For the data-intensive healthcare industry, the power and versatility of advanced analytics can’t be overstated. The confluence of big data, technology, and the application of statistical theories can give a competitive advantage to impact profitability across the healthcare services sector. Advanced analytics is critical for healthcare payers that want to make proactive changes in managing their populations to promote better health and outcomes.
A few broad benefits of advanced analytics in the healthcare world
Data and technology is rapidly changing—therefore, it is important to be adaptable to customize predictive analytics applications in healthcare. There are certain unique applications within the world of healthcare that are readily attainable, including:
• Population Health-focused Analytics. The complexity of factors influencing health outcomes can yield real issues related to morbidity and mortality. Targeted analytics can help shape cohort analyses related to spend, episodes of care and other root cause analyses to improve processes related to care and utilization management.
• Fraud, Waste and Abuse (FWA). Analytics are an increasingly important lever to be proactive related to FWA. Traditional outlier detection algorithms provide a front-line defense; however, hidden relationships and correlations can still exist. Advanced analytics can provide a robust way to show hidden relationships of sub cohorts to proactively impact waste.
• Pharmacy and Cost Control. Pharmacy continues to be a significant cost for managed care payers. The ability of healthcare analytics to drill down into specific data and identify costly drugs, then find less-expensive generic replacements, is powerful. Also, advanced analytics Allow for rapid and targeted insights for cost reduction opportunities while positively impacting outcomes.
How predictive analytics can lead to solutions and benefits
The insights and reporting offered by healthcare analytics could, for example, help managed care executive address persistent volatility in cost for both medical and pharmacy claims with a lens on population sub cohorts to positively impact outcomes. Predictive analytics are a powerful way to enhance decision making with confidence. By leveraging existing claims data, it is possible to creatively find options to lower costs while improving population health. Advanced analytics and emerging technologies provide this option.
A customized, well-implemented predictive analytics solution should both address an immediate problem and make sure it doesn’t return in the future. Healthcare executives should be able to recognize the positive change that can arise from taking the right approach to predictive analytics, and look for areas where it could potentially improve their operations—from reducing pharmacy costs to improving patient health outcomes.
Mike Kim is a director at AArete, a global consultancy specializing in data-informed performance improvement, and heads its Center of Data Excellence. He can be reached at firstname.lastname@example.org.