You might be surprised that the US spends around $4.5 trillion annually on healthcare, averaging $13,493 per person, and placing it ahead of any other developed country in terms of healthcare expenditure per capita! Increasing from 5% of GDP in 1962 to 17% in 2022, healthcare costs have experienced a steady ascent in the past few decades.
In the ever-evolving world of healthcare, controlling costs while delivering top-notch care is the ultimate goal. In an attempt to achieve this, healthcare providers and insurers focus on two key metrics; Total Cost of Care (TCOC) and Per Member Per Month (PMPM) costs. According to the National Association Of Insurance Commissioners, claims Per Member Per Month was reported at 44.900 USD in 2022, compared to 43.000 USD for 2021.
Analysing TCOC helps organizations understand precisely where their value-based care initiatives should be focused for the most efficient use of resources. Fortunately, the rise of data analytics and artificial intelligence (AI) offers innovative ways to achieve this goal.
AI’s Role in Lowering PMPM and TCOC
The insights generated by advanced analytics help healthcare providers and insurers reduce Total Cost of Care (TCOC) and Per Member Per Month (PMPM) costs by identifying high-risk patients, delivering personalized interventions, optimizing resource allocation and streamlining administrative processes.
Felix’s Value-Based Care tool is designed to enhance the quality and effectiveness of healthcare services for providers and payers alike. Aimed at preventive care and management of chronic conditions, our solution allows healthcare organizations to deliver targeted interventions, identify at-risk patients, and monitor patient health to achieve superior outcomes. By harnessing the power of advanced analytics and streamlined care management workflows, our model optimizes care coordination, lowers costs, and fosters improved health outcomes for patients.
Now, let’s see how data analytics and AI can help minimize costs and improve care.
Predictive Analytics: Population Health Management
Imagine being able to predict health problems before they become serious. Predictive analytics makes this possible by analyzing historical data to forecast future health events.
Felix’s Value-Based Care system uses predictive analytics and risk stratification algorithms to identify high-risk patients and allowing for targeted interventions and focused care efforts. By allowing healthcare providers to proactively manage patient health and optimize treatment plans at an early stage, it prevents expensive treatments, costly emergency room visits and hospitalizations for the patient down the road. A report showed that value-based care patients saw a 23.2% cost savings compared to original Medicare, averaging $527 in savings per patient per year. The patients were also said to have had 30.1% fewer hospital admissions compared to original Medicare beneficiaries.
Personalized Treatment: Tailoring Care to Individuals
Gone are the days of one-size-fits-all healthcare. AI and data analytics allow for the creation of personalized treatment plans that consider each patient’s unique needs.Customized care plans ensure patients get the right treatments, reducing unnecessary tests and procedures, which ultimately leads to better health outcomes and lowers overall healthcare costs.
Smart Resource Management: Getting the Most from What You Have
AI can optimize the use of resources, ensuring they are used efficiently and effectively.By creating optimal staff schedules, AI tools can reduce overtime costs and ensuring proper coverage. Predictive analytics can also forecast the demand for supplies, reducing waste and ensuring availability when and where they are needed.
Engaging Patients: Keeping Patients Involved in Their Own Care
When patients are engaged in their care, they’re more likely to stick to their treatment plans, leading to better outcomes and lower costs. Felix Value Based Care tool engages members through personalized outreach and communication to promote preventative care and early intervention.
AI-powered telehealth services offer convenient, cost-effective care options, reducing the need for in-person visits. They are programmed to provide personalized health tips, reminders, and support, promoting adherence to treatment plans.
Financial Insights: Understanding and Controlling Costs
AI-powered data analytics provide organizations with a clear picture of healthcare costs, allowing them to make informed financial decisions.A thorough cost analysis uncovers the cost-effectiveness of different treatments and helps in selecting the most economical options. Additionally, predictive models can aid in budget forecasting by predicting future costs and aiding in financial planning and resource allocation.
Conclusion
As we can see, by improving the quality of healthcare and reducing its associated costs, value-based care has a significant impact on both Per Member Per Month (PMPM) costs and Total Cost of Care (TCOC). Similarly, poor population health management has a negative correlation on both Per Member Per Month (PMPM) costs and Total Cost of Care (TCOC).
The increasing burden of chronic diseases among the population has propelled the market growth for value-based healthcare to reduce unnecessary healthcare spending. A 2023 report found that the number of patients receiving care under value based models has increased by 2.3 million in the last decade.
By leveraging population health management techniques and value based care models that focus on early intervention, personalized treatments, and optimized resource allocation, healthcare providers can deliver high-quality care while keeping costs under control. With the power of AI, reducing the Total Cost of Care (TCOC) and Per Member Per Month (PMPM) costs has become an achievable goal. As these technologies continue to evolve, their impact on healthcare will only grow, making for a healthier and more cost-effective future for everyone.