A New View of What is Possible for Health Care Payers

Incremental capability improvements just aren’t enough to push health care payers ahead of the competitive pack. Yet most payers are taking only small steps, deploying IT tools to streamline discrete activities like member servicing and care management. What’s crucial now is an entire rethink of the payer model, borrowing from other sectors’ successes with analytics and using proven integrated health analytics that are receiving investment and attention by leading payers. The new approaches will put those leaders on a new competitive plane, driving radical innovation in products and processes and helping them differentiate their offerings.

Already, several frontline payers are testing innovative new business models that use the kinds of deeply analytical approaches proven in other industries. They are going much further than the incremental moves seen to date—limited efforts to share electronic health records or to better integrate servicing models, for instance—as they move toward truly integrated health analytics frameworks on a much broader scale than anything in use today. The frameworks draw on multiple data streams from all over the health care ecosystem—from providers and third parties to the member’s own behavior patterns—along with elements of entertainment marketing, social networking, expert systems, and sophisticated analytics engines.

Such a holistic approach can fundamentally change every aspect of a payer’s business and decision-making processes. It can even become its own distinctive capability for payers, delivering sustained high performance in ways that rivals cannot easily match.

Download the condensed article—A New View of What’s Possible for Health Care Payers: Accenture Integrated Health Analytics Solution [PDF, 149KB]

Change is possible now because several factors are converging: the retailing of health care, the intensity of competition among payers and the imminent need for “someone”—federal government, state government, the private sector—to do something about a system that many perceive as broken.

There is a noticeable groundswell toward consumer-driven retail health care. Working directly with plan members will demand deep insights about members’ behaviors and their health factors as well as better products and improved customer service.

Advances in technology also make it practical to consider radically different approaches. Advances in information technology are allowing the democratization of sophisticated analytics. Cloud computing is enabling more IT functions to be migrated into the cloud, and mash-ups are allowing data integration to be done directly by enterprise user groups. Clearly, data is emerging as the most important asset for enterprises at large.

The proliferation of new data types is propelling analytics beyond the back rooms and embedding them at scale across the enterprise for everything from budgeting to forecasting, sales promotion to customer intelligence, pricing to member health and so forth. Finally, increasingly sophisticated analytical software and techniques are unlocking insights and actions that are faster, at scale and more accurate than today’s business intelligence solutions.

And more refined business processes are now flexible enough to tie together disparate data inputs from an ever-evolving mix of participants. The future health care information supply chain will necessitate dynamic information sharing for collaborative product design, health/wellness and care decisions.

The elements of these solutions are available now—the sensors, the analytics software and the “engine” at the heart of the emerging integrated health analytics systems. The systems have four core characteristics that apply no matter which payer scenario the analytics capability is applied to:

• Broad data sets: From many sources (including third parties) including wireless, point-of-sale, evidence-based medicine, actuarial, etc.; from glucose levels sent wirelessly every day by the patient to care management records from the provider through to pharmacy purchases and actuarial data coming in flat files from an underwriter. The data is amalgamated and kept active in a consumer-centric metadata repository.
  
  
• Predictive and proactive intervention: Using timely data about members and about relevant trends to take action before the member or his physician does. The system’s analytical “insight engine” is key here, going beyond simply monitoring the rhythm of the business to anticipating threats and presenting opportunities for appropriate intervention. Exploiting analytics in clustering, optimization, unbiased predictive modeling, and propensity-score shaping, the solution creates control groups to predict the outcomes likely to result from different kinds of interventions.
  
  
• Emphasis on optimizing responses: Once you have predictions, you can understand the menu of options that are available. In a resource-constrained world, an optimization capability helps to rationalize what to do given the trade-offs and ROI expectations. In the case of wellness management, this includes selecting the channels, content, and so on, across the entire patient population that will yield the greatest impact.
  
  
• Outcomes-focused: Across all of the scenarios, we want to encourage the use of rigorous ROI/outcomes analysis to drive decisions and help business leaders understand trade-offs. This is not trivial: It demands inclusion of not just the direct effects of an action but also an understanding of and accounting for unintended consequences.
  
  

Put it all together across the scope of a payer’s enterprise and it’s possible to glimpse how an industrialized integrated analytics suite can not only improve consumer health and identify where cuts in medical costs can occur, but it can continually help payers’ business leaders make the right investment trade-offs by advising on what works, what doesn’t and how to improve the operation continuously.

Leading payers are moving toward an enterprise-wide view of analytics by applying integrated capabilities—going beyond transaction and data management so they start to tie information together across the company and use the resulting insights to differentiate their offerings and themselves. Their management teams view integrated analytics as a growth engine, enabling the business model to shift the company toward becoming analytically competitive. In other words, integrated analytics becomes a radical driver of innovation that can transform payers into high-performance businesses that compete on an entirely different plane.

To reach this new plane, payers have to integrate, innovate and industrialize. They have to do so because the points of need are distributed more widely, timing of services delivery is becoming more important and relevant data is coming from many more new and nontraditional sources. Their integrated approach extends across the health care ecosystem: providers, patients, insurers, employers, pharmacies, consumer data firms and more. This requires the “industrialization” of analytics so the payer’s analytics systems become self-sustaining.

Leading payers are realizing the opportunity in catering to those who are, for the most part, in good health. The systems with which they are now experimenting are helping payers know which members to “touch,” when to touch them and how—targeting the right members with relevant incentives through channels that will engage them. In short, integrated analytics systems are enabling payers to make sure that healthy plan members stay that way—and remain profitably enrolled—as long as they can.

The best starting point for payers is to recognize the scope of what is now possible. The next logical step is a shift in mindset from “spot” applications of analytics—focused on improving transaction efficiency—to the application of integrated and industrialized analytics that leverage cross-industry innovation to build a self-sustaining high-performance organization.

With the right executive mindset in place, payers can start tackling the fundamentals of integrated health analytics excellence. Taking a page from the playbooks of analytics leaders in other industries, they can identify and organize sources of analytics talent within their four walls. Another key step: taking an inventory of the data they already have available as well as the data they can easily access. Most payers already have many of the data assets they need to start becoming true analytical competitors.

While a shift in actual implementation is likely to show a steady progression the shift in mindset has to happen soon. It also has to come with a long-term commitment from payers’ business leaders. And it calls for a concerted shift from creating products that match competitors’ offerings to an innovation stance in which the organization proactively creates new products that use tiered networks, real-time consumer utility testing and system-driven benefit optimization routines while balancing predicted risk and projected profit.

The current trajectory of investments in analytics suggests that payers’ data silos are indeed being broken down and that fact-based analysis is steadily replacing intuition-driven decision making. There is a clear move toward predictive modeling and toward enterprise management models that extend to other health care partners.

The opportunity for lasting differentiation is enormous. The chance to transform the US health care industry is alluring. What’s your plan for being on the front lines?

Contact us to find out more about how Accenture can help health care payers achieve high performance.