Harnessing Data Science in Healthcare with Stuart Piltch

Risk Strategies Consulting promotes that an effective use of data science, which is also a part of machine learning technology, is to meaningfully integrate, enrich, categorize, and curate data in a method that helps users create a more fact-based platform from which to measure value and transform initiatives to benefit stakeholders.

Moreover, data science is a tool and one that does not produce all the answers. In fact, data science may produce as many questions as conclusions; however, those who use data science well know that the healthcare industry stands to gain a richer understanding and insights into drivers of healthcare outcomes and the experiences individuals have as they navigate the care continuum. The use of data must be well-coordinated across care teams, technologists, and administrators, so that identification of patients, prioritization of conditions, transitions of care, and digital and non-digital communications are effective, methodical, and patient-centered within a patient population.

Health industry experts including benefit consultants must make the necessary investments into buying, building, or renting up-to-date data science tools and capabilities, and making sure their clients know about these investments is an imperative to differentiate them in the marketplace. These technology investments must be paired with human capital capabilities to thoughtful, actionable insights with short-term and long-term knowable outcomes.

Risk Strategies Consulting applies a diversified approach and mix of tools within data science, coupled with a blend of staff talent, to research and curate the healthcare data that our clients demand. We promote the use of a deep-learning platform, predictive modeling, artificial intelligence (AI), and cloud computing strategies that position users to harness pertinent health information, so that a revealing view of their population is possible, making the development of actional outcomes more realistic. The crux of data usage is that we can learn intended and unintended consequences of our initiatives, and we can study the knowable outcomes as well as better foresee the unknowable outcomes.

Emerging Technologies: AI, Machine Learning (ML) and Natural Language Processing (NLP)

AI, ML, and NLP are being leveraged in multiple capacities to standardize operational efficiencies, predict adverse health outcomes, train medical professionals, and augment the pharmaceutical discovery and development process. AI is a collection of technologies including ML and NLP, which work to imitate human behavior. Risk Strategies Consulting believes with a framework that leverages clinical outcomes, member experience, and health equity within a whole health approach, AI and ML can support the patient journey across their ecosystem by identifying the emerging risk and using a personalized approach to managing/ coordinating resources and care.

Additionally, as technology takes a more formidable role in healthcare, more nuanced regulations and safeguards will need to be put into place. October 2023 saw the enactment of an executive order from President Biden establishing safety and security standards around AI. March 2023 saw the announcement of a cybersecurity implementation guide, created by DHHS in conjunction with the cybersecurity and preparedness focused working groups.

Implications of Data Science

Health Equity and Legislation

Noteworthily in 2023, the Centers for Medicare and Medicaid Services (CMS) released an updated Framework for Health Equity, directly impacting the quality and efficacy of care and outcomes throughout the ecosystem. Furthermore in 2024, the Inpatient Prospective Payment System and Long-Term Care Hospital Prospective Payment System final rule updated Medicare payments for quality measures that foster safety, equity, and reduce preventable harm in the hospital setting. Risk Strategies Consulting also sees the need for similar requirements across the commercial market, and we find numerous opportunities to address social determinants of health (SDOH).

With increased costs to plan sponsors from legislative efforts supporting government pricing negotiation, specialty drug spend, and Food and Drug Administration accelerated approval pathways, having pharmacy benefit manager strategies that address pipeline, formulary, medical benefit drug management, and total person management with sophisticated data integration of traditional and non-traditional assets is crucial.

Audit

As the healthcare industry becomes increasingly complex, the depth and types of required auditing become more complex. Healthcare systems face unique challenges and require more efficient auditing approaches. Innovation in financial, operational, and clinical auditing will help bring increased accountability to an industry struggling with outdated claims systems and technology platforms, patient-value transitions, and a flawed “status quo.” Forward-thinking consultants such as Risk Strategies Consulting advise adopting innovative auditing approaches to help healthcare organizations deal with outdated systems and mitigate potential difficulties.

Provider Network Valuation

Network designs must be evaluated for quality at the provider level, sustainability, potential disruption from market strongholds, and contracting hurdles that may prohibit volume direction or tiering. Vertical consolidation offers the opportunity to improve interoperability, promote value frameworks, identify solutions for health equity, and provide a schematic for horizontal impact. However, the critical to mass opportunity is incumbent on managing, modeling, and curating real world data for a longitudinal view of patients, quality of care, network performance, pharmaceutical product value outcomes, and comprehensive return on investment (ROI) analyses.

Value-Based Reimbursement

Value-based healthcare (VBC) models differ from the traditional fee-for-service approach. Under fee-for-service, providers are paid for each service, potentially incentivizing overutilization and driving up costs. In contrast, VBC models are designed to prioritize quality and outcomes, compensating providers based on effectiveness. This shift aligns incentives with enhanced patient health and cost control, fostering more efficient, patient-centered care.

Looking to the Future

As plan sponsors and health plans determine optimal health-oriented courses of action, the need for consultants with experience navigating complex health industry challenges and expertise across benefit, actuarial, and data science is paramount to ensuring effective outcomes and improved experience. Our team of experts at Risk Strategies Consulting leverage real-world data, market insights, and conduct comprehensive ROI analyses with dynamic actuarial modeling to advise our clients on impactful strategies that address upcoming challenges with considerations for their unique ecosystems. Data science is one such tool, that when paired with trained resources, can illuminate opportunities to improve health outcomes, member and provider engagement, affordability of health services, and socioeconomic disparities.