the health system.(Galileo is allowing patients to connect with the right healthcare solution)
3. Remote Patient Monitoring- GA will increasingly be used to alert medical professionals to trends seen in vital signs, physiologic and patient reported data that can predict patient risk. It will also allow monitoring to become more autonomous independent of healthcare professionals. (Cadence is providing remote monitoring solutions and data analysis for several conditions like congestive heart failure and Kaia is providing analysis of data from musculoskeletal conditions)
4. Improved Diagnosis- GA will be used to analyze patient data (electronic patient records, laboratory test results, radiographic images, genomic data) to improve diagnostic accuracy.(Google Health/Deep Mind and Babylon Health are using machine learning to better match symptoms with diagnoses).
5. Drug Discovery- GA will help identify new drug candidates faster and cheaper than current methods (Saama is a company that is ingesting data and GA to dramatically improve the time required for drug discovering)
6. Personalized Treatment Plans- GA will generate specific treatment plans for patients based on medical history, lab data, and genetic makeup.
7. Reduce Drug Adverse Events- GA will be used to identify side effects and pharmacogenomic difference for patients taking multiple medications, OTC products, dietary supplements, and foods.
8. Fraud, Waste, and Abuse- GA will help detect fraud and inappropriate utilization through pattern recognition and data identification.
9 Health Risk Assessments- GA will be used to increasingly predict a patients risk of developing disease and help target preventative care and vaccine applicability.
10. Access to Care- GA will be used to help match supply and demand of healthcare services, address no-show rates, and better predict resource utilization in order to ensure more efficient and timely scheduling of services. (Dexcare is a company using technology to address access)
11. Reduced Documentation- GA will be able to create patient notes and complete other paperwork tasks that take time away from patient time with healthcare professionals. This will improve efficiency, the patient experience, and reduce professional burnout.
12. Virtual Assistants and Robotics- GA can create automated processes and robotic devices to speed workflow in clinical settings. These virtual assistants and new robotic innovations will make medical practices more efficient and help in a variety of ways including logistics and supply chain management. Robotic patient assistants will become commonplace in long term care and the home settings for assistive care services.
13. Regulatory Compliance- GA will enable simulation techniques and synthetic data to test new pharmaceuticals, devices, and digital strategies to examine real world evidence, speed regulatory approvals, and to ensure adequate post-marketing surveillance.
14. Pre-Authorization of Services- GA can efficiently run data from patient reported data, physician records, and other clinical sources to ensure compliance with guidelines and give rapid authorization to high costs services and products.
15. Medical Education and Simulation- GA be increasingly be used to train medical professionals, assess competencies, and test new devices and procedures to improve safety ensure faster regulatory approval (Companies like Indegene and Edocate are increasingly using interactive data and scientific information to provide interactive education)
16. Medical Billing – GA will help with revenue cycle management by improving the accuracy of billing, coding records, finding data from various clinical sources for accurate risk adjustments, and in ensuring accurate revenue capture. (Cedar is using data with behavioral economics to improve transparency and the billing experience).
17. Clinical Trial Design- GA can run various scenarios and use synthetic data to test and identify clinical trial designs with high precision for recruitment, data analysis, and compliance with protocols.(Trinetx is a company that is using patient data to develop better clinical trials and drug discovery and MD Clone is creating synthetic data sets to better test innovation and new discoveries}
18. Surgical Performance- using video capture of surgical procedures, GA can identify unnecessary variations in surgical performance, identify preventable postoperative complications and improve surgical operating times by predicting surgical resource needs. (Theator is implementing surgical learning systems to improve operative performance)
19. Improving Outcomes in Behavioral Health – With natural language processing, GA can analyze behavioral health sessions to identify more effective treatment interventions (Eleos uses NPL and AI to identify value based behavioral healthcare and reduce inefficient care)..
20. Reducing Disparities and Addressing Disabilities- GA will not only help identify where disparities in care exist through data analysis but it will also create solutions. Through targeted outreach, educational and behavioral strategies that are targeted to specific needs of communities, more effective health interventions can be implemented. (Companies like CareJourney and Datavant are using data from a variety of sources to identify opportunities for improvement and Voiceitt is using AI to facilitate better communication for those with severe speech disorders).
21. Reducing Gaps in Care- When it comes to chronic illness management, GA can more easily use data and algorhythms to identify gaps in care that often result in poorer outcomes for patients.
22. Early Intervention- GA can use unstructured data and image analyses to identify patients a risk that would benefit from early intervention. We are already seeing this with kidney disease, sepsis, early stroke identification, and even suicide prevention. (AIdoc is using GA to identify early intervention for patients with stoke and a number of other conditions)
23. Improving Point of Care Testing – GA will allow the smartphone to become an even more useful tool for diagnostic evaluations. With improved molecular testing and lateral flow analyses, GA will allow more sophisticated testing to be run in the home setting. (Ixlayer offers an enterprise system for managing data for point of care testing and TytoCare brings the ability to test right in the home).
24.. Reducing the Cost of Care- GA can help develop tools to identify “low value” care. GA will help already existing technology getter better at identifying care that is not appropriate or effective and channel resources into areas where effective care can best targeted.
25. Reducing Medical Errors- Using predictive modeling, GA can help identify before they occur and create early warning systems to alert healthcare professionals and patients (or caregivers) of high risk situations.(Sparta Science is a company using predictive data to identifying patients at risk for falls and in speeding rehabilitation).
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