HOW MIGHT WE.....
How might we help members become more engaged in their own care?
How might we close communication gaps?
How might we identify members' needs and tailoring services to meet them?
How might we enable consumers to get care in convenient, cost-effective ways?
How might we improve decision-making by consumers and providers?
Managing with Analytics at Procter & Gamble
Over time, managers found that the single, company-wide database played a much more strategic role in aiding decision making by serving as the “one truth” for the entire corporation. “Instead of spending our time debating the data, we eliminate the need for those discussions. The data is the data, and leaders can spend their time concentrating on the business and the decisions that need to be made to move the business--instead of which set of data points is correct. This speeds decision-making and ultimately improves time to market.”
P&G employed two types of statistical models for forecasting. The first type, generally time series-based forecasting models, produced the most accurate forecasts. These models constructed forecasts using previous results as well as macroeconomic conditions and other basic inputs. Although the outputs were precise, this set of models provided little insights as to why the outcome would occur. Propensity models, on the other hand, attempted to better understand the causes, or drivers, of the outcomes. By incorporating information on drivers such as new product introductions, marketing campaigns, and competitor actions, propensity models served as useful tools to measure the potential impact of management actions.
The picture: For management teams, P&G developed a patent-pending physical environment for information-based decision-making called the Business Sphere.
Takeaways: 1, "One truth"- focus on why and how, not what . 2, Integrate clinical data and claim data to predict and prescribe products and services to consumers.
GE's Big Data and Analytics
“The digital company. That’s also an industrial company.” — of GE’s massive digital transformation effort. GE has bet big on the Industrial Internet — the convergence of industrial machines, data, and the Internet (also referred to as the Internet of Things)
GE has long had the ability to collect machine data: Sensors have been riding on GE machines for years. But these pre-Internet of Things (IoT) sensors were used to conduct real-time operational performance monitoring, such as displaying a pressure reading on a machine, not to collect data. Indeed, a technician would often take a reading from a machine to check its performance and then discard the data.
Predix software, a cloud-based platform for creating Industrial Internet applications.Predix was designed to be a software platform, not just a tool for collecting, analyzing, and manag- ing sensor data.
That same year, GE executives began to think there could be a market opportunity for Predix, much as Amazon.com Inc. created a market for its cloud- computing platform, Amazon Web Services Inc. “We realized that there were three developing markets for cloud platforms — consumer, enterprise, and industrial. Industrial was essentially being treated as an extension of enterprise, which we knew wouldn’t work. There were no credible cloud-based platforms for industrial being developed, and we saw that as a potential opportunity for growth,”
Predix was designed to be a software platform, not just a tool for collecting, analyzing, and managing sensor data.For GE customers, this approach is expected to have several benefits. The platform has open standards and protocols that allow customers to more easily and quickly connect their machines to the Industrial Internet. The platform can accommodate the size and scale of industrial data for every customer at current levels of use, but it also has been designed to scale up as demand grows.
Takeaways: 1, What is our pre-IoT? 2, Do we have the scale to bet on a "Healthcare Predix"?
Anthem Blue Cross of California and Valley Radiotherapy Associates Implement New Rates for Breast Cancer Patients
"This is the first cancer bundled payment program that Anthem has piloted," said Dr. Jennifer Malin, vice president for clinical strategy at Anthem. The rate is available for patients with Stages 1-3 breast cancer because it often requires outpatient radiation treatment only. Radiation treatment for breast cancer is a viable bundled payment option because studies show that women are often eligible for shorter treatment plans than what they receive. She said reimbursement policies may influence this excessive treatment. With bundled payments, revenue will be the same no matter how much radiation treatment they need. Valley Radiotherapy treats several hundred breast cancer patients in a year. The recurrence rate among its breast cancer patients is about 3%. Anthem and Valley Radiotherapy will look at patient data after the program is implemented for several months. They may adjust the price depending on how long patients are treated.
The payment approach best aligned with value is a bundled payment that covers the full care cycle for acute medical conditions, the overall care for chronic conditions for a defined period (usually a year), or primary and preventive care for a defined patient population (healthy children, for instance). Well-designed bundled payments directly encourage teamwork and high-value care. Payment is tied to overall care for a patient with a particular medical condition, aligning payment with what the team can control. Providers benefit from improving efficiency while maintaining or improving outcomes.
Sound bundled payment models should include: severity adjustments or eligibility only for qualifying patients; care guarantees that hold the provider responsible for avoidable complications, such as infections after surgery; stop-loss provisions that mitigate the risk of unusually high-cost events; and mandatory outcomes reporting.