How Data Analytics Is Helping Healthcare Embrace Value-Based Care

Between 2015 and 2018, the percentage of healthcare organizations having a defined data analytics strategy jumped from 40 percent to 70 percent. This underscores the increasingly important role data analytics plays in healthcare operations today.

With providers experiencing pressure to transition from volume-based care to value-based care — to optimize patient outcomes while reducing costs — the role of data analytics within the industry is growing.

The Basics of Value-Based Care

First, let’s talk about value-based care: what it is and why organizations are shifting toward it.

Healthcare in America has traditionally operated on a fee-per service model. Under this volume-based approach, providers would get paid per service they provided to patients, regardless of the outcomes. The limitations here are pretty glaring. Among them is the fact there’s little financial incentive for providers to prioritize patient outcomes when they’re receiving payment on the basis of services rendered.

Value-based care, on the other hand, “is derived from measuring health outcomes against the cost of delivering the outcomes. According to the New England Journal of Medicine, everyone from patients to providers to society as a whole can reap the benefits of a value-based system. The driving goals behind this model are lowering costs for everyone involved, coupled with improving patient outcomes.

However, successfully shifting toward value-based care means healthcare organizations must have the data analytics strategy in place to facilitate decision-making and performance tracking.

The Role of Analytics Tools in Value-Based Care

Today’s self-service analytics tools like search and conversational analytics empower decision-makers throughout healthcare organizations to ask questions and get answers in seconds. Modern analytics platforms allow everyone from administrators to clinicians to pull insights related to patient outcomes, cost of services, patient behavior patterns, risk, and more.

Here’s one example from Health IT Analytics: Executives can “examine utilization patterns and measure the revenue impacts associated with specific population segments.” This type of information lays the foundation for later efforts to address gaps in patient care and engage under-served portions of the population.

Value-based care depends on creating holistic views of the patient experience, which providers can then work to optimize. If a hospital wants to reduce readmissions as part of a value-based care initiative, clinicians and administrators need access to current readmission rates and an understanding of why readmissions are occurring. Only then can they decide how to address the risk factors that are linked to readmissions — and change organizational policy to address them. Ideally, the hospital will be able to cut down on costly readmissions and patients will see fewer issues following medical procedures.

One challenge healthcare providers face is convincing employees to adopt these data analytics tools into their workflows. The degree to which users buy into data analytics affects the system’s bottom-line impact. Organizations can drive adoption by ensuring the tools they deploy are accessible, easy to use, understandable, and easy to integrate into existing workflows. It’s also important to ensure everyone has the training they need to comfortably pull data insights and the shared language with which to communicate findings.

Artificial Intelligence and Machine Learning in Healthcare

Artificial intelligence (AI) and machine learning (ML) in data analytics are capable of improving value-based care, too. One health system recently used AI analytics to reduce hospital visits for high-risk health failure patients by 23 percent. How? By using predictive analytics to trigger timely interventions via the telephone — before patients ended up needing to visit the hospital.

AI and ML algorithms are capable of deep diving into huge data lakes to identify potentially relevant patterns, which they can then push to human users. Armed with these insights, decision-makers can take action to try to boost patient outcomes and reduce inefficiency.

Value-based healthcare is the way of the future for providers, and data analytics is helping organizations make this transition.