Using advanced analytics to manage patient risk and deliver value-based care

To improve health outcomes and reduce costs, the US healthcare system must move away from fee-for-service models and provide value-based, proactive comprehensive care (VBC). High-quality data and advanced analytics that produce actionable insights into patients’ medical and social needs are a critical part of this transition.

Focus on patient outcomes

In a values-based system, patient outcomes, patient experience and quality of care become the drivers of clinical care delivery. Costly, low-impact services such as emergency room visits for conditions treatable by primary care physicians can be avoided by improving access to primary care – annual wellness visits, screening and preventative medical procedures – and chronic care management. VBC contracts actively support the transition from unnecessary reliance on emergency services to appropriate use through incentives for preventive care and the achievement of quality goals.

Health systems fully evolving in the area of ​​GBV benefit from predictions about future patient health needs and information about early interventions that can maintain health over time. Using artificial intelligence, providers can predict patient outcomes and risk by integrating data in various areas, including demographics, social determinants of health, utilization, claims, and patient information. consumers to identify necessary interventions such as:

  • Personalized education and communication with patients
  • Improving access to preventive services
  • Chronic Disease Management
  • Automated pre-visit planning
  • Integration of ancillary services such as nutrition counseling and behavioral health
  • Referral to social services

Management of patients at risk

By using advanced analytics to drive population health management and risk stratification, healthcare systems can meet the challenges of disease burden and tight cost controls. Health systems should also leverage analytics to ensure appropriate reimbursement for the extra work required to deliver BCV.

For example, analytical tools are needed to calculate risk scores such as the hierarchical condition category score and the risk adjustment factor. Proper coding literally pays off for healthcare systems. With an understanding and documentation of patients’ total disease burden, providers not only expand their capabilities to improve health outcomes, but they also increase revenue per member per month for patients, ensuring that they receive a refund in accordance with the necessary procedures.

Addressing social drivers of health outcomes

Since the onset of the COVID-19 pandemic, the health industry has become more aware of the critical link between social determinants and overall health and well-being. As cases rose at first, primary care and specialist visits declined and cancer screenings were reduced. Providers quickly recognized that disadvantaged subpopulations and people with chronic conditions needed rapid diagnosis and patient-centered treatment plans to optimize care, improve performance on quality and utilization measures and maximize reimbursement.

The Centers for Medicare & Medicaid Services is considering new measures to ensure data capture on food insecurity, housing instability, transportation, and interpersonal safety to help health plans be more proactive and offer more results-based reimbursements. Advanced analytics can ingest this information and improve health plans’ readiness to take on financial BCV risk, reduce costs, manage health inequities, and improve quality of care. They represent an opportunity for healthcare organizations to respond to the imperative realized through COVID – to create more accessible, affordable and equitable healthcare that ties payment more closely to value.

About the Author

Michael Dulin, MD, PhD, Chief Medical Officer, Gray Matter Analytics. Dr. Dulin is a nationally recognized leader in the field of health information technology and the application of analytics and outcomes research to improve the delivery of care and make improve the health of the population. He is currently a professor at UNC Charlotte in the Department of Public Health Sciences where he directs the Academy for Population Health Innovation. As Medical Director of Gray Matter Analytics, Dr. Dulin drives the company’s growth and success by directing clinical activities across the organization. He leads the overall clinical strategy and design of the CoreTechs® Healthcare Analytics platform and Gray Matters analytics solutions and teaches clients how to leverage healthcare data analytics to advance their clinical outcomes, operational and financial. He began his career as an electrical and biomedical engineer and earned his doctorate in neurophysiology before becoming a primary care physician.

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