Over the last few weeks, political campaign rallies, social justice protests, holiday celebrations, and economic reopenings have brought more people into closer proximity than at any time since social distancing measures took effect in March. Coupled with perhaps less diligent adherence to hand washing and facemask wearing, the result was predictable: a second wave of COVID-19 cases has erupted. The U.S. Centers for Disease Control (CDC) monitors reported cases, and can identify hotspots. Unfortunately, health plans that do not partner with strong data-analysis partners cannot use CDC data to efficiently educate and treat their members who are at the greatest risk.
Health plans without access to analysis of CDC data put their case managers at a distinct disadvantage. A recent article in the Journal of the American Medical Association notes that “the current approach to quality and safety measurement remains too labor intensive, contains significant data lags, and lacks sufficient standardization that allows for rapid sharing of data.” A typical 45-day lag time can prove critical during a health crisis such as COVID-19. Without a data-driven clinical partner, plans lack the resources to operationalize internal and external data sources in ways that can inform treatment decisions and prioritize encounters based on comorbidity status, geography, and other factors.
A Better Approach
Health plans that harness artificial intelligence and powerful algorithms to activate data can deliver better clinical outcomes. The data is there for anyone to use, but only data science and AI can make it operational. For instance, certified diabetes educators (CDE) may want to educate their plan’s members on precautions to take in the wake of the pandemic and what to do if they think they might have been exposed. Without a data-driven approach, they may contact diabetes members by age or some other arbitrary method, moving down a spreadsheet. But using public and internal data, the CDE can find granular information to help their segment their patients
- Which zip codes have experienced spikes in COVID-19 cases
- Which members share households with confirmed COVID-19 patients
- Which patients have comorbidities that increase their risk of complications or mortality in the event they contract the virus
These and other risk factors can be overlaid with patient lists so the CDE can rank clients based on their susceptibility to the virus. They can prioritize their outreach, first scheduling encounters to educate and test those most at risk.
The Vital Data Technology Advantage
Vital Data Technology’s cloud-based system readily captures and incorporates and analyzes external data from CDC and other sources, making it immediately available to enrich internal data for more robust and deeper understanding of trends in COVID-19’s spread. We have developed several models to help our health plan partners fight the disease.
For information on these models and how Vital Data Technology can help your care managers stratify and prioritize outreach efforts, read more here or contact us below.
Keep On Learning
Laura Barnett, BSN, RN, CDE
Vice President Client Partnerships
Laura is the Vice President of Client Partnerships at Vital Data Technology and product owner of Affinitē PlanLink. In this role, Laura oversees all aspects of the customer life-cycle, serving as an ambassador for all clients and partners to ensure a world-class customer experience. With her career spanning over 20 years in healthcare ranging from nursing leadership, medical device sales, and healthcare information technology account development, and partner management, her clinically-founded expertise ensures her astute alignment with health plan goals.
Laura is nearing completion of her Masters of Health System Information Management from Texas Women’s University, and she holds her BSN, Nursing from The University of Texas Health Science Center San Antonio.