Using Advanced Analytics to Address Patient Risk and Deliver Value-based Care

Print Friendly, PDF & Email

To improve health outcomes and lower cost, the U.S. healthcare system must abandon fee for service models and provide comprehensive, proactive value-based care (VBC). High-quality data and advanced analytics that produce actionable insights into patients’ medical and social needs are an essential building block for this transition. 

Putting patient outcomes first 

In a value-based system, patient outcomes, patient experience and quality of care become the drivers for clinical care delivery. High-cost, low-impact services such as emergency department (ED) visits for conditions treatable by primary care physicians can be avoided by improved access to primary care — annual wellness visits, screening and preventive medical procedures — and chronic care management. VBC contracts actively support the transition from unnecessary reliance on ED service to appropriate utilization through incentives for preventive care and quality goals achievement.

Health systems moving fully into the domain of VBC benefit from predictions about patients’ future health needs and insights to early interventions that can maintain health over time. With artificial intelligence, providers can forecast outcomes and a patient’s risk by integrating data across various domains, including demographics, social determinants of health, utilization, claims and consumer information to identify needed interventions such as:

  • Personalized patient outreach and communication
  • Improved 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

Managing patients at risk

Using advanced analytics to drive population health management and risk stratification, health systems can meet the challenges of illness burdens and tenuous cost controls. Health systems also must leverage analytics to ensure appropriate reimbursement for the additional work required to provide VBC.

For example, analytic 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 health systems. With an understanding and documentation of patients’ full illness burden, providers not only expand their abilities to improve health outcomes, but they grow per-member-per-month revenue for patients, ensuring they receive reimbursement in line with necessary procedures.

Addressing social drivers of health outcomes

Since the start of the COVID-19 pandemic, the healthcare industry has become more aware of the critical link between social determinants and overall health and well-being. As cases surged in the early days, primary care and specialist visits diminished and cancer screenings were curtailed. Providers soon recognized that disadvantaged subpopulations and individuals with chronic disease needed timely diagnosis and patient-centric treatment plans to optimize care, lift quality and utilization measures’ performance and maximize reimbursement. 

The Centers for Medicare & Medicaid Services is considering new measures to ensure the capture of data about food insecurity, housing instability, transportation and interpersonal safety to help health plans be more proactive and offer more outcome-based reimbursements. Advanced analytics can ingest this information and raise the readiness of health plans to take on VBC financial risk, drive down costs, manage health inequity and elevate quality of care. They represent an opportunity for healthcare organizations to meet the imperative realized through COVID — to create more accessible, affordable and equitable healthcare that links 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 application of analytics and outcomes research to improve care delivery and advance population health. 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 Chief Medical Officer for Gray Matter Analytics, Dr. Dulin directs the company’s growth and success by leading the clinical activities throughout the organization. He drives overall clinical strategy and design for Gray Matters’ CoreTechs® Healthcare Analytics platform and Analytics Solutions and educates the customer base on how to leverage healthcare data analytics to advance their clinical, operational and financial outcomes. He started his career as an Electrical and Biomedical Engineer and received his PhD in Neurophysiology prior to becoming a primary care physician.

Sign up for the free insideAI News newsletter.

Join us on Twitter: @InsideBigData1 – https://twitter.com/InsideBigData1

Speak Your Mind

*