Artemis by Nomi Health’s Post

Does racial bias exist in risk adjustment algorithms used across the healthcare industry?     Risk adjustment algorithms can impact care management initiatives, as well as payments to payers, managed care organizations, and providers.     Don’t miss Milliman Principal and consulting actuary Erica Baird (Erica Rode), who leads MARA’s R&D team, in this upcoming SAS webinar on March 6th at 9:10 am ET!     In the webinar, Erica will talk about:  ▪ Potential causes and consequences of bias in risk adjustment models   ▪ How SAS and open-source tools were used to test Milliman Advanced Risk Adjusters™ (MARA) risk adjustment models for racial bias  ▪ How racial bias can manifest in healthcare AI/ML models  ▪ What actions can be taken in the model development and testing phases to mitigate racial bias    Sign up using this link:  https://bit.ly/48BkIxf. 

I'm excited to share that I will be speaking at this week's MASI fall conference! My session will be covering insights into AI in Medical Underwriting & Health Risk Mitigation. If you won't be able to attend, please reach out to me to get the highlights from the presentation: ryan.chapman@hcare.net #MASI #MASI2024 #HealthcareAI #AI

We're excited to share that Ryan Chapman will be speaking at this week's MASI fall conference! He will be sharing insight into AI in Medical Underwriting & Health Risk Mitigation. If you won't be able to attend, please reach out to Ryan to get the highlights of his presentation: ryan.chapman@hcare.net #MASI #MASI2024 #HealthcareAI #AI

We're excited to share that Ryan Chapman will be speaking at this week's MASI fall conference! He will be sharing insight into AI in Medical Underwriting & Health Risk Mitigation. If you won't be able to attend, please reach out to Ryan to get the highlights of his presentation: ryan.chapman@hcare.net #MASI #MASI2024 #HealthcareAI #AI

Combating #UnstructuredData is the rite of passage for all data exploration. Join Sribatsa D. from Memorial Sloan Kettering Cancer Center who talks about "De-identifying Unstructured Data" at #HDAA2024. "Data is core to healthcare research. A large percentage of data is available as unstructured data. Unstructured is available from sources including doctors’ notes, clinical trial reports, or radiology reports and images. Structured data needs to be extracted from these sources to become useful. However, the extracted data contains PHI. To comply with the Health Insurance Portability and Accountability Act (HIPAA), any Personally Identifiable Health Information (PHI) must be removed or de-identified before it can be shared for research. To address this challenge, this paper proposes tools and methods for data de-identification from unstructured data that considers the need for HIPAA compliance. The method involves the use of de-identification techniques, such as masking or substitution, to remove or obfuscate PHI data in the production data. The resulting de-identified data can then be shared for research without compromising patient privacy or violating HIPAA regulations. Overall, this paper presents a practical solution for healthcare providers who need to generate de-identified data from unstructured data while maintaining HIPAA compliance and ensuring patient privacy. At Memorial Sloan Kettering Cancer Center, we are in the early stages of modernizing data de-identification tool suite. We hope to implement few use cases by the time we attend the convention and to share the best practices." #DataScience #DataAnalytics #HDAA #AnalyticsTakesFlight #healthdata #healthcareanalytics

Harnessing the Power Within Healthcare Data See how Careever is arming insurers with integrated analytics on treatments, outcomes, and costs - enabling smarter global healthcare delivery through granular, actionable insights. Get an inside look as our analytics leads explain how our platform is empowering insurers to: The future of healthcare lies in data mining and analytics illumination. Discover how Careever puts this power directly into insurers' hands. #healthinsurance #healthdata #analytics #insurtech #innovation #digitalhealth

At HIMSS, Unlock the Power of Your Data Data is the currency of the next century and nowhere are health data and data management processes discussed, analyzed and examined more than at the annual HIMSS Annual Conference and Exhibition. I wrote this in Healthcare IT News seven years ago and it is certainly still true today. Interoperability is more than simply the exchange of health data, but once standards-based exchange is achieved then it is the use of these data that comes into focus. I am sure that many examples of progress with regards to interoperability will be showcased at #HIMM24

himss: data is currency power of data

On the ‘Prudential + Human API: Driving Innovation and Business Value with Digital Data’ webinar session, Nick Zambruno sat down with Gretchen Juneau to discuss how Prudential adopted and has seen tremendous success with digital health data. In case you missed it, we have recapped it here!

Payers are increasingly turning to advanced actuarial models to enhance their decision-making processes and optimize patient outcomes. By integrating consumer data into these models, we're not just predicting costs; we're reshaping how healthcare is delivered and financed. Here are some key use cases where advanced actuarial modeling stands out: 1. **Personalized Premium Setting**: Leveraging consumer behavior data allows for more accurate and individualized premium calculations. By analyzing lifestyle choices, purchasing behaviors, and wellness activities, payers can tailor premiums that reflect the true risk and potential healthcare costs of individuals. 2. **Enhanced Risk Assessment**: Consumer data provides deeper insights into the social determinants of health, offering a broader perspective on risk factors. Actuarial models that incorporate this data can better predict high-cost events, leading to more effective risk management strategies. 3. **Targeted Health Interventions**: With a richer dataset, models can identify at-risk populations and guide the deployment of targeted intervention programs. This proactive approach not only improves patient health but also reduces unnecessary expenditures by preventing adverse health events before they occur. 4. **Improved Member Engagement**: Understanding consumer preferences and behaviors helps payers design more engaging and effective communication strategies. This results in higher member satisfaction and retention rates, as interventions and communications are more likely to resonate and encourage positive health behaviors. 5. **Fraud Detection and Prevention**: Advanced modeling techniques can detect anomalies in claims data that may indicate fraudulent activities. By integrating consumer data, these models become more adept at spotting irregular patterns, safeguarding against losses and ensuring financial stability. The integration of consumer data into actuarial models is not without challenges, particularly around data privacy and security. However, with robust data governance frameworks, we can harness the full potential of this data while upholding the highest standards of consumer protection. Let's connect and discuss how we can further advance the role of actuarial science in healthcare. The future is data-driven, and together, we can lead the way. #ActuarialScience #HealthcareData #DataAnalytics #HealthcareInnovation #ConsumerData