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ACO Success Made Simple 

Accountable Care Organizations (ACOs) are at the forefront of the shift to value-based care, tasked with improving outcomes while reducing costs. But for many ACO leaders, success feels elusive.  

Yet, the results are clear: when ACOs get it right, the impact is profound. MSSP has been financially beneficial for both Medicare and ACOs, with 82% of participants achieving a positive savings rate. 4 These savings weren’t just financial—they reflected better care coordination, fewer emergency visits, and improved chronic disease management.  

The Challenge of ACO Participation 

Participating in MSSP or ACO REACH can be a balancing act—navigating quality reporting, managing cost benchmarks, and addressing equity requirements—all while caring for patients. Add on complex reporting requirements, fragmented data systems, and rising clinician burnout, the promise of coordinated, high-quality care can be difficult to realize. 

Without the right tools, ACO participation can feel like an administrative weight. But with AI-powered platforms like BettrAi, ACOs can turn complexity into clarity and accelerate performance. 

The Burnout Barrier 

One of the biggest threats to ACO performance is clinician burnout, with 43.2% reporting at least 1 symptom of burnout in 2024. 9 Burnout leads to lower productivity, higher turnover, and diminished patient satisfaction—all of which undermine the goals of value-based care. 11 

Burnout isn’t just a personal issue—it’s a systemic one. The administrative burden of documentation, reporting, and care coordination often falls on providers already stretched thin. Without relief, even the most well-intentioned ACOs struggle to meet performance benchmarks. 

So how do successful ACOs make it work? Increasingly, the answer lies in smart technology, strategic data use, and a renewed focus on provider well-being. 

Predicting Financial Performance: Seeing Risk Before It Escalates 

Another key to ACO success is predictive analytics. By analyzing claims and clinical data, ACOs can identify rising-risk patients before they become high-cost cases. This enables early intervention, targeted care management, and reduced hospitalizations. 5 

However, not all risk models are created equal. A study in Health Affairs found that coding-driven risk scores often outpace actual health status changes, suggesting that data quality and methodology matter. 6 ACOs must ensure their analytics are not only predictive but clinically meaningful.  

When done right, predictive modeling enables proactive care—helping ACOs reduce avoidable costs and improve outcomes. By identifying high-risk patients and tailoring interventions to their specific needs, healthcare providers can foster a more proactive approach to health management.  

Virtual Health Assistants, like Sophie 

Technology isn’t just about automation—it’s about connection. Virtual health assistants (VHAs) like Sophie, BettrAi’s AI-powered engagement tool, are transforming how care teams interact with patients. Sophie supports outreach, education, and care plan adherence, helping patients stay engaged between visits. By automating routine tasks and enabling timely interventions, VHAs free up clinical teams to focus on complex care, while ensuring patients receive consistent, personalized support. 

In a recent study evaluating the efficacy of patient engagement solutions, they were found to have reduced emergency department visits by 35% and were associated with a 45% decrease in mortality rates for chronic disease. 61% of patients reported that AI-powered chatbots helped with symptom self-management, reducing calls to their care team to allow them to focus on direct patient care. 1  

Structured follow-up calls led by nonphysician providers—similar to Sophie’s capabilities—increased 7-day post-discharge follow-up rates from 79% to 92%, while reducing in-person visits and maintaining comparable 30-day outcomes. This kind of efficiency is critical for ACOs managing large populations with limited staff. 8 

When ACOs leverage AI-enabled platforms, they see measurable impact—quality reporting time can be cut by up to 50%, 10 freeing staff to focus on patient care. 

Telemedicine: A Proven Tool for Reducing Readmissions 

During the COVID-19 pandemic, telemedicine emerged as a lifeline for patients with chronic conditions. A study of heart failure patients found that telemedicine follow-up within 14 days of discharge reduced 30-day readmissions by 45%, compared to no follow-up. And a remote monitoring program led to a 50% reduction in 30-day readmissions for patients with congestive heart failure. 8 

This is more than a pandemic workaround—it’s a scalable strategy. For ACOs managing high-risk populations, telehealth offers a cost-effective way to maintain continuity of care, especially in rural or underserved areas. 

The BettrAi Solution: Simplifying the Journey 

  • AI modeling for savings projections, cost-driver analysis and identifying rising risk patients 
  • Coordinating Care with AI Virtual Assistant Sophie supports patient outreach and adherence. Empowering teams and patients. 
  • Customized and personalized care management programs from complex, SDOH, CCM and RPM 
  • Automating Reporting & Compliance – Real-time dashboards for HEDIS and STAR measure tracking 
  • Unifying Data – Seamless integration across EHRs and payers for a single source of truth 

Ready to transform your ACO performance? Schedule a consultation with BettrAi and see how our AI-driven platform can make participation easier, improve outcomes, and maximize your shared savings. 
 
 

References 

  1. Al-Siddiq W. Accelerating healthcare with AI: Reducing administrative burdens. Forbes. Published January 7, 2025. https://www.forbes.com/councils/forbesbusinesscouncil/2025/01/07/accelerating-healthcare-with-ai-reducing-administrative-burdens/ .  
  1. American Heart Association. Remote Monitoring Reduces Readmissions in Heart Failure (https://www.ahajournals.org/doi/10.1161/CIRCHEARTFAILURE.119.006376) 
  1. AMA Digital Health Research 2023. Physician Time Saved with AI Tools (https://www.ama-assn.org/practice-management/digital/ama-digital-health-study) 
  1. CMS. 2024 Shared Savings Program Results: Program Data | CMS  
  1. Gaireview.com. Predictive Analytics for Population Health Management – GenAI Review. GenAI Review – Pioneering the Generative AI Frontier. Published September 15, 2025. Accessed September 24, 2025. https://gaireview.com/predictive-analytics-for-population-health-management/ 
  1. Health Affairs. Predictive Analytics for Population Health Management (https://www.healthaffairs.org/doi/10.1377/hlthaff.2019.00020) 
  1. 1.Lee KK, Thomas RC, Tan TC, Leong TK, Steimle A, Go AS. The heart failure readmission intervention by variable early follow-up (THRIVE) study. Circulation: Cardiovascular Quality and Outcomes. 2020;13(10):719-729. doi:https://doi.org/10.1161/circoutcomes.120.006553 
  1. ‌Klein HE. Remote Monitoring Program Cuts Heart Failure Readmissions in Half. AJMC. Published October 11, 2024. Accessed October 28, 2024. https://www.ajmc.com/view/remote-monitoring-program-cuts-heart-failure-readmissions-in-half 
  1. ‌Nearly half of doctors report burnout, but there is some progress, survey finds. OncLive. Published January 25, 2024. https://www.chiefhealthcareexecutive.com/view/nearly-half-of-doctors-report-burnout-but-there-is-some-progress-survey-finds  
  1. ‌Tech Autonmis. Can an AI Data Platform Cut Reporting Time by 50%? Medium. Published June 7, 2025. Accessed September 24, 2025. https://medium.com/%40tech_autonmis/can-an-ai-data-platform-cut-reporting-time-by-50-2015231c6591 
  1. U.S. physician burnout hits lowest rate since COVID-19. American Medical Association. Published May 2025. https://www.ama-assn.org/practice-management/physician-health/us-physician-burnout-hits-lowest-rate-covid-19